what is case study research in qualitative research

The Ultimate Guide to Qualitative Research - Part 1: The Basics

• Introduction and overview
• What is qualitative research?
• What is qualitative data?
• Examples of qualitative data
• Qualitative vs. quantitative research
• Mixed methods
• Qualitative research preparation
• Theoretical perspective
• Theoretical framework
• Literature reviews

Research question

• Conceptual framework
• Conceptual vs. theoretical framework

Data collection

• Qualitative research methods
• Focus groups
• Observational research

What is a case study?

Applications for case study research, what is a good case study, process of case study design, benefits and limitations of case studies.

• Ethnographical research
• Ethical considerations
• Confidentiality and privacy
• Power dynamics
• Reflexivity

Case studies

Case studies are essential to qualitative research , offering a lens through which researchers can investigate complex phenomena within their real-life contexts. This chapter explores the concept, purpose, applications, examples, and types of case studies and provides guidance on how to conduct case study research effectively.

Whereas quantitative methods look at phenomena at scale, case study research looks at a concept or phenomenon in considerable detail. While analyzing a single case can help understand one perspective regarding the object of research inquiry, analyzing multiple cases can help obtain a more holistic sense of the topic or issue. Let's provide a basic definition of a case study, then explore its characteristics and role in the qualitative research process.

Definition of a case study

A case study in qualitative research is a strategy of inquiry that involves an in-depth investigation of a phenomenon within its real-world context. It provides researchers with the opportunity to acquire an in-depth understanding of intricate details that might not be as apparent or accessible through other methods of research. The specific case or cases being studied can be a single person, group, or organization – demarcating what constitutes a relevant case worth studying depends on the researcher and their research question .

Among qualitative research methods , a case study relies on multiple sources of evidence, such as documents, artifacts, interviews , or observations , to present a complete and nuanced understanding of the phenomenon under investigation. The objective is to illuminate the readers' understanding of the phenomenon beyond its abstract statistical or theoretical explanations.

Characteristics of case studies

Case studies typically possess a number of distinct characteristics that set them apart from other research methods. These characteristics include a focus on holistic description and explanation, flexibility in the design and data collection methods, reliance on multiple sources of evidence, and emphasis on the context in which the phenomenon occurs.

Furthermore, case studies can often involve a longitudinal examination of the case, meaning they study the case over a period of time. These characteristics allow case studies to yield comprehensive, in-depth, and richly contextualized insights about the phenomenon of interest.

The role of case studies in research

Case studies hold a unique position in the broader landscape of research methods aimed at theory development. They are instrumental when the primary research interest is to gain an intensive, detailed understanding of a phenomenon in its real-life context.

In addition, case studies can serve different purposes within research - they can be used for exploratory, descriptive, or explanatory purposes, depending on the research question and objectives. This flexibility and depth make case studies a valuable tool in the toolkit of qualitative researchers.

Remember, a well-conducted case study can offer a rich, insightful contribution to both academic and practical knowledge through theory development or theory verification, thus enhancing our understanding of complex phenomena in their real-world contexts.

What is the purpose of a case study?

Case study research aims for a more comprehensive understanding of phenomena, requiring various research methods to gather information for qualitative analysis . Ultimately, a case study can allow the researcher to gain insight into a particular object of inquiry and develop a theoretical framework relevant to the research inquiry.

Why use case studies in qualitative research?

Using case studies as a research strategy depends mainly on the nature of the research question and the researcher's access to the data.

Conducting case study research provides a level of detail and contextual richness that other research methods might not offer. They are beneficial when there's a need to understand complex social phenomena within their natural contexts.

The explanatory, exploratory, and descriptive roles of case studies

Case studies can take on various roles depending on the research objectives. They can be exploratory when the research aims to discover new phenomena or define new research questions; they are descriptive when the objective is to depict a phenomenon within its context in a detailed manner; and they can be explanatory if the goal is to understand specific relationships within the studied context. Thus, the versatility of case studies allows researchers to approach their topic from different angles, offering multiple ways to uncover and interpret the data .

The impact of case studies on knowledge development

Case studies play a significant role in knowledge development across various disciplines. Analysis of cases provides an avenue for researchers to explore phenomena within their context based on the collected data.

This can result in the production of rich, practical insights that can be instrumental in both theory-building and practice. Case studies allow researchers to delve into the intricacies and complexities of real-life situations, uncovering insights that might otherwise remain hidden.

Types of case studies

In qualitative research , a case study is not a one-size-fits-all approach. Depending on the nature of the research question and the specific objectives of the study, researchers might choose to use different types of case studies. These types differ in their focus, methodology, and the level of detail they provide about the phenomenon under investigation.

Understanding these types is crucial for selecting the most appropriate approach for your research project and effectively achieving your research goals. Let's briefly look at the main types of case studies.

Exploratory case studies

Exploratory case studies are typically conducted to develop a theory or framework around an understudied phenomenon. They can also serve as a precursor to a larger-scale research project. Exploratory case studies are useful when a researcher wants to identify the key issues or questions which can spur more extensive study or be used to develop propositions for further research. These case studies are characterized by flexibility, allowing researchers to explore various aspects of a phenomenon as they emerge, which can also form the foundation for subsequent studies.

Descriptive case studies

Descriptive case studies aim to provide a complete and accurate representation of a phenomenon or event within its context. These case studies are often based on an established theoretical framework, which guides how data is collected and analyzed. The researcher is concerned with describing the phenomenon in detail, as it occurs naturally, without trying to influence or manipulate it.

Explanatory case studies

Explanatory case studies are focused on explanation - they seek to clarify how or why certain phenomena occur. Often used in complex, real-life situations, they can be particularly valuable in clarifying causal relationships among concepts and understanding the interplay between different factors within a specific context.

Intrinsic, instrumental, and collective case studies

These three categories of case studies focus on the nature and purpose of the study. An intrinsic case study is conducted when a researcher has an inherent interest in the case itself. Instrumental case studies are employed when the case is used to provide insight into a particular issue or phenomenon. A collective case study, on the other hand, involves studying multiple cases simultaneously to investigate some general phenomena.

Each type of case study serves a different purpose and has its own strengths and challenges. The selection of the type should be guided by the research question and objectives, as well as the context and constraints of the research.

The flexibility, depth, and contextual richness offered by case studies make this approach an excellent research method for various fields of study. They enable researchers to investigate real-world phenomena within their specific contexts, capturing nuances that other research methods might miss. Across numerous fields, case studies provide valuable insights into complex issues.

Critical information systems research

Case studies provide a detailed understanding of the role and impact of information systems in different contexts. They offer a platform to explore how information systems are designed, implemented, and used and how they interact with various social, economic, and political factors. Case studies in this field often focus on examining the intricate relationship between technology, organizational processes, and user behavior, helping to uncover insights that can inform better system design and implementation.

Health research

Health research is another field where case studies are highly valuable. They offer a way to explore patient experiences, healthcare delivery processes, and the impact of various interventions in a real-world context.

Case studies can provide a deep understanding of a patient's journey, giving insights into the intricacies of disease progression, treatment effects, and the psychosocial aspects of health and illness.

Asthma research studies

Specifically within medical research, studies on asthma often employ case studies to explore the individual and environmental factors that influence asthma development, management, and outcomes. A case study can provide rich, detailed data about individual patients' experiences, from the triggers and symptoms they experience to the effectiveness of various management strategies. This can be crucial for developing patient-centered asthma care approaches.

Other fields

Apart from the fields mentioned, case studies are also extensively used in business and management research, education research, and political sciences, among many others. They provide an opportunity to delve into the intricacies of real-world situations, allowing for a comprehensive understanding of various phenomena.

Case studies, with their depth and contextual focus, offer unique insights across these varied fields. They allow researchers to illuminate the complexities of real-life situations, contributing to both theory and practice.

Whatever field you're in, ATLAS.ti puts your data to work for you

Download a free trial of ATLAS.ti to turn your data into insights.

Understanding the key elements of case study design is crucial for conducting rigorous and impactful case study research. A well-structured design guides the researcher through the process, ensuring that the study is methodologically sound and its findings are reliable and valid. The main elements of case study design include the research question , propositions, units of analysis, and the logic linking the data to the propositions.

The research question is the foundation of any research study. A good research question guides the direction of the study and informs the selection of the case, the methods of collecting data, and the analysis techniques. A well-formulated research question in case study research is typically clear, focused, and complex enough to merit further detailed examination of the relevant case(s).

Propositions

Propositions, though not necessary in every case study, provide a direction by stating what we might expect to find in the data collected. They guide how data is collected and analyzed by helping researchers focus on specific aspects of the case. They are particularly important in explanatory case studies, which seek to understand the relationships among concepts within the studied phenomenon.

Units of analysis

The unit of analysis refers to the case, or the main entity or entities that are being analyzed in the study. In case study research, the unit of analysis can be an individual, a group, an organization, a decision, an event, or even a time period. It's crucial to clearly define the unit of analysis, as it shapes the qualitative data analysis process by allowing the researcher to analyze a particular case and synthesize analysis across multiple case studies to draw conclusions.

Argumentation

This refers to the inferential model that allows researchers to draw conclusions from the data. The researcher needs to ensure that there is a clear link between the data, the propositions (if any), and the conclusions drawn. This argumentation is what enables the researcher to make valid and credible inferences about the phenomenon under study.

Understanding and carefully considering these elements in the design phase of a case study can significantly enhance the quality of the research. It can help ensure that the study is methodologically sound and its findings contribute meaningful insights about the case.

Ready to jumpstart your research with ATLAS.ti?

Conceptualize your research project with our intuitive data analysis interface. Download a free trial today.

Conducting a case study involves several steps, from defining the research question and selecting the case to collecting and analyzing data . This section outlines these key stages, providing a practical guide on how to conduct case study research.

Defining the research question

The first step in case study research is defining a clear, focused research question. This question should guide the entire research process, from case selection to analysis. It's crucial to ensure that the research question is suitable for a case study approach. Typically, such questions are exploratory or descriptive in nature and focus on understanding a phenomenon within its real-life context.

Selecting and defining the case

The selection of the case should be based on the research question and the objectives of the study. It involves choosing a unique example or a set of examples that provide rich, in-depth data about the phenomenon under investigation. After selecting the case, it's crucial to define it clearly, setting the boundaries of the case, including the time period and the specific context.

Previous research can help guide the case study design. When considering a case study, an example of a case could be taken from previous case study research and used to define cases in a new research inquiry. Considering recently published examples can help understand how to select and define cases effectively.

Developing a detailed case study protocol

A case study protocol outlines the procedures and general rules to be followed during the case study. This includes the data collection methods to be used, the sources of data, and the procedures for analysis. Having a detailed case study protocol ensures consistency and reliability in the study.

The protocol should also consider how to work with the people involved in the research context to grant the research team access to collecting data. As mentioned in previous sections of this guide, establishing rapport is an essential component of qualitative research as it shapes the overall potential for collecting and analyzing data.

Collecting data

Gathering data in case study research often involves multiple sources of evidence, including documents, archival records, interviews, observations, and physical artifacts. This allows for a comprehensive understanding of the case. The process for gathering data should be systematic and carefully documented to ensure the reliability and validity of the study.

Analyzing and interpreting data

The next step is analyzing the data. This involves organizing the data , categorizing it into themes or patterns , and interpreting these patterns to answer the research question. The analysis might also involve comparing the findings with prior research or theoretical propositions.

Writing the case study report

The final step is writing the case study report . This should provide a detailed description of the case, the data, the analysis process, and the findings. The report should be clear, organized, and carefully written to ensure that the reader can understand the case and the conclusions drawn from it.

Each of these steps is crucial in ensuring that the case study research is rigorous, reliable, and provides valuable insights about the case.

The type, depth, and quality of data in your study can significantly influence the validity and utility of the study. In case study research, data is usually collected from multiple sources to provide a comprehensive and nuanced understanding of the case. This section will outline the various methods of collecting data used in case study research and discuss considerations for ensuring the quality of the data.

Interviews are a common method of gathering data in case study research. They can provide rich, in-depth data about the perspectives, experiences, and interpretations of the individuals involved in the case. Interviews can be structured , semi-structured , or unstructured , depending on the research question and the degree of flexibility needed.

Observations

Observations involve the researcher observing the case in its natural setting, providing first-hand information about the case and its context. Observations can provide data that might not be revealed in interviews or documents, such as non-verbal cues or contextual information.

Documents and artifacts

Documents and archival records provide a valuable source of data in case study research. They can include reports, letters, memos, meeting minutes, email correspondence, and various public and private documents related to the case.

These records can provide historical context, corroborate evidence from other sources, and offer insights into the case that might not be apparent from interviews or observations.

Physical artifacts refer to any physical evidence related to the case, such as tools, products, or physical environments. These artifacts can provide tangible insights into the case, complementing the data gathered from other sources.

Ensuring the quality of data collection

Determining the quality of data in case study research requires careful planning and execution. It's crucial to ensure that the data is reliable, accurate, and relevant to the research question. This involves selecting appropriate methods of collecting data, properly training interviewers or observers, and systematically recording and storing the data. It also includes considering ethical issues related to collecting and handling data, such as obtaining informed consent and ensuring the privacy and confidentiality of the participants.

Data analysis

Analyzing case study research involves making sense of the rich, detailed data to answer the research question. This process can be challenging due to the volume and complexity of case study data. However, a systematic and rigorous approach to analysis can ensure that the findings are credible and meaningful. This section outlines the main steps and considerations in analyzing data in case study research.

Organizing the data

The first step in the analysis is organizing the data. This involves sorting the data into manageable sections, often according to the data source or the theme. This step can also involve transcribing interviews, digitizing physical artifacts, or organizing observational data.

Categorizing and coding the data

Once the data is organized, the next step is to categorize or code the data. This involves identifying common themes, patterns, or concepts in the data and assigning codes to relevant data segments. Coding can be done manually or with the help of software tools, and in either case, qualitative analysis software can greatly facilitate the entire coding process. Coding helps to reduce the data to a set of themes or categories that can be more easily analyzed.

Identifying patterns and themes

After coding the data, the researcher looks for patterns or themes in the coded data. This involves comparing and contrasting the codes and looking for relationships or patterns among them. The identified patterns and themes should help answer the research question.

Interpreting the data

Once patterns and themes have been identified, the next step is to interpret these findings. This involves explaining what the patterns or themes mean in the context of the research question and the case. This interpretation should be grounded in the data, but it can also involve drawing on theoretical concepts or prior research.

Verification of the data

The last step in the analysis is verification. This involves checking the accuracy and consistency of the analysis process and confirming that the findings are supported by the data. This can involve re-checking the original data, checking the consistency of codes, or seeking feedback from research participants or peers.

Like any research method , case study research has its strengths and limitations. Researchers must be aware of these, as they can influence the design, conduct, and interpretation of the study.

Understanding the strengths and limitations of case study research can also guide researchers in deciding whether this approach is suitable for their research question . This section outlines some of the key strengths and limitations of case study research.

Benefits include the following:

• Rich, detailed data: One of the main strengths of case study research is that it can generate rich, detailed data about the case. This can provide a deep understanding of the case and its context, which can be valuable in exploring complex phenomena.
• Flexibility: Case study research is flexible in terms of design , data collection , and analysis . A sufficient degree of flexibility allows the researcher to adapt the study according to the case and the emerging findings.
• Real-world context: Case study research involves studying the case in its real-world context, which can provide valuable insights into the interplay between the case and its context.
• Multiple sources of evidence: Case study research often involves collecting data from multiple sources , which can enhance the robustness and validity of the findings.

On the other hand, researchers should consider the following limitations:

• Generalizability: A common criticism of case study research is that its findings might not be generalizable to other cases due to the specificity and uniqueness of each case.
• Time and resource intensive: Case study research can be time and resource intensive due to the depth of the investigation and the amount of collected data.
• Complexity of analysis: The rich, detailed data generated in case study research can make analyzing the data challenging.
• Subjectivity: Given the nature of case study research, there may be a higher degree of subjectivity in interpreting the data , so researchers need to reflect on this and transparently convey to audiences how the research was conducted.

Being aware of these strengths and limitations can help researchers design and conduct case study research effectively and interpret and report the findings appropriately.

Ready to analyze your data with ATLAS.ti?

See how our intuitive software can draw key insights from your data with a free trial today.

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, automatically generate references for free.

• Knowledge Base
• Methodology
• Case Study | Definition, Examples & Methods

Case Study | Definition, Examples & Methods

Published on 5 May 2022 by Shona McCombes . Revised on 30 January 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organisation, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating, and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyse the case.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

Prevent plagiarism, run a free check.

Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

• Provide new or unexpected insights into the subject
• Challenge or complicate existing assumptions and theories
• Propose practical courses of action to resolve a problem
• Open up new directions for future research

Unlike quantitative or experimental research, a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

If you find yourself aiming to simultaneously investigate and solve an issue, consider conducting action research . As its name suggests, action research conducts research and takes action at the same time, and is highly iterative and flexible. 

However, you can also choose a more common or representative case to exemplify a particular category, experience, or phenomenon.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

• Exemplify a theory by showing how it explains the case under investigation
• Expand on a theory by uncovering new concepts and ideas that need to be incorporated
• Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews, observations, and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data .

The aim is to gain as thorough an understanding as possible of the case and its context.

In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis, with separate sections or chapters for the methods , results , and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyse its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

McCombes, S. (2023, January 30). Case Study | Definition, Examples & Methods. Scribbr. Retrieved 7 June 2024, from https://www.scribbr.co.uk/research-methods/case-studies/

Is this article helpful?

Shona McCombes

Other students also liked, correlational research | guide, design & examples, a quick guide to experimental design | 5 steps & examples, descriptive research design | definition, methods & examples.

Research Writing and Analysis

• NVivo Group and Study Sessions
• SPSS This link opens in a new window
• Statistical Analysis Group sessions
• Using Qualtrics
• Dissertation and Data Analysis Group Sessions
• Defense Schedule - Commons Calendar This link opens in a new window
• Research Process Flow Chart
• Research Alignment Chapter 1 This link opens in a new window
• Step 1: Seek Out Evidence
• Step 2: Explain
• Step 3: The Big Picture
• Step 4: Own It
• Step 5: Illustrate
• Annotated Bibliography
• Literature Review This link opens in a new window
• Systematic Reviews & Meta-Analyses
• How to Synthesize and Analyze
• Synthesis and Analysis Practice
• Synthesis and Analysis Group Sessions
• Problem Statement
• Purpose Statement
• Conceptual Framework
• Theoretical Framework
• Locating Theoretical and Conceptual Frameworks This link opens in a new window
• Quantitative Research Questions
• Qualitative Research Questions
• Trustworthiness of Qualitative Data
• Analysis and Coding Example- Qualitative Data
• Thematic Data Analysis in Qualitative Design
• Dissertation to Journal Article This link opens in a new window
• International Journal of Online Graduate Education (IJOGE) This link opens in a new window
• Journal of Research in Innovative Teaching & Learning (JRIT&L) This link opens in a new window

Writing a Case Study

What is a case study?

A Case study is: 

• An in-depth research design that primarily uses a qualitative methodology but sometimes​​ includes quantitative methodology.
• Used to examine an identifiable problem confirmed through research.
• Used to investigate an individual, group of people, organization, or event.
• Used to mostly answer "how" and "why" questions.

What are the different types of case studies?

Note: These are the primary case studies. As you continue to research and learn

about case studies you will begin to find a robust list of different types. 

Who are your case study participants?

What is triangulation ? 

Validity and credibility are an essential part of the case study. Therefore, the researcher should include triangulation to ensure trustworthiness while accurately reflecting what the researcher seeks to investigate.

How to write a Case Study?

When developing a case study, there are different ways you could present the information, but remember to include the five parts for your case study.

Was this resource helpful?

• << Previous: Thematic Data Analysis in Qualitative Design
• Next: Journal Article Reporting Standards (JARS) >>
• Last Updated: May 29, 2024 8:05 AM
• URL: https://resources.nu.edu/researchtools

• Open access
• Published: 27 June 2011

The case study approach

• Sarah Crowe 1 ,
• Kathrin Cresswell 2 ,
• Ann Robertson 2 ,
• Guro Huby 3 ,
• Anthony Avery 1 &
• Aziz Sheikh 2  

BMC Medical Research Methodology volume  11 , Article number:  100 ( 2011 ) Cite this article

784k Accesses

1048 Citations

37 Altmetric

Metrics details

The case study approach allows in-depth, multi-faceted explorations of complex issues in their real-life settings. The value of the case study approach is well recognised in the fields of business, law and policy, but somewhat less so in health services research. Based on our experiences of conducting several health-related case studies, we reflect on the different types of case study design, the specific research questions this approach can help answer, the data sources that tend to be used, and the particular advantages and disadvantages of employing this methodological approach. The paper concludes with key pointers to aid those designing and appraising proposals for conducting case study research, and a checklist to help readers assess the quality of case study reports.

Peer Review reports

Introduction

The case study approach is particularly useful to employ when there is a need to obtain an in-depth appreciation of an issue, event or phenomenon of interest, in its natural real-life context. Our aim in writing this piece is to provide insights into when to consider employing this approach and an overview of key methodological considerations in relation to the design, planning, analysis, interpretation and reporting of case studies.

The illustrative 'grand round', 'case report' and 'case series' have a long tradition in clinical practice and research. Presenting detailed critiques, typically of one or more patients, aims to provide insights into aspects of the clinical case and, in doing so, illustrate broader lessons that may be learnt. In research, the conceptually-related case study approach can be used, for example, to describe in detail a patient's episode of care, explore professional attitudes to and experiences of a new policy initiative or service development or more generally to 'investigate contemporary phenomena within its real-life context' [ 1 ]. Based on our experiences of conducting a range of case studies, we reflect on when to consider using this approach, discuss the key steps involved and illustrate, with examples, some of the practical challenges of attaining an in-depth understanding of a 'case' as an integrated whole. In keeping with previously published work, we acknowledge the importance of theory to underpin the design, selection, conduct and interpretation of case studies[ 2 ]. In so doing, we make passing reference to the different epistemological approaches used in case study research by key theoreticians and methodologists in this field of enquiry.

This paper is structured around the following main questions: What is a case study? What are case studies used for? How are case studies conducted? What are the potential pitfalls and how can these be avoided? We draw in particular on four of our own recently published examples of case studies (see Tables 1 , 2 , 3 and 4 ) and those of others to illustrate our discussion[ 3 – 7 ].

What is a case study?

A case study is a research approach that is used to generate an in-depth, multi-faceted understanding of a complex issue in its real-life context. It is an established research design that is used extensively in a wide variety of disciplines, particularly in the social sciences. A case study can be defined in a variety of ways (Table 5 ), the central tenet being the need to explore an event or phenomenon in depth and in its natural context. It is for this reason sometimes referred to as a "naturalistic" design; this is in contrast to an "experimental" design (such as a randomised controlled trial) in which the investigator seeks to exert control over and manipulate the variable(s) of interest.

Stake's work has been particularly influential in defining the case study approach to scientific enquiry. He has helpfully characterised three main types of case study: intrinsic , instrumental and collective [ 8 ]. An intrinsic case study is typically undertaken to learn about a unique phenomenon. The researcher should define the uniqueness of the phenomenon, which distinguishes it from all others. In contrast, the instrumental case study uses a particular case (some of which may be better than others) to gain a broader appreciation of an issue or phenomenon. The collective case study involves studying multiple cases simultaneously or sequentially in an attempt to generate a still broader appreciation of a particular issue.

These are however not necessarily mutually exclusive categories. In the first of our examples (Table 1 ), we undertook an intrinsic case study to investigate the issue of recruitment of minority ethnic people into the specific context of asthma research studies, but it developed into a instrumental case study through seeking to understand the issue of recruitment of these marginalised populations more generally, generating a number of the findings that are potentially transferable to other disease contexts[ 3 ]. In contrast, the other three examples (see Tables 2 , 3 and 4 ) employed collective case study designs to study the introduction of workforce reconfiguration in primary care, the implementation of electronic health records into hospitals, and to understand the ways in which healthcare students learn about patient safety considerations[ 4 – 6 ]. Although our study focusing on the introduction of General Practitioners with Specialist Interests (Table 2 ) was explicitly collective in design (four contrasting primary care organisations were studied), is was also instrumental in that this particular professional group was studied as an exemplar of the more general phenomenon of workforce redesign[ 4 ].

What are case studies used for?

According to Yin, case studies can be used to explain, describe or explore events or phenomena in the everyday contexts in which they occur[ 1 ]. These can, for example, help to understand and explain causal links and pathways resulting from a new policy initiative or service development (see Tables 2 and 3 , for example)[ 1 ]. In contrast to experimental designs, which seek to test a specific hypothesis through deliberately manipulating the environment (like, for example, in a randomised controlled trial giving a new drug to randomly selected individuals and then comparing outcomes with controls),[ 9 ] the case study approach lends itself well to capturing information on more explanatory ' how ', 'what' and ' why ' questions, such as ' how is the intervention being implemented and received on the ground?'. The case study approach can offer additional insights into what gaps exist in its delivery or why one implementation strategy might be chosen over another. This in turn can help develop or refine theory, as shown in our study of the teaching of patient safety in undergraduate curricula (Table 4 )[ 6 , 10 ]. Key questions to consider when selecting the most appropriate study design are whether it is desirable or indeed possible to undertake a formal experimental investigation in which individuals and/or organisations are allocated to an intervention or control arm? Or whether the wish is to obtain a more naturalistic understanding of an issue? The former is ideally studied using a controlled experimental design, whereas the latter is more appropriately studied using a case study design.

Case studies may be approached in different ways depending on the epistemological standpoint of the researcher, that is, whether they take a critical (questioning one's own and others' assumptions), interpretivist (trying to understand individual and shared social meanings) or positivist approach (orientating towards the criteria of natural sciences, such as focusing on generalisability considerations) (Table 6 ). Whilst such a schema can be conceptually helpful, it may be appropriate to draw on more than one approach in any case study, particularly in the context of conducting health services research. Doolin has, for example, noted that in the context of undertaking interpretative case studies, researchers can usefully draw on a critical, reflective perspective which seeks to take into account the wider social and political environment that has shaped the case[ 11 ].

How are case studies conducted?

Here, we focus on the main stages of research activity when planning and undertaking a case study; the crucial stages are: defining the case; selecting the case(s); collecting and analysing the data; interpreting data; and reporting the findings.

Defining the case

Carefully formulated research question(s), informed by the existing literature and a prior appreciation of the theoretical issues and setting(s), are all important in appropriately and succinctly defining the case[ 8 , 12 ]. Crucially, each case should have a pre-defined boundary which clarifies the nature and time period covered by the case study (i.e. its scope, beginning and end), the relevant social group, organisation or geographical area of interest to the investigator, the types of evidence to be collected, and the priorities for data collection and analysis (see Table 7 )[ 1 ]. A theory driven approach to defining the case may help generate knowledge that is potentially transferable to a range of clinical contexts and behaviours; using theory is also likely to result in a more informed appreciation of, for example, how and why interventions have succeeded or failed[ 13 ].

For example, in our evaluation of the introduction of electronic health records in English hospitals (Table 3 ), we defined our cases as the NHS Trusts that were receiving the new technology[ 5 ]. Our focus was on how the technology was being implemented. However, if the primary research interest had been on the social and organisational dimensions of implementation, we might have defined our case differently as a grouping of healthcare professionals (e.g. doctors and/or nurses). The precise beginning and end of the case may however prove difficult to define. Pursuing this same example, when does the process of implementation and adoption of an electronic health record system really begin or end? Such judgements will inevitably be influenced by a range of factors, including the research question, theory of interest, the scope and richness of the gathered data and the resources available to the research team.

Selecting the case(s)

The decision on how to select the case(s) to study is a very important one that merits some reflection. In an intrinsic case study, the case is selected on its own merits[ 8 ]. The case is selected not because it is representative of other cases, but because of its uniqueness, which is of genuine interest to the researchers. This was, for example, the case in our study of the recruitment of minority ethnic participants into asthma research (Table 1 ) as our earlier work had demonstrated the marginalisation of minority ethnic people with asthma, despite evidence of disproportionate asthma morbidity[ 14 , 15 ]. In another example of an intrinsic case study, Hellstrom et al.[ 16 ] studied an elderly married couple living with dementia to explore how dementia had impacted on their understanding of home, their everyday life and their relationships.

For an instrumental case study, selecting a "typical" case can work well[ 8 ]. In contrast to the intrinsic case study, the particular case which is chosen is of less importance than selecting a case that allows the researcher to investigate an issue or phenomenon. For example, in order to gain an understanding of doctors' responses to health policy initiatives, Som undertook an instrumental case study interviewing clinicians who had a range of responsibilities for clinical governance in one NHS acute hospital trust[ 17 ]. Sampling a "deviant" or "atypical" case may however prove even more informative, potentially enabling the researcher to identify causal processes, generate hypotheses and develop theory.

In collective or multiple case studies, a number of cases are carefully selected. This offers the advantage of allowing comparisons to be made across several cases and/or replication. Choosing a "typical" case may enable the findings to be generalised to theory (i.e. analytical generalisation) or to test theory by replicating the findings in a second or even a third case (i.e. replication logic)[ 1 ]. Yin suggests two or three literal replications (i.e. predicting similar results) if the theory is straightforward and five or more if the theory is more subtle. However, critics might argue that selecting 'cases' in this way is insufficiently reflexive and ill-suited to the complexities of contemporary healthcare organisations.

The selected case study site(s) should allow the research team access to the group of individuals, the organisation, the processes or whatever else constitutes the chosen unit of analysis for the study. Access is therefore a central consideration; the researcher needs to come to know the case study site(s) well and to work cooperatively with them. Selected cases need to be not only interesting but also hospitable to the inquiry [ 8 ] if they are to be informative and answer the research question(s). Case study sites may also be pre-selected for the researcher, with decisions being influenced by key stakeholders. For example, our selection of case study sites in the evaluation of the implementation and adoption of electronic health record systems (see Table 3 ) was heavily influenced by NHS Connecting for Health, the government agency that was responsible for overseeing the National Programme for Information Technology (NPfIT)[ 5 ]. This prominent stakeholder had already selected the NHS sites (through a competitive bidding process) to be early adopters of the electronic health record systems and had negotiated contracts that detailed the deployment timelines.

It is also important to consider in advance the likely burden and risks associated with participation for those who (or the site(s) which) comprise the case study. Of particular importance is the obligation for the researcher to think through the ethical implications of the study (e.g. the risk of inadvertently breaching anonymity or confidentiality) and to ensure that potential participants/participating sites are provided with sufficient information to make an informed choice about joining the study. The outcome of providing this information might be that the emotive burden associated with participation, or the organisational disruption associated with supporting the fieldwork, is considered so high that the individuals or sites decide against participation.

In our example of evaluating implementations of electronic health record systems, given the restricted number of early adopter sites available to us, we sought purposively to select a diverse range of implementation cases among those that were available[ 5 ]. We chose a mixture of teaching, non-teaching and Foundation Trust hospitals, and examples of each of the three electronic health record systems procured centrally by the NPfIT. At one recruited site, it quickly became apparent that access was problematic because of competing demands on that organisation. Recognising the importance of full access and co-operative working for generating rich data, the research team decided not to pursue work at that site and instead to focus on other recruited sites.

Collecting the data

In order to develop a thorough understanding of the case, the case study approach usually involves the collection of multiple sources of evidence, using a range of quantitative (e.g. questionnaires, audits and analysis of routinely collected healthcare data) and more commonly qualitative techniques (e.g. interviews, focus groups and observations). The use of multiple sources of data (data triangulation) has been advocated as a way of increasing the internal validity of a study (i.e. the extent to which the method is appropriate to answer the research question)[ 8 , 18 – 21 ]. An underlying assumption is that data collected in different ways should lead to similar conclusions, and approaching the same issue from different angles can help develop a holistic picture of the phenomenon (Table 2 )[ 4 ].

Brazier and colleagues used a mixed-methods case study approach to investigate the impact of a cancer care programme[ 22 ]. Here, quantitative measures were collected with questionnaires before, and five months after, the start of the intervention which did not yield any statistically significant results. Qualitative interviews with patients however helped provide an insight into potentially beneficial process-related aspects of the programme, such as greater, perceived patient involvement in care. The authors reported how this case study approach provided a number of contextual factors likely to influence the effectiveness of the intervention and which were not likely to have been obtained from quantitative methods alone.

In collective or multiple case studies, data collection needs to be flexible enough to allow a detailed description of each individual case to be developed (e.g. the nature of different cancer care programmes), before considering the emerging similarities and differences in cross-case comparisons (e.g. to explore why one programme is more effective than another). It is important that data sources from different cases are, where possible, broadly comparable for this purpose even though they may vary in nature and depth.

Analysing, interpreting and reporting case studies

Making sense and offering a coherent interpretation of the typically disparate sources of data (whether qualitative alone or together with quantitative) is far from straightforward. Repeated reviewing and sorting of the voluminous and detail-rich data are integral to the process of analysis. In collective case studies, it is helpful to analyse data relating to the individual component cases first, before making comparisons across cases. Attention needs to be paid to variations within each case and, where relevant, the relationship between different causes, effects and outcomes[ 23 ]. Data will need to be organised and coded to allow the key issues, both derived from the literature and emerging from the dataset, to be easily retrieved at a later stage. An initial coding frame can help capture these issues and can be applied systematically to the whole dataset with the aid of a qualitative data analysis software package.

The Framework approach is a practical approach, comprising of five stages (familiarisation; identifying a thematic framework; indexing; charting; mapping and interpretation) , to managing and analysing large datasets particularly if time is limited, as was the case in our study of recruitment of South Asians into asthma research (Table 1 )[ 3 , 24 ]. Theoretical frameworks may also play an important role in integrating different sources of data and examining emerging themes. For example, we drew on a socio-technical framework to help explain the connections between different elements - technology; people; and the organisational settings within which they worked - in our study of the introduction of electronic health record systems (Table 3 )[ 5 ]. Our study of patient safety in undergraduate curricula drew on an evaluation-based approach to design and analysis, which emphasised the importance of the academic, organisational and practice contexts through which students learn (Table 4 )[ 6 ].

Case study findings can have implications both for theory development and theory testing. They may establish, strengthen or weaken historical explanations of a case and, in certain circumstances, allow theoretical (as opposed to statistical) generalisation beyond the particular cases studied[ 12 ]. These theoretical lenses should not, however, constitute a strait-jacket and the cases should not be "forced to fit" the particular theoretical framework that is being employed.

When reporting findings, it is important to provide the reader with enough contextual information to understand the processes that were followed and how the conclusions were reached. In a collective case study, researchers may choose to present the findings from individual cases separately before amalgamating across cases. Care must be taken to ensure the anonymity of both case sites and individual participants (if agreed in advance) by allocating appropriate codes or withholding descriptors. In the example given in Table 3 , we decided against providing detailed information on the NHS sites and individual participants in order to avoid the risk of inadvertent disclosure of identities[ 5 , 25 ].

What are the potential pitfalls and how can these be avoided?

The case study approach is, as with all research, not without its limitations. When investigating the formal and informal ways undergraduate students learn about patient safety (Table 4 ), for example, we rapidly accumulated a large quantity of data. The volume of data, together with the time restrictions in place, impacted on the depth of analysis that was possible within the available resources. This highlights a more general point of the importance of avoiding the temptation to collect as much data as possible; adequate time also needs to be set aside for data analysis and interpretation of what are often highly complex datasets.

Case study research has sometimes been criticised for lacking scientific rigour and providing little basis for generalisation (i.e. producing findings that may be transferable to other settings)[ 1 ]. There are several ways to address these concerns, including: the use of theoretical sampling (i.e. drawing on a particular conceptual framework); respondent validation (i.e. participants checking emerging findings and the researcher's interpretation, and providing an opinion as to whether they feel these are accurate); and transparency throughout the research process (see Table 8 )[ 8 , 18 – 21 , 23 , 26 ]. Transparency can be achieved by describing in detail the steps involved in case selection, data collection, the reasons for the particular methods chosen, and the researcher's background and level of involvement (i.e. being explicit about how the researcher has influenced data collection and interpretation). Seeking potential, alternative explanations, and being explicit about how interpretations and conclusions were reached, help readers to judge the trustworthiness of the case study report. Stake provides a critique checklist for a case study report (Table 9 )[ 8 ].

Conclusions

The case study approach allows, amongst other things, critical events, interventions, policy developments and programme-based service reforms to be studied in detail in a real-life context. It should therefore be considered when an experimental design is either inappropriate to answer the research questions posed or impossible to undertake. Considering the frequency with which implementations of innovations are now taking place in healthcare settings and how well the case study approach lends itself to in-depth, complex health service research, we believe this approach should be more widely considered by researchers. Though inherently challenging, the research case study can, if carefully conceptualised and thoughtfully undertaken and reported, yield powerful insights into many important aspects of health and healthcare delivery.

Yin RK: Case study research, design and method. 2009, London: Sage Publications Ltd., 4

Google Scholar  

Keen J, Packwood T: Qualitative research; case study evaluation. BMJ. 1995, 311: 444-446.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Sheikh A, Halani L, Bhopal R, Netuveli G, Partridge M, Car J, et al: Facilitating the Recruitment of Minority Ethnic People into Research: Qualitative Case Study of South Asians and Asthma. PLoS Med. 2009, 6 (10): 1-11.

Article   Google Scholar  

Pinnock H, Huby G, Powell A, Kielmann T, Price D, Williams S, et al: The process of planning, development and implementation of a General Practitioner with a Special Interest service in Primary Care Organisations in England and Wales: a comparative prospective case study. Report for the National Co-ordinating Centre for NHS Service Delivery and Organisation R&D (NCCSDO). 2008, [ http://www.sdo.nihr.ac.uk/files/project/99-final-report.pdf ]

Robertson A, Cresswell K, Takian A, Petrakaki D, Crowe S, Cornford T, et al: Prospective evaluation of the implementation and adoption of NHS Connecting for Health's national electronic health record in secondary care in England: interim findings. BMJ. 2010, 41: c4564-

Pearson P, Steven A, Howe A, Sheikh A, Ashcroft D, Smith P, the Patient Safety Education Study Group: Learning about patient safety: organisational context and culture in the education of healthcare professionals. J Health Serv Res Policy. 2010, 15: 4-10. 10.1258/jhsrp.2009.009052.

Article   PubMed   Google Scholar  

van Harten WH, Casparie TF, Fisscher OA: The evaluation of the introduction of a quality management system: a process-oriented case study in a large rehabilitation hospital. Health Policy. 2002, 60 (1): 17-37. 10.1016/S0168-8510(01)00187-7.

Stake RE: The art of case study research. 1995, London: Sage Publications Ltd.

Sheikh A, Smeeth L, Ashcroft R: Randomised controlled trials in primary care: scope and application. Br J Gen Pract. 2002, 52 (482): 746-51.

PubMed   PubMed Central   Google Scholar  

King G, Keohane R, Verba S: Designing Social Inquiry. 1996, Princeton: Princeton University Press

Doolin B: Information technology as disciplinary technology: being critical in interpretative research on information systems. Journal of Information Technology. 1998, 13: 301-311. 10.1057/jit.1998.8.

George AL, Bennett A: Case studies and theory development in the social sciences. 2005, Cambridge, MA: MIT Press

Eccles M, the Improved Clinical Effectiveness through Behavioural Research Group (ICEBeRG): Designing theoretically-informed implementation interventions. Implementation Science. 2006, 1: 1-8. 10.1186/1748-5908-1-1.

Article   PubMed Central   Google Scholar  

Netuveli G, Hurwitz B, Levy M, Fletcher M, Barnes G, Durham SR, Sheikh A: Ethnic variations in UK asthma frequency, morbidity, and health-service use: a systematic review and meta-analysis. Lancet. 2005, 365 (9456): 312-7.

Sheikh A, Panesar SS, Lasserson T, Netuveli G: Recruitment of ethnic minorities to asthma studies. Thorax. 2004, 59 (7): 634-

CAS   PubMed   PubMed Central   Google Scholar  

Hellström I, Nolan M, Lundh U: 'We do things together': A case study of 'couplehood' in dementia. Dementia. 2005, 4: 7-22. 10.1177/1471301205049188.

Som CV: Nothing seems to have changed, nothing seems to be changing and perhaps nothing will change in the NHS: doctors' response to clinical governance. International Journal of Public Sector Management. 2005, 18: 463-477. 10.1108/09513550510608903.

Lincoln Y, Guba E: Naturalistic inquiry. 1985, Newbury Park: Sage Publications

Barbour RS: Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?. BMJ. 2001, 322: 1115-1117. 10.1136/bmj.322.7294.1115.

Mays N, Pope C: Qualitative research in health care: Assessing quality in qualitative research. BMJ. 2000, 320: 50-52. 10.1136/bmj.320.7226.50.

Mason J: Qualitative researching. 2002, London: Sage

Brazier A, Cooke K, Moravan V: Using Mixed Methods for Evaluating an Integrative Approach to Cancer Care: A Case Study. Integr Cancer Ther. 2008, 7: 5-17. 10.1177/1534735407313395.

Miles MB, Huberman M: Qualitative data analysis: an expanded sourcebook. 1994, CA: Sage Publications Inc., 2

Pope C, Ziebland S, Mays N: Analysing qualitative data. Qualitative research in health care. BMJ. 2000, 320: 114-116. 10.1136/bmj.320.7227.114.

Cresswell KM, Worth A, Sheikh A: Actor-Network Theory and its role in understanding the implementation of information technology developments in healthcare. BMC Med Inform Decis Mak. 2010, 10 (1): 67-10.1186/1472-6947-10-67.

Article   PubMed   PubMed Central   Google Scholar  

Malterud K: Qualitative research: standards, challenges, and guidelines. Lancet. 2001, 358: 483-488. 10.1016/S0140-6736(01)05627-6.

Article   CAS   PubMed   Google Scholar  

Yin R: Case study research: design and methods. 1994, Thousand Oaks, CA: Sage Publishing, 2

Yin R: Enhancing the quality of case studies in health services research. Health Serv Res. 1999, 34: 1209-1224.

Green J, Thorogood N: Qualitative methods for health research. 2009, Los Angeles: Sage, 2

Howcroft D, Trauth E: Handbook of Critical Information Systems Research, Theory and Application. 2005, Cheltenham, UK: Northampton, MA, USA: Edward Elgar

Book   Google Scholar  

Blakie N: Approaches to Social Enquiry. 1993, Cambridge: Polity Press

Doolin B: Power and resistance in the implementation of a medical management information system. Info Systems J. 2004, 14: 343-362. 10.1111/j.1365-2575.2004.00176.x.

Bloomfield BP, Best A: Management consultants: systems development, power and the translation of problems. Sociological Review. 1992, 40: 533-560.

Shanks G, Parr A: Positivist, single case study research in information systems: A critical analysis. Proceedings of the European Conference on Information Systems. 2003, Naples

Pre-publication history

The pre-publication history for this paper can be accessed here: http://www.biomedcentral.com/1471-2288/11/100/prepub

Download references

Acknowledgements

We are grateful to the participants and colleagues who contributed to the individual case studies that we have drawn on. This work received no direct funding, but it has been informed by projects funded by Asthma UK, the NHS Service Delivery Organisation, NHS Connecting for Health Evaluation Programme, and Patient Safety Research Portfolio. We would also like to thank the expert reviewers for their insightful and constructive feedback. Our thanks are also due to Dr. Allison Worth who commented on an earlier draft of this manuscript.

Author information

Authors and affiliations.

Division of Primary Care, The University of Nottingham, Nottingham, UK

Sarah Crowe & Anthony Avery

Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, UK

Kathrin Cresswell, Ann Robertson & Aziz Sheikh

School of Health in Social Science, The University of Edinburgh, Edinburgh, UK

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Sarah Crowe .

Additional information

Competing interests.

The authors declare that they have no competing interests.

Authors' contributions

AS conceived this article. SC, KC and AR wrote this paper with GH, AA and AS all commenting on various drafts. SC and AS are guarantors.

Rights and permissions

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and permissions

About this article

Cite this article.

Crowe, S., Cresswell, K., Robertson, A. et al. The case study approach. BMC Med Res Methodol 11 , 100 (2011). https://doi.org/10.1186/1471-2288-11-100

Download citation

Received : 29 November 2010

Accepted : 27 June 2011

Published : 27 June 2011

DOI : https://doi.org/10.1186/1471-2288-11-100

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Case Study Approach
• Electronic Health Record System
• Case Study Design
• Case Study Site
• Case Study Report

BMC Medical Research Methodology

ISSN: 1471-2288

• General enquiries: [email protected]

• Search Menu
• Sign in through your institution
• Browse content in Arts and Humanities
• Browse content in Archaeology
• Anglo-Saxon and Medieval Archaeology
• Archaeological Methodology and Techniques
• Archaeology by Region
• Archaeology of Religion
• Archaeology of Trade and Exchange
• Biblical Archaeology
• Contemporary and Public Archaeology
• Environmental Archaeology
• Historical Archaeology
• History and Theory of Archaeology
• Industrial Archaeology
• Landscape Archaeology
• Mortuary Archaeology
• Prehistoric Archaeology
• Underwater Archaeology
• Zooarchaeology
• Browse content in Architecture
• Architectural Structure and Design
• History of Architecture
• Residential and Domestic Buildings
• Theory of Architecture
• Browse content in Art
• Art Subjects and Themes
• History of Art
• Industrial and Commercial Art
• Theory of Art
• Biographical Studies
• Byzantine Studies
• Browse content in Classical Studies
• Classical History
• Classical Philosophy
• Classical Mythology
• Classical Literature
• Classical Reception
• Classical Art and Architecture
• Classical Oratory and Rhetoric
• Greek and Roman Papyrology
• Greek and Roman Epigraphy
• Greek and Roman Law
• Greek and Roman Archaeology
• Late Antiquity
• Religion in the Ancient World
• Digital Humanities
• Browse content in History
• Colonialism and Imperialism
• Diplomatic History
• Environmental History
• Genealogy, Heraldry, Names, and Honours
• Genocide and Ethnic Cleansing
• Historical Geography
• History by Period
• History of Emotions
• History of Agriculture
• History of Education
• History of Gender and Sexuality
• Industrial History
• Intellectual History
• International History
• Labour History
• Legal and Constitutional History
• Local and Family History
• Maritime History
• Military History
• National Liberation and Post-Colonialism
• Oral History
• Political History
• Public History
• Regional and National History
• Revolutions and Rebellions
• Slavery and Abolition of Slavery
• Social and Cultural History
• Theory, Methods, and Historiography
• Urban History
• World History
• Browse content in Language Teaching and Learning
• Language Learning (Specific Skills)
• Language Teaching Theory and Methods
• Browse content in Linguistics
• Applied Linguistics
• Cognitive Linguistics
• Computational Linguistics
• Forensic Linguistics
• Grammar, Syntax and Morphology
• Historical and Diachronic Linguistics
• History of English
• Language Evolution
• Language Reference
• Language Acquisition
• Language Variation
• Language Families
• Lexicography
• Linguistic Anthropology
• Linguistic Theories
• Linguistic Typology
• Phonetics and Phonology
• Psycholinguistics
• Sociolinguistics
• Translation and Interpretation
• Writing Systems
• Browse content in Literature
• Bibliography
• Children's Literature Studies
• Literary Studies (Romanticism)
• Literary Studies (American)
• Literary Studies (Asian)
• Literary Studies (European)
• Literary Studies (Eco-criticism)
• Literary Studies (Modernism)
• Literary Studies - World
• Literary Studies (1500 to 1800)
• Literary Studies (19th Century)
• Literary Studies (20th Century onwards)
• Literary Studies (African American Literature)
• Literary Studies (British and Irish)
• Literary Studies (Early and Medieval)
• Literary Studies (Fiction, Novelists, and Prose Writers)
• Literary Studies (Gender Studies)
• Literary Studies (Graphic Novels)
• Literary Studies (History of the Book)
• Literary Studies (Plays and Playwrights)
• Literary Studies (Poetry and Poets)
• Literary Studies (Postcolonial Literature)
• Literary Studies (Queer Studies)
• Literary Studies (Science Fiction)
• Literary Studies (Travel Literature)
• Literary Studies (War Literature)
• Literary Studies (Women's Writing)
• Literary Theory and Cultural Studies
• Mythology and Folklore
• Shakespeare Studies and Criticism
• Browse content in Media Studies
• Browse content in Music
• Applied Music
• Dance and Music
• Ethics in Music
• Ethnomusicology
• Gender and Sexuality in Music
• Medicine and Music
• Music Cultures
• Music and Media
• Music and Religion
• Music and Culture
• Music Education and Pedagogy
• Music Theory and Analysis
• Musical Scores, Lyrics, and Libretti
• Musical Structures, Styles, and Techniques
• Musicology and Music History
• Performance Practice and Studies
• Race and Ethnicity in Music
• Sound Studies
• Browse content in Performing Arts
• Browse content in Philosophy
• Aesthetics and Philosophy of Art
• Epistemology
• Feminist Philosophy
• History of Western Philosophy
• Metaphysics
• Moral Philosophy
• Non-Western Philosophy
• Philosophy of Language
• Philosophy of Mind
• Philosophy of Perception
• Philosophy of Science
• Philosophy of Action
• Philosophy of Law
• Philosophy of Religion
• Philosophy of Mathematics and Logic
• Practical Ethics
• Social and Political Philosophy
• Browse content in Religion
• Biblical Studies
• Christianity
• East Asian Religions
• History of Religion
• Judaism and Jewish Studies
• Qumran Studies
• Religion and Education
• Religion and Health
• Religion and Politics
• Religion and Science
• Religion and Law
• Religion and Art, Literature, and Music
• Religious Studies
• Browse content in Society and Culture
• Cookery, Food, and Drink
• Cultural Studies
• Customs and Traditions
• Ethical Issues and Debates
• Hobbies, Games, Arts and Crafts
• Natural world, Country Life, and Pets
• Popular Beliefs and Controversial Knowledge
• Sports and Outdoor Recreation
• Technology and Society
• Travel and Holiday
• Visual Culture
• Browse content in Law
• Arbitration
• Browse content in Company and Commercial Law
• Commercial Law
• Company Law
• Browse content in Comparative Law
• Systems of Law
• Competition Law
• Browse content in Constitutional and Administrative Law
• Government Powers
• Judicial Review
• Local Government Law
• Military and Defence Law
• Parliamentary and Legislative Practice
• Construction Law
• Contract Law
• Browse content in Criminal Law
• Criminal Procedure
• Criminal Evidence Law
• Sentencing and Punishment
• Employment and Labour Law
• Environment and Energy Law
• Browse content in Financial Law
• Banking Law
• Insolvency Law
• History of Law
• Human Rights and Immigration
• Intellectual Property Law
• Browse content in International Law
• Private International Law and Conflict of Laws
• Public International Law
• IT and Communications Law
• Jurisprudence and Philosophy of Law
• Law and Politics
• Law and Society
• Browse content in Legal System and Practice
• Courts and Procedure
• Legal Skills and Practice
• Primary Sources of Law
• Regulation of Legal Profession
• Medical and Healthcare Law
• Browse content in Policing
• Criminal Investigation and Detection
• Police and Security Services
• Police Procedure and Law
• Police Regional Planning
• Browse content in Property Law
• Personal Property Law
• Study and Revision
• Terrorism and National Security Law
• Browse content in Trusts Law
• Wills and Probate or Succession
• Browse content in Medicine and Health
• Browse content in Allied Health Professions
• Arts Therapies
• Clinical Science
• Dietetics and Nutrition
• Occupational Therapy
• Operating Department Practice
• Physiotherapy
• Radiography
• Speech and Language Therapy
• Browse content in Anaesthetics
• General Anaesthesia
• Neuroanaesthesia
• Clinical Neuroscience
• Browse content in Clinical Medicine
• Acute Medicine
• Cardiovascular Medicine
• Clinical Genetics
• Clinical Pharmacology and Therapeutics
• Dermatology
• Endocrinology and Diabetes
• Gastroenterology
• Genito-urinary Medicine
• Geriatric Medicine
• Infectious Diseases
• Medical Toxicology
• Medical Oncology
• Pain Medicine
• Palliative Medicine
• Rehabilitation Medicine
• Respiratory Medicine and Pulmonology
• Rheumatology
• Sleep Medicine
• Sports and Exercise Medicine
• Community Medical Services
• Critical Care
• Emergency Medicine
• Forensic Medicine
• Haematology
• History of Medicine
• Browse content in Medical Skills
• Clinical Skills
• Communication Skills
• Nursing Skills
• Surgical Skills
• Browse content in Medical Dentistry
• Oral and Maxillofacial Surgery
• Paediatric Dentistry
• Restorative Dentistry and Orthodontics
• Surgical Dentistry
• Medical Ethics
• Medical Statistics and Methodology
• Browse content in Neurology
• Clinical Neurophysiology
• Neuropathology
• Nursing Studies
• Browse content in Obstetrics and Gynaecology
• Gynaecology
• Occupational Medicine
• Ophthalmology
• Otolaryngology (ENT)
• Browse content in Paediatrics
• Neonatology
• Browse content in Pathology
• Chemical Pathology
• Clinical Cytogenetics and Molecular Genetics
• Histopathology
• Medical Microbiology and Virology
• Patient Education and Information
• Browse content in Pharmacology
• Psychopharmacology
• Browse content in Popular Health
• Caring for Others
• Complementary and Alternative Medicine
• Self-help and Personal Development
• Browse content in Preclinical Medicine
• Cell Biology
• Molecular Biology and Genetics
• Reproduction, Growth and Development
• Primary Care
• Professional Development in Medicine
• Browse content in Psychiatry
• Addiction Medicine
• Child and Adolescent Psychiatry
• Forensic Psychiatry
• Learning Disabilities
• Old Age Psychiatry
• Psychotherapy
• Browse content in Public Health and Epidemiology
• Epidemiology
• Public Health
• Browse content in Radiology
• Clinical Radiology
• Interventional Radiology
• Nuclear Medicine
• Radiation Oncology
• Reproductive Medicine
• Browse content in Surgery
• Cardiothoracic Surgery
• Gastro-intestinal and Colorectal Surgery
• General Surgery
• Neurosurgery
• Paediatric Surgery
• Peri-operative Care
• Plastic and Reconstructive Surgery
• Surgical Oncology
• Transplant Surgery
• Trauma and Orthopaedic Surgery
• Vascular Surgery
• Browse content in Science and Mathematics
• Browse content in Biological Sciences
• Aquatic Biology
• Biochemistry
• Bioinformatics and Computational Biology
• Developmental Biology
• Ecology and Conservation
• Evolutionary Biology
• Genetics and Genomics
• Microbiology
• Molecular and Cell Biology
• Natural History
• Plant Sciences and Forestry
• Research Methods in Life Sciences
• Structural Biology
• Systems Biology
• Zoology and Animal Sciences
• Browse content in Chemistry
• Analytical Chemistry
• Computational Chemistry
• Crystallography
• Environmental Chemistry
• Industrial Chemistry
• Inorganic Chemistry
• Materials Chemistry
• Medicinal Chemistry
• Mineralogy and Gems
• Organic Chemistry
• Physical Chemistry
• Polymer Chemistry
• Study and Communication Skills in Chemistry
• Theoretical Chemistry
• Browse content in Computer Science
• Artificial Intelligence
• Computer Architecture and Logic Design
• Game Studies
• Human-Computer Interaction
• Mathematical Theory of Computation
• Programming Languages
• Software Engineering
• Systems Analysis and Design
• Virtual Reality
• Browse content in Computing
• Business Applications
• Computer Security
• Computer Games
• Computer Networking and Communications
• Digital Lifestyle
• Graphical and Digital Media Applications
• Operating Systems
• Browse content in Earth Sciences and Geography
• Atmospheric Sciences
• Environmental Geography
• Geology and the Lithosphere
• Maps and Map-making
• Meteorology and Climatology
• Oceanography and Hydrology
• Palaeontology
• Physical Geography and Topography
• Regional Geography
• Soil Science
• Urban Geography
• Browse content in Engineering and Technology
• Agriculture and Farming
• Biological Engineering
• Civil Engineering, Surveying, and Building
• Electronics and Communications Engineering
• Energy Technology
• Engineering (General)
• Environmental Science, Engineering, and Technology
• History of Engineering and Technology
• Mechanical Engineering and Materials
• Technology of Industrial Chemistry
• Transport Technology and Trades
• Browse content in Environmental Science
• Applied Ecology (Environmental Science)
• Conservation of the Environment (Environmental Science)
• Environmental Sustainability
• Environmentalist Thought and Ideology (Environmental Science)
• Management of Land and Natural Resources (Environmental Science)
• Natural Disasters (Environmental Science)
• Nuclear Issues (Environmental Science)
• Pollution and Threats to the Environment (Environmental Science)
• Social Impact of Environmental Issues (Environmental Science)
• History of Science and Technology
• Browse content in Materials Science
• Ceramics and Glasses
• Composite Materials
• Metals, Alloying, and Corrosion
• Nanotechnology
• Browse content in Mathematics
• Applied Mathematics
• Biomathematics and Statistics
• History of Mathematics
• Mathematical Education
• Mathematical Finance
• Mathematical Analysis
• Numerical and Computational Mathematics
• Probability and Statistics
• Pure Mathematics
• Browse content in Neuroscience
• Cognition and Behavioural Neuroscience
• Development of the Nervous System
• Disorders of the Nervous System
• History of Neuroscience
• Invertebrate Neurobiology
• Molecular and Cellular Systems
• Neuroendocrinology and Autonomic Nervous System
• Neuroscientific Techniques
• Sensory and Motor Systems
• Browse content in Physics
• Astronomy and Astrophysics
• Atomic, Molecular, and Optical Physics
• Biological and Medical Physics
• Classical Mechanics
• Computational Physics
• Condensed Matter Physics
• Electromagnetism, Optics, and Acoustics
• History of Physics
• Mathematical and Statistical Physics
• Measurement Science
• Nuclear Physics
• Particles and Fields
• Plasma Physics
• Quantum Physics
• Relativity and Gravitation
• Semiconductor and Mesoscopic Physics
• Browse content in Psychology
• Affective Sciences
• Clinical Psychology
• Cognitive Psychology
• Cognitive Neuroscience
• Criminal and Forensic Psychology
• Developmental Psychology
• Educational Psychology
• Evolutionary Psychology
• Health Psychology
• History and Systems in Psychology
• Music Psychology
• Neuropsychology
• Organizational Psychology
• Psychological Assessment and Testing
• Psychology of Human-Technology Interaction
• Psychology Professional Development and Training
• Research Methods in Psychology
• Social Psychology
• Browse content in Social Sciences
• Browse content in Anthropology
• Anthropology of Religion
• Human Evolution
• Medical Anthropology
• Physical Anthropology
• Regional Anthropology
• Social and Cultural Anthropology
• Theory and Practice of Anthropology
• Browse content in Business and Management
• Business Ethics
• Business Strategy
• Business History
• Business and Technology
• Business and Government
• Business and the Environment
• Comparative Management
• Corporate Governance
• Corporate Social Responsibility
• Entrepreneurship
• Health Management
• Human Resource Management
• Industrial and Employment Relations
• Industry Studies
• Information and Communication Technologies
• International Business
• Knowledge Management
• Management and Management Techniques
• Operations Management
• Organizational Theory and Behaviour
• Pensions and Pension Management
• Public and Nonprofit Management
• Strategic Management
• Supply Chain Management
• Browse content in Criminology and Criminal Justice
• Criminal Justice
• Criminology
• Forms of Crime
• International and Comparative Criminology
• Youth Violence and Juvenile Justice
• Development Studies
• Browse content in Economics
• Agricultural, Environmental, and Natural Resource Economics
• Asian Economics
• Behavioural Finance
• Behavioural Economics and Neuroeconomics
• Econometrics and Mathematical Economics
• Economic History
• Economic Systems
• Economic Methodology
• Economic Development and Growth
• Financial Markets
• Financial Institutions and Services
• General Economics and Teaching
• Health, Education, and Welfare
• History of Economic Thought
• International Economics
• Labour and Demographic Economics
• Law and Economics
• Macroeconomics and Monetary Economics
• Microeconomics
• Public Economics
• Urban, Rural, and Regional Economics
• Welfare Economics
• Browse content in Education
• Adult Education and Continuous Learning
• Care and Counselling of Students
• Early Childhood and Elementary Education
• Educational Equipment and Technology
• Educational Strategies and Policy
• Higher and Further Education
• Organization and Management of Education
• Philosophy and Theory of Education
• Schools Studies
• Secondary Education
• Teaching of a Specific Subject
• Teaching of Specific Groups and Special Educational Needs
• Teaching Skills and Techniques
• Browse content in Environment
• Applied Ecology (Social Science)
• Climate Change
• Conservation of the Environment (Social Science)
• Environmentalist Thought and Ideology (Social Science)
• Natural Disasters (Environment)
• Social Impact of Environmental Issues (Social Science)
• Browse content in Human Geography
• Cultural Geography
• Economic Geography
• Political Geography
• Browse content in Interdisciplinary Studies
• Communication Studies
• Museums, Libraries, and Information Sciences
• Browse content in Politics
• African Politics
• Asian Politics
• Chinese Politics
• Comparative Politics
• Conflict Politics
• Elections and Electoral Studies
• Environmental Politics
• Ethnic Politics
• European Union
• Foreign Policy
• Gender and Politics
• Human Rights and Politics
• Indian Politics
• International Relations
• International Organization (Politics)
• International Political Economy
• Irish Politics
• Latin American Politics
• Middle Eastern Politics
• Political Behaviour
• Political Economy
• Political Institutions
• Political Methodology
• Political Communication
• Political Philosophy
• Political Sociology
• Political Theory
• Politics and Law
• Politics of Development
• Public Policy
• Public Administration
• Quantitative Political Methodology
• Regional Political Studies
• Russian Politics
• Security Studies
• State and Local Government
• UK Politics
• US Politics
• Browse content in Regional and Area Studies
• African Studies
• Asian Studies
• East Asian Studies
• Japanese Studies
• Latin American Studies
• Middle Eastern Studies
• Native American Studies
• Scottish Studies
• Browse content in Research and Information
• Research Methods
• Browse content in Social Work
• Addictions and Substance Misuse
• Adoption and Fostering
• Care of the Elderly
• Child and Adolescent Social Work
• Couple and Family Social Work
• Direct Practice and Clinical Social Work
• Emergency Services
• Human Behaviour and the Social Environment
• International and Global Issues in Social Work
• Mental and Behavioural Health
• Social Justice and Human Rights
• Social Policy and Advocacy
• Social Work and Crime and Justice
• Social Work Macro Practice
• Social Work Practice Settings
• Social Work Research and Evidence-based Practice
• Welfare and Benefit Systems
• Browse content in Sociology
• Childhood Studies
• Community Development
• Comparative and Historical Sociology
• Economic Sociology
• Gender and Sexuality
• Gerontology and Ageing
• Health, Illness, and Medicine
• Marriage and the Family
• Migration Studies
• Occupations, Professions, and Work
• Organizations
• Population and Demography
• Race and Ethnicity
• Social Theory
• Social Movements and Social Change
• Social Research and Statistics
• Social Stratification, Inequality, and Mobility
• Sociology of Religion
• Sociology of Education
• Sport and Leisure
• Urban and Rural Studies
• Browse content in Warfare and Defence
• Defence Strategy, Planning, and Research
• Land Forces and Warfare
• Military Administration
• Military Life and Institutions
• Naval Forces and Warfare
• Other Warfare and Defence Issues
• Peace Studies and Conflict Resolution
• Weapons and Equipment

• < Previous chapter
• Next chapter >

23 Case Study Research: In-Depth Understanding in Context

Helen Simons, School of Education, University of Southampton

• Published: 02 September 2020
• Cite Icon Cite
• Permissions Icon Permissions

This chapter explores case study as a major approach to research and evaluation. After first noting various contexts in which case studies are commonly used, the chapter focuses on case study research directly. Strengths and potential problematic issues are outlined, followed by key phases of the process. The chapter emphasizes how important it is to design the case, to collect and interpret data in ways that highlight the qualitative, to have an ethical practice that values multiple perspectives and political interests, and to report creatively to facilitate use in policymaking and practice. Finally, the chapter explores how to generalize from the single case. Concluding issues center on the need to think more imaginatively about design and the range of methods and forms of reporting required to persuade audiences to value qualitative ways of knowing in case study research.

Introduction

This chapter explores case study as a major approach to research and evaluation using primarily qualitative methods, as well as documentary sources, contemporaneous or historical. However, this is not the only way in which case study can be conceived. No one has a monopoly on the term. While sharing a focus on the singular in a particular context, case study has a wide variety of uses, not all associated with research. A case study, in common parlance, documents a particular situation or event in detail in a specific sociopolitical context. The particular can be a person, a classroom, an institution, a program, or a policy. In the sections that follow, I identify different ways in which case study is used before focusing directly on qualitative case study research. However, first I wish to indicate how I came to advocate and practice this form of research. Origins, context, and opportunity often shape the research processes we endorse. It is helpful for the reader, I think, to know how I came to the perspective I hold.

The Beginnings

I first came to appreciate and enjoy the virtues of case study research when I entered the field of curriculum evaluation and research in the 1970s. The dominant research paradigm for educational research at that time was experimental or quasi-experimental, cost–benefit, or systems analysis, and the dominant curriculum model was aims and objectives (House, 1993 ). The field was dominated, in effect, by a psychometric view of research in which quantitative methods were preeminent. But the innovative projects we were asked to evaluate (predominantly, but not exclusively, in the humanities) were not amenable to such methodologies. The projects were challenging to the status quo of institutions, involved people interpreting the policy and programs, were implemented differently in different contexts and regions, and had many unexpected effects.

We had no choice but to seek other ways to evaluate these complex programs, and case study was the methodology we found ourselves exploring to understand how the projects were being implemented, why they had positive effects in some regions of the country and not others, and what the outcomes meant in different sociopolitical and cultural contexts. What better way to do this than to talk with people to see how they interpreted the “new” curriculum; to watch how teachers and students put it into practice; to document transactions, outcomes, and unexpected consequences; and to interpret all in the specific context of the case (Simons, 1971 , 1987 , ch. 3). From this point on and in further studies, case study in educational research and evaluation came to be a major methodology for understanding complex educational and social programs. It also extended to other practice professions, such as nursing, health, and social care (Greenhalgh & Worrall, 1997 ; Shaw & Gould, 2001 ; Zucker, 2001 ). (For further details of the evolution of the case study approach and qualitative methodologies in evaluation, see Greene, 2000 ; House, 1993 , pp. 2–3; Simons, 2009 , pp. 14–18).

This was not exactly the beginning of case study, of course. It has a long history in many disciplines (Gomm, Hammersley, & Foster, 2004 ; Platt, 2007 ; Ragin, 1992 ; Simons, 1980 ), many aspects of which form part of case study practice to this day. But its evolution in the context just described was a major move in the contemporary evolution of the logic of evaluative inquiry (House, 1980 ). It also coincided with movement toward the qualitative in other disciplines, such as sociology and psychology. This was all part of what Denzin & Lincoln ( 1994 ) termed “a quiet methodological revolution” (p. ix) in qualitative inquiry that had been evolving over the past two decades.

There is a further reason why I continue to advocate and practice case study research and evaluation to this day, and that is my personal predilection for trying to understand and represent complexity, for puzzling through the ambiguities that exist in many contexts and programs, and for presenting and negotiating different values and interests in fair and just ways.

Put more simply, I like interacting with people, listening to their stories, trials and tribulations—giving them a voice in understanding the contexts and projects with which they are involved and finding ways to share these with a range of audiences. In other words, the move toward case study methodology suited my preference for how I learn—through observation of people, events and social interaction in particular sociopolitical contexts.

Concepts and Purposes of Case Study

Before exploring case study as it has come to be established in educational research and evaluation since the mid-sixties I wish to acknowledge other uses of case study. More often than not, these relate to purpose, and appropriately so in their different contexts, but many do not have a research intention. For a study to count as research, it would need to be a systematic investigation generating evidence that leads to “new” knowledge that is made public and open to scrutiny. There are many ways to conduct research stemming from different traditions and disciplines, but they all, in different ways, involve these characteristics.

Everyday Usage: Stories We Tell

The most familiar of these uses of case study is the everyday reference to a person, an anecdote or story illustrative of a particular incident, event, or experience of that person. It is often a short, reported account seen commonly in journalism but also in books exploring a phenomenon, such as recovery from serious accidents or tragedies where the author chooses to illustrate the story or argument with a “lived” example. The story is sometimes written by the author and sometimes by the person whose tale it is. “Let me share with you a story” is a phrase frequently heard.

The spirit behind this everyday usage and its power to connect can be seen in a report by Tim Adams of the London Olympics opening ceremony’s dramatization by Danny Boyle.

It was the point when we suddenly collectively wised up to the idea that what we are about to receive over the next two weeks was not only about “legacy collateral” and “targeted deliverables,” not about G4S failings and traffic lanes and branding opportunities, but about the second-by-second possibilities of human endeavour and spirit and communality, enacted in multiple places and all at the same time. Stories in other words (Adams, 2012 ).

This was a collective story, of course, not an individual one, but it does convey some of the major characteristics of case study—that richness of detail, time, place, multiple happenings, and experiences—that are also manifest in case study research, although carefully evidenced in the latter instance. We can see from this common usage how people have come to associate case study with story. I return to this thread in the reporting section.

Individual Cases in the Professions

In professional settings, in health and social care, case studies, often called case histories , are used to accurately record a person’s health or social care history and his or her current symptoms, experience, and treatment. These case histories include facts, as well as judgments and observations about the person’s reaction to situations or medication. Usually they are confidential. Not dissimilar is the detailed documentation of a case in law, often termed a case precedent when referred to in a court case to support an argument being made. However, in law there is a difference in that such case precedents are publicly documented, whereas in health and social care, confidentiality of the client is the prime concern.

Case Studies in Teaching

Exemplars of practice.

In education, but also in health and social care training contexts, case studies have long been used as exemplars of practice. These are brief descriptions with some detail of a person or project’s experience in an area of practice. Though frequently reported accounts, they are based on a person’s experience and sometimes on previous research.

Case Scenarios

Management studies are a further context in which case studies are often used. Here the case is more like a scenario outlining a particular problem situation for the management student to resolve. These scenarios may be based on research, but frequently are hypothetical situations used to raise issues for discussion and resolution. What distinguishes these case scenarios and the case exemplars in education from case study research is the intention to use them for teaching purposes.

Country Case Studies

Then there are case studies of programs, projects, and even countries, as in international development, where a whole-country study might be termed a case study or, in the context of the Organization for Economic Co-operation and Development, which examines the state of the art of a subject, such as education or environmental science in one or several countries. This may be a contemporaneous study and/or what transpired in a program over a period of time. Such studies often do have a research base, but frequently are reported accounts that do not detail the design, methodology, and analysis of the case as a research case study would do. Nor do they report in ways that give readers a vicarious experience, through observations, incidents, and voices of participants, of what it is like to live in the particular context of the case. Such case studies tend to be more knowledge and information focused than experiential.

Case Study as History

Closer to a research context is case study as history—what transpired at a certain time in a certain place. This is likely to be supported by documentary evidence but not primary data, unless it is an oral history (see Leavy, 2011 , for the evolution and practice of oral history as a research method). In education, in the late 1970s, Stenhouse ( 1978 ) experimented with a case study archive. Using contemporaneous data gathering, primarily through interviewing, he envisaged this database, which he termed a case record , forming an archive from which different individuals, at some later date, could write a case study . This approach uses case study as a documentary source to begin to generate a history of education, as indicated in the subtitle of Stenhouse’s 1978 paper, “Towards a Contemporary History of Education.”

Case Study Research

From here on, my focus is on case study research per se, adopting for this purpose the following definition: “Case study is an in-depth exploration from multiple perspectives of the complexity and uniqueness of a particular project, policy, institution or system in a “real-life” context. It is research based, inclusive of different methods and is evidence-led” (Simons, 2009 , p. 21). For further related definitions of case study, see Stake ( 1995 ), Merriam ( 1988 ), and Chadderton and Torrance ( 2011 ). For definitions from a slightly different perspective, see Yin ( 2004 ) and Thomas ( 2016 , p. 23).

Not Defined by Method or Perspective

The inclusion of different methods in the definition quoted above signals that case study research is not defined by methodology or method. What defines case study is its singularity and the concept and boundary of the case. It is theoretically possible to conduct a case study using primarily quantitative data if this is the best way of providing evidence to inform the issues the case is exploring. This may not happen often, and only perhaps in some disciplines like medicine, although even in that context, there is increasing recognition, particularly in clinical settings, that client-centered and context studies are important for diagnosis and treatment (Greenhalgh & Worrall, 1997 ). It is equally possible to conduct case study that is mainly qualitative, to engage people with the experience of the case or to provide a rich portrayal of a person (MacDonald, 1977 ) or an event, project, or program. While the focus of the case is usually a project, program, or policy, within the case there can be portrayals of individuals who are key actors. These are what I term case profiles . In some instances, these profiles, or even shorter cameos of individuals, may be quite prominent. For it is through the perceptions, interpretations, and interactions of people that we learn how policies and programs are enacted (Kushner, 2000 , p. 12). The program is still the main focus of analysis in such cases, but, in exploring how individuals play out their different roles in the program, we get closer to the actual experience and meaning of the program in practice.

In the past three decades the literature and associated courses and conferences on mixed methods in educational and social research has proliferated (Greene, Caracelli, & Graham, 1989 ); (Greene & Caracelli, 1997 ; Tashakkori & Teddlie, 1998, 2003). This development, which first became evident in the eighties, evolved partly to overcome the partisan focus of either quantitative or qualitative research, but it also provides a perspective from different methodologies that may add to understanding of the case and increases the options for learning from different ways of knowing. Mixed methods methodology is sometimes preferred by stakeholders who believe it provides a firmer basis for informing policy. This is not necessarily the case, but is beyond the scope of this chapter to explore. Case study research has always been open to the inclusion of different methods because what is paramount in case research is understanding the complexity and uniqueness of the case, and a variety of methods offer different angles to comprehending this complexity and uniqueness. For further discussion of the complexities of mixing methods and the virtue of using qualitative methods and case study in a mixed methods design, see Greene ( 2007 ). The focus for the remainder of this chapter will be on the qualitative dimension of case study research.

Case study research may also be conducted from different standpoints—realist, interpretivist, or constructivist, for example. My perspective falls within a constructivist, interpretivist framework. What interests me is how I and those in the case perceive and interpret what we find and how we construct or co-construct understandings of the case. This suits not only my predilection for how I see the world, but also my preferred phenomenological approach to interviewing and curiosity about people and how they act in social and professional life.

Qualitative Case Study Research

Qualitative case study research shares many characteristics with other forms of qualitative research, such as narrative, oral history, life history, ethnography, in-depth interview and observational studies that utilize qualitative methods. However, its focus, purpose, and origins, in educational research and evaluation at least, are a little different. The focus is clearly the study of the singular. The purpose is to portray an in-depth view of the quality and complexity of social/educational programs or policies as they are implemented in specific sociopolitical contexts. What makes it qualitative is its emphasis on subjective ways of knowing, particularly the experiential, practical, and presentational rather than the propositional (Heron, 1992 , 1999 ) to comprehend and communicate what transpired in the case.

Characteristic Features and Advantages

Case study research is not method dependent, as noted earlier, nor is it constrained by resources or time. Although it can be conducted over several years, which provides an opportunity to explore the process of change and explain how and why things happened, it can equally be carried out contemporaneously in a few days, weeks, or months. This flexibility is extremely useful in many contexts, particularly when a change in policy or unforeseen issues in the field require modifying the design.

Flexibility extends to reporting. The case can be written up in different lengths and forms to meet different audience needs and to maximize use (see the section on reporting). Using the natural language of participants and familiar methods (like interview, observation and oral history) also enables participants to engage in the research process, thereby contributing significantly to the generation of knowledge of the case. As I have indicated elsewhere (Simons, 2009 ), “This is both a political and epistemological point. It signals a potential shift in the power base of who controls knowledge and recognizes the importance of co-constructing perceived reality through the relationships and joint understandings we create in the field” (p. 23).

Possible Disadvantages

If one is an advocate, identifying advantages of a research approach is easier than pointing out its disadvantages, something detractors are quite keen to do anyway! But no approach is perfect, and here are some of the issues that often trouble people about case study research. The sample of one is an obvious issue that worries those convinced that only large samples can constitute valid research, especially if it is to inform policy. Understanding complexity in depth may not be a sufficient counterargument, and I suspect there is little point in trying to persuade otherwise. For frequently this perception is one of epistemological and methodological, if not ideological, preference.

However, there are some genuine concerns that many case researchers face: the difficulty of processing a mass of data; of “telling the truth” in contexts where people may be identifiable; personal involvement, when the researcher is the main instrument of data gathering; and writing reports that are data based, yet readable in style and length. But one issue that concerns advocates and nonadvocates alike is how inferences are drawn from the single case.

Answers to some of these issues are covered in the sections that follow. Whether they convince may again be a question of preference. However, it is worth noting here that I do not think we should seek to justify these concerns in terms identified by other methodologies. Many are intrinsic to the nature and strength of qualitative case study research.

Subjectivity, for instance, both of participants and of the researcher, is inevitable, as it is in many other qualitative methodologies. This is often the basis on which we act. Rather than seeing this as bias or something to counter, it is an intelligence that is essential to understanding and interpreting the experience of participants and stakeholders. Such subjectivity needs to be disciplined, of course, through procedures that examine the validity of individuals’ representations of “their truth” and demonstrate how the researcher took a reflexive approach to monitoring how his or her own values and predilections may have unduly influenced the data.

Types of Case Study

There are numerous types of case study, too many to categorize, I think, as there are overlaps between them. However, attempts have been made to do so and, for those who value typologies, I refer them to Bassey ( 1999 ) and, for a more extended typology, to Thomas ( 2011 ). A slightly different approach is taken by Gomm et al. ( 2004 ): noting, in an annotated bibliography, the different emphases in major texts on case study. What I prefer to do here is to highlight a few familiar types to focus the discussion that follows on the practice of case study research.

Stake ( 1995 ) offered a threefold distinction that is helpful when it comes to practice, he says, because it influences the methods we choose to gather data (p. 4). He distinguishes between an intrinsic case study , one that is studied to learn about the particular case itself, and an instrumental case study , in which we choose a case to gain insight into a particular issue (i.e., the case is instrumental to understanding something else; p. 3). The collective case study is what its name suggests: an extension of the instrumental to several cases.

Theory-led or theory-generated case study is similarly self-explanatory, the first starting from a specific theory that is tested through the case and the second constructing a theory through interpretation of data generated in the case. In other words, one ends rather than begins with a theory. In qualitative case study research, this is the more familiar route. The theory of the case becomes the argument or story you will tell.

Evaluation case study has three essential elements. Its purpose is to determine the value of a particular project, program or policy, to include and balance different interests and perspectives and to report findings to a range of stakeholders in ways that they can use. It is a social, political and ethical practice. It needs to be responsive to issues or questions identified by stakeholders, including those who commission evaluations, who often have different perspectives of the program and different interests in the expected outcomes. The task of the evaluator in such situations becomes one of negotiating and representing all interests and values in the program fairly and justly. This is an inherently political process and requires an ethical practice that offers participants some protection over the personal data they give as part of the research and agreed audiences access to the findings presented in ways they can understand. The ethical protocols that have evolved to support this process are outlined in the section on ethics.

Designing Case Study Research

Design issues in case study sometimes take second place to those of data gathering, the more exciting task, perhaps, in beginning research. However, it is critical to consider the design at the outset, even if changes are required in practice due to the reality of what is encountered in the field. In this sense, the design of case study is emergent, rather than preordinate (predetermined in advance), shaped and reshaped as understanding of the significance of foreshadowed issues emerges and other, perhaps more pertinent issues are discovered.

Before entering the field, there are a myriad of planning issues to think about related to stakeholders, participants, and audiences. These include whose values matter, whether to engage these groups in data gathering and interpretation, the style of reporting appropriate for each, and the ethical guidelines that will underpin data collection and reporting. However, here I emphasize only three: the broad focus of the study, what the case is a case of, and framing questions/issues. These steps are often ignored in an enthusiasm to gather data, resulting in a case study that claims to be research but lacks the basic principles required for generation of valid, public knowledge.

Conceptualize the Topic

First, it is important that the topic of the research is conceptualized in a way that it can be researched (i.e., it is not too wide). This seems an obvious point to make, but failure to think through precisely what it is about your research topic you wish to investigate will have a knock-on effect on the framing of the case, data gathering and interpretation and may lead, in some instances, to not gathering or analyzing data that actually inform the topic. Further conceptualization or reconceptualization may be necessary as the study proceeds, but it is critical to have a clear focus at the outset.

What Constitutes the Case

Second, it is important to decide what would constitute the case (i.e., what it is a case of) and where the boundaries lie. This often proves more difficult than first appears. And sometimes, partly because of the semifluid nature of the way the case evolves, it is only possible to finally establish what the case is a case of at the end. Nevertheless, it is useful to identify what the case and its boundaries are at the outset to help focus data collection while maintaining an awareness that they may shift. This is emergent design in action.

In deciding the boundary of the case, there are several factors to bear in mind. Is it bounded by an institution or a unit within an institution, by people within an institution, by region, or by project, program, or policy? If we take a school as an example, the case could be composed of the principal, teachers and students, or the boundary could be extended to the cleaners, the caretaker, or the receptionist, people who often know a great deal about the subnorms and culture of the institution.

If the case is a policy or particular parameter of a policy, the considerations may be slightly different. People will still be paramount—those who generated the policy and those who implemented it—but there is likely also to be a political culture surrounding the policy that had an influence on the way the policy evolved. Would this be part of the case? In evaluation case study it invariably would, because it is difficult to fully comprehend how a policy is interpreted and implemented without an understanding of the values and intentions behind the setting up of the policy in the first place.

Whatever boundary is chosen, it may change in the course of conducting the study when issues arise that can only be understood by going to another level. What transpires in a classroom, for example, if a classroom is the case, is often partly dependent on the support of the school leadership and culture of the institution and this, in turn, to some extent is dependent on what resources are allocated from the local education administration. Much like a series of Russian dolls, one context inside the other.

Unit of analysis

Thinking about what would constitute the unit of analysis—a classroom, an institution, a program, a region—may help in setting the boundaries of the case, and it will certainly facilitate analysis. But this is a slightly different issue from deciding what the case is a case of. Taking a health example, the case may be palliative care support, but the unit of analysis the palliative care ward. The focus would be directly on how palliative care was managed in the context of a particular ward or wards and the understanding this generated for palliative care support in general. Here, as in the school example, you would need to consider which of the many people who populate the ward form part of the case—is it the nurses, interns, or doctors only, or does it extend to patients, cleaners, nurse aides, and medical students? If you took palliative care support as the unit of analysis, you would be less concerned about the specific details of the ward. Your focus would be more on the broader policy, key strategies, and units supporting palliative care, as well as the perspective of key actors in the process and how they delivered such care.

Framing Questions and Issues

The third most important consideration is how to frame the study, and you are likely to do this once you have selected the site or sites for study. There are at least four approaches: specific research or evaluative questions, foreshadowed issues (Smith & Pohland, 1974 ), theoretical framework, or a program logic. To some extent, your choice will be dictated by the type of case you have chosen, as well as by your personal preference for how to conduct it—in either a structured or an open way.

Initial questions give structure; foreshadowed issues give more freedom to explore. In qualitative case study, foreshadowed issues are more common, allowing scope for issues to change as the study evolves, guided by participants’ perspectives and events in the field. With this perspective, it is more likely that you will generate a theory of the case toward the end, through your interpretation and analysis, rather than start with a preexisting theoretical framework. See Thomas ( 2016 , ch. 11) for an exploration of different ways to generate theory in and of your case.

If you are conducting an instrumental case study , staying close to the questions or foreshadowed issues is necessary to be sure you gain data that will illuminate the central focus of the study. This is critical if you are exploring issues across several cases, although it is possible also to do a cross-case analysis from cases that have each followed a different route to discovering significant issues.

Opting to start with a theoretical framework provides a basis for formulating questions or identifying issues, but it can also constrain the study to only those questions/issues that fit the framework. The same is true with using program logic to frame the case. This approach is frequently adopted in evaluation case study, where the evaluator, individually or with stakeholders, examines how the aims and objectives of the program relate to the activities designed to promote it and the outcomes and impacts expected. It provides direction and is useful for engaging stakeholders in thinking through the assumptions underlying any theory of change they propose. However, it can lead to simply confirming what was anticipated, rather than documenting what transpired in the case (see Rogers, 2017 ; and Funnell & Rogers, 2011 , for helpful accounts of the potential and pitfalls of adopting a logic model as a framework).

Whichever approach you choose to frame the case, it is useful to think about the rationale or theory for each question or aspect of the framing and what methods would best enable you to gain an understanding of them. This will not only start a reflexive process of examining your choices—an important aspect of the process of data gathering and interpretation—but also aid analysis and interpretation further down the track.

Methodology and Methods

Qualitative case study research, as already noted, appeals to subjective ways of knowing and to a primarily qualitative methodology that captures experiential understanding (Stake, 2010 , pp. 56–70). It follows that the main methods of data gathering to access this way of knowing will be qualitative. Interviewing, observation, and document analysis are the primary three, often supported by critical incidents, focus groups, cameos, vignettes, diaries/journals, and photographs. Before gathering any primary data, however, it is useful to search relevant existing sources (written or visual) to learn about the antecedents and context of a project, program, or policy as a backdrop to the case. This can sharpen framing questions, avoid unnecessary data gathering, and shorten the time needed in the field.

Given that there are excellent texts on qualitative methods (see, for example, Denzin & Lincoln, 1994 ; Seale, 1999 ; Silverman, 2000 , 2004 ; Stake, 2010 ), I will not discuss all potential relevant methods here, but simply focus on the qualities of the primary methods that are particularly appropriate for case study research.

Primary Qualitative Data Gathering Methods

Interviewing.

The most effective style of interviewing in qualitative case study research is the unstructured interview, in which active listening and open questioning are paramount, whatever prequestions or foreshadowed issues have been identified. Specific advantages of this approach to gaining in-depth data are the opportunity to document multiple perspectives and experiences and establish which issues are most significant in the case—an important step in refining the emergent design. This form of interviewing can include photographs—a useful starting point with certain cultural groups and the less articulate, to encourage them to tell their story through connecting or identifying with something in the image. The flexibility of unstructured interviewing has three further advantages for understanding participants’ experiences. First, through questioning, probing, listening, and, above all, paying attention to the silences and what they mean, you can get closer to the meaning of participants’ experiences. It is not always what they say. For thoughtful observations of the meaning of silences in qualitative research, see Mazzei ( 2003 , 2007 ).Second, unstructured interviewing is useful for engaging participants in the process of research. Instead of starting with questions and issues, invite participants to tell their stories or reflect on specific issues, to conduct their own self-evaluative interview, in fact. Not only will they contribute their particular perspective to the case, they will also learn about themselves, thereby making the process of research educative for them as well as for audiences of the research. Third, the open-endedness of this style of interviewing has the potential for creating a dialogue between participants and the researcher and between the researcher and the public, if enough of the dialogue is retained in the publication (Bellah, Madsen, Sullivan, Swidler, & Tipton, 1985 ).

Observations

Observations in case study research are likely to be close-up descriptions of events, activities, and incidents that detail what happens in a particular context. These will record time, place, specific incidents, transactions, dialogue, and note characteristics of the setting and of people within it without preconceived categories or judgment. No description is devoid of some judgment in selection, but, on the whole, the intent is to describe the scene or event as it is, providing a rich, textured description to give readers a sense of what it was like to be there or provide a basis for later interpretation.

Take the following excerpt from a study of the West Bromwich Operatic Society. It is the first night of a new production, The Producers , by this amateur operatic society. This brief excerpt is from a much longer observation of the overture to the first evening’s performance, detailing exactly what the production is, where it is, and why there is such a tremendous sense of atmosphere and expectation surrounding the event. Space prevents including the whole observation, but I hope you can get a glimmer of the passion and excitement that precedes the performance:

Birmingham, late November, 2011, early evening.… Bars and restaurants spruce up for the evening’s trade. There is a chill in the air but the party season is just starting … A few hundred yards away, past streaming traffic on Suffolk Street, Queensway, an audience is gathering at the New Alexandra Theatre. The foyer windows shine in the orange sodium night. Above each one is the rubric: WORLD CLASS THEATRE. Inside the preparatory rituals are being observed; sweets chosen, interval drinks ordered and programmes bought. People swap news and titbits about the production … The bubble of anticipation grows as the 5-minute warning sounds. People make their way to the auditorium. There have been so many nights like this in the past 110 years since a man named William Coutts invested £10,000 to build this palace of dreams.… So many fantasies have been played under this arch: melodramas and pantomimes, musicals and variety.… So many audiences, settling down in their tip-up seats, wanting to be transported away from work, from ordinariness and private troubles … The dimming lights act like a mother’s hush. You could touch the silence. Boinnng! A spongy thump on a bass drum, and the horns pipe up that catchy, irrepressible, tasteless tune and already you’re singing under your breath, “Springtime for Hitler and Germany …” The orchestra is out of sight in the pit. There’s just the velvet curtain to watch as your fingers tap along. What’s waiting behind? Then it starts it to move. Opening night … It’s opening night! (Matarasso, 2012 , pp. 1–2)

For another and different example—a narrative observation of an everyday but unique incident that details date, time, place, and experience—see Simons ( 2009 , p. 60).

Such naturalistic observations are also useful in contexts where we cannot understand what is going on through interviewing alone or in cultures with which we are less familiar and where key actors may not share our language or have difficulty expressing what they mean. Careful description in these situations can help identify key issues, discover the norms and values that exist in the culture, and, if sufficiently detailed, allow others to cross-corroborate what significance we draw from these observations. This last point is very important to avoid the danger in observation of ascribing motivations to people and meanings to transactions.

Finally, naturalistic observations are very important in highly politicized environments, often the case in commissioned evaluation case study, where individuals in interview may try to elude the “truth” or press upon you that their view is the right view of the situation. In these contexts, naturalistic observations not only enable you to document interactions as you perceive them, but also provide a cross-check on the veracity of information obtained in interviews.

Document Analysis

Analysis of documents, as already intimated, is useful for establishing what historical antecedents might exist to provide a springboard for contemporaneous data gathering. In most cases, existing documents are also extremely pertinent for understanding the policy context.

In a national policy case study I conducted on a major curriculum change, the importance of preexisting documentation was brought home to me sharply when certain documentation initially proved elusive to obtain. It was difficult to believe that it did not exist, because the evolution of the innovation involved several parties who had not worked together before and they needed to develop a shared understanding of the ‘new’ curriculum. There was bound, I thought, to be minuted meetings sharing progress and documentation of the “new” curriculum. In the absence of some crucial documents, I began to piece together the story through interviewing different individuals who had a role to play in the evolution of the new curriculum. But there were gaps, and certain issues did not make sense.

It was only when I presented two versions of what I discerned had transpired in the development of this initiative in an interim report 18 months into the study that things started to change. Subsequent to the meeting at which the report was presented, the “missing” documents started to appear. Suddenly found! What lay behind the “missing” documents, something I suspected from what certain individuals did and did not say in interview, was a major difference of view about how the innovation evolved, who was key in the process, and whose voice was more important in the context: political differences, in other words, that some stakeholders were trying to keep from me. The emergence of the documents enabled me to finally produce an accurate and fair account.

This is an example of the importance of having access to all relevant documents relating to a program or policy to study it fairly. The other major way in which document analysis is useful in case study is for understanding the values, explicit and hidden, in policy and program documents and in the organization where the program or policy is implemented. Not to be ignored as documents are photographs; these, too, can form the basis of a cultural and value analysis of an organization (Prosser, 2000 ).

Creative Artistic Approaches

Increasingly, some case study researchers are employing creative approaches associated with the arts as a means of data gathering and analysis. Artistic approaches have often been used in representing findings, but less frequently in data gathering and interpretation (Simons & McCormack, 2007 ). A major exception is the work of Richardson ( 1994 ), who views the very process of writing as an interpretative act, and that of Cancienne and Snowber ( 2003 ), who argue for movement as method.

The most familiar of these creative and artistic forms are written—narratives and short stories (Clandinin & Connelly, 2000 ; Richardson, 1994 ; Sparkes, 2002 ), poems or poetic form (Butler-Kisber, 2010 ; Duke, 2007 ; Richardson, 1997; Sparkes & Douglas, 2007 ), and cameos of people, or vignettes of situations. These can be written by participants or by the researcher or developed in partnership. They can also be shared with participants to further the interpretation of the data.

Photographs also have a long history in qualitative research for presenting and constructing understanding (Butler-Kisber, 2010 ; Collier, 1967 ; Prosser, 2000 ; Rugang, 2006 ; Walker, 1993 ). The photo story in particular—a selection of photographs placed in sequence to show the interpretation of an event or circumstance—is a powerful way of telling. Less common are other visual forms of gathering data, such as “draw and write” (Sewell, 2011 ), artifacts, drawings, sketches, paintings, and collages, although these, too, are increasingly being adopted. For examples of the use of collage in data gathering, see Duke ( 2007 ) and Butler-Kisber ( 2010 ), and for charcoal drawing, see Elliott ( 2008 ). Collages have the potential not only for revealing inner states and feelings, but also for documenting conflicts and tensions in a case. Duke ( 2007 ) made effective use of collage in this respect to portray differences and tensions with doctors in a medical setting where she, in her role as a nurse consultant, was conducting research as well as performing her normal nurse duties. The collage served to channel the emotions she was experiencing in this hierarchical context without influencing the research or her professional role. More recently, Plakoyiannaki & Stavraki ( 2018 ) explored the various ways in which collages can be interpreted to reveal the meaning embedded in the juxtaposition of images and visual metaphors in a collage. They also offer a heuristic analytic approach to counter what they see as limitations in some of the other forms of analyzing collages. Though written primarily for an audience in management research, many aspects of their paper are pertinent for case study research.

Videos can be a useful means of documenting events and interactions between people, especially when individuals cannot be interviewed. See, for example, Flewitt ( 2005 ) for a discussion of the value of video for exploring communications between young children in the home and preschool contexts. In other contexts—videos of classroom events, for example—they can be extremely useful for engaging participants and stakeholders in the interpretation of such events. It is often suggested, furthermore, that videos are a useful means of reporting case study data. Not, I suggest, in raw form. Beyond the ethical issue of the potential identification of individuals is the difficulty of understanding what is going on if you were not present at the time and had a grasp of other data relevant to that understanding. In other words, videos have a temporary life. Without additional data, the distant viewer may not comprehend. This is a separate issue from preparing a video report, composed of different kinds of data to tell the story of the case in a visual, succinct way. Such videos have the power to engage different audiences and can facilitate immediate understanding of the critical issues in the case. An excellent example of this is the CD that Jenny Elliot ( 2008 ) prepared as part of her Ph.D. thesis, showing how it was possible through the research she conducted to get a unit of brain-damaged men to dance. The video was widely shown subsequently in many healthcare contexts.

In qualitative inquiry broadly, these creative approaches are now quite common. And in the context of arts and health (see, for example, Frank, 1997 ; Liamputtong & Rumbold, 2008 ; Spouse, 2000 ), they are frequently used to illuminate perspectives of individuals in therapeutic settings or enhance understanding of how spaces and environments in health and social care affect those who inhabit them (Fenner, 2011 , 2017 ). However, in case study research to date, narrative forms have tended to dominate, possibly because the contexts in which much case study research is conducted are policy or program focused where narrative forms of understanding are more the norm. This is not to say creative approaches may not be useful in these contexts. It may be a question of lack of familiarity with such approaches and acceptance of their usefulness in those environments.

Finally, for capturing the quality and essence of peoples’ experience, nothing could be more revealing than a recording of their voices. Video diaries—self-evaluative portrayals by individuals of their perspectives, feelings, or experience of an event or situation—are a most potent way both of gaining understanding and of communicating that to others. It is rather more difficult to gain access for observational videos because it is hard to effectively disguise individuals. Even if consent is granted, where individuals are visible it is not possible to foresee how portrayals of their life and experience will be viewed years after the research is completed. Research is context and time bound. So, video diaries may be most useful in a temporal sense to facilitate understanding of the case. See Simons ( 2007 ) for an exploration of the ethical dimension of the use of visual data.

It will be evident from the foregoing discussion of qualitative methods that close-up portrayals of individuals and contexts requires sensitive ethical protocols. Negotiating what information becomes public can be quite difficult in singular settings where people are identifiable and intricate or problematic transactions have been documented. The consequences that ensue from making knowledge public that hitherto was private may be considerable for those in the case. It may also be difficult to portray some of the contextual detail that would enhance understanding for readers because it would raise the risk of identifiability of individuals, as would visual data, as already noted.

The ethical stance that underpins the case study research and evaluation I conduct stems from a theory of ethics that emphasizes the centrality of relationships in the specific context (see Kirkhart, 2013 , for the concept of relational validity that supports this focus) and the consequences for individuals, while remaining aware of the research imperative to publicly report. It is essentially an independent democratic process based on the concepts of fairness and justice, in which confidentiality, negotiation, and accessibility are key principles (MacDonald, 1976 ; Simons, 2009 , ch. 6; and Simons, 2010 ). The principles are translated into specific procedures to guide the collection, validation, and dissemination of data in the field. These include:

engaging participants and stakeholders in identifying issues to explore and sometimes also in interpreting the data;

documenting how different people interpret and value the program;

negotiating what data become public, respecting both the individual’s “right to privacy” and the public’s “right to know”;

offering participants opportunities to check how their data are used in the context of reporting;

reporting in language and forms accessible to a wide range of audiences; and

disseminating to audiences within and beyond the case.

For further discussion of the ethics of democratic case study evaluation and examples of their use in practice, see Simons ( 2000 , 2006 , 2009 , ch. 6, 2010 ).

Getting It All Together

Case study is so often associated with story or with a report of some event or program that it is easy to forget that much analysis and interpretation has gone on before we reach this point. In many case study reports, this process is hidden, leaving the reader with little evidence on which to assess the validity of the findings and having to trust the one who wrote the tale.

This section briefly outlines possibilities, first, for analyzing and interpreting data, and second, for how to communicate the findings to others. However, it is useful to think of them together and indeed, at the start, because decisions about how you report may influence how you choose to make sense of the data. Your choice may also vary according to the context of the study—what is expected or acceptable—and your personal predilections, whether you prefer a more rational than intuitive mode of analysis, for example, or a formal or informal style of writing up that includes images, metaphor, narratives, or poetic forms.

Analyzing and Interpreting Data

When it comes to making sense of data, I make a distinction between analysis—a formal inductive process that seeks to explain—and interpretation, a more intuitive process that gains understanding and insight from an holistic grasp of data, although they may interact and overlap at different stages.

The process, whichever emphasis you choose, is one of reducing or transforming a large amount of data to themes that can encapsulate the overarching meaning in the data. This involves sorting, refining, and refocusing data until they make sense. It starts at the beginning with preliminary hunches, sometimes called interpretative asides or working hypotheses , later moving to themes, analytic propositions, or a theory of the case.

There are many ways to conduct this process. Two strategies often employed are concept mapping —a means of representing data visually to explore links between related concepts—and progressive focusing (Parlett & Hamilton, 1976 ), the gradual reframing of initially identified issues into themes that are then further interpreted to generate findings. Each of these strategies tends to have three stages: initial sense making, identification of themes, and examination of patterns and relationships between them.

If taking a formal analytic approach to the task, the data would likely be broken down into segments or data sets (coded and categorized) and then reordered and explored for themes, patterns, and possible propositions. If adopting a more intuitive process, you might focus on identifying insights through metaphors and images, lateral thinking, or puzzling over paradoxes and ambiguities in the data, after first immersing yourself in the total data set and reading and rereading interview scripts, observations, and field notes to get a sense of the whole. Trying different forms of making sense through poetry, vignettes, cameos, narratives, collages, and drawing are further creative ways to interpret data, as are photographs taken in the case arranged to explain or tell the story of the case.

Reporting Case Study Research

Narrative structure and story.

As indicated in the introduction, telling a story is often associated with case study and some think this is what a case study is. In one sense it is, and, given that story is the natural way in which we learn (Okri, 1997 ), it is a useful framework both for gathering data and for communicating case study findings. Not any story will do, however. To count as research, it must be authentic, grounded in data, interpreted and analyzed to convey the meaning of the case.

There are several senses in which story is appropriate in qualitative case study: in capturing stories participants tell, in generating a narrative structure that makes sense of the case (i.e., the story you will tell), and in deciding how you communicate this narrative (i.e., in story form). If you choose a written story form, Harrington ( 2003 ) and Caulley ( 2008 ) are useful authors to consult to ensure the story is clearly structured, well written, and contains only the detail that is necessary to give readers the vicarious experience of what it was like in the case. Harrington ( 2003 ) reminds us, among other things, that it is not only in the technical sense that good writing is required—using plain, precise, direct language and grammar—but also how we convey meaning—“‘selecting telling details’ … ‘balancing the particular and the universal’ … ‘structuring stories so insight emerges’” (p. 97). If the story is to be communicated in other ways, through, for example, audio or videotape or computer or personal interaction, the same applies, substituting visual and interpersonal skill for written. In addition to these authors, I often get inspiration for constructing a story or a portrayal of a person from novelists who write well.

Matching Forms of Reporting to Audience

The art of reporting is strongly connected to usability, so forms of reporting need to connect to the audiences we hope to inform: how they learn, what kind of evidence they value, and what kind of reporting maximizes the chances they will use the findings to promote policies and programs in the interests of beneficiaries. As Okri ( 1997 ) further reminds us “The writer only does half the work, the reader does the other” (p. 41).

There may be other considerations as well: How open are commissioners to receiving stories of difficulties as well as success stories? What might they need to hear beyond what is sought in the technical brief? And through what style of reporting would you try to persuade them? If you are conducting noncommissioned case study research, the scope for different forms of reporting is wider. In academia, for instance, many institutions these days accept creative and artistic forms of reporting when supported by supervisors and appreciated by examiners.

Styles of Reporting

The most obvious form of reporting is linear , often starting with a short executive summary and a brief description of focus and context, followed by methodology, the case study itself in its totality, or demonstrated in the thematic analysis, findings, and conclusions or implications. Conclusion-led reporting is similar in terms of its formality, but simply starts the other way around. From the conclusions drawn from the analyzed data, it works backward to tell the story through narrative, verbatim, and observational data of how these conclusions were reached. Both have a strong storyline. The intent is analytic and explanatory.

Quite a different approach is to engage the reader in the experience and veracity of the case. Rather like constructing a portrait or editing a documentary film, this involves the sifting, constructing, and reordering of frames, events, and episodes to tell a coherent story primarily through interview excerpts, observations, vignettes, and critical incidents that depict what transpired in the case. Interpretation is indirect through the weaving of the data. The story can start at any point, provided the underlying narrative structure is maintained to establish coherence (House, 1980 , p. 116).

Different again, and from the other end of a continuum, is a highly interpretative account that may use similar ways of presenting data but weaves a story from the outset that is highly interpretative. Engaging metaphor, images, short stories, contradictions, paradoxes, and puzzles, it is invariably interesting to read and can be most persuasive. However, the evidence is less visible and therefore less open to alternative interpretations.

Even more persuasive is a case study that uses artistic forms to communicate the story of the case. Paintings, poetic form, drawings, photography, collage, and movement can all be adopted to report findings, whether the data were acquired using these forms or by other means. The arts-based inquiry movement (Mullen & Finley, 2003 ) has contributed hugely to the validation and legitimation of artistic and creative ways of representing qualitative research findings. The journal Qualitative Inquiry contains many good examples, but see also Liamputtong & Rumbold ( 2008 ). Such artistic forms of representation may not be for everyone or appropriate in some contexts, but they do have the power to engage an audience and the potential to facilitate use.

Before leaving reporting, it is important to mention that in recent years, not surprisingly given the rapid growth and ever-changing technology at our disposal, there has been an increase in the use of data visualization techniques, both to present data and to report findings. See, for example, some of the excellent ideas offered by Stephanie Evergreen ( 2013 , 2016 ) using graphics and charts of different kinds to summarize data effectively. Telling the story of the case, then, can be visual as well as literary. Using these techniques, linked often with quotations from interviews and pictorial evidence of context, it is possible to communicate the findings of a case in a few pages, or even just one page. This can be of immense benefit to policy makers who may have little time to read long case reports or those who value visual learning as much as written. Such techniques are unlikely to replace the narrative form. Given the importance of people and context in case study, the need to represent participants’ voices and the sociopolitical context will invariably demand a longer and integrated story. Data visualization is an added strength and an option for those who are persuaded by visual means or who have little time.

Generalization in Case Study Research

One of the potential limitations of case study often proposed is that it is impossible to generalize. This is not so. However, the way in which one generalizes from a case is different from that adopted in traditional forms of social science research that utilize large samples (randomly selected) and statistical procedures and that assume regularities in the social world that allow cause and effect to be determined. In this form of research, inferences from data are stated as formal propositions that apply to all in the target population. See Donmoyer ( 1990 ) for an argument on the restricted nature of this form of generalization when considering single-case studies.

Making inferences from cases with a qualitative data set arises more from a process of interpretation in context, appealing to tacit and situated understanding for acceptance of their validity. Such inferences are possible where the context and experience of the case is richly described so the reader can recognize and connect with the events and experiences portrayed. There are two ways to examine how to reach these generalized understandings. One is to generalize from the case to other cases of a similar or dissimilar nature. The other is to see what we learn in depth from the uniqueness of the single case itself.

Generalizing from the Single Case

A common approach to generalization and one most akin to a propositional form is cross-case generalization. In a collective or multisite case study, each case is explored to see if issues that arise in one case also exist in other cases and what interconnecting themes exist between them. This kind of generalization has a degree of abstraction and potential for theorizing and is often welcomed by commissioners of research concerned that findings from the single case do not provide an adequate or “safe” basis for policy determination.

However, there are four additional ways to generalize from the single case, all of which draw more on tacit knowledge and recognition of context, although in different ways. In naturalistic generalization , first proposed by Stake ( 1978 ), generalization is reached on the basis of recognition of similarities and differences to cases with which we are familiar. To enable such recognition, the case should feature rich description; people’s voices; and enough detail of time, place, and context to provide a vicarious experience to help readers discern what is similar and dissimilar to their own context (Stake, 1978 ).

Situated generalization (Simons, Kushner, Jones, & James, 2003 ) is close to the concept of naturalistic generalization in relying for its generality on retaining a connectedness with the context in which it first evolved. However, it has an extra dimension in a practice context. This notion of generalization was identified in an evaluation of a research project that engaged teachers in and with research. Here, in addition to the usual validity criteria to establish the methodological warrant for the findings, the generalization was seen as dependable if trust existed between those who conducted the research (teachers, in this example) and those thinking about using it (other teachers). In other words, beyond the technical validity of the research, teachers considered using the findings in their own practice because they had confidence in those who generated them. This is a useful way to think about generalization if we wish research findings to improve professional practice.

The next two concepts of generalization— concept and process generalization —relate more to what you discover in making sense of the case. As you interpret and analyze, you begin to generate a theory of the case that makes sense of the whole. Concepts may be identified that make sense in the one case but have equal significance in other cases of a similar kind, even if the contexts are different. It is the concept that generalizes, not the specific content or context. This may be similar to the process Donmoyer ( 2008 ) identifies of “intellectual generalization” (as cited in Butler-Kisber, 2010 , p. 15) to indicate the cognitive understanding one can gain from qualitative accounts even if settings are quite different.

The same is true for generalization of a process. It is possible to identify a significant process in one case (or several cases) that is transferable to other contexts, irrespective of the precise content and contexts of those other cases. An example here is the collaborative model for sustainable school self-evaluation I identified in researching school self-evaluation in a number of schools and countries (Simons, 2002 ). Schools that successfully sustained school self-evaluation had an infrastructure that was collaborative at all stages of the evaluation process from design to conduct of the study, to analyzing and interpreting the results, and to reporting the findings. This ensured that the whole school was involved and that results were discussed and built into the ongoing development of school policies and practice. In other cases, different processes may be discovered that have applicability in a range of contexts. As with concept generalization, it is the process that generalizes not the substantive content or specific context.

Particularization

The forms of generalization discussed above are useful when we have to justify case study in a research or policy context. But the overarching justification for how we learn from case study is particularization —a rich portrayal of insights and understandings interpreted in the particular context. Several authors have made this point (Flyvberg, 2006 ; Simons, 2009 ; Stake, 1995 , 2006 ). Stake (2005) puts it most sharply when he observes that “the real business of case study is particularization, not generalization” (p. 8), referring here to the main reason for studying the singular, which is to understand the uniqueness of the case itself.

My perspective (explored further in Simons, 1996 , 2009 , p. 239; Simons & McCormack, 2007 ) is similar in that I believe the “real” strength of case study lies in the insights we gain from in-depth study of the particular. But I also argue for the universality of such insights—if we get it “right,” by which I mean that if we are able to capture and report the uniqueness, the essence of the case, in all its particularity and present it in a way we can all recognize, we will discover something of universal significance. This is something of a paradox. The more you learn in depth about the particularity of one person, situation, or context, the more likely you are to discover something universal. This process of reaching understanding has support both from the way in which many discoveries are made in science and in how we learn from artists, poets, and novelists, who reach us by communicating a recognizable truth about individuals, human relationships, and/or social contexts.

This concept of particularization is far from new, as the quotation below from a preface to a book written in 1908 attests. Stephen Reynolds, the author of A Poor Man’s House (Reynolds, 1908 ) noted in the preface that the substance of the book was first recorded in a journal, kept for purposes of fiction and in letters to one of his friends, but fiction proved an inappropriate medium. He felt that the life and the people were so much better than anything he could invent. The book therefore consists of the journal and letters drawn together to present a picture of a typical poor man’s house and life, much as we might draw together a range of data to present a case study. It is not the substance of the book that concerns us here, but the methodological relevance to case study research. Reynolds pointed out that the conclusions in his book were tentative and possibly went beyond this man’s life, so he thought some explanation of the way he arrived at them was needed:

Educated people usually deal with the poor man’s life deductively; they reason from the general to the particular; and, starting with a theory, religious, philanthropic, political, or what not, they seek, and too easily find, among the millions of poor, specimens—very frequently abnormal—to illustrate their theories. With anything but human beings, that is an excellent method. Human beings, unfortunately, have individualities. They do what, theoretically, they ought not to do, and leave undone those things they ought to do. They are even said to possess souls—untrustworthy things beyond the reach of sociologists. The inductive method—reasoning from the particular to the general … should at least help to counterbalance the psychological superficiality of the deductive method. (Reynolds, 1908 , preface) 1

Slightly overstated, perhaps, but the point is well made. In our search for general laws, we not only lose sight of the uniqueness and humanity of individuals, but also reduce them in the process, failing to present their experience in any “real” sense. What is astonishing about the quotation is that it was written over a century ago, and yet many still argue that you cannot generalize from the particular.

Going even further back to 1798, Blake proclaimed that ‘To generalise is to be an idiot; to particularise is the alone distinction of merit&quot; (Blake,1798, cited by Keynes (1957). In research, we may not wish to make such a strong distinction; these processes both have their uses in different kinds of research. But there is a major point here for the study of the particular that Wilson ( 2008 ) notes in commenting on Blake’s perception when he says, “Favouring the abstract over the concrete, one ‘sees all things only thro’ the narrow chinks of his cavern’ ” (referring here to Blake’s The Marriage of Heaven and Hell [1793], as cited in Wilson, 2008 , p. 62). The danger Wilson is pointing to here is that abstraction relies heavily on what we know from our past understanding of things, and this may prevent us experiencing a concrete event directly or “apprehend[ing] a particular moment” (Wilson, 2008 , p. 63).

Blake had a different mission, of course, from case researchers, and he was not himself free from abstractions, as Wilson points out, although he [Blake] fought hard “to break through mental barriers to something unique and living” (Wilson, 2008 , p. 65). It is this search for the “unique and living” and experiencing the “isness” of the particular that we should take from the Blake example to remind us of the possibility of discovering something “new,” beyond our current understanding of the way things are.

Focusing on particularization does not diminish the usefulness of case study research for policy makers or practitioners. Grounded in recognizable experience, the potential is there to reach a range of audiences and to facilitate use of the findings. It may be more difficult for those who seek formal generalizations that seem to offer a safe basis for policy making to accept case study reports. However, particular stories often hold the key to why policies have or have not worked well in the past. It is not necessary to present long cases—a criticism frequently leveled—to demonstrate the story of the case. Such case stories can be most insightful for policy makers who, like many of us in everyday life, often draw inferences from a single instance or case, whatever the formal evidence presented “I am reminded of the story of …” Stake ( 2006 , pp. 197–198) also reminds us that we are constantly making small generalizations from particular situations as we go about our professional work and life. These may not survive systematic research scrutiny, but the point Stake is making here is that it is our natural tendency to generalize from the particular in making sense of our worlds. In case study research that aspires to represent “lived experience,” this seems a natural way to proceed.

The case for studying the particular to inform practice in professional contexts needs less persuasion because practitioners can recognize the content and context quite readily and make the inference to their own particular context (Simons et al., 2003 ). In both sets of circumstances—policy and practice—it is more a question of whether the readers of our case research accept the validity of findings determined in this way, how they choose to learn, and our skill in telling the case study story.

Conclusion and Future Directions

In this chapter, I have presented an argument for case study research, making the case, in particular, for using qualitative methods to highlight what qualitative case study research can bring to the study of social and educational programs. I outlined the various ways in which case study is commonly used before focusing directly on case study as a major mode of research inquiry, noting characteristics it shares with other qualitative methodologies, as well as its difference and the difficulties it is often perceived to have. The chapter emphasizes the importance of thinking through what the case is to be sure that the issues explored and the data generated do illuminate this case and not any other.

But there is still more to be done. In particular, I think we need to be more adventurous in how we craft and report the case, and I have made several suggestions in the text as to how this could be done. I suspect also that we may have been too cautious in the past in how we justified case study research, borrowing concepts from other disciplines and forms of educational research. Fifty years on, it is time to take a greater risk—in demonstrating the intrinsic nature of case study research and what it can offer our understanding of human and social situations.

I have already drawn attention to the need to design the case, although this could be developed further to accentuate the uniqueness of the particular case. One way to do this is to feature individuals more in the design itself, not only to explore programs and policies through perspectives of key actors or groups and transactions between them, which to some extent happens already, but also to get them to characterize what makes the context unique. This is the reversal of many a design framework that starts with the logic of a program and takes forward the argument for personalizing evaluation (Kushner, 2000 ) on the grounds that it is through individuals that programs and policies are enacted. Apart from this attention to design, there are three other issues I think we need to explore further: the warrant for creative methods in case study, more imaginative reporting, and how we learn from a study of the singular.

Warrant for More Creative Methods in Case Study Research

The promise that creative methods have for eliciting in-depth understanding and capturing the unusual, the idiosyncratic, the uniqueness of the case, was mentioned in the methods section. Yet, in case study research, particularly in program and policy contexts, we have few good examples of the use of artistic approaches for eliciting and interpreting data, although there are more, indicated below for presenting it. This may be because case study research is often conducted in academic or policy environments, where propositional ways of knowing are more valued.

Using creative and artistic forms in generating and interpreting case study data offers a form of evidence that acknowledges experiential understanding in illuminating the uniqueness of the case. The question is how to establish the warrant for this way of knowing and persuade others of its virtue. The answer is simple: by demonstrating the use of these methods in action, by arguing for a different form of validity that matches the intrinsic nature of the method, and, above all, by good examples. I earlier noted the impact that Elliott’s CD of men with brain damage had on audiences beyond the case. Rugang ( 2006 ) also used the CD form, two in this instance, presenting contrasting photographs of a “new” culture and an old culture in one province in China. These told the story well, as did a narrative poem by Duke ( 2007 ) of her leadership illustrating how she performed her role as a nurse consultant with responsibility to help other nurses research concurrent with her usual job as a senior nurse.

Re-presenting Findings to Engage Audiences in Learning

In evaluative and research policy contexts, where case study is often the main mode of inquiry or part of a broader study, case study reports often take a formal structure or, sometimes, where the context is receptive, a portrayal or interpretative form. But, too often, the qualitative is an add-on to a story told by other means or reduced to issues in which the people who gave rise to the data are no longer seen. However, there are many ways to put them center stage.

Tell good stories and tell them well. Or, let key actors tell their own stories in narrative or on video. Explore the different ways technology can help. Make video clips that demonstrate events in context, illustrate interactions between people, give voice to participants—show the reality of the program, in other words. Use graphics to summarize key issues and interactive cartoon technology, as seen on some TED presentations, to summarize and visually show the complexity of the case. Explore the data visualization techniques now becoming widely available. Video diaries were mentioned in the methods section: seeing individuals tell their tales directly is a powerful way of communicating, unhindered by “our” sense making. Tell photo stories. Let the photos convey the narrative, but make sure the structure of the narrative is evident to ensure coherence. These are just the beginnings. Those skilled in information technology could no doubt stretch our imagination further.

One problem and a further question concerns our audiences. In your thesis you may well have scope to experiment with some of these alternative forms of presentation. In other contexts—I am thinking here of policy makers and commissioners—it may be more challenging, and you may wonder if they will accept these alternative modes of communication. Maybe not, in some cases. However, there are three points I wish to leave you with. First, if people are fully present in the story and the complexity is not diminished, those reading, watching, or hearing about the case will get the message. If you are worried about how commissioners might respond, remember that they are no different from any other stakeholder or participant when it comes to how they learn from human experience. Witness the reference to Okri ( 1997 ) earlier about how we learn and Stake’s ( 2010 ) reminder of how we generalize from the particular in everyday life.

Second, when you detect that the context requires a more formal presentation of findings, respond according to expectation, but also include elements of other forms of presentation. Nudge a little in the direction of creativity. Third, simply take a chance. Challenge the status quo. Find situations and contexts where you can fully represent the qualitative nature of the experience in the cases you study with creative forms of interpretation and representation. And let the audience decide.

Learning from a Study of the Singular

Finally, to return to the issue of “generalization” in case study that worries some audiences. I pointed out in the generalization section several ways in which it is possible to generalize from case study research, not in a formal propositional sense or from a case to a population, but by retaining a connection with the context in which the generalization first arose—that is, to realize in-depth understanding in context in different circumstances and situations. However, I also emphasized that, in many instances, it is particularization from which we learn. That is the point of the singular case study, and it is an art to perceive and craft the case in ways that we can.

Acknowledgments

Parts of this chapter build on ideas first explored in Simons ( 2009 ).

I am grateful to Bob Williams for pointing out the relevance of this quotation from Reynolds to remind us that “there is nothing new under the sun” and that we sometimes continue to engage endlessly in debates that have been well rehearsed before.

Adams, T. (2012). Olympics 2012: Team GB falters but London shines bright on opening day.   Observer , July 29.

Bassey, M. ( 1999 ). Case study research in educational settings . Buckingham, England: Open University Press.

Google Scholar

Google Preview

Bellah, R. N. , Madsen, R. , Sullivan, W. M. , Swidler, A. , & Tipton, S. M. ( 1985 ). Habits of the heart . London, England: Harper & Row.

Blake, W. (1798–1809). Annotations to Sir Joshua Reynolds’s discourses. In G. Keynes (Ed.), ( 1957 ) Complete writings, “Discourse II,” Annotations to Sir Joshua Reynolds, Discourses (c. 1808) (pp. xvii–xcviii). London, England: Nonesuch Press.

Butler-Kisber, L. ( 2010 ). Qualitative inquiry: Thematic, narrative and arts-informed perspectives . London, England: Sage.

Cancienne, M. B. , & Snowber, C. N. ( 2003 ). Writing rhythm: Movement as method.   Qualitative Inquiry, 9, 237–253.

Caulley, D. N. ( 2008 ). Making qualitative research reports less boring: The techniques of writing creative nonfiction.   Qualitative Inquiry, 14, 424–449.

Chadderton, C. , & Torrance, H. ( 2011 ). Case study. In B. Somekh & C. Lewin (Eds.), Theory and methods in social research (2nd ed., pp. 53–60). London, England: Sage.

Clandinin, D. J. , & Connelly, F. M. ( 2000 ). Narrative inquiry: Experience and story in qualitative research . San Francisco, CA: Jossey–Bass.

Collier, J., Jr . ( 1967 ). Visual anthropology: Photography as a research method . New York, NY: Holt, Reinhart, & Winston.

Denzin, N. K. , & Lincoln, Y. S. (Eds.). ( 1994 ). Handbook of qualitative research . London, England: Sage.

Donmoyer, R. ( 1990 ). Generalization and the single case study. In E. W. Eisner & A. Peshkin (Eds.), Qualitative inquiry in education (pp. 175–200). New York, NY: Teachers College Press.

Donmoyer, R. ( 2008 ). Generalizability. In L. M. Givens (Ed.), The Sage encyclopedia of qualitative inquiry (Vol. 2, pp. 371–372). Thousand Oaks, CA: Sage.

Duke, S. ( 2007 ). A narrative case study evaluation of the role of the Nurse Consultant in palliative care (Unpublished doctoral dissertation). University of Southampton, England.

Elliott, J. ( 2008 ). Dance mirrors: Embodying, actualizing and operationalizing a dance experience in a healthcare context (Unpublished doctoral dissertation). University of Ulster, Belfast.

Evergreen, S. D. H. ( 2013 ). Presenting data effectively: Communicating your findings for maximum impact . London, England: Sage.

Evergreen, S. D. H. ( 2016 ). Effective data visualization: The right chart for the right data . London, England: Sage.

Fenner, P. ( 2011 ) Place, matter and meaning: Extending the relationship in psychological therapies.   Health & Place, 17, 851–857.

Fenner, P. ( 2017 ). Art therapy, places, flows, forces and becoming.   ATOL Art Therapy OnLine, 8, 1.

Flewitt, R. ( 2005 ). Is every child’s voice heard? Researching the different ways 3-year-old children communicate and make meaning at home and in a pre-school playgroup.   Early Years, 25, 207–222.

Flyvberg, B. ( 2006 ). Five misunderstandings about case-study research.   Qualitative Inquiry, 12, 219–245.

Frank. A. ( 1997 ). Enacting illness stories: When, what, why. In H. L. Nelson (Ed.), Stories and their limits (pp. 31–49). London, England: Routledge.

Funnell, S. C. , & Rogers, P. J. ( 2011 ) Effective use of theories of change and logic models . New York, NY: Wiley.

Gomm, R. , Hammersley, M. , & Foster, P. (Eds.). ( 2004 ). Case study method: Key issues, key texts . London, England: Sage.

Greene, J. C. ( 2000 ). Understanding social programs through evaluation. In N. K. Denzin & Y. S. Lincoln (Eds.), The handbook of qualitative research (2nd ed., pp. 981–999). Thousand Oaks, CA: Sage.

Greene, J. C. ( 2007 ). Mixing methods in social inquiry . San Francisco, CA: Jossey–Bass.

Greene, J. C. , & Caracelli, V. J. ( 1997 ). Defining and describing the paradigm issue in mixed-method evaluation.   New Directions for Evaluation, 74, 5–17.

Greene, J. C. , Caracelli, V. J. , & Graham, W. F. ( 1989 ). Toward a conceptual framework for mixed-method evaluation designs.   Educational Evaluation and Policy Analysis, 11, 255–274.

Greenhalgh, T. , & Worrall, J. G. ( 1997 ). From EBM to CSM: The evolution of context-sensitive medicine.   Journal of Evaluation in Clinical Practice, 3, 105–108.

Harrington, W. ( 2003 ). What journalism can offer ethnography.   Qualitative Inquiry, 9, 90–114.

Heron, J. ( 1992 ). Feeling and personhood . London, England: Sage.

Heron, J. ( 1999 ). The complete facilitator’s handbook . London, England: Kogan Page.

House, E. R. ( 1980 ). Evaluating with validity . London, England: Sage.

House, E. R. ( 1993 ). Professional evaluation: Social impact and political consequences . Newbury Park, CA: Sage.

Kirkhart, K. (2013, April) Repositioning validity . Paper presented at the CREA Inaugural Conference, Chicago, IL.

Kushner, S. ( 2000 ). Personalizing evaluation . London, England: Sage.

Leavy, P. ( 2011 ). Oral history: Understanding qualitative research . Oxford, England: Oxford University Press.

Liamputtong, P. , & Rumbold, J. (Eds.). ( 2008 ). Knowing differently: Arts-based and collaborative research methods . New York, NY: Nova Science.

MacDonald, B. ( 1976 ). Evaluation and the control of education. In D. Tawney (Ed.), Curriculum evaluation today: Trends and implications (pp. 125–136). London, England: Macmillan.

MacDonald, B. ( 1977 ). The portrayal of persons as evaluation data. In N. Norris (Ed.), Safari 2: Theory in practice (pp. 50–67). Norwich: University of East Anglia, Centre for Applied Research in Education.

Matarasso, F. ( 2012 ). Where We Dream: West Bromich Operatic Society and the Fine Art of Musical Theatre, West Bromwich, England: Multistory.

Mazzei, L. A. ( 2003 ) Inhabited silences: In pursuit of a muffled subtext.   Qualitative Inquiry, 9, 355–368.

Mazzei, L. A. ( 2007 ). Inhabited silence in qualitative research: Putting poststructural theory to work . New York, NY: Lang.

Merriam, S. B. ( 1988 ). Case study research in education: A qualitative approach . San Francisco, CA: Jossey–Bass.

Mullen, C. A. , & Finley, S. (Eds.). ( 2003 ). Arts-based approaches to qualitative inquiry [Special Issue].   Qualitative Inquiry, 9, 165–329.

Okri, B. ( 1997 ). A way of being free . London, England: Phoenix.

Parlett, M. , & Hamilton, D. ( 1976 ). Evaluation as illumination: A new approach to the study of innovatory programmes. In G. Glass (Ed.), Evaluation studies review annual (Vol. I, pp. 140–157). Beverly Hills: CA: Sage. [First published in 1972 as Occasional Paper 9, Centre for Research in the Educational Sciences, University of Edinburgh.]

Plakoyiannaki, E. , & Stavraki, G. ( 2018 ). Collage visual data: Pathways to data analysis. In C. Cassell , A. L. Cunliffe , & G. Grandy (Eds.), Case management research methods: Vol. 2, Methods and challenges (ch. 19, pp. 313–328). London, England: Sage. Retrieved from https://www.researchgate.net/publication/325404748_Collage_Visual_Data_Pathways_to_Data_Analysis .

Platt, J. ( 2007 ). Case study. In W. Outhwaite & S. P. Turner (Eds.), The Sage handbook of social science methodology (pp. 100–118). London, England: Sage.

Prosser, J. ( 2000 ). The moral maze of image ethics. In H. Simons & R. Usher (Eds.), Situated ethics in educational research (pp. 116–132). London, England: Routledge/Falmer.

Ragin, C. C. ( 1992 ). Cases of “What is a case?” In C. C. Ragin & H. S. Becker (Eds.), What is a case? Exploring the foundations of social inquiry (pp. 1–17). Cambridge, England: Cambridge University Press.

Reynolds, S. S. (1908). A poor man’s house [eBook#26126]. Retrieved from http://www.gutenberg.org

Richardson, L. ( 1994 ). Writing as a form of inquiry. In N. K. Denzin & Y. S. Lincoln (Eds.), Handbook of qualitative research (pp. 516–529). London, England: Sage.

Rogers, P. ( 2017 ). Using logic models and theories of change in evaluation. Retrieved from https://www.betterevaluation.org/en/node/4902

Rugang, L. ( 2006 ). Chinese culture in globalisation: A multi-modal case study on visual discourse (Unpublished doctoral dissertation). University of Southampton, England.

Seale, C. ( 1999 ). The quality of qualitative research . London, England: Sage.

Sewell, K. ( 2011 ). Researching sensitive issues: A critical appraisal of “draw and write” as a data collection technique in eliciting children’s perceptions.   International Journal of Research Methods in Education, 34, 175–191.

Shaw, I. , & Gould, N. ( 2001 ). Qualitative research in social work: Context and method . London, England: Sage.

Silverman, D. ( 2000 ). Doing qualitative research: A practical handbook . London, England: Sage.

Silverman, D. (Ed.). ( 2004 ). Qualitative research: Theory, methods and practice (2nd ed.). London, England: Sage.

Simons, H. ( 1971 ). Innovation and the case study of schools.   Cambridge Journal of Education, 3, 118–123.

Simons, H. (Ed.). ( 1980 ). Towards a science of the singular: Essays about case study in educational research and evaluation . Occasional Papers No. 10. Norwich, England: Centre for Applied Research, University of East Anglia.

Simons, H. ( 1987 ). Getting to know schools in a democracy: The politics and process of evaluation . Lewes, England: Falmer Press.

Simons, H. ( 1996 ). The paradox of case study.   Cambridge Journal of Education, 26, 225–240.

Simons, H. ( 2000 ). Damned if you do, damned if you don’t: Ethical and political dilemmas in evaluation. In H. Simons & R. Usher (Eds.), Situated ethics in educational research (pp. 39–Falmer.

Simons, H. ( 2002 ). School self-evaluation in a democracy. In D. Nevo (Ed.), School-based evaluation: An international perspective . London, England: Sage.

Simons, H. ( 2006 ). Ethics and evaluation. In I. F. Shaw , J. C. Greene , & M. M. Mark (Eds.), The international handbook of evaluation (pp. 243–265). London, England: Sage.

Simons, H. ( 2007 ) Whose data is it anyway? Ethical issues in qualitative research.   The Malaysian Journal of Qualitative Research , (Vol. 1, pp. 6–18). Malaysia: Qualitative Research Association of Malaysia (QRAM).

Simons, H. ( 2009 ). Case study research in practice . London, England: Sage.

Simons, H. (2010, May). Democratic evaluation: Theory and practice . Paper prepared for Virtual Evaluation Conference, University of the Witwatersrand, Johannesburg, South Africa.

Simons, H. , Kushner, S. , Jones, K. , & James, D. ( 2003 ). From evidence-based practice to practice-based evidence: The idea of situated generalization.   Research Papers in Education: Policy and Practice, 18, 347–364.

Simons, H. , & McCormack, B. ( 2007 ). Integrating arts-based inquiry in evaluation methodology.   Qualitative Inquiry, 13, 292–311.

Smith, L. M. , & Pohland, P. A. ( 1974 ). Education, technology, and the rural highlands. In R. H. P. Kraft ., L. M. Smith ., P. A. Pohland ., C. J. Brauner , & C. Gjerde (Eds.), Four evaluation examples: Anthropological, economic, narrative and portrayal (pp. 5–54), AERA Monograph Series on Curriculum Evaluation 7. Chicago, IL: Rand McNally.

Sparkes, A. ( 2002 ). Telling tales in sport and physical activity: A qualitative journey . Champaign, IL: Human Kinetics Press.

Sparkes, A. C. , & Douglas, K. ( 2007 ). Making the case for poetic representations: An example in action.   The Sport Psychologist, 21, 170–190.

Spouse, J. ( 2000 ). Talking pictures: Investigating personal knowledge though illuminating artwork.   Nursing Times Research Journal, 5, 253–261.

Stake, R. E. ( 1978 ). The case study method in social inquiry.   Educational Researcher, 7, 5–9.

Stake, R. E. ( 1995 ). The art of case study research . Thousand Oaks, CA: Sage.

Stake, R. E. ( 2006 ). Multiple Case Study Analysis. New York, NY: The Guildford Press

Stake, R. E. ( 2010 ). Qualitative research: Studying how things work . New York, NY: Guildford Press.

Stenhouse, L. ( 1978 ). Case study and case records: Towards a contemporary history of education.   British Educational Research Journal, 4, 21–39.

Tashakkori, A. & Teddlie, C. (1998, 2003 ) Handbook of Mixed Methods in Social &. Behavioral Research. Thousand Oaks: Sage

Thomas, G. ( 2011 ). A typology for the case study in social science following a review of definition, discourse and structure.   Qualitative Inquiry, 17, 511–521.

Thomas, G. ( 2016 ). How to do your case study (2nd ed.). London, England: Sage.

Walker, R. ( 1993 ). Finding a silent voice for the researcher: Using photographs in evaluation and research. In M. Schratz (Ed.), Qualitative voices in educational research (pp. 72–92). Lewes, England: Falmer Press.

Wilson, E. G. ( 2008 ). Against happiness . New York, NY: Sarah Crichton Books.

Yin, R. K. ( 2004 ). Case study research: Design and methods . Thousand Oaks, CA: Sage.

Zucker, D. M. ( 2001 ). Using case study methodology in nursing research.   Qualitative Report, 6(2).

• About Oxford Academic
• Publish journals with us
• University press partners
• What we publish
• New features  
• Open access
• Institutional account management
• Rights and permissions
• Get help with access
• Accessibility
• Advertising
• Media enquiries
• Oxford University Press
• Oxford Languages
• University of Oxford

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide

• Copyright © 2024 Oxford University Press
• Cookie settings
• Cookie policy
• Privacy policy
• Legal notice

This Feature Is Available To Subscribers Only

Sign In or Create an Account

This PDF is available to Subscribers Only

For full access to this pdf, sign in to an existing account, or purchase an annual subscription.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Int J Qual Stud Health Well-being

Methodology or method? A critical review of qualitative case study reports

Despite on-going debate about credibility, and reported limitations in comparison to other approaches, case study is an increasingly popular approach among qualitative researchers. We critically analysed the methodological descriptions of published case studies. Three high-impact qualitative methods journals were searched to locate case studies published in the past 5 years; 34 were selected for analysis. Articles were categorized as health and health services ( n= 12), social sciences and anthropology ( n= 7), or methods ( n= 15) case studies. The articles were reviewed using an adapted version of established criteria to determine whether adequate methodological justification was present, and if study aims, methods, and reported findings were consistent with a qualitative case study approach. Findings were grouped into five themes outlining key methodological issues: case study methodology or method, case of something particular and case selection, contextually bound case study, researcher and case interactions and triangulation, and study design inconsistent with methodology reported. Improved reporting of case studies by qualitative researchers will advance the methodology for the benefit of researchers and practitioners.

Case study research is an increasingly popular approach among qualitative researchers (Thomas, 2011 ). Several prominent authors have contributed to methodological developments, which has increased the popularity of case study approaches across disciplines (Creswell, 2013b ; Denzin & Lincoln, 2011b ; Merriam, 2009 ; Ragin & Becker, 1992 ; Stake, 1995 ; Yin, 2009 ). Current qualitative case study approaches are shaped by paradigm, study design, and selection of methods, and, as a result, case studies in the published literature vary. Differences between published case studies can make it difficult for researchers to define and understand case study as a methodology.

Experienced qualitative researchers have identified case study research as a stand-alone qualitative approach (Denzin & Lincoln, 2011b ). Case study research has a level of flexibility that is not readily offered by other qualitative approaches such as grounded theory or phenomenology. Case studies are designed to suit the case and research question and published case studies demonstrate wide diversity in study design. There are two popular case study approaches in qualitative research. The first, proposed by Stake ( 1995 ) and Merriam ( 2009 ), is situated in a social constructivist paradigm, whereas the second, by Yin ( 2012 ), Flyvbjerg ( 2011 ), and Eisenhardt ( 1989 ), approaches case study from a post-positivist viewpoint. Scholarship from both schools of inquiry has contributed to the popularity of case study and development of theoretical frameworks and principles that characterize the methodology.

The diversity of case studies reported in the published literature, and on-going debates about credibility and the use of case study in qualitative research practice, suggests that differences in perspectives on case study methodology may prevent researchers from developing a mutual understanding of practice and rigour. In addition, discussion about case study limitations has led some authors to query whether case study is indeed a methodology (Luck, Jackson, & Usher, 2006 ; Meyer, 2001 ; Thomas, 2010 ; Tight, 2010 ). Methodological discussion of qualitative case study research is timely, and a review is required to analyse and understand how this methodology is applied in the qualitative research literature. The aims of this study were to review methodological descriptions of published qualitative case studies, to review how the case study methodological approach was applied, and to identify issues that need to be addressed by researchers, editors, and reviewers. An outline of the current definitions of case study and an overview of the issues proposed in the qualitative methodological literature are provided to set the scene for the review.

Definitions of qualitative case study research

Case study research is an investigation and analysis of a single or collective case, intended to capture the complexity of the object of study (Stake, 1995 ). Qualitative case study research, as described by Stake ( 1995 ), draws together “naturalistic, holistic, ethnographic, phenomenological, and biographic research methods” in a bricoleur design, or in his words, “a palette of methods” (Stake, 1995 , pp. xi–xii). Case study methodology maintains deep connections to core values and intentions and is “particularistic, descriptive and heuristic” (Merriam, 2009 , p. 46).

As a study design, case study is defined by interest in individual cases rather than the methods of inquiry used. The selection of methods is informed by researcher and case intuition and makes use of naturally occurring sources of knowledge, such as people or observations of interactions that occur in the physical space (Stake, 1998 ). Thomas ( 2011 ) suggested that “analytical eclecticism” is a defining factor (p. 512). Multiple data collection and analysis methods are adopted to further develop and understand the case, shaped by context and emergent data (Stake, 1995 ). This qualitative approach “explores a real-life, contemporary bounded system (a case ) or multiple bounded systems (cases) over time, through detailed, in-depth data collection involving multiple sources of information … and reports a case description and case themes ” (Creswell, 2013b , p. 97). Case study research has been defined by the unit of analysis, the process of study, and the outcome or end product, all essentially the case (Merriam, 2009 ).

The case is an object to be studied for an identified reason that is peculiar or particular. Classification of the case and case selection procedures informs development of the study design and clarifies the research question. Stake ( 1995 ) proposed three types of cases and study design frameworks. These include the intrinsic case, the instrumental case, and the collective instrumental case. The intrinsic case is used to understand the particulars of a single case, rather than what it represents. An instrumental case study provides insight on an issue or is used to refine theory. The case is selected to advance understanding of the object of interest. A collective refers to an instrumental case which is studied as multiple, nested cases, observed in unison, parallel, or sequential order. More than one case can be simultaneously studied; however, each case study is a concentrated, single inquiry, studied holistically in its own entirety (Stake, 1995 , 1998 ).

Researchers who use case study are urged to seek out what is common and what is particular about the case. This involves careful and in-depth consideration of the nature of the case, historical background, physical setting, and other institutional and political contextual factors (Stake, 1998 ). An interpretive or social constructivist approach to qualitative case study research supports a transactional method of inquiry, where the researcher has a personal interaction with the case. The case is developed in a relationship between the researcher and informants, and presented to engage the reader, inviting them to join in this interaction and in case discovery (Stake, 1995 ). A postpositivist approach to case study involves developing a clear case study protocol with careful consideration of validity and potential bias, which might involve an exploratory or pilot phase, and ensures that all elements of the case are measured and adequately described (Yin, 2009 , 2012 ).

Current methodological issues in qualitative case study research

The future of qualitative research will be influenced and constructed by the way research is conducted, and by what is reviewed and published in academic journals (Morse, 2011 ). If case study research is to further develop as a principal qualitative methodological approach, and make a valued contribution to the field of qualitative inquiry, issues related to methodological credibility must be considered. Researchers are required to demonstrate rigour through adequate descriptions of methodological foundations. Case studies published without sufficient detail for the reader to understand the study design, and without rationale for key methodological decisions, may lead to research being interpreted as lacking in quality or credibility (Hallberg, 2013 ; Morse, 2011 ).

There is a level of artistic license that is embraced by qualitative researchers and distinguishes practice, which nurtures creativity, innovation, and reflexivity (Denzin & Lincoln, 2011b ; Morse, 2009 ). Qualitative research is “inherently multimethod” (Denzin & Lincoln, 2011a , p. 5); however, with this creative freedom, it is important for researchers to provide adequate description for methodological justification (Meyer, 2001 ). This includes paradigm and theoretical perspectives that have influenced study design. Without adequate description, study design might not be understood by the reader, and can appear to be dishonest or inaccurate. Reviewers and readers might be confused by the inconsistent or inappropriate terms used to describe case study research approach and methods, and be distracted from important study findings (Sandelowski, 2000 ). This issue extends beyond case study research, and others have noted inconsistencies in reporting of methodology and method by qualitative researchers. Sandelowski ( 2000 , 2010 ) argued for accurate identification of qualitative description as a research approach. She recommended that the selected methodology should be harmonious with the study design, and be reflected in methods and analysis techniques. Similarly, Webb and Kevern ( 2000 ) uncovered inconsistencies in qualitative nursing research with focus group methods, recommending that methodological procedures must cite seminal authors and be applied with respect to the selected theoretical framework. Incorrect labelling using case study might stem from the flexibility in case study design and non-directional character relative to other approaches (Rosenberg & Yates, 2007 ). Methodological integrity is required in design of qualitative studies, including case study, to ensure study rigour and to enhance credibility of the field (Morse, 2011 ).

Case study has been unnecessarily devalued by comparisons with statistical methods (Eisenhardt, 1989 ; Flyvbjerg, 2006 , 2011 ; Jensen & Rodgers, 2001 ; Piekkari, Welch, & Paavilainen, 2009 ; Tight, 2010 ; Yin, 1999 ). It is reputed to be the “the weak sibling” in comparison to other, more rigorous, approaches (Yin, 2009 , p. xiii). Case study is not an inherently comparative approach to research. The objective is not statistical research, and the aim is not to produce outcomes that are generalizable to all populations (Thomas, 2011 ). Comparisons between case study and statistical research do little to advance this qualitative approach, and fail to recognize its inherent value, which can be better understood from the interpretive or social constructionist viewpoint of other authors (Merriam, 2009 ; Stake, 1995 ). Building on discussions relating to “fuzzy” (Bassey, 2001 ), or naturalistic generalizations (Stake, 1978 ), or transference of concepts and theories (Ayres, Kavanaugh, & Knafl, 2003 ; Morse et al., 2011 ) would have more relevance.

Case study research has been used as a catch-all design to justify or add weight to fundamental qualitative descriptive studies that do not fit with other traditional frameworks (Merriam, 2009 ). A case study has been a “convenient label for our research—when we ‘can't think of anything ‘better”—in an attempt to give it [qualitative methodology] some added respectability” (Tight, 2010 , p. 337). Qualitative case study research is a pliable approach (Merriam, 2009 ; Meyer, 2001 ; Stake, 1995 ), and has been likened to a “curious methodological limbo” (Gerring, 2004 , p. 341) or “paradigmatic bridge” (Luck et al., 2006 , p. 104), that is on the borderline between postpositivist and constructionist interpretations. This has resulted in inconsistency in application, which indicates that flexibility comes with limitations (Meyer, 2001 ), and the open nature of case study research might be off-putting to novice researchers (Thomas, 2011 ). The development of a well-(in)formed theoretical framework to guide a case study should improve consistency, rigour, and trust in studies published in qualitative research journals (Meyer, 2001 ).

Assessment of rigour

The purpose of this study was to analyse the methodological descriptions of case studies published in qualitative methods journals. To do this we needed to develop a suitable framework, which used existing, established criteria for appraising qualitative case study research rigour (Creswell, 2013b ; Merriam, 2009 ; Stake, 1995 ). A number of qualitative authors have developed concepts and criteria that are used to determine whether a study is rigorous (Denzin & Lincoln, 2011b ; Lincoln, 1995 ; Sandelowski & Barroso, 2002 ). The criteria proposed by Stake ( 1995 ) provide a framework for readers and reviewers to make judgements regarding case study quality, and identify key characteristics essential for good methodological rigour. Although each of the factors listed in Stake's criteria could enhance the quality of a qualitative research report, in Table I we present an adapted criteria used in this study, which integrates more recent work by Merriam ( 2009 ) and Creswell ( 2013b ). Stake's ( 1995 ) original criteria were separated into two categories. The first list of general criteria is “relevant for all qualitative research.” The second list, “high relevance to qualitative case study research,” was the criteria that we decided had higher relevance to case study research. This second list was the main criteria used to assess the methodological descriptions of the case studies reviewed. The complete table has been preserved so that the reader can determine how the original criteria were adapted.

Framework for assessing quality in qualitative case study research.

Adapted from Stake ( 1995 , p. 131).

Study design

The critical review method described by Grant and Booth ( 2009 ) was used, which is appropriate for the assessment of research quality, and is used for literature analysis to inform research and practice. This type of review goes beyond the mapping and description of scoping or rapid reviews, to include “analysis and conceptual innovation” (Grant & Booth, 2009 , p. 93). A critical review is used to develop existing, or produce new, hypotheses or models. This is different to systematic reviews that answer clinical questions. It is used to evaluate existing research and competing ideas, to provide a “launch pad” for conceptual development and “subsequent testing” (Grant & Booth, 2009 , p. 93).

Qualitative methods journals were located by a search of the 2011 ISI Journal Citation Reports in Social Science, via the database Web of Knowledge (see m.webofknowledge.com). No “qualitative research methods” category existed in the citation reports; therefore, a search of all categories was performed using the term “qualitative.” In Table II , we present the qualitative methods journals located, ranked by impact factor. The highest ranked journals were selected for searching. We acknowledge that the impact factor ranking system might not be the best measure of journal quality (Cheek, Garnham, & Quan, 2006 ); however, this was the most appropriate and accessible method available.

International Journal of Qualitative Studies on Health and Well-being.

Search strategy

In March 2013, searches of the journals, Qualitative Health Research , Qualitative Research , and Qualitative Inquiry were completed to retrieve studies with “case study” in the abstract field. The search was limited to the past 5 years (1 January 2008 to 1 March 2013). The objective was to locate published qualitative case studies suitable for assessment using the adapted criterion. Viewpoints, commentaries, and other article types were excluded from review. Title and abstracts of the 45 retrieved articles were read by the first author, who identified 34 empirical case studies for review. All authors reviewed the 34 studies to confirm selection and categorization. In Table III , we present the 34 case studies grouped by journal, and categorized by research topic, including health sciences, social sciences and anthropology, and methods research. There was a discrepancy in categorization of one article on pedagogy and a new teaching method published in Qualitative Inquiry (Jorrín-Abellán, Rubia-Avi, Anguita-Martínez, Gómez-Sánchez, & Martínez-Mones, 2008 ). Consensus was to allocate to the methods category.

Outcomes of search of qualitative methods journals.

In Table III , the number of studies located, and final numbers selected for review have been reported. Qualitative Health Research published the most empirical case studies ( n= 16). In the health category, there were 12 case studies of health conditions, health services, and health policy issues, all published in Qualitative Health Research . Seven case studies were categorized as social sciences and anthropology research, which combined case study with biography and ethnography methodologies. All three journals published case studies on methods research to illustrate a data collection or analysis technique, methodological procedure, or related issue.

The methodological descriptions of 34 case studies were critically reviewed using the adapted criteria. All articles reviewed contained a description of study methods; however, the length, amount of detail, and position of the description in the article varied. Few studies provided an accurate description and rationale for using a qualitative case study approach. In the 34 case studies reviewed, three described a theoretical framework informed by Stake ( 1995 ), two by Yin ( 2009 ), and three provided a mixed framework informed by various authors, which might have included both Yin and Stake. Few studies described their case study design, or included a rationale that explained why they excluded or added further procedures, and whether this was to enhance the study design, or to better suit the research question. In 26 of the studies no reference was provided to principal case study authors. From reviewing the description of methods, few authors provided a description or justification of case study methodology that demonstrated how their study was informed by the methodological literature that exists on this approach.

The methodological descriptions of each study were reviewed using the adapted criteria, and the following issues were identified: case study methodology or method; case of something particular and case selection; contextually bound case study; researcher and case interactions and triangulation; and, study design inconsistent with methodology. An outline of how the issues were developed from the critical review is provided, followed by a discussion of how these relate to the current methodological literature.

Case study methodology or method

A third of the case studies reviewed appeared to use a case report method, not case study methodology as described by principal authors (Creswell, 2013b ; Merriam, 2009 ; Stake, 1995 ; Yin, 2009 ). Case studies were identified as a case report because of missing methodological detail and by review of the study aims and purpose. These reports presented data for small samples of no more than three people, places or phenomenon. Four studies, or “case reports” were single cases selected retrospectively from larger studies (Bronken, Kirkevold, Martinsen, & Kvigne, 2012 ; Coltart & Henwood, 2012 ; Hooghe, Neimeyer, & Rober, 2012 ; Roscigno et al., 2012 ). Case reports were not a case of something, instead were a case demonstration or an example presented in a report. These reports presented outcomes, and reported on how the case could be generalized. Descriptions focussed on the phenomena, rather than the case itself, and did not appear to study the case in its entirety.

Case reports had minimal in-text references to case study methodology, and were informed by other qualitative traditions or secondary sources (Adamson & Holloway, 2012 ; Buzzanell & D'Enbeau, 2009 ; Nagar-Ron & Motzafi-Haller, 2011 ). This does not suggest that case study methodology cannot be multimethod, however, methodology should be consistent in design, be clearly described (Meyer, 2001 ; Stake, 1995 ), and maintain focus on the case (Creswell, 2013b ).

To demonstrate how case reports were identified, three examples are provided. The first, Yeh ( 2013 ) described their study as, “the examination of the emergence of vegetarianism in Victorian England serves as a case study to reveal the relationships between boundaries and entities” (p. 306). The findings were a historical case report, which resulted from an ethnographic study of vegetarianism. Cunsolo Willox, Harper, Edge, ‘My Word’: Storytelling and Digital Media Lab, and Rigolet Inuit Community Government (2013) used “a case study that illustrates the usage of digital storytelling within an Inuit community” (p. 130). This case study reported how digital storytelling can be used with indigenous communities as a participatory method to illuminate the benefits of this method for other studies. This “case study was conducted in the Inuit community” but did not include the Inuit community in case analysis (Cunsolo Willox et al., 2013 , p. 130). Bronken et al. ( 2012 ) provided a single case report to demonstrate issues observed in a larger clinical study of aphasia and stroke, without adequate case description or analysis.

Case study of something particular and case selection

Case selection is a precursor to case analysis, which needs to be presented as a convincing argument (Merriam, 2009 ). Descriptions of the case were often not adequate to ascertain why the case was selected, or whether it was a particular exemplar or outlier (Thomas, 2011 ). In a number of case studies in the health and social science categories, it was not explicit whether the case was of something particular, or peculiar to their discipline or field (Adamson & Holloway, 2012 ; Bronken et al., 2012 ; Colón-Emeric et al., 2010 ; Jackson, Botelho, Welch, Joseph, & Tennstedt, 2012 ; Mawn et al., 2010 ; Snyder-Young, 2011 ). There were exceptions in the methods category ( Table III ), where cases were selected by researchers to report on a new or innovative method. The cases emerged through heuristic study, and were reported to be particular, relative to the existing methods literature (Ajodhia-Andrews & Berman, 2009 ; Buckley & Waring, 2013 ; Cunsolo Willox et al., 2013 ; De Haene, Grietens, & Verschueren, 2010 ; Gratton & O'Donnell, 2011 ; Sumsion, 2013 ; Wimpenny & Savin-Baden, 2012 ).

Case selection processes were sometimes insufficient to understand why the case was selected from the global population of cases, or what study of this case would contribute to knowledge as compared with other possible cases (Adamson & Holloway, 2012 ; Bronken et al., 2012 ; Colón-Emeric et al., 2010 ; Jackson et al., 2012 ; Mawn et al., 2010 ). In two studies, local cases were selected (Barone, 2010 ; Fourie & Theron, 2012 ) because the researcher was familiar with and had access to the case. Possible limitations of a convenience sample were not acknowledged. Purposeful sampling was used to recruit participants within the case of one study, but not of the case itself (Gallagher et al., 2013 ). Random sampling was completed for case selection in two studies (Colón-Emeric et al., 2010 ; Jackson et al., 2012 ), which has limited meaning in interpretive qualitative research.

To demonstrate how researchers provided a good justification for the selection of case study approaches, four examples are provided. The first, cases of residential care homes, were selected because of reported occurrences of mistreatment, which included residents being locked in rooms at night (Rytterström, Unosson, & Arman, 2013 ). Roscigno et al. ( 2012 ) selected cases of parents who were admitted for early hospitalization in neonatal intensive care with a threatened preterm delivery before 26 weeks. Hooghe et al. ( 2012 ) used random sampling to select 20 couples that had experienced the death of a child; however, the case study was of one couple and a particular metaphor described only by them. The final example, Coltart and Henwood ( 2012 ), provided a detailed account of how they selected two cases from a sample of 46 fathers based on personal characteristics and beliefs. They described how the analysis of the two cases would contribute to their larger study on first time fathers and parenting.

Contextually bound case study

The limits or boundaries of the case are a defining factor of case study methodology (Merriam, 2009 ; Ragin & Becker, 1992 ; Stake, 1995 ; Yin, 2009 ). Adequate contextual description is required to understand the setting or context in which the case is revealed. In the health category, case studies were used to illustrate a clinical phenomenon or issue such as compliance and health behaviour (Colón-Emeric et al., 2010 ; D'Enbeau, Buzzanell, & Duckworth, 2010 ; Gallagher et al., 2013 ; Hooghe et al., 2012 ; Jackson et al., 2012 ; Roscigno et al., 2012 ). In these case studies, contextual boundaries, such as physical and institutional descriptions, were not sufficient to understand the case as a holistic system, for example, the general practitioner (GP) clinic in Gallagher et al. ( 2013 ), or the nursing home in Colón-Emeric et al. ( 2010 ). Similarly, in the social science and methods categories, attention was paid to some components of the case context, but not others, missing important information required to understand the case as a holistic system (Alexander, Moreira, & Kumar, 2012 ; Buzzanell & D'Enbeau, 2009 ; Nairn & Panelli, 2009 ; Wimpenny & Savin-Baden, 2012 ).

In two studies, vicarious experience or vignettes (Nairn & Panelli, 2009 ) and images (Jorrín-Abellán et al., 2008 ) were effective to support description of context, and might have been a useful addition for other case studies. Missing contextual boundaries suggests that the case might not be adequately defined. Additional information, such as the physical, institutional, political, and community context, would improve understanding of the case (Stake, 1998 ). In Boxes 1 and 2 , we present brief synopses of two studies that were reviewed, which demonstrated a well bounded case. In Box 1 , Ledderer ( 2011 ) used a qualitative case study design informed by Stake's tradition. In Box 2 , Gillard, Witt, and Watts ( 2011 ) were informed by Yin's tradition. By providing a brief outline of the case studies in Boxes 1 and 2 , we demonstrate how effective case boundaries can be constructed and reported, which may be of particular interest to prospective case study researchers.

Article synopsis of case study research using Stake's tradition

Ledderer ( 2011 ) used a qualitative case study research design, informed by modern ethnography. The study is bounded to 10 general practice clinics in Denmark, who had received federal funding to implement preventative care services based on a Motivational Interviewing intervention. The researcher question focussed on “why is it so difficult to create change in medical practice?” (Ledderer, 2011 , p. 27). The study context was adequately described, providing detail on the general practitioner (GP) clinics and relevant political and economic influences. Methodological decisions are described in first person narrative, providing insight on researcher perspectives and interaction with the case. Forty-four interviews were conducted, which focussed on how GPs conducted consultations, and the form, nature and content, rather than asking their opinion or experience (Ledderer, 2011 , p. 30). The duration and intensity of researcher immersion in the case enhanced depth of description and trustworthiness of study findings. Analysis was consistent with Stake's tradition, and the researcher provided examples of inquiry techniques used to challenge assumptions about emerging themes. Several other seminal qualitative works were cited. The themes and typology constructed are rich in narrative data and storytelling by clinic staff, demonstrating individual clinic experiences as well as shared meanings and understandings about changing from a biomedical to psychological approach to preventative health intervention. Conclusions make note of social and cultural meanings and lessons learned, which might not have been uncovered using a different methodology.

Article synopsis of case study research using Yin's tradition

Gillard et al. ( 2011 ) study of camps for adolescents living with HIV/AIDs provided a good example of Yin's interpretive case study approach. The context of the case is bounded by the three summer camps of which the researchers had prior professional involvement. A case study protocol was developed that used multiple methods to gather information at three data collection points coinciding with three youth camps (Teen Forum, Discover Camp, and Camp Strong). Gillard and colleagues followed Yin's ( 2009 ) principles, using a consistent data protocol that enhanced cross-case analysis. Data described the young people, the camp physical environment, camp schedule, objectives and outcomes, and the staff of three youth camps. The findings provided a detailed description of the context, with less detail of individual participants, including insight into researcher's interpretations and methodological decisions throughout the data collection and analysis process. Findings provided the reader with a sense of “being there,” and are discovered through constant comparison of the case with the research issues; the case is the unit of analysis. There is evidence of researcher immersion in the case, and Gillard reports spending significant time in the field in a naturalistic and integrated youth mentor role.

This case study is not intended to have a significant impact on broader health policy, although does have implications for health professionals working with adolescents. Study conclusions will inform future camps for young people with chronic disease, and practitioners are able to compare similarities between this case and their own practice (for knowledge translation). No limitations of this article were reported. Limitations related to publication of this case study were that it was 20 pages long and used three tables to provide sufficient description of the camp and program components, and relationships with the research issue.

Researcher and case interactions and triangulation

Researcher and case interactions and transactions are a defining feature of case study methodology (Stake, 1995 ). Narrative stories, vignettes, and thick description are used to provoke vicarious experience and a sense of being there with the researcher in their interaction with the case. Few of the case studies reviewed provided details of the researcher's relationship with the case, researcher–case interactions, and how these influenced the development of the case study (Buzzanell & D'Enbeau, 2009 ; D'Enbeau et al., 2010 ; Gallagher et al., 2013 ; Gillard et al., 2011 ; Ledderer, 2011 ; Nagar-Ron & Motzafi-Haller, 2011 ). The role and position of the researcher needed to be self-examined and understood by readers, to understand how this influenced interactions with participants, and to determine what triangulation is needed (Merriam, 2009 ; Stake, 1995 ).

Gillard et al. ( 2011 ) provided a good example of triangulation, comparing data sources in a table (p. 1513). Triangulation of sources was used to reveal as much depth as possible in the study by Nagar-Ron and Motzafi-Haller ( 2011 ), while also enhancing confirmation validity. There were several case studies that would have benefited from improved range and use of data sources, and descriptions of researcher–case interactions (Ajodhia-Andrews & Berman, 2009 ; Bronken et al., 2012 ; Fincham, Scourfield, & Langer, 2008 ; Fourie & Theron, 2012 ; Hooghe et al., 2012 ; Snyder-Young, 2011 ; Yeh, 2013 ).

Study design inconsistent with methodology

Good, rigorous case studies require a strong methodological justification (Meyer, 2001 ) and a logical and coherent argument that defines paradigm, methodological position, and selection of study methods (Denzin & Lincoln, 2011b ). Methodological justification was insufficient in several of the studies reviewed (Barone, 2010 ; Bronken et al., 2012 ; Hooghe et al., 2012 ; Mawn et al., 2010 ; Roscigno et al., 2012 ; Yeh, 2013 ). This was judged by the absence, or inadequate or inconsistent reference to case study methodology in-text.

In six studies, the methodological justification provided did not relate to case study. There were common issues identified. Secondary sources were used as primary methodological references indicating that study design might not have been theoretically sound (Colón-Emeric et al., 2010 ; Coltart & Henwood, 2012 ; Roscigno et al., 2012 ; Snyder-Young, 2011 ). Authors and sources cited in methodological descriptions were inconsistent with the actual study design and practices used (Fourie & Theron, 2012 ; Hooghe et al., 2012 ; Jorrín-Abellán et al., 2008 ; Mawn et al., 2010 ; Rytterström et al., 2013 ; Wimpenny & Savin-Baden, 2012 ). This occurred when researchers cited Stake or Yin, or both (Mawn et al., 2010 ; Rytterström et al., 2013 ), although did not follow their paradigmatic or methodological approach. In 26 studies there were no citations for a case study methodological approach.

The findings of this study have highlighted a number of issues for researchers. A considerable number of case studies reviewed were missing key elements that define qualitative case study methodology and the tradition cited. A significant number of studies did not provide a clear methodological description or justification relevant to case study. Case studies in health and social sciences did not provide sufficient information for the reader to understand case selection, and why this case was chosen above others. The context of the cases were not described in adequate detail to understand all relevant elements of the case context, which indicated that cases may have not been contextually bounded. There were inconsistencies between reported methodology, study design, and paradigmatic approach in case studies reviewed, which made it difficult to understand the study methodology and theoretical foundations. These issues have implications for methodological integrity and honesty when reporting study design, which are values of the qualitative research tradition and are ethical requirements (Wager & Kleinert, 2010a ). Poorly described methodological descriptions may lead the reader to misinterpret or discredit study findings, which limits the impact of the study, and, as a collective, hinders advancements in the broader qualitative research field.

The issues highlighted in our review build on current debates in the case study literature, and queries about the value of this methodology. Case study research can be situated within different paradigms or designed with an array of methods. In order to maintain the creativity and flexibility that is valued in this methodology, clearer descriptions of paradigm and theoretical position and methods should be provided so that study findings are not undervalued or discredited. Case study research is an interdisciplinary practice, which means that clear methodological descriptions might be more important for this approach than other methodologies that are predominantly driven by fewer disciplines (Creswell, 2013b ).

Authors frequently omit elements of methodologies and include others to strengthen study design, and we do not propose a rigid or purist ideology in this paper. On the contrary, we encourage new ideas about using case study, together with adequate reporting, which will advance the value and practice of case study. The implications of unclear methodological descriptions in the studies reviewed were that study design appeared to be inconsistent with reported methodology, and key elements required for making judgements of rigour were missing. It was not clear whether the deviations from methodological tradition were made by researchers to strengthen the study design, or because of misinterpretations. Morse ( 2011 ) recommended that innovations and deviations from practice are best made by experienced researchers, and that a novice might be unaware of the issues involved with making these changes. To perpetuate the tradition of case study research, applications in the published literature should have consistencies with traditional methodological constructions, and deviations should be described with a rationale that is inherent in study conduct and findings. Providing methodological descriptions that demonstrate a strong theoretical foundation and coherent study design will add credibility to the study, while ensuring the intrinsic meaning of case study is maintained.

The value of this review is that it contributes to discussion of whether case study is a methodology or method. We propose possible reasons why researchers might make this misinterpretation. Researchers may interchange the terms methods and methodology, and conduct research without adequate attention to epistemology and historical tradition (Carter & Little, 2007 ; Sandelowski, 2010 ). If the rich meaning that naming a qualitative methodology brings to the study is not recognized, a case study might appear to be inconsistent with the traditional approaches described by principal authors (Creswell, 2013a ; Merriam, 2009 ; Stake, 1995 ; Yin, 2009 ). If case studies are not methodologically and theoretically situated, then they might appear to be a case report.

Case reports are promoted by university and medical journals as a method of reporting on medical or scientific cases; guidelines for case reports are publicly available on websites ( http://www.hopkinsmedicine.org/institutional_review_board/guidelines_policies/guidelines/case_report.html ). The various case report guidelines provide a general criteria for case reports, which describes that this form of report does not meet the criteria of research, is used for retrospective analysis of up to three clinical cases, and is primarily illustrative and for educational purposes. Case reports can be published in academic journals, but do not require approval from a human research ethics committee. Traditionally, case reports describe a single case, to explain how and what occurred in a selected setting, for example, to illustrate a new phenomenon that has emerged from a larger study. A case report is not necessarily particular or the study of a case in its entirety, and the larger study would usually be guided by a different research methodology.

This description of a case report is similar to what was provided in some studies reviewed. This form of report lacks methodological grounding and qualities of research rigour. The case report has publication value in demonstrating an example and for dissemination of knowledge (Flanagan, 1999 ). However, case reports have different meaning and purpose to case study, which needs to be distinguished. Findings of our review suggest that the medical understanding of a case report has been confused with qualitative case study approaches.

In this review, a number of case studies did not have methodological descriptions that included key characteristics of case study listed in the adapted criteria, and several issues have been discussed. There have been calls for improvements in publication quality of qualitative research (Morse, 2011 ), and for improvements in peer review of submitted manuscripts (Carter & Little, 2007 ; Jasper, Vaismoradi, Bondas, & Turunen, 2013 ). The challenging nature of editor and reviewers responsibilities are acknowledged in the literature (Hames, 2013 ; Wager & Kleinert, 2010b ); however, review of case study methodology should be prioritized because of disputes on methodological value.

Authors using case study approaches are recommended to describe their theoretical framework and methods clearly, and to seek and follow specialist methodological advice when needed (Wager & Kleinert, 2010a ). Adequate page space for case study description would contribute to better publications (Gillard et al., 2011 ). Capitalizing on the ability to publish complementary resources should be considered.

Limitations of the review

There is a level of subjectivity involved in this type of review and this should be considered when interpreting study findings. Qualitative methods journals were selected because the aims and scope of these journals are to publish studies that contribute to methodological discussion and development of qualitative research. Generalist health and social science journals were excluded that might have contained good quality case studies. Journals in business or education were also excluded, although a review of case studies in international business journals has been published elsewhere (Piekkari et al., 2009 ).

The criteria used to assess the quality of the case studies were a set of qualitative indicators. A numerical or ranking system might have resulted in different results. Stake's ( 1995 ) criteria have been referenced elsewhere, and was deemed the best available (Creswell, 2013b ; Crowe et al., 2011 ). Not all qualitative studies are reported in a consistent way and some authors choose to report findings in a narrative form in comparison to a typical biomedical report style (Sandelowski & Barroso, 2002 ), if misinterpretations were made this may have affected the review.

Case study research is an increasingly popular approach among qualitative researchers, which provides methodological flexibility through the incorporation of different paradigmatic positions, study designs, and methods. However, whereas flexibility can be an advantage, a myriad of different interpretations has resulted in critics questioning the use of case study as a methodology. Using an adaptation of established criteria, we aimed to identify and assess the methodological descriptions of case studies in high impact, qualitative methods journals. Few articles were identified that applied qualitative case study approaches as described by experts in case study design. There were inconsistencies in methodology and study design, which indicated that researchers were confused whether case study was a methodology or a method. Commonly, there appeared to be confusion between case studies and case reports. Without clear understanding and application of the principles and key elements of case study methodology, there is a risk that the flexibility of the approach will result in haphazard reporting, and will limit its global application as a valuable, theoretically supported methodology that can be rigorously applied across disciplines and fields.

Conflict of interest and funding

The authors have not received any funding or benefits from industry or elsewhere to conduct this study.

• Adamson S, Holloway M. Negotiating sensitivities and grappling with intangibles: Experiences from a study of spirituality and funerals. Qualitative Research. 2012; 12 (6):735–752. doi: 10.1177/1468794112439008. [ CrossRef ] [ Google Scholar ]
• Ajodhia-Andrews A, Berman R. Exploring school life from the lens of a child who does not use speech to communicate. Qualitative Inquiry. 2009; 15 (5):931–951. doi: 10.1177/1077800408322789. [ CrossRef ] [ Google Scholar ]
• Alexander B. K, Moreira C, Kumar H. S. Resisting (resistance) stories: A tri-autoethnographic exploration of father narratives across shades of difference. Qualitative Inquiry. 2012; 18 (2):121–133. doi: 10.1177/1077800411429087. [ CrossRef ] [ Google Scholar ]
• Austin W, Park C, Goble E. From interdisciplinary to transdisciplinary research: A case study. Qualitative Health Research. 2008; 18 (4):557–564. doi: 10.1177/1049732307308514. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Ayres L, Kavanaugh K, Knafl K. A. Within-case and across-case approaches to qualitative data analysis. Qualitative Health Research. 2003; 13 (6):871–883. doi: 10.1177/1049732303013006008. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Barone T. L. Culturally sensitive care 1969–2000: The Indian Chicano Health Center. Qualitative Health Research. 2010; 20 (4):453–464. doi: 10.1177/1049732310361893. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bassey M. A solution to the problem of generalisation in educational research: Fuzzy prediction. Oxford Review of Education. 2001; 27 (1):5–22. doi: 10.1080/03054980123773. [ CrossRef ] [ Google Scholar ]
• Bronken B. A, Kirkevold M, Martinsen R, Kvigne K. The aphasic storyteller: Coconstructing stories to promote psychosocial well-being after stroke. Qualitative Health Research. 2012; 22 (10):1303–1316. doi: 10.1177/1049732312450366. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Broyles L. M, Rodriguez K. L, Price P. A, Bayliss N. K, Sevick M. A. Overcoming barriers to the recruitment of nurses as participants in health care research. Qualitative Health Research. 2011; 21 (12):1705–1718. doi: 10.1177/1049732311417727. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Buckley C. A, Waring M. J. Using diagrams to support the research process: Examples from grounded theory. Qualitative Research. 2013; 13 (2):148–172. doi: 10.1177/1468794112472280. [ CrossRef ] [ Google Scholar ]
• Buzzanell P. M, D'Enbeau S. Stories of caregiving: Intersections of academic research and women's everyday experiences. Qualitative Inquiry. 2009; 15 (7):1199–1224. doi: 10.1177/1077800409338025. [ CrossRef ] [ Google Scholar ]
• Carter S. M, Little M. Justifying knowledge, justifying method, taking action: Epistemologies, methodologies, and methods in qualitative research. Qualitative Health Research. 2007; 17 (10):1316–1328. doi: 10.1177/1049732307306927. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Cheek J, Garnham B, Quan J. What's in a number? Issues in providing evidence of impact and quality of research(ers) Qualitative Health Research. 2006; 16 (3):423–435. doi: 10.1177/1049732305285701. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Colón-Emeric C. S, Plowman D, Bailey D, Corazzini K, Utley-Smith Q, Ammarell N, et al. Regulation and mindful resident care in nursing homes. Qualitative Health Research. 2010; 20 (9):1283–1294. doi: 10.1177/1049732310369337. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Coltart C, Henwood K. On paternal subjectivity: A qualitative longitudinal and psychosocial case analysis of men's classed positions and transitions to first-time fatherhood. Qualitative Research. 2012; 12 (1):35–52. doi: 10.1177/1468794111426224. [ CrossRef ] [ Google Scholar ]
• Creswell J. W. Five qualitative approaches to inquiry. In: Creswell J. W, editor. Qualitative inquiry and research design: Choosing among five approaches. 3rd ed. Thousand Oaks, CA: Sage; 2013a. pp. 53–84. [ Google Scholar ]
• Creswell J. W. Qualitative inquiry and research design: Choosing among five approaches. 3rd ed. Thousand Oaks, CA: Sage; 2013b. [ Google Scholar ]
• Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach. BMC Medical Research Methodology. 2011; 11 (1):1–9. doi: 10.1186/1471-2288-11-100. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Cunsolo Willox A, Harper S. L, Edge V. L, ‘My Word’: Storytelling and Digital Media Lab, & Rigolet Inuit Community Government Storytelling in a digital age: Digital storytelling as an emerging narrative method for preserving and promoting indigenous oral wisdom. Qualitative Research. 2013; 13 (2):127–147. doi: 10.1177/1468794112446105. [ CrossRef ] [ Google Scholar ]
• De Haene L, Grietens H, Verschueren K. Holding harm: Narrative methods in mental health research on refugee trauma. Qualitative Health Research. 2010; 20 (12):1664–1676. doi: 10.1177/1049732310376521. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• D'Enbeau S, Buzzanell P. M, Duckworth J. Problematizing classed identities in fatherhood: Development of integrative case studies for analysis and praxis. Qualitative Inquiry. 2010; 16 (9):709–720. doi: 10.1177/1077800410374183. [ CrossRef ] [ Google Scholar ]
• Denzin N. K, Lincoln Y. S. Introduction: Disciplining the practice of qualitative research. In: Denzin N. K, Lincoln Y. S, editors. The SAGE handbook of qualitative research. 4th ed. Thousand Oaks, CA: Sage; 2011a. pp. 1–6. [ Google Scholar ]
• Denzin N. K, Lincoln Y. S, editors. The SAGE handbook of qualitative research. 4th ed. Thousand Oaks, CA: Sage; 2011b. [ Google Scholar ]
• Edwards R, Weller S. Shifting analytic ontology: Using I-poems in qualitative longitudinal research. Qualitative Research. 2012; 12 (2):202–217. doi: 10.1177/1468794111422040. [ CrossRef ] [ Google Scholar ]
• Eisenhardt K. M. Building theories from case study research. The Academy of Management Review. 1989; 14 (4):532–550. doi: 10.2307/258557. [ CrossRef ] [ Google Scholar ]
• Fincham B, Scourfield J, Langer S. The impact of working with disturbing secondary data: Reading suicide files in a coroner's office. Qualitative Health Research. 2008; 18 (6):853–862. doi: 10.1177/1049732307308945. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Flanagan J. Public participation in the design of educational programmes for cancer nurses: A case report. European Journal of Cancer Care. 1999; 8 (2):107–112. doi: 10.1046/j.1365-2354.1999.00141.x. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Flyvbjerg B. Five misunderstandings about case-study research. Qualitative Inquiry. 2006; 12 (2):219–245. doi: 10.1177/1077800405284.363. [ CrossRef ] [ Google Scholar ]
• Flyvbjerg B. Case study. In: Denzin N. K, Lincoln Y. S, editors. The SAGE handbook of qualitative research. 4th ed. Thousand Oaks, CA: Sage; 2011. pp. 301–316. [ Google Scholar ]
• Fourie C. L, Theron L. C. Resilience in the face of fragile X syndrome. Qualitative Health Research. 2012; 22 (10):1355–1368. doi: 10.1177/1049732312451871. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Gallagher N, MacFarlane A, Murphy A. W, Freeman G. K, Glynn L. G, Bradley C. P. Service users’ and caregivers’ perspectives on continuity of care in out-of-hours primary care. Qualitative Health Research. 2013; 23 (3):407–421. doi: 10.1177/1049732312470521. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Gerring J. What is a case study and what is it good for? American Political Science Review. 2004; 98 (2):341–354. doi: 10.1017/S0003055404001182. [ CrossRef ] [ Google Scholar ]
• Gillard A, Witt P. A, Watts C. E. Outcomes and processes at a camp for youth with HIV/AIDS. Qualitative Health Research. 2011; 21 (11):1508–1526. doi: 10.1177/1049732311413907. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Grant M, Booth A. A typology of reviews: An analysis of 14 review types and associated methodologies. Health Information and Libraries Journal. 2009; 26 :91–108. doi: 10.1111/j.1471-1842.2009.00848.x. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Gratton M.-F, O'Donnell S. Communication technologies for focus groups with remote communities: A case study of research with First Nations in Canada. Qualitative Research. 2011; 11 (2):159–175. doi: 10.1177/1468794110394068. [ CrossRef ] [ Google Scholar ]
• Hallberg L. Quality criteria and generalization of results from qualitative studies. International Journal of Qualitative Studies on Health and Wellbeing. 2013; 8 :1. doi: 10.3402/qhw.v8i0.20647. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hames I. Committee on Publication Ethics, 1. 2013, March. COPE Ethical guidelines for peer reviewers. Retrieved April 7, 2013, from http://publicationethics.org/resources/guidelines . [ Google Scholar ]
• Hooghe A, Neimeyer R. A, Rober P. “Cycling around an emotional core of sadness”: Emotion regulation in a couple after the loss of a child. Qualitative Health Research. 2012; 22 (9):1220–1231. doi: 10.1177/1049732312449209. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Jackson C. B, Botelho E. M, Welch L. C, Joseph J, Tennstedt S. L. Talking with others about stigmatized health conditions: Implications for managing symptoms. Qualitative Health Research. 2012; 22 (11):1468–1475. doi: 10.1177/1049732312450323. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Jasper M, Vaismoradi M, Bondas T, Turunen H. Validity and reliability of the scientific review process in nursing journals—time for a rethink? Nursing Inquiry. 2013 doi: 10.1111/nin.12030. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Jensen J. L, Rodgers R. Cumulating the intellectual gold of case study research. Public Administration Review. 2001; 61 (2):235–246. doi: 10.1111/0033-3352.00025. [ CrossRef ] [ Google Scholar ]
• Jorrín-Abellán I. M, Rubia-Avi B, Anguita-Martínez R, Gómez-Sánchez E, Martínez-Mones A. Bouncing between the dark and bright sides: Can technology help qualitative research? Qualitative Inquiry. 2008; 14 (7):1187–1204. doi: 10.1177/1077800408318435. [ CrossRef ] [ Google Scholar ]
• Ledderer L. Understanding change in medical practice: The role of shared meaning in preventive treatment. Qualitative Health Research. 2011; 21 (1):27–40. doi: 10.1177/1049732310377451. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Lincoln Y. S. Emerging criteria for quality in qualitative and interpretive research. Qualitative Inquiry. 1995; 1 (3):275–289. doi: 10.1177/107780049500100301. [ CrossRef ] [ Google Scholar ]
• Luck L, Jackson D, Usher K. Case study: A bridge across the paradigms. Nursing Inquiry. 2006; 13 (2):103–109. doi: 10.1111/j.1440-1800.2006.00309.x. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Mawn B, Siqueira E, Koren A, Slatin C, Devereaux Melillo K, Pearce C, et al. Health disparities among health care workers. Qualitative Health Research. 2010; 20 (1):68–80. doi: 10.1177/1049732309355590. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Merriam S. B. Qualitative research: A guide to design and implementation. 3rd ed. San Francisco, CA: Jossey-Bass; 2009. [ Google Scholar ]
• Meyer C. B. A case in case study methodology. Field Methods. 2001; 13 (4):329–352. doi: 10.1177/1525822x0101300402. [ CrossRef ] [ Google Scholar ]
• Morse J. M. Mixing qualitative methods. Qualitative Health Research. 2009; 19 (11):1523–1524. doi: 10.1177/1049732309349360. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Morse J. M. Molding qualitative health research. Qualitative Health Research. 2011; 21 (8):1019–1021. doi: 10.1177/1049732311404706. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Morse J. M, Dimitroff L. J, Harper R, Koontz A, Kumra S, Matthew-Maich N, et al. Considering the qualitative–quantitative language divide. Qualitative Health Research. 2011; 21 (9):1302–1303. doi: 10.1177/1049732310392386. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Nagar-Ron S, Motzafi-Haller P. “My life? There is not much to tell”: On voice, silence and agency in interviews with first-generation Mizrahi Jewish women immigrants to Israel. Qualitative Inquiry. 2011; 17 (7):653–663. doi: 10.1177/1077800411414007. [ CrossRef ] [ Google Scholar ]
• Nairn K, Panelli R. Using fiction to make meaning in research with young people in rural New Zealand. Qualitative Inquiry. 2009; 15 (1):96–112. doi: 10.1177/1077800408318314. [ CrossRef ] [ Google Scholar ]
• Nespor J. The afterlife of “teachers’ beliefs”: Qualitative methodology and the textline. Qualitative Inquiry. 2012; 18 (5):449–460. doi: 10.1177/1077800412439530. [ CrossRef ] [ Google Scholar ]
• Piekkari R, Welch C, Paavilainen E. The case study as disciplinary convention: Evidence from international business journals. Organizational Research Methods. 2009; 12 (3):567–589. doi: 10.1177/1094428108319905. [ CrossRef ] [ Google Scholar ]
• Ragin C. C, Becker H. S. What is a case?: Exploring the foundations of social inquiry. Cambridge: Cambridge University Press; 1992. [ Google Scholar ]
• Roscigno C. I, Savage T. A, Kavanaugh K, Moro T. T, Kilpatrick S. J, Strassner H. T, et al. Divergent views of hope influencing communications between parents and hospital providers. Qualitative Health Research. 2012; 22 (9):1232–1246. doi: 10.1177/1049732312449210. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Rosenberg J. P, Yates P. M. Schematic representation of case study research designs. Journal of Advanced Nursing. 2007; 60 (4):447–452. doi: 10.1111/j.1365-2648.2007.04385.x. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Rytterström P, Unosson M, Arman M. Care culture as a meaning- making process: A study of a mistreatment investigation. Qualitative Health Research. 2013; 23 :1179–1187. doi: 10.1177/1049732312470760. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Sandelowski M. Whatever happened to qualitative description? Research in Nursing & Health. 2000; 23 (4):334–340. doi: 10.1002/1098-240X. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Sandelowski M. What's in a name? Qualitative description revisited. Research in Nursing & Health. 2010; 33 (1):77–84. doi: 10.1002/nur.20362. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Sandelowski M, Barroso J. Reading qualitative studies. International Journal of Qualitative Methods. 2002; 1 (1):74–108. [ Google Scholar ]
• Snyder-Young D. “Here to tell her story”: Analyzing the autoethnographic performances of others. Qualitative Inquiry. 2011; 17 (10):943–951. doi: 10.1177/1077800411425149. [ CrossRef ] [ Google Scholar ]
• Stake R. E. The case study method in social inquiry. Educational Researcher. 1978; 7 (2):5–8. [ Google Scholar ]
• Stake R. E. The art of case study research. Thousand Oaks, CA: Sage; 1995. [ Google Scholar ]
• Stake R. E. Case studies. In: Denzin N. K, Lincoln Y. S, editors. Strategies of qualitative inquiry. Thousand Oaks, CA: Sage; 1998. pp. 86–109. [ Google Scholar ]
• Sumsion J. Opening up possibilities through team research: Investigating infants’ experiences of early childhood education and care. Qualitative Research. 2013; 14 (2):149–165. doi: 10.1177/1468794112468471.. [ CrossRef ] [ Google Scholar ]
• Thomas G. Doing case study: Abduction not induction, phronesis not theory. Qualitative Inquiry. 2010; 16 (7):575–582. doi: 10.1177/1077800410372601. [ CrossRef ] [ Google Scholar ]
• Thomas G. A typology for the case study in social science following a review of definition, discourse, and structure. Qualitative Inquiry. 2011; 17 (6):511–521. doi: 10.1177/1077800411409884. [ CrossRef ] [ Google Scholar ]
• Tight M. The curious case of case study: A viewpoint. International Journal of Social Research Methodology. 2010; 13 (4):329–339. doi: 10.1080/13645570903187181. [ CrossRef ] [ Google Scholar ]
• Wager E, Kleinert S. Responsible research publication: International standards for authors. A position statement developed at the 2nd World Conference on Research Integrity, Singapore, July 22–24, 2010. In: Mayer T, Steneck N, editors. Promoting research integrity in a global environment. Singapore: Imperial College Press/World Scientific; 2010a. pp. 309–316. [ Google Scholar ]
• Wager E, Kleinert S. Responsible research publication: International standards for editors. A position statement developed at the 2nd World Conference on Research Integrity, Singapore, July 22–24, 2010. In: Mayer T, Steneck N, editors. Promoting research integrity in a global environment. Singapore: Imperial College Press/World Scientific; 2010b. pp. 317–328. [ Google Scholar ]
• Webb C, Kevern J. Focus groups as a research method: A critique of some aspects of their use in nursing research. Journal of Advanced Nursing. 2000; 33 (6):798–805. doi: 10.1046/j.1365-2648.2001.01720.x. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Wimpenny K, Savin-Baden M. Exploring and implementing participatory action synthesis. Qualitative Inquiry. 2012; 18 (8):689–698. doi: 10.1177/1077800412452854. [ CrossRef ] [ Google Scholar ]
• Yeh H.-Y. Boundaries, entities, and modern vegetarianism: Examining the emergence of the first vegetarian organization. Qualitative Inquiry. 2013; 19 (4):298–309. doi: 10.1177/1077800412471516. [ CrossRef ] [ Google Scholar ]
• Yin R. K. Enhancing the quality of case studies in health services research. Health Services Research. 1999; 34 (5 Pt 2):1209–1224. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Yin R. K. Case study research: Design and methods. 4th ed. Thousand Oaks, CA: Sage; 2009. [ Google Scholar ]
• Yin R. K. Applications of case study research. 3rd ed. Thousand Oaks, CA: Sage; 2012. [ Google Scholar ]

6 Qualitative data examples for thorough market researchers

Types of qualitative data in market research, 6 qualitative data examples, get nuanced insights from qualitative market research.

There are plenty of ways to gather consumer insights for fresh campaigns and better products, but qualitative research is up there with the best sources of insight.

This guide is packed with examples of how to turn qualitative data into actionable insights, to spark your creativity and sharpen your research strategy. You’ll see how qualitative data, especially through surveys, opens doors to deeper understanding by inviting consumers to share their experiences and thoughts freely, in their own words — and how qualitative data can transform your brand.

Before we dig into some examples of how qualitative data can empower your teams to make focused, confident and quick decisions on anything from product to marketing, let’s go back to basics. We can categorize qualitative data into roughly three categories: binary, nominal and ordinal data. Here’s how each of them is used in qualitative data analysis.

Binary data

Binary data represents a choice between two distinct options, like ‘yes’ or ‘no’. In market research, this type of qualitative data is useful for filtering responses or making clear distinctions in consumer preferences.

Binary data in qualitative research is great for straightforward insights, but has its limits. Here’s a quick guide on when to use it and when to opt for qualitative data that is more detailed:

Binary data is great for:

• Quick Yes/No questions : like “Have you used our app? Yes or No.”
• Initial screening : to quickly sort participants for further studies.
• Clear-cut answers : absolute factors, such as ownership or usage.

Avoid binary data for:

• Understanding motivations : it lacks the depth to explore why behind actions.
• Measuring intensity : can’t show how much someone likes or uses something.
• Detail needed for product development : misses the nuanced feedback necessary for innovations.

Nominal data

Nominal data categorizes responses without implying any order. For example, when survey respondents choose their favorite brand from a list, the data collected is nominal, offering insights into brand preferences among different demographics.

Some other examples of qualitative data that can be qualified as nominal are asking participants to name their primary information source about products in categories like social media, friends, or online reviews. Or in focus groups, discussing brand perceptions could classify brands into categories such as luxury, budget-friendly, or eco-conscious, based on participant descriptions.

Nominal data is great for:

• Categorizing responses : such as types of consumer complaints (product quality, customer service, delivery issues).
• Identifying preferences : like favorite product categories (beverages, electronics, apparel).
• Segmentation : grouping participants based on attributes (first-time buyers, loyal customers).

Nominal data is not for:

• Measuring quantities : it can’t quantify how much more one category is preferred over another.
• Ordering or ranking responses : it doesn’t indicate which category is higher or lower in any hierarchy.
• Detailed behavioral analysis : While it can group behaviors, it doesn’t delve into the frequency or intensity of those behaviors.

Ordinal data

Ordinal data introduces a sense of order, ranking preferences or satisfaction levels. In qualitative analysis, it’s particularly useful for understanding how consumers prioritize features or products, giving researchers a clearer picture of market trends.

Other examples of qualitative data analyses that use ordinal data, are for instance a study on consumer preferences for coffee flavors, participants might rank flavors in order of preference, providing insights into flavor trends. You can also get ordinal data from focus groups on things like customer satisfaction surveys or app usability, by asking users to rate their ease of use or happiness on an ordinal scale.

Ordinal data is great for:

• Ranking preferences : asking participants to rank product features from most to least important.
• Measuring satisfaction levels : using scales like “very satisfied,” “satisfied,” “neutral,” “dissatisfied,” “very dissatisfied.”
• Assessing Agreement : with statements on a scale from “strongly agree” to “strongly disagree.”

Ordinal data is not for:

• Quantifying differences : it doesn’t show how much more one rank is preferred over another, just the order.
• Precise measurements : can’t specify the exact degree of satisfaction or agreement, only relative positions.

This mix of qualitative and quantitative data will give you a well-rounded view of participant attitudes and preferences.

The things you can do with qualitative data are endless. But this article shouldn’t turn into a work of literature, so we’ll highlight six ways to collect qualitative data and give you examples of how to use these qualitative research methods to get actionable results.

How to get qual insights with Attest

You can get to the heart of what your target customers think, with reliable qualitative insights from Attest Video Responses

1. Highlighting brand loyalty drivers with open-ended surveys and questionnaires

Open-ended surveys and questionnaires are great at finding out what makes customers choose and stick with a brand. Here’s why this qualitative data analysis tool is so good for gathering qualitative data on things like brand loyalty and customer experience:

Straight from the source

Open-ended survey responses show the actual thoughts and feelings of your target audience in their own words, while still giving you structure in your data analysis.

Understanding ‘why’

Numbers can show us how many customers are loyal; open-ended survey responses explain why they are. You can also easily add thematic analysis to the mix by counting certain keywords or phrases.

Guiding decisions

The insights from these surveys can help a brand decide where to focus its efforts, from making sure their marketing highlights what customers love most to improving parts of their product.

Surveys are one of the most versatile and efficient qualitative data collection methods out there. We want to bring the power of qualitative data analysis to every business and make it easy to gather qualitative data from the people who matter most to your brand. Check out our survey templates to hit the ground running. And you’re not limited to textual data as your only data source — we also enable you to gather video responses to get additional context from non verbal cues and more.

2. Trend identification with observation notes

Observation notes are a powerful qualitative data analysis tool for spotting trends as they naturally unfold in real-world settings. Here’s why they’re particularly valuable insights and effective for identifying new trends:

Real behavior

Observing people directly shows us how they actually interact with products or services, not just how they say they do. This can highlight emerging trends in consumer behavior or preferences before people can even put into words what they are doing and why.

Immediate insights

By watching how people engage with different products, we can quickly spot patterns or changes in behavior. This immediate feedback is invaluable for catching trends as they start.

Context matters

Observations give you context. You can see not just what people do, but where and how they do it. This context can be key to understanding why a trend is taking off.

Unprompted reactions

Since people don’t know they’re being observed for these purposes, their actions are genuine. This leads to authentic insights about what’s really catching on.

3. Understanding consumer sentiments through semi-structured interviews

Semi-structured interviews for qualitative data analysis are an effective method for data analysts to get a deep understanding of consumer sentiments. It provides a structured yet flexible approach to gather in-depth insights. Here’s why they’re particularly useful for this type of research question:

Personal connection

These interviews create a space for a real conversation, allowing consumers to share their feelings, experiences, and opinions about a brand or product in a more personal setting.

Flexibility

The format lets the interviewer explore interesting points that come up during the conversation, diving deeper into unexpected areas of discussion. This flexibility uncovers richer insights than strictly structured interviews.

Depth of understanding

By engaging in detailed discussions, brands can understand not just what consumers think but why they think that way and what stations their train of thought passes by.

Structure and surprise

Semi-structured interviews can be tailored to explore specific areas of interest while still allowing for new insights to emerge.

4. Using focus groups for informing market entry strategies

Using a focus group to inform market entry strategies provides a dynamic way to discover your potential customers’ needs, preferences, and perceptions before launching a product or entering a new market. Here’s how focus groups can be particularly effective for this kind of research goal:

Real conversations

Focus groups allow for real-time, interactive discussions, giving you a front-row seat to hear what your potential customers think and feel about your product or service idea.

Diverse Perspectives

By bringing together people from various backgrounds, a focus group can offer a wide range of views and insights, highlighting different consumer needs and contextual information that you might miss out on in a survey.

Spotting opportunities and challenges

The dynamic nature of focus groups can help uncover unique market opportunities or potential challenges that might not be evident through other research methods, like cultural nuances.

Testing ideas

A focus group is a great way to test and compare reactions to different market entry strategies, from pricing models to distribution channels, providing clear direction on what approach might work best.

5. Case studies to gain a nuanced understanding of consumers on a broad level

Case studies in qualitative research zoom in on specific stories from customers or groups using a product or service, great for gaining a nuanced understanding of consumers at a broad level. Here’s why case studies are a particularly effective qualitative data analysis tool for this type of research goal:

In-depth analysis

Case studies can provide a 360-degree look at the consumer experience, from initial awareness to post-purchase feelings.

This depth of insight reveals not just what consumers do, but why they do it, uncovering motivations, influences, and decision-making processes.

Longitudinal insight

Case studies can track changes in consumer behavior or satisfaction over time, offering a dynamic view of how perceptions evolve.

This longitudinal perspective is crucial for giving context to the lifecycle of consumer engagement with a brand.

Storytelling power

The narrative nature of case studies — when done right — makes them powerful tools for communicating complex consumer insights in an accessible and engaging way, which can be especially useful for internal strategy discussions or external marketing communications.

6. Driving product development with diary studies

Diary studies are a unique qualitative research method that involves participants recording their thoughts, experiences, or behaviors over a period of time, related to using a product or service. This qualitative data analysis method is especially valuable for driving product development for several reasons:

Real-time insights

Diary studies capture real-time user experiences and feedback as they interact with a product in their daily lives.

This ongoing documentation provides a raw, unfiltered view of how a product fits into the user’s routine, highlighting usability issues or unmet needs that might not be captured in a one-time survey or interview.

Realistic user journey mapping

By analyzing diary entries, you can map out the entire user journey, identifying critical touch points where users feel delighted, frustrated, or indifferent.

This then enables you to implement targeted improvements and innovations at the moments that matter most.

Identifying patterns

Over the course of a diary study, patterns in behavior, preferences, and challenges can emerge, which is great for thematic analysis.

It can guide product developers to prioritize features or fixes that will have the most significant impact on user satisfaction, which is especially great if they don’t know what areas to focus on first.

Qualitative research brings your consumers’ voices directly to your strategy table. The examples we’ve explored show how qualitative data analysis methods like surveys, interviews, and case studies illuminate the ‘why’ behind consumer choices, guiding more informed decisions. Using these insights means crafting products and messages that resonate deeply, ensuring your brand not only meets but exceeds consumer expectations.

Customer Research Manager 

Related articles

Making it personal – using tech to build connections with consumers | diageo, panel discussion – future-proofing your brand with consumer insights, attest product release: multi-market | attest’s alyssa stringer, subscribe to our newsletter.

Fill in your email and we’ll drop fresh insights and events info into your inbox each week.

* I agree to receive communications from Attest. Privacy Policy .

You're now subscribed to our mailing list to receive exciting news, reports, and other updates!

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• My Account Login
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 30 May 2024

Longitudinal qualitative study on the psychological experiences of COVID-19 patients based on timing it right framework

• Liangyan Zhang 1 ,
• Chen Zhang 2 ,
• Kesang Li 1 &
• Yan Zhang 3  

Scientific Reports volume  14 , Article number:  12409 ( 2024 ) Cite this article

164 Accesses

Metrics details

• Health care

Timing it right framework was used as a framework to explore the illness experiences of patients infected with COVID-19 and to analyze the patients' perceptions of the disease and their true inner feelings to provide a reference for the control of infectious diseases. This research adopted a phenomenological research approach to develop a longitudinal qualitative study. A purposive sampling method was used to select participants and 37 patients were recruited. Depending on the principle that participants should have maximum variation and sampling should cease when interviews content saturation is achieved, 16 COVID-19 patients in an isolation ward in Ningbo City, Zhejiang Province were finally included. Data were collected using semi-structured interviews, and the content of the interviews was analyzed by Colaizzi’s 7-step method. The themes of COVID-19 patients’ experiences at various phase were presented as follows: multiple emotions intertwined at the time of diagnosis (anxiety, stressful panic, facing the diagnosis calmly), multiple pressures during the hospitalization period (concerns about the disease, unable to adapt to the ward environment, worrying about future hardship), growth of positive illness experience during the isolation and observation period (sublimated outlook on life, affirmation of the government's anti-epidemic policy, more concerned about their own health), adjustment after returning to society (stigma, loss of previous living environment, problems caused by nucleic acid testing), and adaptation to social life (return to normal life, avoidance of illness experience, post-covid-19 syndrome). The illness experience of COVID-19 patients changed dynamically with time, but a sense of shame and uncertainty about recovery was present throughout the process. Interventions should be developed according to the needs of the patients at different times to inform subsequent optimization of care and management of infectious diseases.

Similar content being viewed by others

Long COVID: major findings, mechanisms and recommendations

Post-COVID conditions following COVID-19 vaccination: a retrospective matched cohort study of patients with SARS-CoV-2 infection

Exploring the reported adverse effects of COVID-19 vaccines among vaccinated Arab populations: a multi-national survey study

Introduction.

The ongoing global epidemic of coronavirus disease 2019 (COVID-19) has had a significant impact on human society, primarily in terms of public health. As of 2 February 2023, the reported cumulative number of confirmed cases worldwide is approximately 753 million, with approximately 6,814,900 deaths 1 . Importantly, the actual number of infections worldwide may be higher than the reported data due to factors such as limited testing capacity. The Omicron and Delta strains are variants of coronaviruses with high loads, high infectivity, short incubation times, and antigenic escape 2 . Patients experience long viral nucleic acid conversion times and are more likely to develop severe and critical illnesses, with long periods of hospital isolation and medical observation 3 . Studies have shown 4 that patients with COVID-19 who stay in isolation are prone to psychological problems such as anxiety, depression, and fear. The study 5 showed that infected patients had problems such as fatigue, sleep difficulties, and anxiety after discharge from the hospital, and those with severe lung damage during hospitalization were even more likely to be in the target population for long-term rehabilitation interventions after discharge; however, the study was conducted on patients at the beginning of the 2019 outbreak, and the characteristics of the coronavirus variants can cause various psychological experiences in infected patients. There are currently few studies exploring mild COVID-19 patients' experiences during hospitalization and after reintegration into society 6 . The Timing it Right (TIR) framework was proposed by Cameron et al. 7 in the study of stroke care; it divides the process of disease development into five phases: diagnosis, stabilization, preparation, implementation and adaptation. At present, a number of scholars have used different research methods to study the dynamic needs of patients and caregivers with the TIR framework, and have achieved initial results 8 . Based on the TIR framework, it is possible to understand the changes in the experience of COVID-19 patients at different stages of illness, and formulate corresponding support plans, so that the intervention timing and intervention content can match the needs of patients at the current phase of disease 9 , 10 . Therefore, based on the five phases of disease development in the TIR framework, this research explore the illness experiences of COVID-19 patients in a longitudinal study to provide a reference for the subsequent care of patients with infectious diseases and the development of epidemic prevention and control strategies.

Design and participants

This study utilized a phenomenological research approach to develop a longitudinal qualitative study using the TIR framework. To conduct a longitudinal qualitative study, it is necessary to select specific time points for data collection, and the chosen time frame should be adequate for observing changes in the phenomenon under investigation 11 . In this study, the time frame for data collection was established through two interviews. The first interview (T1) took place during the period when the infected individuals were isolated, and the second interview (T2) occurred 6 months after their reintegration into society. The study employed a purposive sampling method to select patients who had been diagnosed with COVID-19 and were admitted to an isolation ward in Ningbo City, Zhejiang Province, between January and October 2022. The inclusion criteria were as follows: (1) confirmed COVID-19 infection; (2) age above 18 years; and (3) voluntary participation in this study and providing informed consent. The exclusion criteria were as follows: (1) those who were seriously ill and unable to communicate and (2) those with serious psychological or cognitive dysfunction. Those who automatically withdrew or were lost to follow-up during the interview were dropped from the study. A total of 37 patients were recruited for the study, and the sample size of the study was determined based on information saturation of the interviewees 12 . The specificity of the sampling was measured by demographic characteristics and the Self-Rating Depression Scale (SDS) 13 . Sampling ceased when interviews content saturation was achieved. Finally, 16 cases of representative infected patients were included in the study, including patients with no depression (9 cases, 56%), suspected mild depression (1 case, 6%), and suspected moderate depression (6 cases, 37.5%), numbered "N1" to "N16". In this study, two in-depth interviews were conducted with the infected patients, one during their isolation period and another after 6 months of reintegrating into society. Notably, during the second interview, two of the participants exhibited evasive behavior. For example, one participant was very talkative in the first interview, and he was able to talk more about his true feelings and describe them in more details based on the experience of the illness. However, in the second interview, he spoke less and only answered yes, no or fine, showing an evasive attitude. In order to fully understand the thoughts of the participants and enhance the integrity and continuity of the study, after obtaining informed consent, the interviewer supplemented the interview content by contacting their relatives, and returned the transcript of the interview content to the participants for confirmation, so as to ensure the authenticity of the content. The basic information of the study participants is shown in Table 1 .

Data collection

The participants provided informed consent and completed the demographic scale and SDS scale assessment before the interview. The interview outline was designed according to the five phases of diagnosis, stabilization, preparation, implementation and adaptation in the TIR framework. Longitudinal qualitative studies require researchers to use the insights gained from previous interviews to inform the focus of subsequent data collection 14 . The researcher preinterviewed two infected individuals prior to the formal interview and amended the interview outline. The interview outline was as follows. During Phase 1 (T1), the following questions were asked: ① How did you feel when you were diagnosed with COVID-19? ② What was your initial feeling after arriving at the isolation ward? ③ What are your needs and feelings during hospitalization? ④ How do you feel when you go to the quarantine point for medical observation? ⑤ How will the Spring Festival affect you? ⑥ If you are cured and returned to society, what expectations or concerns do you have? During Phase 2 (T2), the following questions were asked: ① What was your mood at the beginning of reintegration? Give an example of 1–2 things that were particularly impressive at that time. ② How do you feel now? How has your life changed? ③ Is there anything particularly troubling you at present? How do you solve these troubles? Do you have any hopes or suggestions? Due to the requirements of epidemic prevention and control, the interview was conducted by telephone, and the interview time was 15–60 min.

Data analysis

The interview content was analyzed by Colaizzi’s 7-step method. The steps are as follows: (1) two researchers carefully read all the original data; (2) they independently identify significant statements that were repeated by multiple participants and were important and meaningful to the research question; (3) they code repetitive and meaningful views by temporarily "suspending" their assumptions and value judgments; (4) they gather ideas after coding to form the prototype of the theme; (5) they write a detailed typical original description; (6) they identify similar ideas and condense them into themes; and (7) they return the topic structure to the participants for verification. The results of the SDS questionnaire were descriptive statistical analyzed by SPSS 25.0.

Quality control

SDS questionnaire collection: during hospitalization, a researcher issued and collected the questionnaire, explained the questions appropriately, and checked the completeness of the answers on the spot. (2) Interview data collection: all researchers in the study received professional training in qualitative research, and all interview data collection was completed by the first author (isolation ward nurse). The researcher kept in touch with the participants during the follow-up period to establish trust and friendly relationships. The researcher used the daily chat information as supplementary information. At the end of each interview, the researcher transcribed the audio-recorded information within 24 h and recorded the tone of voice, pitch change and other information of the participants. (3) Data analysis: data collection and analysis were carried out in parallel, with each of the 2 researchers listening to the audio-recordings and reading the textual information repeatedly, independently summarizing statements of significance, and summarizing the text of the statements. And the themes and subthemes extracted from the collected data were repeated to the participants by instant messaging software to further confirm whether they had the same feeling or experience and record any possible supplemental information. It was explained to the participants at the first interview that the preliminary results would be reported back to them for verification.

This study was reviewed and approved by the Ethics Committee of Ningbo No.2 Hospital (YJ-NBEY-KY-2022-102-01). All methods were performed in accordance with the relevant guidelines and regulations such as ethical standards of the institutional ethics committee and with the Declaration of Helsinki. All participants signed informed consent forms.

An interpretive understanding of the illness experiences of patients infected with COVID-19 was constructed in this study. The analysis yielded five categories and fifteen sub-categories (Table 2 ).

Theme 1: multiple emotions intertwined at the time of diagnosis

Due to different personality characteristics and understanding of the disease, infected patients showed the following emotional changes in the early stage of diagnosis.

Anxiety: since most infected patients learned about their infection suddenly, most of them had significant fidgeting, irritability, insomnia, and felt inexplicably nervous and worried when they were diagnosed or preparing for medical isolation. N5-T1: "I was so anxious when I was diagnosed that I felt like the sky was falling." N9-T1: "Since that time I have not been able to sleep well at night, I wake up after an hour of sleep." N2-T1: "I felt like it was going by so slowly and every day felt like years. Before the quarantine, I was worried that I wouldn't eat or sleep well, and that was true." Some of the infected patients felt upset when they were first diagnosed, as they received many calls for epidemiological investigations from various departments and organizations. N6-T1: "The initial phase has been very busy. I was the first to be infected, and there was a particular focus on me. At that time, my sleep was disturbed."

Stressful panic: the knowledge that there was no effective treatment, the uncertainty of the sequelae and the possibility of recurrence all put the infected patients in fear of the disease at the time of diagnosis, with three infected patients displaying more pronounced despair. N12-T1: "At that time, I was lying in bed for two days feeling like I was going to die. It was bad anyway. I was scared, scared of the after-effects, scared for my life (emotional)." N9-T1: "[Messages on my mobile phone] made me think nonsense. If the virus in my body had stayed, I would have been locked up forever. It gave me a feeling of panic."

Facing the diagnosis calmly: some of the infected patients were not so afraid of the diagnosis because people around them had already been infected. N1-T1: "The mood was a bit panicky, not particularly panicky. Because my in-laws have already been diagnosed, I already have a general idea in my mind." Some infected patients had a more comprehensive understanding of the corresponding symptoms of infection and were more receptive. N11-T1: "Not afraid of the disease. I have read the news that most of the foreign countries are infected, so I am calm." N3-T1: "It was mild… and curable, so I just didn't have much stress anyway."

Theme 2: multiple pressures during the hospitalization period

When patients were hospitalized, the disease itself, positivity for 2019-nCoV nucleic acid, and the specificity of the isolation environment made them feel deeply stressed.

Concerns about the disease: the threat to COVID-19 patients' lives and safety during hospitalization was stressful for those infected, either because of their own experiences of repositivity or because they witnessed others experiencing repositivity. N11-T1: "The biggest concern was that I didn't know how long it would take to be discharged from the hospital, how long it would take to recover … I didn't know if there were any after effects and whether there would be a relapse." N5-T1: "(After being repositive for the third time) I cried all the time during those 2 days when I was isolated again. The last 2 days were fine, (my mood) calmed down, and today I'm a little bit annoyed again, my wife and my youngest daughter they don't seem to have a good nucleic acid result. That aspect is affecting me a lot, a lot of stress (speaking faster)." N14-T1: "There is a feeling of fear in my heart. This is the first time I've had a repositive, and I've heard that there are a lot of repositive people, and I'm scared in my heart." Due to the special nature of COVID-19 patients, the vast majority of them chose to conceal their condition to avoid worrying about their families. N3-T1: "I didn't dare to make a video call to my mother. I was afraid that if my mother knew I was inside the hospital, she would have to worry about me."

Unable to adapt to the ward environment: most infected patients were transferred to isolation wards for medical observation and treatment, and the unfamiliar and confined environment often made them feel uncomfortable. N4-T1: "It feels unreal to be here, the air is treated and the rooms are airtight." Meanwhile, due to the shortage of beds, most isolation wards housed many people, to which some infected patients are not accustomed, and some infected patients were deeply stressed about secondary infections. N2-T2: "I don't like to sleep with other people in the same room. But, since I was a child, I have been timid and I am afraid to sleep alone. I am not used to sleeping in the hospital." N12-T1: "I was worried about my problems and whether sleeping in the same ward would spread the virus to each other, so I never took off my mask." Isolation also prevents infected patients from spending time with their families. During the festive season, which symbolizes reunion, they had to spend time alone. N10-T1: "The arrival of Chinese New Year had an impact on me. There are so many things I can't do because (I can't) be reunited with my family."

Worrying about future hardship: because the whole family was quarantined or because they themselves were the main laborer in the family, most infected patients reported that the long period of isolation had affected their financial income and were worried about the future. N5-T1: "There has been no income for a few months now, which means that life may be hard in the future." Due to the release of information from epidemiological surveys, infected patients are often worried about having the disease known to their acquaintances. N5-T2: "[The flow survey information] would be better to change that column where the surname is written to a number. Because we are the only ones infected in the factory, it is easy for others to guess." Infectious patients worry about social discrimination brought about by the disease and about whether they will still be able to have a suitable learning environment, job, and residence in the future. N5-T1: "I worry about whether it will affect my youngest daughter's ability to go to a better kindergarten." N10-T1: "I feel that I will not be able to find a job if people know about my disease. … I am sure I will be treated differently." "N2-T1: "We are renting a house outside, the landlord knows about it and may not let us stay in this place. What should we do?"

Theme 3: growth of positive illness experience during the isolation and observation period

Patients were under medical isolation and observation during this period. There is deeper thinking after enduring pressure from all sides, and some patients gain growth.

Sublimated outlook on life. Some infected patients were grateful for the dedication of healthcare workers. N1-T1: "Really, I feel that you are all very good. Doctors have it so hard. I didn't feel it before." Some patients thanked the teachers for caring for their children during the infection. N1-T2: "The teachers and classmates are very caring for my daughter. In particular, her class teacher was really nice. There was no one to look after her when she first came out (family members were quarantined for infection). My daughter was alone at home, and I was worried. Her teacher let my daughter go to her house. The teacher said I am not afraid." Some infected patients also said that during the isolation period, they had time to calm down and question their souls and thought more about life. N6-T1: "Actually, when I was in the isolation ward, I had more time and space to think, and then I might think more deeply about something, like the meaning of life. I would find so many things that I just naturally realized."

Affirmation of the government's anti-epidemic policy. N6-T1: "I think our government departments are very committed because our national situation is different from that of foreign countries, with a large population. If our country really doesn't care about controlling the epidemic at all, the medical resources can't keep up." N9-T1: "I fully comply with the rules and regulations of the isolation ward. The country invests a lot of resources. We eat and live medically for free."

More concerned about their own health. The experience of falling ill has made more patients pay more attention to their own health, and they actively participate in sports and pay attention to physical checkups and rest. N11-T1: "It's better to have a medical checkup to see if this virus has any other effects on your body. In the future, I will have regular medical check-ups once every six months or a year. Now, I also started to run (during the quarantine phase), I didn't run much before."

Theme 4: adjustment after returning to society

The infected often return to society in a state of fear and with a deep sense of stigma. Some infected patients have lost their former jobs and living environments, and their finances and lives have been greatly affected. At the same time, the nucleic acid test also brought troubles to their lives after returning to society.

Stigma: infected patients often have a heavy self-psychological burden when they return to society. They are afraid of being rejected and treated differently. The main manifestations are fear of stigma and concealment of medical history. N1-T2: "We definitely have to report to the community when we go back. We have to explain the situation. After explaining the situation, the people in the village will be scared to death, they will ostracize them (brother, parents), and then it will definitely have an impact on my parents and my brother's lives, so we didn't dare to go back." Some infected patients were worried that they would cause others to become infected, causing them to be quarantined as well. N16-T1: "I'm worried that if I go back to being positive in the future, I will infect others, even if it doesn't hurt, will I have to quarantine people for so many days?" With the shame of the disease, many infected patients were unable to go home to their families. N1-T2: "I would love to go back to my hometown. Because my parents are also 70 years old, and I can't take care of them when I'm out of town. But, now I can't go back to my hometown."

Loss of previous living environment. Some infected patients lost their original living and working environments after returning to society. Some COVID-19 patients moved away from their original environments of their own initiative because they were afraid that others would know that they had been infected by COVID-19. N1-T2: "We moved home. But, we are still afraid of bumping into people we know: "Some infected patients were asked not to go to work or to change their working environments for fear of mutual infection in their workplaces. N2-T2: "We were not allowed to go to work in the factory at that time because the other employees didn't agree to let us go to work." N9-T2: "She used to work in Department 5, but the original department didn't want her anymore." A new environment means a new start, which leads to greater pressure on the lives of infected patients. N1-T2: The pressure on my husband's life is too great. I also went to look for a job. After looking for a few days, I felt very sad and found that I could only do more flexible work like takeaway. Life is difficult, we've borrowed a lot of money now, and there's a lot of financial pressure and mental stress."

Problems caused by nucleic acid testing. Because of previous infections, policies require infected patients to have a separate nucleic acid test. This often meant that they had to spend time and effort looking for a separate site where they could do a separate nucleic acid test. N1-T2: "My child can't do a separate nucleic acid test at school anyway, so we have to find a nucleic acid test site by ourselves." When doing the nucleic acid test alone, they were split into two teams, separate from the people doing the mixed nucleic acid test, and the people in their team were faced with more inquiries about infection, which put more pressure on them." N1-T2: "When we went to do the nucleic acid test, the security guard at the door asked once, then the person who checked the identity after the questioning asked again, and the sampler asked again. I had nightmares every day." In addition, they were concerned that doing the nucleic acid test alone would increase the risk of reinfection. N5-T2: "When we do the nucleic acid test alone, we are with people who are at high risk. The book they have registered in we touch it again, register it again and go with them. If I get infected again, I reckon I'm going to go mad." Because of the fear of repositivity, infected patients are extremely concerned about the results of their own and their family's nucleic acid tests." N3-T2: "To be honest, some people, like my wife, have repeated repositive and go to quarantine sites over and over again. Very upset and depressed. I'm worried about my own and my wife's nucleic acid test results."

Theme 5: adaptation to social life

Six months after returning to society, most of the infected patients returned to normal life with the support and tolerance of society, but some of them still avoided infection and concealed their status as recovered persons. Some of the infected patients developed post-COVID-19 syndrome.

Return to normal life. Some infected patients integrated into society with the tolerance of colleagues and friends around them. N2-T2: "Still working as normal. My friends and I still play well and sit together for meals." N8-T2: "I was a bit afraid that my colleagues would laugh at me in various ways before I came to work. But, none of them did." Nucleic acid testing is also gradually becoming less frequent. N7-T2: "In the beginning, it was a single test, now it's all mixed." Some infected patients said that they no longer avoided the fact that they were infected under self-regulation and gradually returned to normal life. T12-N2: "When I first came out of quarantine, whenever people talked about this stuff, I wanted to avoid it and didn't want to hear about it. Now, when people talk about doing nucleic acids, I seem to slowly be able to accept it."

Avoidance of illness experience. Some infected patients still avoided infection and concealed their identities as a recovered person. N16-T2 Husband added: "Whoever mentions this, she is anxious about it. Some old folks called me and asked about this, and she was also a little anxious in her heart. There is nervousness in her heart, and she doesn't want to talk about it anymore." During the interview with N5-T2, the infected patient herself said, "I don't feel anything, it doesn't affect me at the moment. Everything is fine. Don't want to think about it." However, interviewing his lover, he said, "He used to look like a child, he used to laugh and joke around, but now he looks sad every day. He doesn't talk much in his free time." This experience has changed his personality.

Post-COVID-19 syndrome. Some infected patients still have residual weakness, chest tightness, loss of smell, sleep disorders, etc. N14-T2: "The body is a bit different anyway. I'm more tired than I used to be at work, and I'm not as fit as I used to be. Sleep has been bad, easy to wake up. I have no sense of smell." N15-T2: "I feel a bit breathless sometimes when I walk a few steps. I feel tired."

This study conducted a longitudinal exploration of COVID-19 patients' experience based on the TIR framework. In general, the TIR framework has played a good guiding role in the exploration of COVID-19 patients' illness experience. During the diagnosis phase, COVID-19 patients were usually very concerned about their own health problems, and due to great pressure caused by isolation, they were prone to psychological problems. The stabilization and preparation phase of COVID-19 patients were in the long isolation treatment. Patients gradually adapted to isolation treatment and started to plan their life after discharge. They were worried about discrimination and worried that they would never go back to the original life. In addition, because COVID-19 patients were kept in isolation for a long time, some patients began to reflect on the experience of the disease and the past life status, and thus gained growth. The stigma of COVID-19 patients was felt throughout the course of the illness, but it was particularly evident during the implementation and adaptation phase. Due to the stigma and discrimination, some patients actually made great changes to their work and life during this two phase. At this time, social support was particularly important for patients to reintegrate into society. The following discussion provides detailed analysis of the above phenomena.

The results of this study showed that all infected patients diagnosed for the first time had psychological problems such as anxiety, fear, and sleep disorders, and seven patients (43.75%) were suspected of having mild to moderate depression according to the SDS scores, which is similar to the results of the study by Deng et al. 15 . This may be due to the highly contagious nature of COVID-19 and the lack of specific treatment, resulting in infected patients being prone to excessive stress, panic, and even psychological stress disorder at the early stage of diagnosis 16 . At the same time, 14 cases (87.5%) of the infected patients expressed concern about the possibility of "repositivity" after recovery and the existence of sequelae. A related study found that noninfectious viral RNA persisted in most of the "repositive" cases, which may be due to slow disease regression 17 . A positive test does not always mean that the patient is infectious, as it may detect fragments of viral nucleic acid 18 . However, most patients know little about this and develop more anxiety and fear. In contrast, those patients who have knowledge of the new coronavirus tend to have less fear and worry. Cheng Hualing et al. 19 meta-integrated the psychological experience of COVID-19 patients in China and found that more information provided by medical personnel to infected patients about the treatment and prognosis of the disease could eliminate the anxiety caused by the patients' lack of knowledge. Therefore, health promotion should be strengthened, and patients should be encouraged to acquire knowledge of the disease in various aspects, including transmission channels, protective measures, symptom classification, prognosis, etc. Patients’ questions should be patiently answered based on their own conditions, and they should be encouraged to obtain correct information through official authoritative channels to avoid "information panic" 20 .

Four infected patients (25%) in this study indicated that the relatively confined environment and instruments in the isolation area caused feelings of loneliness and helplessness. The isolation treatment measures separated the patients from the outside world, as they left their familiar working and living environments to enter a state of isolation, confinement and monotony. The patients' original lifestyles were completely disrupted, and certain financial losses were incurred. The unfamiliar environment and medical equipment increased the patients' fear and loneliness while also hindering the discharge of their negative emotions. This is consistent with the findings of Wang et al. 20 and Shaban et al. 21 . A retrospective study 22 found that isolation may cause unexpected mental trauma for patients and may even lead to self-injurious behaviors such as suicide. These effects persisted 3 years after desegregation. Psychological disorders can lead to low immunity and reduced motivation for treatment, thus negatively affecting disease recovery 23 . Currently, the treatment and care of patients in isolation wards are mainly focused on the disease itself, with relatively little attention given to the physical and psychological effects of isolation. Improving the treatment environment in isolation areas, providing as much stimulation as possible during the normal routine of work and rest, establishing a good lifestyle, and diversifying hospital activities are of great significance in relieving emotional tension, breaking psychological barriers, and promoting disease recovery 24 . Studies have shown that having sufficient sunlight is particularly effective for psychological relief 25 . Isolation areas should be set up to face south, and lighting measures should be strengthened. Public corridors can be set up in the isolation area so that infected patients can stagger their activities appropriately. Healthcare workers who are fully "armed" can paste their names on their protective clothing to improve communication between doctors and patients and reduce patients' sense of isolation. There are also studies 26 suggesting the use of the Rosenthal effect, that is, using praise, trust and expectation, and other psychological hints to help patients regain confidence and obtain positive motivation to change their own behaviors. By communicating with patients to understand their psychological needs, sources of negative emotions and specific factors affecting their emotions, healthcare professionals, in collaboration with teams from various disciplines, can encourage infected patients to cope positively and provide social support and psychological guidance to improve their quality of life 27 . The patients in this study were often in a state of confusion and worry before discharge and were also often unable to adjust to a good rhythm of life within a short period after discharge. Healthcare professionals can help patients develop a postdischarge transition plan during inpatient isolation so that they can quickly return to their original lives. At the same time, a scale of social reintegration behavior of infected patients with infectious diseases that is suitable for our country should be developed to prospectively investigate the current status of social reintegration of infected patients and to understand the changes in social reintegration behaviors in different periods to take corresponding measures to help such people adapt to their situations as soon as possible.

As a contagious disease, COVID-19 can lead to fear among the population as well as stigma and discrimination against specific groups of people 28 , and patients develop a sense of shame about their illness as a result. The results of this study show that patients often want to keep their experience of the disease confidential. The vast majority of infected patients in this study chose to conceal their illness from their family members. Due to the existence of a sense of shame, patients not only kept their disease experience secret but also often consciously reduced their mobility after discharge from the hospital to avoid infecting others. Patients may actively distance themselves from their friends and relatives, resulting in the loss of an important source of social support and a sense of isolation 29 . There were also patients who did not actively conceal their condition, but friends and colleagues of the infected patients intentionally chose to distance themselves from the infected patients out of fear and rejection after learning of their condition. Six patients (37.5%) in this study were thus forced to leave their original places of residence or work, causing them to develop more negative emotions. On the other hand, the infected patients who indicated that their colleagues and friends treated them no differently than before reported that they resumed normal life more quickly after returning to society. Yuan et al. 19 showed that the social support system of infected patients is an important factor in their posttraumatic growth. Social support based on kinship is the main way for most Chinese people to obtain social support. If this basic relationship is damaged, it prevents infected patients from obtaining the understanding and support of others, which can have a great impact on their physical and mental health 30 . The establishment of a good social support system will enhance psychological health; in contrast, the accumulation of negative emotions will lead to a variety of psychological problems 31 . Healthcare workers in the diagnosis and treatment of COVID-19 patients not only need to give the necessary treatment measures but also need to comprehensively assess the degree of understanding of the disease and social support system of infected patients. Healthcare workers should encourage infected patients to inform their families of their illnesses through daily communication, collaborate with their families to provide relevant psychological care, and improve the level of posttraumatic growth of patients 32 . In addition, the limitations of the public's knowledge of the disease will increase the individual's self-psychological burden, which will deepen the self-perception and experience of public stigma, resulting in the internalization of stigma 33 . Therefore, it is necessary to strengthen the information dissemination of infectious diseases, set up relevant policies for social groups such as communities and companies to avoid the public's rough treatment of infected patients returning to society, to protect the normal work and lives of infected patients and to reduce economic losses. This study shows that the policy benefits given by the government make infected patients believe in the national epidemic prevention policy and thus have confidence in the diagnosis and treatment of the disease. Therefore, state policy supports the reintegration of COVID-19 patients into society through macrocontrol.

Six months after returning to the community, some of the patients in this study still had sequelae of COVID-19, such as malaise, insomnia, chest tightness, and loss of smell. A recent study published in The Lancet 34 also confirmed this phenomenon. Similar studies have shown that the acute phase of COVID-19 and subsequent health damage involves multiple systems, such as the respiratory, neurological, and cardiovascular systems 18 . Given that infected patients at this stage need professional guidance to avoid delaying their illness, we call for greater collaboration among scholars from different countries to share experiences in the treatment of the disease to improve the physical and mental health of the population in the face of the postinfection syndrome caused by the global pandemic of COVID-19 patients.

This study found that there is a lack of clarity in the division of labor between departments and duplication of investigations by various departments in the process of epidemiological investigation.. It is recommended that the relevant departments should strengthen the integration and sharing of information by using big data and increase training in epidemiological investigation to improve efficiency 26 . Knowing the benefits of epidemiological investigation and personal information protection can reduce the uneasiness of infected patients, it is recommended that the media increase the scientific knowledge of epidemiological investigations and, at the same time, hide patients’ last names in the publication of epidemiological investigation information to protect the privacy of infected patients, and prohibit malicious human searches and other behaviors.

Limitations

While the study has its merits, it also has its limitations. First, this study interviewed COVID-19 patients only in Ningbo and did not include patients from multiple regions and centers. Second, this study was conducted during the control phase of the epidemic in China, and except for filling out the SDS scale, which was face-to-face, both interviews were conducted over the phone, and preventing the use of visual aids.

Conclusions

The objective of this study was to explore the perceptions and comprehension of patients infected with COVID-19 during the Chinese new coronavirus epidemic. COVID-19 patients encounter numerous psychological challenges while simultaneously experiencing physical discomfort, isolation, a sense of shame, and uncertainty regarding recovery. While some patients eventually adapt to their circumstances, not all are able to do so. Therefore, it is crucial for healthcare providers and families to provide support in order to facilitate patient adjustment to normal life. Interventions should be tailored according to the specific needs of patients at different stages, informing subsequent optimization of care and management strategies for infectious diseases.

Data availability

The datasets generated and analysed during the current study are not publicly available due privacy protection but are available from the corresponding author on reasonable request.

World health organization (WHO). Coronavirus (COVID-19) dashboard [DB/OL] . https://covid19.who.int/ . 2023-02-03.

Chen, W. X. et al. Comparison of three experimental methods for detecting antibody levels after immunization with COVID-19 vaccine [J]. Chin. J. Microbiol. Immunol. 41 (6), 423–426 (2021).

MathSciNet   Google Scholar  

Zhou, X. Y., Wang, H., & Hang, H. R., et al. Epidemiological and clinical characteristics of SARS-CoV-2 Delta variant infected patients with COVID-19 in Gansu province [J/OL]. Nurs. J. Chin PLA 1–14 (2022).

Chen, H. L., & He, Q. A meta synthesis of qualitative research on the psychological experience of patients with COVID-19 infection in China. J. Southw. Jiaotong Univ. 2022 (06), 73–82 (2023). http://kns.cnki.net/kcms/detail/51.1586.c.20221123.1638.018.html .

Hanson, S. W. et al. Global burden of disease long COVID collaborators; Estimated global proportions of individuals with persistent fatigue, cognitive, and respiratory symptom clusters following symptomatic COVID-19 in 2020 and 2021 [J]. JAMA. 328 (16), 1604–1615. https://doi.org/10.1001/jama.2022.18931 (2022).

Article   Google Scholar  

Guo, M., Kong, M., Shi, W., Wang, M. & Yang, H. Listening to COVID-19 survivors: What they need after early discharge from hospital—A qualitative study [J]. Int. J. Qual. Stud. Health Well-being. 17 (1), 2030001. https://doi.org/10.1080/17482631.2022.2030001 (2022).

Article   PubMed   PubMed Central   Google Scholar  

Cameron, J. I. & Gigrac, M. A. “Timing It Right”: A conceptual framework for addressing the support needs of family caregivers to stroke survivors from the hospital to the home [J]. Patient Educ. Couns. 70 (3), 305–314. https://doi.org/10.1016/j.pec.2007.10.020 (2008).

Article   PubMed   Google Scholar  

Liang, L. L. et al. Research progress on application of timing theory in disease nursing [J]. Chin. Nurs. Res. 30 (05), 524–525 (2016).

Google Scholar  

Chu, H. L. et al. Sample size was determined for qualitative interviews based on the information efficacy model [J]. Chin. Gen. Pract. 24 (10), 1274–1276. https://doi.org/10.12114/j.issn.1007-9572.2020.00.415 (2021).

Ding, X. & Yao, J. Peer education intervention on adolescents’ anxiety, depression, and sleep disorder during the COVID-19 pandemic [J]. Psychiatr. Danub. 32 (3–4), 527–535. https://doi.org/10.24869/psyd.2020.527 (2020).

Balmer, D. F. & Richards, B. F. Conducting qualitative research through time: how might theory be useful in longitudinal qualitative research? [J]. Adv. Health Sci. Educ. Theory Pract. 27 (1), 277–288. https://doi.org/10.1007/s10459-021-10068-5 (2022).

Audulv, Å. et al. Qualitative longitudinal research in health research: A method study [J]. BMC Med. Res. Methodol. 22 (1), 255. https://doi.org/10.1186/s12874-022-01732-4 (2022).

Sun, J. et al. Psychological anxiety of patients with novel pneumonia during isolation period [J]. Hosp. Admin. J. Chin. People’s Liberation Army 28 (8), 758–760 (2021).

Zhang, W. et al. To summarize the experience of psychological intervention and rehabilitation of patients with COVID-19 in mobile cabin hospital [J]. Chin. J. Nurs. 55 (S1), 603–605. https://doi.org/10.3761/j.issn.0254-1769.2020.S1.231 (2020).

Article   CAS   Google Scholar  

Deng, C. Y. et al. To analyze the depression level and its influencing factors in patients with COVID-19 [J]. Tianjin J. Nurs. 30 (04), 400–403. https://doi.org/10.3969/j.issn.1006-9143.2022.04.005 (2022).

Yao, L. Y. et al. To evaluate the mental health status and nursing of 45 patients injured in earthquake [J]. Chin. J. Nurs. 43 (12), 3. https://doi.org/10.3761/j.issn.0254-1769.2008.12.003 (2008).

Gidari, A. et al. Is recurrence possible in coronavirus disease 2019 (COVID-19)? Case series and systematic review of literature [J]. Eur. J. Clin. Microbiol. Infect. Dis. 40 (1), 1–12. https://doi.org/10.1007/s10096-020-04057-6 (2021).

Article   CAS   PubMed   Google Scholar  

Chen, H. et al. To explore the effects of life intervention on anxiety, depression and quality of life in patients with COVID-19 [J]. J. Nurs. Sci. 35 (09), 27–29 (2020).

Yuan, Z. F. et al. Current status and influencing factors of post-traumatic growth in patients with COVID-19 [J]. Chin. J. Nurs. 55 (S1), 587–589. https://doi.org/10.3761/j.issn.0254-1769.2020.S1.225 (2020).

Wang, J. Y. et al. A qualitative study on disease experience of 15 patients with COVID-19 [J]. J. Nurs. 27 (14), 63–67. https://doi.org/10.16460/j.issn1008-9969.2020.14.063 (2020).

Shaban, R. Z. et al. SARS-CoV-2 infection and COVID-19: The lived experience and perceptions of patients in isolation and care in an Australian healthcare setting [J]. Am. J. Infect. Control. 48 (12), 1445–1450. https://doi.org/10.1016/j.ajic.2020.08.032 (2020).

Brooks, S. K. et al. The psychological impact of quarantine and how to reduce it:rapid review of the evidence [J]. Lancet 395 (10227), 912–920 (2020).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Li, S. & Zhang, X. L. To analyze the effect of psychological nursing on elderly patients with chronic obstructive pulmonary disease [J]. China Rural Health 11 (24), 55 (2019).

Chen, J. G. et al. Study on the influencing factors of psychological status of confirmed COVID-19 patients and quarantine visitors [J]. J. Nurs. Admin. 20 (04), 247–251 (2020).

Korkut, S. Research of the coronavirus anxiety, post-traumatic stress, generalized anxiety disorder, quality of life, and stress coping styles in COVID-19 survivor [J]. Psychol. Rep. 125 (6), 3069–3083. https://doi.org/10.1177/00332941221129131 (2022).

Zhang, S. S. & Xie, W. Y. To explore the effect of psychological nursing based on Rosenthal effect on negative emotions of patients with suspected COVID-19 [J]. J. Nurs. Sci. 35 (09), 24–26 (2020).

Yuan, K. et al. A systematic review and meta-analysis on the prevalence of stigma in infectious diseases, including COVID-19: a call to action [J]. Mol. Psychiatry. 27 (1), 19–33. https://doi.org/10.1038/s41380-021-01295-8 (2022).

Huang, L. X. et al. Health outcomes in people 2 years after surviving hospitalization with COVID-19: A longitudinal cohort study [J]. Lancet Respir. Med. 10 (9), 863–876. https://doi.org/10.1016/S2213-2600(22)00126-6 (2022).

Wang, T. et al. Current status and influencing factors of stigma in patients after COVID-19 recovery [J]. Shanghai Nurs. 20 (10), 28–31 (2020).

Zhen, X. Y. Quality of life and related psychosocial factors in people living with HIV/AIDS [D] (Shanxi Medical University, 2011).

Zhou, S. J. et al. Common psychological conflicts and coping strategies of COVID-19 patients [J]. Chin. Mental Health J. 34 (03), 248–250. https://doi.org/10.3969/j.issn1000-6729.2020.3.021 (2020).

Nan, F. F. et al. Remote psychological crisis intervention service under the COVID-19 epidemic in Zhejiang province [J]. China J. Health Psychol. 29 (03), 367–370. https://doi.org/10.13342/j.cnki.cjhp.2021.03.010 (2021).

Li, R. J. et al. Qualitative research on psychological experience of pregnant women with COVID-19 [J]. Milit. Nurs. 39 (09), 49–52 (2022).

Huang, L. et al. 1-year outcomes in hospital survivors with COVID-19: A longitudinal cohort study [J]. Lancet. 398 (10302), 747–758. https://doi.org/10.1016/S0140-6736(21)01755-4 (2021).

Download references

This research was supported by Medical Scientific Research Foundation of Zhejiang Province under Grant No. 2023KY1091; Zhejiang Provincial Natural Science Foundation of China under Grant No. LY22H160006.

Author information

Authors and affiliations.

Hemtology Department, Ningbo No. 2 Hospital, Ningbo, Zhejiang, China

Liangyan Zhang & Kesang Li

Intensive Care Unit, Ningbo No. 2 Hospital, Ningbo, Zhejiang, China

Infection Department, Ningbo No. 2 Hospital, Ningbo, Zhejiang, China

You can also search for this author in PubMed   Google Scholar

Contributions

Liangyan Zhang organized interviews and collected the data. Liangyan Zhang and Chen Zhang analyzed the data and wrote the main manuscript text. All authors reviewed the manuscript.

Corresponding author

Correspondence to Chen Zhang .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Zhang, L., Zhang, C., Li, K. et al. Longitudinal qualitative study on the psychological experiences of COVID-19 patients based on timing it right framework. Sci Rep 14 , 12409 (2024). https://doi.org/10.1038/s41598-024-63215-4

Download citation

Received : 17 December 2023

Accepted : 27 May 2024

Published : 30 May 2024

DOI : https://doi.org/10.1038/s41598-024-63215-4

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Longitudinal qualitative study
• Timing it right framework

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

• Open access
• Published: 29 May 2024

Cannabis use in a Canadian long-term care facility: a case study

• Lynda G. Balneaves 1 , 4 ,
• Abeer A. Alraja 1 ,
• Genevieve Thompson 1 ,
• Jamie L. Penner 1 ,
• Philip St. John 2 ,
• Daniella Scerbo 1 &
• Joanne van Dyck 3  

BMC Geriatrics volume  24 , Article number:  467 ( 2024 ) Cite this article

313 Accesses

2 Altmetric

Metrics details

Following the legalization of cannabis in Canada in 2018, people aged 65 + years reported a significant increase in cannabis consumption. Despite limited research with older adults regarding the therapeutic benefits of cannabis, there is increasing interest and use among this population, particularly for those who have chronic illnesses or are at end of life. Long-term Care (LTC) facilities are required to reflect on their care and policies related to the use of cannabis, and how to address residents’ cannabis use within what they consider to be their home.

Using an exploratory case study design, this study aimed to understand how one LTC facility in western Canada addressed the major policy shift related to medical and non-medical cannabis. The case study, conducted November 2021 to August 2022, included an environmental scan of existing policies and procedures related to cannabis use at the LTC facility, a quantitative survey of Healthcare Providers’ (HCP) knowledge, attitudes, and practices related to cannabis, and qualitative interviews with HCPs and administrators. Quantitative survey data were analyzed using descriptive statistics and content analysis was used to analyze the qualitative data.

A total of 71 HCPs completed the survey and 12 HCPs, including those who functioned as administrators, participated in the interview. The largest knowledge gaps were related to dosing and creating effective treatment plans for residents using cannabis. About half of HCPs reported providing care in the past month to a resident who was taking medical cannabis (54.9%) and a quarter (25.4%) to a resident that was taking non-medical cannabis. The majority of respondents (81.7%) reported that lack of knowledge, education or information about medical cannabis were barriers to medical cannabis use in LTC. From the qualitative data, we identified four key findings regarding HCPs’ attitudes, cannabis access and use, barriers to cannabis use, and non-medical cannabis use.

Conclusions

With the legalization of medical and non-medical cannabis in jurisdictions around the world, LTC facilities will be obligated to develop policies, procedures and healthcare services that are able to accommodate residents’ use of cannabis in a respectful and evidence-informed manner.

Peer Review reports

In October 2018, Canada became the second country to legalize non-medical cannabis [ 1 ]. Despite the increasing interest in cannabis among Canadians of all ages [ 2 ], the percentage of individuals over the age of 15 years reporting cannabis use a year following legalization remained relatively unchanged at 18% [3]. The only age group to report a significant increase in cannabis consumption was those aged 65 + years, with 7.6% reporting cannabis use in the past 3 months [ 3 ] in 2019 compared to 4% in 2018. This upward trend in cannabis use among Canadians 65 years or older was also observed in 2021 [ 4 ].

This increase may reflect a growing acceptance of cannabis among older populations who were previously dissuaded from taking cannabis due to its illegal status as well as limited accessibility through legal means. In addition, the rise in cannabis use among older adults may reflect a harm reduction approach, substituting cannabis for other recreational substances with substantial health risks, such as alcohol [ 5 ]. Moreover, the belief in the potential therapeutic benefits of cannabis [ 6 , 7 , 8 ], such as the management of pain and sleep issues, is becoming increasingly prevalent among older adults. There has been limited research, however, among older adults in Canada to understand this progressive trend in cannabis use and the influencing factors [ 9 ].

Canada has been a world leader in cannabis legalization, launching a federal medical cannabis program in 2001. Since this time, the medical cannabis program has undergone numerous revisions, including how authorization is obtained, what types of products are available, and where cannabis is purchased. Currently, Canadians can seek medical authorization from either a physician or a nurse practitioner, and access a variety of cannabis products, including dried flower, capsules, and oils, which are purchased online through a licensed producer (LP). Some individuals also apply for a personal or designated grow license to produce their own supply of dried cannabis. Outside of the medical authorization program, individuals can access non-medical cannabis through an authorized storefront. It is estimated that over 1 million Canadians are using cannabis for therapeutic purposes [4], with 247,548 individuals officially registered as of March 2022 [ 10 ]. Among the 479,400 individuals over the age of 65 who reported cannabis use in the third quarter of 2019, 52% utilized cannabis exclusively for medical reasons, and another 24% reported using cannabis for both recreational and medical purposes [ 3 ].

Despite the growing interest in cannabis as a therapeutic agent, there has been limited human research due to its illegal status in many countries, as well as the challenges posed by the complexity of the cannabis plant compared to single agent, pharmaceutical forms of cannabis (e.g., nabilone) [ 11 , 12 ]. Notwithstanding these challenges, there is emergent research on the potential role of cannabis-based medicines in the management of health conditions common among older adults, including osteoarthritis [ 13 ], sleep disorders [ 14 ], dementia [ 15 ], and Parkinson’s [ 16 , 17 ], which are also prevalent among individuals residing at long-term care (LTC) facilities. For example, several studies have found cannabis-based medicines to significantly reduce neuropsychiatric symptoms and improve quality of life among people living with Alzheimer’s Disease [ 18 , 19 , 20 ]. Cannabis may also play a significant role at end of life in not only alleviating physical symptoms, such as pain, nausea and vomiting, and appetite loss, but also addressing the emotional and existential issues that may arise [ 21 ]. It has also been proposed that cannabis may have a therapeutic role among rehabilitative populations who often reside in LTC settings, including those with spinal cord injuries [ 22 , 23 ] and traumatic brain injury [ 24 ]. The evidence base surrounding cannabis as a therapeutic agent, however, remains limited with few large randomized clinical trials conducted to date.

Cannabis is not a benign substance and may pose risk to older adults, especially those living with frailty or cognitive impairment. Given the known cognitive effects of tetrahydrocannabinol (THC), a cannabinoid found in many forms of cannabis, adults living in long-term and rehabilitative care settings may experience somnolence, confusion, and fatigue [ 25 ]. Cannabis high in THC may also negatively impact motor coordination and increase the risk of falls, especially among those with impaired balance and walking ability [ 25 ]. As research advances on cannabis, there has been growing awareness of its negative interactions with certain medications [ 26 ], which can pose a significant issue among older clients prone to polypharmacy. Lastly, numerous health conditions are contraindicated with cannabis use, including heart disease, and a personal or family history of psychosis, schizophrenia, or bipolar disorder [ 27 ].

Despite limited research with older adults regarding the therapeutic benefits of cannabis, there is increasing interest and use among this population, particularly for those who have chronic illnesses. As adults age, they are more likely to experience multimorbidity, and a significant number of older adults spend their last years of life residing in a LTC facility [ 28 , 29 ]. LTC facilities are, thus, placed in a unique position. While these facilities are considered medical institutions that provide evidence-informed supportive health care, they have also become home for individuals who are no longer able to reside safely in the community. Increasingly, these types of facilities are challenged to create home-like environments and offer residents the opportunity and autonomy to engage in potentially risky health behaviours [ 30 ]; behaviours that individuals in the community have the independence and legal right to choose, such as alcohol or tobacco consumption. With the legalization of non-medical cannabis and the growing interest in the potential of cannabis to manage challenging health conditions, it behooves LTC facilities to reflect on their care and policies related to the use of legal substances, such as cannabis, and how to address residents’ cannabis use within what they consider to be their home.

The overarching aim of this case study was to understand how one LTC facility, and its healthcare professionals (HCPs) and administrators, addressed the major policy shift in Canada related to medical and non-medical cannabis. Specific research questions included: (1) What are the experiences and perceptions of HCPs and administrators regarding the use of medical and non-medical cannabis at LTC settings?; (2) What are the perceived barriers/facilitators to medical and non-medical cannabis use at LTC facilities from the perspective of HCPs and administrators?; and (3) What are the educational needs, attitudes, and practices of HCPs at LTC facilities related to medical and non-medical cannabis?

Research design and setting

An exploratory case study design was utilized in this study. This type of case study is used to explore those situations in which the phenomenon being evaluated has no clear or single set of outcomes [ 31 ]. The case selected for this study was a large LTC facility in Western Canada. This 387-bed residential facility provides 24/7 care to a diverse population, including older adults with cognitive and physical disabilities, individuals recovering from stroke and traumatic brain injury, and those requiring end-of-life care. Individuals with these various conditions may reside in several units, including palliative care, rehabilitation, personal care home, and complex chronic care. The case study included an environmental scan of existing policies and procedures related to medical and non-medical cannabis use at the LTC facility, a quantitative survey of HCPs’ knowledge, attitudes, and practices related to medical and non-medical cannabis, and qualitative interviews with HCPs and administrators. The qualitative interviews were informed by qualitative descriptive methodology [ 32 ] and explored HCPs’ and administrators’ experiences, beliefs, perceptions regarding cannabis use in LTC, and the related barriers and facilitators.

Sample and recruitment

For the survey, a convenience sample was drawn from the entire population of accredited HCPs working in the selected facility. Eligibility criteria included being 18 + years, able to read/speak English, currently employed and providing care at the LTC facility, and able to provide informed written consent. Study participants were recruited through an emailed letter of invitation, posters placed in staff areas, and in-person presentations by a research assistant. From participants who took part in the survey, a subsample of HCPs, including administrators, who expressed interest in taking part in an interview was selected. The data collection period was from November 2021 and August 2022.

Data collection

For the environmental scan, facility administrators were approached via an emailed letter and asked to identify relevant policies and procedures related to cannabis use within their LTC facility. Policies relevant to both residents’ use of cannabis and HCPs’ practice related to medical and non-medical cannabis were requested. Provincial and federal cannabis policies were also collected.

The survey was modified from a questionnaire utilized in two national studies that examined Canadian physicians’ and nurse practitioners’ knowledge, attitudes, and perceptions of the associated barriers and facilitators related to medical cannabis use, as well as their preferences regarding medical cannabis education [ 33 , 34 ]. This survey has been found to be internally consistent, with Cronbach’s alphas of 0.70 to 0.92 reported across subscales [ 33 , 34 ]. Slight word changes were made to reflect the fact that individuals living in LTC facility are referred to as residents, not patients, and the name of the facility was used to orientate the questions towards HCPs’ attitudes and practices related to cannabis use within the LTC setting.

Survey items were added that assessed HCPs’ practices related to addressing residents’ and family members’ questions about cannabis, as well as requests for medical cannabis authorization and follow-up care. A demographic survey that assessed gender, age, professional designation, years in practice, area(s) of practice, and education related to medical cannabis was included. The survey was available in hard copy (Supplementary Material 1 ) as well as online through the software program, Qualtrics®.

An interview guide was developed by the research team, which included a facility administrator and HCP, and was informed by the literature and previous cannabis research conducted by members of the research team [ 35 ] (Supplementary Material 2 ). Due to the COVID-19 pandemic, all but one interview was conducted by the project coordinator (AAA) via Zoom, with one interview occurring over the phone. The interviews were 20–30 min in length and were digitally recorded and transcribed verbatim. Both the survey and interview were completed at times preferred by the respondents, including within and outside work time. No honoraria were provided for study participants.

Data analysis

The policies identified through the environmental scan were reviewed and summarized in table format, with similarities, contradictions and gaps identified.

Quantitative survey data was uploaded into the statistical program, SPSS® v.25. Descriptive statistics were used to summarize demographic information, knowledge about medical cannabis and related attitudes, perceived barriers and facilitators, practice experiences, and preferred educational approaches.

Perceived knowledge gap was calculated by computing the difference between perceived current and desired knowledge levels (i.e., “the level of knowledge you desire” about medical cannabis). Rather than using averages, the knowledge gap was calculated based on how much greater an individual’s desired knowledge level was compared to their current knowledge level [ 36 ]. Only response pairs (i.e., current and desired knowledge) were used, and responses where the desired level was lower than the current level were excluded. To further elucidate, the knowledge gap was calculated by having each respondent’s current knowledge level response subtracted from their desired knowledge level response.

Prior to the onset of qualitative data analysis, the accuracy of the transcripts was checked by listening to the digital recordings. Content analysis was used to analyze the qualitative data [ 37 ], with two team members (AAA and LGB) independently reading the transcripts and developing a preliminary coding scheme. Constant comparison of new and existing data ensured consistency, relevance, and comprehensiveness of emerging codes. Several strategies were applied to ensure rigour in the qualitative analysis. To increase credibility, a team member with expertise in qualitative inquiry (LGB) monitored the qualitative data and its analysis. Confirmability was addressed by using the participants’ own words throughout the process of data analysis, interpretation, and description. An audit trail was kept documenting the activities of the study, including data analysis decisions.

Environmental scan of cannabis-related policies

Administrators at the LTC facility provided the research team with the policies and procedures that addressed the management and use of medical and non-medical cannabis within the facility. The guiding policy adopted by the LTC facility was a generic policy applicable to all sites and facilities governed by a regional health authority. This policy, entitled “Patient Use of Medical Cannabis (Marijuana)” was issued in June 2020. The policy, which aimed to provide individuals with “reasonable access to medical cannabis”, outlined numerous issues that might arise with institutional cannabis use, including “ordering, labeling, packaging, storage, security, administration, documentation and monitoring requirements for the use of medical cannabis”. Key aspects of the policy are summarised in a table found in the Supplementary Material section (Supplementary Material 3 ).

Other relevant policies that were reviewed included the standards of practice issued by the provincial college of nurses and the college of physicians and surgeons [ 38 , 39 , 40 ], which provided direction to HCPs working in LTC about their scope of practice regarding medical and non-medical cannabis. The regional health authority’s smoke-free policy [ 41 ] also informed how inhaled forms of medical and non-medical cannabis were addressed, requiring residents to leave the facility grounds to smoke or vape cannabis. Lastly, the overarching federal Cannabis Act and Regulations provided guidance to both administrators and HCPs regarding the Canadian regulations specific to medical and non-medical cannabis [ 1 , 42 ]. Together, existing facility, regional, and national policies created a context in which cannabis was framed as neither a medicine nor a controlled substance, but something unique and complex that must be navigated by residents, family members and staff in LTC settings.

Quantitative survey

Demographic characteristics.

From the approximately 318 eligible HCPs employed at the LTC facility, a total of 71 participants consented and completed the survey, yielding a response rate of 22.3%. With regards to response rate by profession, pharmacists (50.0%) and social workers (42.9%) were best represented, followed by physicians (23.1%), nurses (21.0%), and PT/OT (11.4%).

Most respondents were women (71.8%), registered nurses (62.0%) and worked within the palliative care unit (76.1%) at the facility. The average age of the sample was 40.9 years and the largest proportion of the sample had worked in the LTC facility for 5 or less years. See Table  1 for additional details.

Knowledge about medical cannabis

HCPs reported being most knowledgeable about the therapeutic potential of cannabis (3.1/5.0), potential risks of medical cannabis (2.9/5.0), and the different ways to administer medical cannabis (2.9/5.0). They reported being least knowledgeable about the dosing of medical cannabis (2.0/5.0), how to create effective treatment plans related to medical cannabis (2.1/5.0), and the similarities and differences between different forms of cannabis products and prescription cannabinoid medications (2.2/5.0). The top three ranked knowledge gaps mirrored the items ranked lowest with regards to knowledge (see Table  2 ). Overall, there was high interest in gaining more medical cannabis knowledge, with all knowledge items scoring greater than 4 on desired knowledge level.

Practice experiences with medical cannabis

About half of HCPs reported providing care in the past month to a resident who was taking medical cannabis (54.9%) and a quarter (25.4%) to a resident that was taking non-medical cannabis. Over 60% had been approached by a resident and/or a family member to discuss the potential use of medical cannabis; however, few HCPs reported initiating these conversations. Moreover, when asked if they felt comfortable discussing medical cannabis, 32.4% of HCPs disagreed (data not shown). Less than 20% reported helping residents, either directly or indirectly, to use medical cannabis and a very small proportion (1.3–2.8%) reported assisting residents’ consumption of non-medical cannabis. With regards to authorizing the use of medical cannabis or prescribing cannabinoid medication, which in Canada can be done by either a physician or nurse practitioner, just over half of physicians reported supporting residents’ access to these types of treatment. See Table  3 for additional details.

Barriers to medical cannabis use in long-term care

Lack of knowledge, education or information about medical cannabis were reported to be barriers to medical cannabis use in LTC by most HCPs (81.7%). Moreover, the uncertain risks and benefits of medical cannabis and the lack of clinical guidelines were also perceived as barriers by 66.2% and 63.4% of HCPs, respectively. The complete list of barriers is presented in Table  4 .

Education about medical cannabis

Most of the HCPs agreed that additional education on medical cannabis would increase their comfort with discussing this treatment option with residents and family members (87.4%; data not shown). With regards to indirectly or directly administering medical cannabis to a resident, most HCPs for which this fell within their scope of practice also reported they would feel more comfortable if they had further education (59.2% and 56.4%, respectively; data not shown).

Over half of HCPs had not received any prior education related to medical cannabis (54.9%). Those that had, received it from conferences or workshops (65.6%), books or journal articles (43.8%) or through a colleague (37.5%). While almost half the sample (49.3%) reported receiving information from peer-reviewed sources, nearly a quarter received information about medical cannabis from a non-peer reviewed source or from a resident or family member. Some participants also received information from a cannabis industry source. Table  5 provides additional details.

The preferred sources of medical cannabis education were online learning programs (i.e., continuing education) (74.6%), monographs (66.2%), and topic-specific one-pagers (64.8%). See Fig.  1 for further details.

Percentage of respondents indicating prefered method of cannabis education*

Qualitative findings

A total of 12 HCPs were interviewed regarding their perceptions and experiences related to medical and non-medical cannabis in the LTC facility. This included 3 HCPs who were administrators, 6 nurses, 1 physician, 1 social worker and 1 pharmacist. Four main themes were identified.

Attitudes regarding medical cannabis: cautious support

There were mixed attitudes regarding the potential role of medical cannabis in general and in LTC populations. While some HCPs felt medical cannabis was a “good idea” for which there was beginning research regarding its health benefits, other HCPs believed additional high-quality evidence was needed prior to medical cannabis becoming a therapeutic option.

I think it’s [medical cannabis] the fair option, it helps some people, but it doesn’t help others. So, I think we need a bit more evidence and a bit more research and having it available sort of allows for that research to occur (Physician; PC07).

There appeared to be greater acceptance for medical cannabis use by individuals at end of life compared to those not considered immediately palliative (i.e., living with dementia, stroke, or traumatic brain injury), the latter of which comprise the majority of the people living in LTC settings. For individuals receiving palliative care, some HCPs perceived medical cannabis to be beneficial in managing pain, nausea, and anxiety, as well as reducing the use of other medications that may be problematic (e.g., opioids) due to their side effects. The potential value of medical cannabis in “adding quality of life and living” at the end of life was also mentioned.

I’m working on the palliative care unit right now. A lot of patients that I’ve seen use it [medical cannabis] for anxiety purposes, or for nausea… some people find beneficial. So, I’ve seen it – people find it helpful for those reasons, and then they have to take less of their other medications. So, if it’s worked well for them and that’s what they prefer to do, then I think it should be an option for people, especially if some people find it beneficial. (Registered nurse; PC03)

Within the context of LTC, several HCPs also spoke of the importance of respecting residents’ autonomy and previous experiences taking medical cannabis. The reality of a LTC facility being a resident’s “home” was particularly influential in HCPs’ support of medical cannabis being included as part of a holistic approach to care.

I guess because people live at [LTC facility’s name], that is their home and if they were at home in the community, they would be able to access it [medical cannabis]. (Registered nurse, PC02)

I think it’s a part of people’s lives. And I think if we’re allowing people to have certain things and keeping it as part of their treatment because if you look at a holistic view, preventing somebody from doing something that they’ve been doing for many years is not going to help them be accepting of other types of therapies. (Pharmacist, PC09)

Some HCPs also perceived medical cannabis as offering an alternative to medical treatments that were not consistently effective in managing challenging health conditions, such as dementia and agitation.

HCPs’ attitudes towards medical cannabis varied across different products and routes of administration. Given the existing smoke-free policy at the facility, HCPs were more supportive of edibles, oils, oral sprays or topical creams and lotions than any form of inhaled medical cannabis (i.e., smoking and vaping). They were concerned not only about lung health, environmental exposure, and maintaining a scent-free facility, but also about how to safely manage vulnerable residents travelling off the facility’s property to smoke or vape.

Medical cannabis access and use: concern, confusion, and limited conversations

According to HCPs interviewed, most residents using medical cannabis obtained their authorization prior to moving to LTC. Individuals who sought authorization after arriving at the facility struggled to have their requests acknowledged or addressed by the health care team. As one nurse shared:

I do remember I had a resident that did ask about it [medical cannabis]. And whenever it was kind of brought up, it didn’t seem to be acknowledged all the time. Or there were people who didn’t like the idea of having a resident on it. (Registered nurse; PC06)

Conversations about medical cannabis were perceived to be severely limited by the culture surrounding medical cannabis at the LTC facility. The lack of open discussion about medical cannabis was seen by some to create conflict and negatively impact the development of trust between residents, family members, and the health care team: “ Without that discussion, it does create conflict within the team and between the physician and family, and perhaps that could impact the trusting relationship” (Administrator; PA03). Further, several HCPs expressed the belief that conversations about non-pharmacological forms of medical cannabis could not be initiated by them due to policy issues; residents who expressed interest but did not have prior authorization were instead directed towards pharmaceutical forms of cannabis.

There have been residents who have asked about using cannabis. And as I said, you can’t initiate it, if they’re going to get it on their own, fair enough. That’s pretty much been the experience I’ve had with residents with just non-pharmaceutical medical cannabis . (Physician, PC07)

The only HCP-initiated conversations about medical cannabis mentioned were those occurring between pharmacists and residents, which focused on the potential side effects, benefits, and “red flags” to watch out for, such as allergic reactions.

HCPs shared that for those residents with authorization, they or a support person were responsible for ordering the medical cannabis product from an LP, which would then send the product to either the resident at the LTC facility or to their support person’s home. The cannabis product was then stored in a locked drawer in the resident’s room if they were self-administering or in a medication room if nursing staff were assisting with administration. According to one pharmacist, the pharmacy department was not permitted, due to existing federal regulations, to either directly order or dispense medical cannabis:

No, we don’t dispense any cannabis. It’s considered resident’s own. So, we don’t acquire it for them. They have to directly be the holders of it and have it provided to them directly. And I think that has more to do with the regulations within Canada, the resident has to have certain type of documentation in order to have medical cannabis. So, it’s directly to them, we’re not able to order it for them or anything like that on their behalf. (Pharmacist; PC09)

With regards to the type of medical cannabis products permitted in the facility, due to non-smoking policies and concerns about safety issues and the “smell”, combustible forms and inhaled routes of administration (i.e., joints, vaporizers, vape pens) were not allowed; instead, ingestible forms were mentioned most frequently by HCPs.

There was some confusion and concerns expressed regarding the storage and disposal of medical cannabis, which may have reflected changes in facility policies over time. Some HCPs expressed concerns about the storage of cannabis in residents’ rooms and the lack of “safeguards” to limit potential diversion and allow an accurate “count” of medical cannabis.

We have to go into our Pyxis machine to retrieve a key to open that drawer. So, by going by that you’re able to know who’s actually accessed the key, but once the key is out you have no idea how many people have used that key and accessed that drawer before it’s gone back. You have no way of knowing how much cannabis has been taken out [of the drawer] or used, because you know there’s no way to measure it. So that’s a huge problem, I find. (Registered nurse; PC01)

This nurse was particularly concerned about the potential risk of being accused of diversion:

I’m not worried about people abusing it, it’s more the worry of being accused. You know, like, if a resident says, ‘why is my cannabis running out already, I thought I had enough for a few more weeks?’ and we’re like, ‘I don’t know’, right? There’s the potential for that sort of thing to happen. (Registered nurse; PC01)

There was also a perception that there was a lack of direction from the facility regarding the appropriate disposal of medical cannabis. Most believed residents or family members were expected to remove any unused product once the resident was no longer at the facility. When such disposal was not possible, the policy was to destroy the cannabis product in a manner similar to narcotics or other controlled substances. However, variations in practice occurred with some HCPs described “throwing it in the trash” or using a medical waste disposal bin with or without a witness.

Barriers to medical cannabis use: safety, stigma and lack of knowledge

Numerous barriers to the use of medical cannabis by LTC residents were identified by HCPs. Foremost, the policies related to how cannabis products were ordered, accessed, stored, and administered were perceived to be complicated and created barriers to residents wanting to take medical cannabis, particularly those without family support. The inability of the LTC facility to order medical cannabis on behalf of a resident was perceived to be especially problematic, as described by one registered nurse:

I know when it became legal, there were a few residents who have inquired about it, but they didn’t have the family resources in place to be able to get it because I believe there’s some hoops that you have to go through to be able to have it medically prescribed in getting it on to the unit. And so, the ones who were interested in it didn’t have those supports in place, so they weren’t able to get it prescribed for them. (Registered nurse; PC05)

The lack of awareness and understanding of the regional policies related to medical cannabis by some of the clinical staff was also seen as being problematic. As one registered nurse shared:

My only concern is that there’s a lot of rules around being able to administer and how it’s [medical cannabis] administered, which can again make things a bit complicated. I would say that’s probably my biggest concern is just it’s hard to remember everything that you have to do when you’re trying to administer it or helping a resident. So, you don’t get involved. (Registered nurse; PC06)

Several HCPs attributed the lack of awareness about cannabis policy to the onset of the COVID-19 pandemic, which overshadowed all other health issues within their facility: “ Everybody’s been so focused on COVID for a year and a half that there hasn’t been really time to really think about or educate on other things. ” (Registered nurse; PC01).

HCPs suggested that more “straight forward” and tailored policies were needed that simplified how medical cannabis was managed. Having facility-specific policies would acknowledge the uniqueness of the LTC population, who may have cognitive impairment, limited social support, and complex healthcare plans. As one nurse shared: “ If it’s a dementia patient, they can’t really administer it on their own. So how do we follow the policy to help the patient take the cannabis? How would we know when they would want to take it PRN?” (Registered nurse; PC03). It was also recommended that the policy that prevented the facility from directly ordering and supplying medical cannabis required revision so that LTC residents were not reliant on family members to gain access. Lastly, several HCPs suggested that medical cannabis policies need to be well advertised and additional training developed for clinical staff to enhance their awareness and comfort level in providing appropriate and supportive care.

There needs to be a training session… staff have to read through them [cannabis policies] and get instructions about them, sort of like a self-learning activity. But that is not part of what we do when orienting. (Registered nurse; PC02)

Another perceived barrier frequently mentioned by HCPs was their lack of knowledge regarding the potential risks and benefits of medical cannabis. There was limited understanding about the effects of medical cannabis, how it may interact with other medications and health conditions, what side effects could arise, as well as basic information about starting dose, titration, and difference between THC and cannabidiol (CBD). Without such information, HCPs were perceived to be very hesitant about recommending or supporting medical cannabis as a treatment alternative for LTC residents:

There’s lots of unknown, that’s the problem. If there were more specifics about the recreational and the medical use of cannabis, then I think health care professionals would be more likely to want to provide it to the residents. But if not, then that’s kind of what’s hindering health care professionals to provide it. (Registered nurse; PC08)

There was also substantial discussion by HCPs regarding the “stigma” that they perceived to exist within the facility regarding medical cannabis. As described by one pharmacist: “ I think the understanding of cannabis, regardless of if it’s medical or anything, it’s still considered in many people’s minds as an illicit drug. It hasn’t shaken that. And I think there’s a lot of stereotypes around the type of people that use cannabis” (Pharmacist; PC09). The stigmatization of medical cannabis was perceived to be particularly pronounced among the medical staff, which led to what was described as a “hands-off approach” with regards to authorizing medical cannabis.

Almost all HCPs and administrators interviewed recommended that education programming and resources for HCPs be developed to address the lingering stigma associated with cannabis and the knowledge gaps that exist about medical cannabis and associated policies. Several participants recommended that education initiatives should first target physicians, who were responsible for authorizing medical cannabis in the facility. Physicians were perceived to need education on when and for whom medical cannabis would be appropriate, the latest evidence regarding efficacy and safety (i.e., drug interactions), and what their obligations and responsibilities were as the authorizing HCP. Participants also thought that all HCPs could benefit from additional training regarding medical cannabis, including the different types of cannabinoids and products, the process of titration, and dosing. Some of the nurses interviewed also expressed the need for education about the legal implications of medical cannabis and their role regarding provision and administration:

I think the legal implications of cannabis use, I think that would be a good focus for the nursing group – so that they understood what their obligations were, what they could be held accountable for, those kinds of things. (Administrator; PA02)

Finally, numerous HCPs spoke of the need for “safeguards” and clear policies and procedures to ensure that clinical staff were aware of what type of medical cannabis products residents were taking, what was the “right dose”, and the possibility of cannabis interacting with other medications. As shared by one pharmacist:

So that we know that this patient is on it because there are potential drug interactions with other things that patients are taking. So, we just have to be cautious and aware that patients are doing this. Because especially right now with studies, there haven’t been a lot of great studies on drug interactions. (Pharmacist; PC09)

Non-medical cannabis use: balancing autonomy and safety

HCPs were asked about their attitudes and experiences about residents’ use of non-medical cannabis in the facility. Two disparate points of view became apparent – those that perceived non-medical cannabis as a legal substance that should be available to LTC residents given the facility was their home and those that saw non-medical cannabis as a stigmatized substance that could lead to problematic use and disruptions in the care environment.

Because it is somebody’s home and so you’re trying to honour and match what their lifestyle and aspects of their life at home were and matching that here [LTC facility]. The bad is, while it is somebody’s home, it’s the next person’s home too, and so it’s trying to balance that, right? In an institutional setting, trying to make it as home-like as possible but, at the same time, you know, monitoring and matching for what everyone’s needs are. (Registered nurse; PA01)

Professionally, I think that it creates issues in terms of trying to police the use of recreational cannabis. In terms of smoking cigarette tobacco, that’s an issue in itself. We’re a non-smoking facility. So, adding cannabis to the mix creates issues…having staff perhaps exposed or other people exposed if people are using cannabis indoors or where they’re not supposed. Or if they want to access and use cannabis outside, who’s going to take them for that? Because that creates exposure too for staff or others who may have to escort them. (Registered nurse; PA03)

HCPs frequently mentioned the complexity of managing residents’ non-medical use of cannabis given the facility’s non-smoking policy that required residents to leave the facility grounds to use inhaled forms of cannabis. With staff unable to transport residents outside, concerns were raised regarding the safety of residents, particularly in the winter months, and who would be responsible for their transfer in and out of the facility as well as monitoring how much cannabis was consumed. In addition, residents’ access to non-medical cannabis was again dependent on having a support person that was able and willing to transport the product to the facility, posing a potential equity issue for some residents:

If someone’s wanting to go smoke outside, then mobility might be an issue. If they don’t have the right wheelchair or family to take them outside for that. If they have the access. Like, if they need family to go and buy it and bring it to them, that could be more of an access issue depending on their family support. (Registered nurse; PC03)

There was specific concern expressed for individuals in the rehabilitation units who may have pre-existing substance use issues. For these individuals, HCPs were concerned that allowing access to non-medical cannabis could add to an already complex care plan. In addition, with many vulnerable residents living at the facility, concerns were raised regarding them being “incredibly suggestible” to others encouraging their consumption of cannabis:

These people – they have an addiction. For sure they’re making choices, but those choices are influenced by physical withdrawal or influenced by stress; they’re influenced by lots of things. So, I would hate to put residents in a position where that was one other [non-medical cannabis] thing they had to contend with during the rehab stay. (Administrator, PA02)

The use of cannabis for therapeutic and recreational purposes is becoming more prevalent within older adult populations, both in the community as well as within healthcare institutions. There has also been growing interest in the possible role of medical cannabis for select chronic, rehabilitative, and palliative health conditions, frequently found among individuals residing within LTC settings. LTC facilities, thus, face the complex practice and policy implications associated with a substance that has been surrounded in controversy for close to a century. This case study is among the first to explore in one LTC facility in Western Canada how cannabis use is being addressed following the legalization of non-medical cannabis products, and what challenges exist. It provides an important snapshot of the complexities surrounding cannabis use in LTC and a foundation for future research.

Cannabis use in LTC settings: a clash of cultures

One challenge experienced by people residing in LTC facilities is the tension that exists between social and medical models of care that most facilities are founded on. Historically, LTC facilities have operated as what Goffman [ 43 ] termed “total institutions”, places where every aspect of a person’s life was controlled by others, paternalism dominated, and the medical needs of people were what drove care practices. Aspects of the total institution still exist, as noted in this case study, whereby cannabis use is in the control of the HCPs; it is dispensed during medication administration times rather than being freely available for use by the resident when they so desire as would be in a person’s home. In trying to create more home-like environments and meet the broad range of social and emotional needs of residents, resident-centred care practices and relational models of care have emerged [ 44 ]. Within this milieu, resident autonomy and choice are at the forefront and HCPs are there to assist, rather than take control of residents’ daily lives. In the most ideal settings, behaviours that are considered ‘risky’, like alcohol consumption, are treated as social experiences, not care tasks to be managed [ 45 ]. The tension arises, however, that despite the desire to be resident-centred, most LTC facilities are highly regulated by governments, putting limits to resident choice and, therefore, their autonomy [ 45 ]. While HCPs in our study acknowledged that residents should have the right to use medical or non-medical cannabis, the regional and institutional policies surrounding safety and the rights of other residents and staff to not be exposed to potentially risky behaviour underscored many of their views. LTC facilities would be wise to consider the principles of dignity of risk [ 46 ] with relation to cannabis consumption/use along the frail elderly population that reside in the home.

Cannabis policies and LTC: one size doesn’t fit all

The cannabis policies developed at the advent of legalization, without consideration of the unique populations and healthcare challenges that exist within LTC facilities, created numerous barriers to residents accessing and using cannabis, as well as for HCPs attempting to provide appropriate care. One of the most significant challenges experienced by LTC residents in our study was the inability to obtain a medical cannabis authorization from a physician working in the facility. Another significant challenge was the regional policy that medical cannabis could not be couriered directly to the LTC pharmacy; instead, the resident or their support persons were responsible for ordering and bringing cannabis products into the facility. Both challenges created enormous inequity in which residents that lacked the physical and cognitive ability to obtain authorization and order medical cannabis from an LP or were without a support person willing and able to obtain medical cannabis on their behalf, were unable to access medical cannabis. Given the nature of LTC populations, these policies led to only a few residents being able to access and use medical cannabis as part of their care.

Another policy that had substantial safety implications for residents wanting to use inhaled forms of cannabis was the regional and institutional no smoking policies that prevented both tobacco and cannabis products from being consumed within the centre as well as on the grounds. As a result, residents had to make their own way, or be accompanied by a support person, to walk approximately 300 m to the public sidewalk where they were allowed to smoke or vape cannabis. With the LTC facility located in a region where winter temperatures can reach − 35 Celsius and sidewalks are covered in snow and ice, this poses significant risk for residents who may be at heightened risk of falls and utilizing assisted walking devices. Similar safety implications of smoke-free policies have been identified in previous research [ 47 ].

Lastly, the policies surrounding the storage and self-administration of medical cannabis for those residents with the physical and emotional capacity (or with a support person willing to administer) may pose potential safety and liability risks and contribute to the concerns held by some HCPs about the use of cannabis in LTC. While residents’ autonomy must be respected, as well as their own expertise with regards to medical cannabis use, the value of standardized medication protocols to ensure the safety of residents as well as to inform care decisions must be acknowledged. The tension experienced in balancing LTC residents’ autonomy with health and safety concerns in the context of substance use has been cited in a recent scoping review [ 48 ] as well as prior research that has examined the use of tobacco in residential care settings [ 49 ].

The policy-related challenges identified by study participants suggest that consultations with LTC residents, families and HCPs are urgently needed to develop and refine cannabis policies that address the needs and reality of individuals living and receiving care in LTC. Future policy reviews must balance LTC residents’ autonomy with the safety issues associated with cannabis use (i.e., dignity of risk), particularly among older adults and those with cognitive and physical impairments. Approaching cannabis policies and procedures in LTC from a harm reduction perspective [ 50 ] with regards to supporting safer consumption of medical cannabis (e.g., route of administration, designated consumption areas) may also be important. Further, the unique context of LTC must also be acknowledged in that for many residents, a LTC facility is their home, and will continue to be so until the end of their lives. But the shared nature of a LTC setting requires that some boundaries be established to protect all residents, as well as those working within LTC. From a staff perspective, a review of policies related to the administration and documentation of cannabis use is needed to protect them from claims of diversion as well as other medicolegal challenges.

Cannabis knowledge gap and stigma in LTC

Across both the quantitative and qualitative data, the gap in knowledge regarding cannabis and the need for continuing education for HCPs working in LTC were readily apparent. When HCPs are unfamiliar about the various forms of medical cannabis, appropriate dosing and titration schedules, and routes of administration, they are hindered in their ability to engage in shared decision making with LTC residents as well as provide high-quality care [ 51 , 52 , 53 , 54 ]. Education is particularly needed that is tailored to the unique risks and benefits of medical cannabis use among LTC populations, including those living with physical and cognitive impairment. Older adults may be more sensitive to the side effects of cannabis due to changes in how medications and drugs are metabolised, and the predominance of polypharmacy among those residing in LTC may further complicate how individuals respond to cannabis [ 55 ]. Therefore, HCPs working in LTC must be aware of how cannabis use may impact individuals’ mobility, memory, and behaviour, as well as the potential for dependency, particularly among those who have experienced substance use issues in the past.

Beyond basic education regarding cannabis and its effects, HCPs must also become aware and informed about existing federal, regional, and institutional policies as well as professional practice standards regarding both medical and non-medical cannabis. The study findings highlighted the uncertainty many HCPs experienced regarding how medical and non-medical cannabis was to be accessed, authorized, administered, stored, and disposed within the LTC facility and what was within their professional scope of practice. Legal concerns about liability, workplace safety, and diversion were also raised.

It is important that future cannabis education programs targeting LTC settings also address the underlying stigma and stereotypes that still surround cannabis use [ 56 , 57 ], despite the existence of a medical cannabis program in Canada for over 20 years and the recent legalization of non-medical cannabis. Experiential training that promotes non-judgmental communication that avoids stigmatizing language (e.g., user, addict, marijuana) and considers both the risks and benefits of cannabis use, particularly within the context of end-of-life care, will help address the stigma that HCPs and LTC residents and families may hold towards cannabis.

With the legalization of cannabis in many regions around the world, it is imperative that undergraduate health professional training programs include information about both medical and non-medical cannabis. Currently, there is a knowledge gap among HCPs due to the lack of standardized curriculum for medical cannabis across nursing or medical schools [ 35 , 58 ]. Understanding such foundational knowledge such as the endocannabinoid system, the different forms and types of cannabis, and the potential health effects will enable physicians, nurses, pharmacists and other HCPs to engage in informed conversations with individuals and families both within and beyond LTC [ 33 ]. In addition, the development of continuing education programs focused on cannabis will ensure practicing HCPs have current knowledge about cannabis, including existing policies and programs relevant to medical and non-medical cannabis. For example, the Canadian Coalition for Seniors’ Mental Health created asynchronous e-learning modules to provide evidence-based knowledge for various clinicians [ 59 ].

Non-medical cannabis use in LTC: it’s legal but…

Despite non-medical cannabis being a legal substance for over three years in Canada at the time of the case study, the use of non-medical cannabis by LTC residents was considered controversial amongst the HCPs interviewed. Not only were HCPs limited in their ability to support the use of non-medical cannabis due to regional policies that prohibited non-medical cannabis consumption at any healthcare facility and surrounding grounds but concerns about potential safety risks and disruptions to the care environment made some HCPs hesitant about supporting residents’ use of non-medical cannabis.

Notwithstanding these challenges, at least a quarter of HCPs surveyed reported providing care to a LTC resident who used non-medical cannabis, which suggests that regulatory and policy changes are required to ensure there is equity across LTC residents who may express interest in non-medical cannabis, as well as to address the unique safety and care issues associated with recreational cannabis use in LTC populations. Similar to medical cannabis, LTC residents’ autonomy must be considered in future policy changes related to non-medical cannabis to facilitate care that is free from stigma and bias, respects residents’ rights to make informed decisions and to live with risk, and to create a home-like environment where residents can engage in activities that were an important part of their lives before entering LTC.

Lessons can be drawn from literature that has examined the use of other legal substances, such as alcohol and tobacco in LTC [ 48 , 60 ], and the need to develop person-centered care plans that ensure the safety of the individual, fellow residents, and the healthcare team.

Limitations

Like all case studies, the findings cannot be extrapolated to other LTC settings and populations. Given that this study was undertaken in Canada, which has a socialized healthcare system and legalized both medical and non-medical cannabis, the experiences and attitudes of HCPs who participated may be unique and limit the generalizability of the findings. However, there are lessons to be learned regarding the challenges that residents in LTC facilities face in using medical and non-medical cannabis, as well as the potential need for both education and policy reform to better support HCPs in providing appropriate, safe, and person-centred care of LTC residents. In addition, the collection of both quantitative and qualitative data allowed triangulation during the data analysis and helped improved the rigor of the findings [ 61 ]. Recruitment and data collection for this study also occurred during the height of the COVID-19 pandemic. Therefore, the response rate was lower than desired and there was limited diversity among study participants with regards health profession designation. However, the proportion of physicians, nurses, pharmacists, and other allied health professions reflected the overall staff composition of the LTC facility.

Implications for future research

Beyond the policy and practice implications discussed earlier, the study findings also point to the urgent need for research focused on cannabis use among populations commonly found within LTC settings. The lack of evidence regarding the potential health effects of cannabis in the management of diseases such as dementia, arthritis, Parkinson’s, traumatic brain injury, and multiple sclerosis led many of the HCPs interviewed to be hesitant about authorizing and supervising cannabis use for LTC residents living with these conditions. While there is a growing number of studies being undertaken focused on medical cannabis, many are limited by their sample size and study design. It is only through high-quality clinical trials that evaluate the efficacy and safety of medical cannabis that a change in practice will occur.

Future medical cannabis research must also be developed in a manner that is inclusive of older adults and those living in LTC. The exclusion of such populations from clinical research has been previously identified as problematic [ 62 ], resulting in research findings that lack generalizability and pose challenges in determining the applicability of research to older adults who may be living with numerous co-morbidities and using multiple medications. While the inclusion of older adults in medical cannabis clinical trials may be more methodologically and ethically challenging, it will lead to evidence that will inform both future policies and practices.

Lastly, our case study offers insight into the reality and challenges of cannabis use by residents of one LTC facility. Additional research across different jurisdictions is needed to explore how LTC settings are addressing cannabis use and to learn from their experiences. We encourage the continued use of mixed methods study designs to ensure the experiences and perspectives of residents, family members and HCPs are captured alongside administrative data related to medical and non-medical cannabis use.

With the legalization of medical and non-medical cannabis in jurisdictions around the world, LTC facilities will be obligated to develop policies, procedures and healthcare services that are able to accommodate residents’ use of cannabis in a respectful and evidence-informed manner. Balancing the safety concerns against the potential therapeutic value of cannabis, as well as considering residents’ autonomy and the home-like environment of LTC, will be important considerations in how cannabis use is addressed and regulated. Our case study highlights the lack of knowledge, inequities, and stigma that continue to surround cannabis in LTC. There is an urgent need for research that not only explores the potential risks and benefits of cannabis, but also informs the development of more nuanced and equitable policies and education resources that will support reasonable and informed access to medical and non-medical cannabis for older adults and others living in LTC.

Data availability

The datasets generated and analysed during the current study are not publicly available due to the small sample size drawn from one health care facility but are available from the corresponding author on reasonable request.

Abbreviations

Cannabidiol

Healthcare provider

Long–term care

Tetrahydrocannabinol

Licensed Producer

Government of Canada. Cannabis Act (S.C. 2018, c.16). 2018. http://canlii.ca/t/5392s retrieved on 2019-10-07.

Sandhu HS, Anderson LN, Busse JW. Characteristics of canadians likely to try or increase cannabis use following legalization for nonmedical purposes: a cross-sectional study. CMAJ Open. 2019;7(2):E399–404.

Article   PubMed   PubMed Central   Google Scholar  

Statistics Canada. National Cannabis Survey, third quarter 2019. https://www150.statcan.gc.ca/n1/daily-quotidien/191030/dq191030a-eng.htm

Statistics Canada. Research to Insights: Cannabis in Canada. 2023. https://www150.statcan.gc.ca/n1/pub/11-631-x/11-631-x2023006-eng.htm

Lau N, Sales P, Averill S, Murphy F, Sato SO, Murphy S. A safer alternative: cannabis substitution as harm reduction. Drug Alcohol Rev. 2015;34(6):654–9.

Bobitt J, Qualls SH, Schuchman M, Wickersham R, Lum HD, Arora K, et al. Qualitative analysis of cannabis use among older adults in Colorado. Drugs Aging. 2019;36(7):655–66.

Article   PubMed   Google Scholar  

Reynolds IR, Fixen DR, Parnes BL, Lum HD, Shanbhag P, Church S, et al. Characteristics and patterns of marijuana use in community-dwelling older adults. J Am Geriatr Soc. 2018;66(11):2167–71.

Baumbusch J, Sloan Yip I. Exploring new use of cannabis among older adults. Clin Gerontol. 2021;44(1):25–31.

Tumati S, Lanctôt KL, Wang RD, Li A, Davis A, Herrmann N. Medical cannabis use among older adults in Canada: self-reported data on types and amount used, and perceived effects. Drugs Aging. 2022;39(2):153–63.

Government of Canada. Data on cannabis for medical purposes. 2022. https://www.canada.ca/en/health-canada/services/drugs-medication/cannabis/research-data/medical-purpose.html

Cooper ZD, Abrams DI, Gust S, Salicrup A, Throckmorton DC. Challenges for clinical cannabis and cannabinoid research in the United States. J Natl Cancer Inst Monogr. 2021;2021(58):114–22.

Piomelli D, Solomon R, Abrams D, Balla A, Grant I, Marcotte T, et al. Regulatory barriers to research on cannabis and cannabinoids: a proposed path forward. Cannabis Cannabinoid Res. 2019;4(1):21–32.

O’Brien M, McDougall JJ. Cannabis and joints: scientific evidence for the alleviation of osteoarthritis pain by cannabinoids. Curr Opin Pharmacol. 2018;40:104–9.

Babson KA, Sottile J, Morabito D. Cannabis, cannabinoids, and sleep: a review of the literature. Curr Psychiatry Rep. 2017;19(4):23.

Hillen JB, Soulsby N, Alderman C, Caughey GE. Safety and effectiveness of cannabinoids for the treatment of neuropsychiatric symptoms in dementia: a systematic review. Ther Adv Drug Saf. 2019;10:2042098619846993.

Chagas MHN, Zuardi AW, Tumas V, Pena-Pereira MA, Sobreira ET, Bergamaschi MM, et al. Effects of cannabidiol in the treatment of patients with Parkinson’s disease: an exploratory double-blind trial. J Psychopharmacol. 2014;28(11):1088–98.

Shohet A, Khlebtovsky A, Roizen N, Roditi Y, Djaldetti R. Effect of medical cannabis on thermal quantitative measurements of pain in patients with Parkinson’s disease. Eur J Pain. 2017;21(3):486–93.

Article   CAS   PubMed   Google Scholar  

Herrmann N, Ruthirakuhan M, Gallagher D, Verhoeff NPLG, Kiss A, Black SE, et al. Randomized placebo-controlled trial of nabilone for agitation in Alzheimer’s disease. Am J Geriatr Psychiatry. 2019;27(11):1161–73.

Shelef A, Barak Y, Berger U, Paleacu D, Tadger S, Plopsky I, et al. Safety and efficacy of medical cannabis oil for behavioral and psychological symptoms of dementia: an open label, add-on, pilot study. J Alzheimer’s Dis. 2016;51(1):15–9.

Article   CAS   Google Scholar  

Volicer L, Stelly M, Morris J, Mclaughlin J, Volicer BJ. Effects of dronabinol on anorexia and disturbed behavior in patients with Alzheimer’s disease. Int J Geriatr Psychiatry. 1997;12(9):913–9.

Cyr C, Arboleda MF, Aggarwal SK, Balneaves LG, Daeninck P, Néron A, et al. Cannabis in palliative care: current challenges and practical recommendations. Ann Palliat Med. 2018;7(4):463–77.

Pooyania S, Ethans K, Szturm T, Casey A, Perry D. A randomized, double-blinded, crossover pilot study assessing the effect of nabilone on spasticity in persons with spinal cord injury. Arch Phys Med Rehabil. 2010;91(5):703–7.

Wilsey B, Marcotte TD, Deutsch R, Zhao H, Prasad H, Phan A. An exploratory human laboratory experiment evaluating vaporized cannabis in the treatment of neuropathic pain from spinal cord injury and disease. J Pain. 2016;17(9):982–1000.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Grenier K, Ponnambalam F, Lee D, Lauwers R, Bhalerao S. Cannabis in the treatment of traumatic brain injury: a primer for clinicians. Can J Neurol Sci. 2019;47(1):11–7.

Minerbi A, Hauser W, Fitzcharles MA. Medical cannabis for older patients. Drugs Aging. 2019;36(1):39–51.

MacCallum CA, Russo EB. Practical considerations in medical cannabis administration and dosing. Eur J Int Med. 2018;49:12–9.

Bertram JR, Porath A, Seitz D, Kalant H, Krishnamoorthy A, Nickerson J, et al. Canadian guidelines on cannabis use disorder among older adults. Can Geriatr J. 2020;23(1):135–42.

Banerjee S. Multimorbidity–older adults need health care that can count past one. Lancet. 2015;385(9968):587–9.

Bom J, Bakx P, Rellstab S. Well-being right before and after a permanent nursing home admission. Health Econ. 2022;31(12):2558–74.

Calkins M, Brush J. Honoring individual choice in long-term residential communities when it involves risk: a person-centered approach. J Gerontol Nurs. 2016;42(8):12–7.

Yin R. Case study research and applications: design and methods. 6th ed. Thousand Oaks, CA: Sage; 2018.

Google Scholar  

Sandelowski M. Whatever happened to qualitative description? Res Nurs Health. 2000;23(4):334–40.

Balneaves LG, Alraja A, Ziemianski D, McCuaig F, Ware M. A national needs assessment of Canadian nurse practitioners regarding cannabis for therapeutic purposes. Cannabis Cannabinoid Res. 2018;3(1):66–73.

Ziemianski D, Capler R, Tekanoff R, Lacasse A, Luconi F, Ware MA. Cannabis in medicine: a national educational needs assessment among Canadian physicians. BMC Med Educ. 2015;15:50–2.

Article   Google Scholar  

Balneaves LG, Alraja AA. Guarding their practice: a descriptive study of Canadian nursing policies and education related to medical cannabis. BMC Nurs. 2019;18(1):66.

Fox RD. Revisiting discrepancy analysis in continuing medical education: a conceptual model 1983. J Contin Health Prof. 2011;31(1):71–6.

Hsieh HF, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res. 2005;15(9):1277–88.

College of Registered Nurses of Manitoba. Medical cannabis: Guidelines for Manitoba nurses. 2019. https://www.crnm.mb.ca/uploads/document/document_file_247.pdf?t=1549645011

College of Registered Nurses of Manitoba. Practice direction: RN(NP) authorization of medical cannabis. 2018. https://www.crnm.mb.ca/uploads/document/document_file_252.pdf?t=1538755351

The College of Physicians & Surgeons of Manitoba. Standard of practice: Cannabis for medical purpose. 2020. https://cpsm.mb.ca/assets/Standards of Practice/Standard of Practice Authorizing Cannabis for Medical Purposes.pdf.

Winnipeg Regional Health Authority. Smoke-Free Policy. 2014. https://wrha.mb.ca/files/wrha-policy-10-00-010.pdf

Government of Canada. Cannabis regulations (SOR/2018 – 144) [. 2018. https://laws-lois.justice.gc.ca/eng/Regulations/SOR-2018-144/index.html

Goffman E. Asylums: essays on the social situations of mental patients and other inmates. Oxford, England: Doubleday (Anchor); 1961.

White-Chu EF, Graves WJ, Godfrey SM, Bonner A, Sloane P. Beyond the medical model: the culture change revolution in long-term care. J Am Med Dir Assoc. 2009;10(6):370–8.

Chivers S. Make mine a double. In: Armstrong P, Daly T, editors. Exercising choice in long-term residential care. Montreal, QC: RR Donnelley; 2017. pp. 55–8.

Woolford MH, de Lacy-Vawdon C, Bugeja L, Weller C, Ibrahim JE. Applying dignity of risk principles to improve quality of life for vulnerable persons. Int J Geriatr Psychiatry. 2020;35(1):122–30.

Schultz ASH, Finegan B, Nykiforuk CIJ, Kvern MA. A qualitative investigation of smoke-free policies on hospital property. CMAJ. 2011;183(18):2085–6.

De Graaf L, Janssen M, Roelofs T, Luijkx K. Substance use and misuse of older adults living in residential care facilities: a scoping review from a person-centred care approach. Ageing Soc. 2021;43(6):1–27.

Adler G, Greeman M, Parker H, Kuskowski M. Self-determination and residents who smoke. J Social Work Long-Term Care. 2002;1(4):19–30.

Lau N, Sales P, Averill S, Murphy F, Sato SO, Murphy S. Responsible and controlled use: older cannabis users and harm reduction. Int J Drug Policy. 2015;26(8):709–18.

Clobes TA, Palmier LA, Gagnon M, Klaiman C, Arellano M. The impact of education on attitudes toward medical cannabis. PEC Innov. 2022;1:100009.

Croker JA, Bobitt J, Sanders S, Arora K, Mueller K, Kaskie B. Cannabis and end-of-life care: a snapshot of hospice planning and experiences among Illinois medical cannabis patients with a terminal diagnosis. Am J Hosp Palliat Med. 2022;39(3):345–52.

Hachem Y, Abdallah SJ, Rueda S, Wiese JL, Mehra K, Rup J, et al. Healthcare practitioner perceptions on barriers impacting cannabis prescribing practices. BMC Complement Med Ther. 2022;22(1):1–12.

Hope J, Schoonhoven L, Griffiths P, Gould L, Bridges J. I’ll put up with things for a long time before I need to call anybody: face work, the Total Institution and the perpetuation of care inequalities. Sociol Health Illn. 2022;44(2):469–87.

Williams AR. Ethical dilemmas in counseling older adults on cannabis use: less science, more quandaries. Generations J. 2020;44(4):1–5.

Skliamis K, Benschop A, Korf DJ. Cannabis users and stigma: a comparison of users from European countries with different cannabis policies. Eur J Crimin. 2022;19(6):1483–500.

Troup LJ, Erridge S, Ciesluk B, Sodergren MH. Perceived stigma of patients undergoing treatment with cannabis-based medicinal products. Int J Env Res Public Health. 2022;19(12).

Evanoff AB, Quan T, Dufault C, Awad M, Bierut LJ. Physicians-in-training are not prepared to prescribe medical marijuana. Drug Alcohol Depend. 2017;180:151–5.

Canadian Coalition for Seniors’ Mental Health. Cannabis and older adults. https://ccsmh.ca/cannabis-and-older-adults-project/

Grossi A, Holmes A, Ibrahim JE. Use of alcohol in long term care settings: a comparative analysis of personal choice, public health advice and the law. J Am Med Dir Assoc. 2021;22(1):9–e141.

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach. BMC Med Res Methodol. 2011;11:100.

Crome P, Lally F, Cherubini A, Oristrell J, Beswick AD, Clarfield AM, et al. Exclusion of older people from clinical trials: professional views from nine European countries participating in the PREDICT study. Drugs Aging. 2011;28(8):667–77.

Download references

Acknowledgements

The authors would like to thank the healthcare professionals that graciously took the time to share their thoughts about cannabis use in long-term care settings. In addition, Ms. Sina Barkman, Chief Human Resources Officer, Riverview Health Centre, helped the research team navigate the complexity of conducting research in long-term care settings during the COVID-19 pandemic.

Funding for this study was received from the Riverview Health Centre Foundation.

Author information

Authors and affiliations.

College of Nursing, University of Manitoba, Winnipeg, MB, Canada

Lynda G. Balneaves, Abeer A. Alraja, Genevieve Thompson, Jamie L. Penner & Daniella Scerbo

Max Rady College of Medicine, University of Manitoba, Winnipeg, MB, Canada

Philip St. John

Riverview Health Centre, Winnipeg, MB, Canada

Joanne van Dyck

College of Nursing, Rady Faculty of Health Sciences, University of Manitoba, 89 Curry Place, Winnipeg, MB, R3T 2N2, Canada

Lynda G. Balneaves

You can also search for this author in PubMed   Google Scholar

Contributions

“L.G.B, G.T, J.P and P.StJ. conceptualised the study. A.A.A. and D.S. engaged in recruitment and data collection activities. L.G.B. and A.A.A. analysed and interpreted the quantitative and qualitative data and developed a first draft of the manuscript, with assistance from G.T. All authors read and approved the final manuscript.”

Corresponding author

Correspondence to Lynda G. Balneaves .

Ethics declarations

Ethics approval and consent to participate.

Ethical approval for the study was obtained from the University of Manitoba Research Ethics Board (R1-2021:011 (HS24693)) and was approved by the Riverview Health Centre Research Committee. Implied consent was received from participants who completed the survey and written informed consent was obtained from all participants who completed an interview. We confirm that all methods were performed in accordance with the relevant ethical guidelines and regulations, (i.e., Tri-Council Policy Statement).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Balneaves, L.G., Alraja, A.A., Thompson, G. et al. Cannabis use in a Canadian long-term care facility: a case study. BMC Geriatr 24 , 467 (2024). https://doi.org/10.1186/s12877-024-05074-2

Download citation

Received : 11 July 2023

Accepted : 13 May 2024

Published : 29 May 2024

DOI : https://doi.org/10.1186/s12877-024-05074-2

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Medical cannabis
• Non-medical cannabis
• Long-term care
• Residential care
• Older adults

BMC Geriatrics

ISSN: 1471-2318

• Submission enquiries: [email protected]
• General enquiries: [email protected]

• Open access
• Published: 03 June 2024

Understanding the integration of artificial intelligence in healthcare organisations and systems through the NASSS framework: a qualitative study in a leading Canadian academic centre

• Hassane Alami 1 , 2 , 3 , 4 ,
• Pascale Lehoux 1 , 2 ,
• Chrysanthi Papoutsi 4 ,
• Sara E. Shaw 4 ,
• Richard Fleet 5 , 6 &
• Jean-Paul Fortin 5 , 6  

BMC Health Services Research volume  24 , Article number:  701 ( 2024 ) Cite this article

241 Accesses

Metrics details

Artificial intelligence (AI) technologies are expected to “revolutionise” healthcare. However, despite their promises, their integration within healthcare organisations and systems remains limited. The objective of this study is to explore and understand the systemic challenges and implications of their integration in a leading Canadian academic hospital.

Semi-structured interviews were conducted with 29 stakeholders concerned by the integration of a large set of AI technologies within the organisation (e.g., managers, clinicians, researchers, patients, technology providers). Data were collected and analysed using the Non-Adoption, Abandonment, Scale-up, Spread, Sustainability (NASSS) framework.

Among enabling factors and conditions, our findings highlight: a supportive organisational culture and leadership leading to a coherent organisational innovation narrative; mutual trust and transparent communication between senior management and frontline teams; the presence of champions, translators, and boundary spanners for AI able to build bridges and trust; and the capacity to attract technical and clinical talents and expertise.

Constraints and barriers include: contrasting definitions of the value of AI technologies and ways to measure such value; lack of real-life and context-based evidence; varying patients’ digital and health literacy capacities; misalignments between organisational dynamics, clinical and administrative processes, infrastructures, and AI technologies; lack of funding mechanisms covering the implementation, adaptation, and expertise required; challenges arising from practice change, new expertise development, and professional identities; lack of official professional, reimbursement, and insurance guidelines; lack of pre- and post-market approval legal and governance frameworks; diversity of the business and financing models for AI technologies; and misalignments between investors’ priorities and the needs and expectations of healthcare organisations and systems.

Thanks to the multidimensional NASSS framework, this study provides original insights and a detailed learning base for analysing AI technologies in healthcare from a thorough socio-technical perspective. Our findings highlight the importance of considering the complexity characterising healthcare organisations and systems in current efforts to introduce AI technologies within clinical routines. This study adds to the existing literature and can inform decision-making towards a judicious, responsible, and sustainable integration of these technologies in healthcare organisations and systems.

Peer Review reports

According to the Organisation for Economic Co-operation and Development (OECD), artificial intelligence (AI) refers to “a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. Different AI systems vary in their levels of autonomy and adaptiveness after deployment” [ 1 ]. Unlike conventional software, many AI systems indeed have learning capabilities and self-correcting error mechanisms that allow them to improve the accuracy of their results based on the feedback they receive [ 1 , 2 ].

There are many application areas for AI in healthcare, for example: diagnosis, treatment, monitoring (e.g., chronic diseases), and patient compliance [ 3 ]. In certain experimental settings, AI technologies have been shown to be more effective than clinicians (e.g., diagnostic accuracy, more personalised diagnostics) [ 4 , 5 , 6 , 7 ]. Several have already been approved for clinical use in real-world care and services [ 8 ]. These technologies are seen as a lever for evidence-based clinical decision-making and practice and for value-based care and services [ 9 , 10 , 11 ]. Research indicates their potential to contribute to better monitoring, detection, and diagnosis of diseases, to the reduction of clinical risk, and to the discovery of new drugs and treatments [ 4 , 9 , 12 , 13 , 14 ]. The use of AI technologies could help to reduce diagnostic and therapeutic errors [ 2 ], contribute to the optimisation of clinicians’ work, and help reduce waiting times by reorganising clinical and administrative tasks, and supporting coordination [ 10 , 14 ]. Many scholars also argue that AI technologies could contribute to reducing healthcare costs by decreasing hospital (re)admissions, medical visits, and treatments [ 14 , 15 ].

A predominant and enthusiastic discourse in the academic literature and media reports is that AI technologies will revolutionise and radically change healthcare in the coming years [ 2 , 16 , 17 , 18 ]. There is an explosion of AI offerings in the market [ 19 ]. In 2018, the global AI market in healthcare was valued at around US$1.4 billion and is expected to grow to US$17.8 billion by 2025 [ 14 ]. In North America, the market for AI in healthcare had exceeded US$1.15 billion by 2020 [ 14 ]. In this context, healthcare organisations and systems are increasingly being solicited (or even pressured) to integrate these technologies, even when evidence of real clinical added value is lacking and many social and ethical as well as adoption, routinisation, and practical issues remain to be clarified [ 16 , 18 ]. According to Topol (2019), who reviewed healthcare workforce readiness for a digital future: “Despite all the promises of AI technology, there are formidable obstacles and pitfalls. The state of AI hype has far exceeded the state of AI science, especially when it pertains to validation and readiness for implementation in patient care” [ 4 ]. Liu et al. (2019) reported that few published studies on AI had results from real-world healthcare contexts [ 20 ]. These findings were corroborated during the COVID-19 pandemic [ 21 , 22 , 23 ]. Wynants et al. (2020) identified 232 AI models for prediction or diagnosis of COVID-19, none of which were appropriate for clinical use and only two showing potential for future clinical use [ 24 ]. Roberts et al. (2021) analysed 415 AI models for COVID-19 detection and concluded similarly [ 25 ].

This gap between the promise and reality of AI technologies in healthcare could be explained by the fact that efforts have historically focused on technology development, market penetration, and commercialisation. Limited work has been done to look specifically at the conditions and factors necessary for the integration of AI technologies into routine clinical care [ 14 , 17 ]. While technical problems (e.g., performance, unreliability) have been regularly put forward as a reason for the difficulties of integrating these technologies into healthcare organisations and systems [ 26 ], they explain only a small part of the problem. Broader socio-technical conditions and factors rather explain many of these difficulties [ 18 , 26 ].

The social scientific literature on health innovations has shown that the introduction of technologies into healthcare organisations and systems is a complex phenomenon [ 27 ]. This is particularly true for many AI technologies, which are sometimes described in the medical literature as disruptive innovation due to their evolving and autonomous nature [ 28 , 29 , 30 ]. Their implementation and use may require rethinking and/or redesigning existing governance frameworks and care models as well as new clinical, organisational, regulatory, and technological processes, business models, capabilities, and skills [ 18 ]. These changes involve, and impact on, a variety of stakeholders who may have divergent or even antagonistic expectations, goals, and visions towards technology [ 31 , 32 , 33 , 34 , 35 , 36 ].

To contribute to addressing current knowledge gaps, the goal of this study is to explore and understand the challenges of integrating AI technologies within a large academic hospital in Canada (referred to as “the City hospital”). We aim to answer two questions:

How do multiple interacting influences facilitate and constrain the integration of AI technologies within the City hospital?

What learning can we derive for policy and practice for better integration of AI technologies in healthcare organisations and systems?

The study is not limited to a specific AI technology or clinical area but encompasses all 87 AI technology-based initiatives developed and used to varying extent in this hospital. Where relevant, we specify the type of AI involved to contextualise the factors, conditions, or challenges described.

Theoretical framework

To make sense of the complexity underpinning the AI integration efforts in the City hospital, we used an adapted version of the Nonadoption, Abandonment, and challenges to Scale-up, Spread, and Sustainability (NASSS) framework developed by Greenhalgh et al. [ 27 ], which supports an exhaustive sociotechnical approach to health innovation. Following this adapted version, we present the seven dimensions of the framework in a different order from the original version in order to make sense of the narrative within the organisation studied, thereby covering: 1) the organisation; 2) the condition(s) or illness; 3) the technology or technologies; 4) the value proposition; 5) the adopter system(s) (e.g., staff, patient, caregivers); 6) embedding and adaptation over time; and 7) the wider system [ 27 ]. See Fig.  1 for a description of the seven dimensions.

An adapted version of the NASSS framework (adapted from Greenhalgh et al. [ 27 ])

There were many reasons for adopting the NASSS framework over other frameworks. First, it stems from a hermeneutic systematic review, supported by empirical case studies of technology implementation in healthcare [ 27 , 37 ], and its key strength lies in its synthesis of 28 technology implementation frameworks, that is informed by several theoretical perspectives [ 27 , 37 ]. Second, it was developed to fill an important gap “on technology implementation—specifically, to address not just adoption but also nonadoption and abandonment of technologies and the challenges associated with moving from a local demonstration project to one that is fully mainstreamed and part of business as usual locally (scale-up), transferable to new settings (spread), and maintained long term through adaptation to context over time (sustainability)” [ 27 , 37 ]. Third, in contrast to the deterministic logic of many existing frameworks, the NASSS framework is characterised by its dynamic aspect, particularly in terms of interaction and adaptation over time. Indeed, a large part of the literature in the field has a tendency to “assume that the issues to be addressed [are] simple or complicated (hence knowable, predictable, and controllable) rather than complex (that is, inherently not knowable or predictable but dynamic and emergent)” [ 27 , 37 ]. Therefore, major failures of large and ambitious technology projects may be underestimated and their complexity for healthcare organisations and systems tossed away [ 27 , 37 ]. Fourth, whereas decision-makers and technology promoters as well as a part of the specialised literature often adopt a linear, predictable, and rational vision of change [ 38 ], the sociotechnical stance of the NASSS framework highlights the importance of examining how technology and the changes associated with it are perceived, interpreted, negotiated, and enacted by individuals and groups [ 33 , 39 , 40 ]. The same applies to AI technologies that may require transformation and/or redesign of services, a profound reconfiguration of clinical and organisational practices, and challenges to professional identities and practices [ 17 , 33 , 40 ]. Certain types of AI technologies also evolve autonomously over time – a particular characteristic that can be explicitly conceptualised through the NASSS framework [ 27 , 41 ]. Overall, the NASSS framework was developed to be used reflectively, to stimulate conversation and generate ideas, which is one of our study’s aspirations.

We conducted a qualitative study within the City hospital (Quebec, Canada) [ 42 ]. The latter had initiated several projects to integrate AI technologies in its care and service offer. Decision-makers and managers expressed a need for (independent) insights into the micro-, meso-, and macro-level systemic implications of the integration of these technologies within the organisation [ 43 ].

Presentation of the organisation

The City hospital is one of the largest academic hospitals in Canada. It offers specialised and sub-specialised services to adult patients. It treats around 500,000 patients annually. It employs over 14,000 people. It also houses one of the largest medical research centres in the country, with an academic mission to produce and disseminate knowledge and research results. It also presents itself as an organisation with state-of-the-art facilities and equipment. It has been ranked by the U.S-based magazine Newsweek as one of the world’s top 250 Best Smart Hospitals for 2021. It hosts one of the largest annual digital innovation events in Canada.

At the time of the study, the City hospital had over 115 digital health projects (Table  1 ), with 87 of these involving AI. Around 95% (≈82/87) of the AI technologies were in the development/experimentation or early implementation phase. Only four were integrated into services. Approximately 72% (≈62/87) of the AI technologies identified within the organisation were for the diagnosis, treatment and/or monitoring of complex chronic or acute conditions: cancers, neurological (e.g., epilepsy), and ocular conditions.

Recruitment

We identified a purposive sample of key stakeholders, with the aim of capturing diverse perspectives and experiences [ 44 ]. We conducted internet searches and consulted reports and documents produced by the City hospital to identify potential participants, who were drawn from distinct roles and varied levels of involvement in the development, implementation, and use of AI technologies.

A personalised invitation email was sent to each potential participant explaining the project and why they were invited to participate. Two reminders were sent in case of non-response. Respondents were invited to indicate other participants (i.e., snowballing) [ 45 ]. This resulted in a sample of senior and middle managers/decision-makers, clinicians (e.g., physicians, nurses), clinicians/informaticians/researchers, technology assessment specialists, procurement specialists, lawyers, patients, and technology providers. Patients were identified through patient partners (volunteers) collaborating with the City hospital. Of the 42 invitations sent, 29 people agreed to participate. Table 2 shows participant profiles, many of whom cumulated multiple professional and/or experiential backgrounds.

Data collection

Between March and July 2021, the first author (HA) conducted 29 interviews in French (27) and English (2), using the Zoom™ videoconferencing platform (interviews lasted 30–90 min). Prior to the interview, a consent form summarising the objectives of the project was shared. Interviews were audio recorded with the permission of the participant and transcribed verbatim by HA. The questions were formulated according to the dimensions of the NASSS framework and informed by documents shared by the City hospital (e.g., list of projects and technologies). HA first tested the qualitative interview guide with two respondents prior to the start of the study. No major revision of the initial version of the guide was required. He took notes during and after the interviews and subsequently used them to contextualise the analyses. The interview guide slightly evolved depending on the participants’ responses as new information emerged. By adapting the interview guide, we were able to capture both expected and unanticipated tensions and practical challenges, grounding the discussion in participant experiences to avoid vague or abstract responses. Given that the same person (HA) co-developed the guide and conducted the interviews in French and English, this minimised the risk of variability that could arise from having different people collecting data in different languages. Interview data and document analysis, alongside our knowledge of the context (team members have been involved in various research and evaluation projects on digital technologies and innovations in Quebec and Canadian healthcare organisations and systems for several years) guided triangulation of data sources [ 46 ].

Data analysis

Data were coded and analysed with Dedoose™ software. HA performed the first round of analysis and developed a preliminary coding scheme. In the second round, the scheme was refined, challenged, and discussed iteratively by the second author (PL) [ 43 ]. We conducted a deductive-inductive thematic analysis. The deductive analysis was guided by the NASSS framework (Fig.  1 ) [ 27 ]. Drawing on its seven dimensions, we created codes to capture the micro, meso and macro-level challenges and implications associated with the integration of AI technologies in the City hospital. The inductive analysis aimed to capture emerging themes not covered by the framework [ 44 , 47 ]. After agreeing on the different themes identified, we concluded that none required the addition of new dimensions, as all identified themes fitted within the NASSS framework. Data saturation was reached for the themes and observations reported in the findings. Given the importance of context in the NASSS framework, we sought to understand and clarify the contextual elements where respondents had different views or judgements. We decided not to disclose certain details either because the participants requested it or to ensure confidentiality. However, this information was useful to contextualise and better understand other findings and events. Our findings are illustrated with participant quotes organised around key themes of the NASSS framework (translated from French to English when needed) (Table 5 in Appendix ). The letter P used in quotes refers to “participant”, followed by numbers designating the order in which interviews were transcribed.

Findings are reported as a narrative account [ 48 ]. This is critical in allowing us to capture the complexity of the subject, the explanatory and interpretative dimensions, and the varied stories and perspectives gained from participants in making sense of the issues around the adoption of AI technologies.

We present the findings according to the seven dimensions of the adapted version of the NASSS framework (Fig.  1 ). To ensure fluidity in the presentation of the findings, the participant roles are used as a general category to help the reader identify certain tensions between the viewpoints and perspectives expressed. In this sense, there is no pretension of generalisation given the small number of respondents in each category. The analyses are intended primarily to provide high-level dynamics related to each dimension of the NASSS framework and not those specific to the types of AI discussed.

The organisation

For the technology providers we interviewed, the City hospital has several internationally renowned clinicians, both in the clinical field and in the use of AI. Several managers and clinicians also reported that senior management is known to value and encourage technological innovation, which has led to the creation of a “data lake” that allows the integration of data from different clinical systems (e.g., clinical records, laboratories, vital signs, imaging), which is a major asset for the development and/or validation of certain AI technologies. According to technology providers, access to the specialised expertise of clinicians who know the data is as important as access to the data itself. These clinicians play an important role as a trusted guarantor (or legitimising authority) for AI with other clinicians, decision-makers/managers, patients, and citizens. In the words of one clinician-manager, the relationship and communication between these clinicians and the City hospital’s senior management is generally perceived as positive. He pointed out that this synergy helps to mitigate some of the issues and conflicting visions and expectations of AI.

According to a technology provider, because of the characteristics of Quebec’s single-payer and universal health system, the City hospital allows for holistic management of patients suffering from several pathologies or requiring different care and treatments. He added that this unique advantage enables the development of AI technologies with a broad spectrum of action (i.e., compared to those developed in contexts where care is fragmented between different hospitals and/or clinics). Despite this asset, there is a broad agreement among the interviewees that the City hospital is characterised by significant complexity that has the potential to impact its ability to realise the value promise of AI technologies.

Use of AI technologies in the City hospital necessarily involves different departments, committees, and stakeholders (e.g., Information technology -IT- department, procurement department, project office, professional services department). According to several managers, clinicians, and industry providers, the roles and mandates for these different groups and stakeholders are not always clear. Coordination and communication between teams and/or departments are sometimes difficult or non-existent. According to a manager, this results in confusion and tension about expectations, visions, and responsibilities. He pointed out that difficulties experienced by some AI projects were due to a department or committee not being engaged at the right time (e.g., as a result of legal and/or procurement framework, Cloud storage space, professional services department). For managers and clinicians, a horizontal body should have been established to coordinate and ensure coherence and communication between the different initiatives and stakeholders, with the aim enabling mutual effort, coordination, and accountability. For another manager, by ensuring an initial screening of technologies proposed by industry, such a body would avoid the influx of useless technologies to clinical teams and associated time and resource costs.

Both industry and organisation respondents agree that the City hospital doesn’t always have the capacity to meet the initial and recurring costs and investments required for the successful integration of AI. To overcome this funding problem, at least partly, an interviewee told us that the organisation is obliged to open its doors to industry for co-development, or as a testing ground, of AI technologies. This sub-contracting allows the City hospital to benefit from a free user licence for a fixed period or for life. However, it was reported that this partnership contracts model (e.g., co-development or serving as a testing ground for the industry) is likely to lock the organisation into a technology-centric logic, with no real margin of manoeuvre to choose technologies that really meet its needs. There are multiple projects under this partnership model within the organisation. Several technologies could simply end up being only partially developed because the technology provider has withdrawn, or the technology was abandoned. Within such a context, several managers and clinicians recognise that it is difficult to create a real organising vision that supports and enables AI within the City hospital.

According to managers and clinicians, these partnerships with industry imply an over-solicitation of the clinical teams as, in addition to their clinical and administrative work, they must dedicate time to testing and experimenting with the various technologies presented by the technology providers. In this regard, several organisation and industry respondents pointed out that clinicians in the City hospital are not valued or remunerated for their contribution to the development and/or experimentation of technologies. It is not uncommon for some clinicians to feel that industry benefits from their clinical expertise without any real return on investment for them. Technology providers interviewed refuted this point. For them, the difficulties in integrating their technologies into the organisation are essentially due to the opposition of some influential clinician-researchers who are themselves developing in-house similar technologies. In the words of one industry respondent, this is a conflict of interest and unfair competition. Nonetheless, technology providers support the importance of creating incentives to encourage clinicians to collaborate with industry. On their part, several clinicians and managers consider that the organisation should value in-house initiatives more highly because they emerge from the needs and expectations of the field. However, there is agreement that the organisation does not have the financial and human resources to support these initiatives. In addition, according to one manager, as a public entity, the City hospital does not have a mandate to develop and/or commercialise technologies. At some point, a company would have to be involved to ensure commercialisation.

Managers, clinicians, and industry acknowledge that the nature and extent of the changes associated with the integration of AI within the organisation are still largely unknown. For example, it is very difficult to assess financial implications over time. Two managers reported that the City hospital paid an additional CA$20,000 to CA$30,000/year for the storage and management of its data. This cost was not initially budgeted but subsequently required by the Cloud service provider who had estimated the size of the data. According to the same respondents, such “little surprises” could lead to some technologies being abandoned along the way, even if they are clinically relevant, either because the organisation cannot afford the costs or the Quebec’s Ministry of Health and Social Services (known as MSSS) refuses to cover them.

Both industry and organisation respondents reported that many AI technologies require access, sometimes in quasi-real time and without human intervention, to large amounts of data of various types. Unanimously, interviewees acknowledge that the organisation’s rules and procedures do not currently allow this (or very barely). Technology providers are calling for easier access to data. However, on the organisational side, several managers consider that such rules and procedures need to be further strengthened. Some of them emphasised the importance of having a Specialist digital lawyer to ensure that these issues are addressed when contracts are signed. They also add that there should also be a Chief data officer to ensure adequate and coherent governance between the various initiatives that involve clinical-administrative data.

The condition(s) or illnesses

Most of the AI technologies identified (72% ≈62/87) within the City hospital are directed at the diagnosis, treatment and/or monitoring of complex chronic or acute conditions (e.g., cancers, neurological, ocular conditions) (Table  1 ). These conditions generally require ongoing or periodic support and monitoring over long periods of time with significant implications for patients and their families, and for the financial sustainability of the healthcare system. They also require complex, individualised, and evolving service models to continue to meet the needs of patients and their families. Several interviewees underscore that the use of AI could reduce waiting times and the costs of managing these pathologies. For a technology provider, these technologies are also expected to help identify new patterns and digital biomarkers that would facilitate the diagnosis and treatment of poorly characterised and/or unpredictable diseases.

For several respondents, this focus on specific diseases is partly due to the nature of the technologies available on the market. These technologies are addressing pathologies mainly through image analysis and/or signal quantification. This makes them more easily measurable, therefore more attractive to technology developers seeking rapid market access.

The technology or technologies

There are diverging perceptions between clinicians, managers, technology providers, and patients on what makes AI attractive, reliable, and mature enough for clinical use and/or interoperable with existing systems.

According to a manager, some of the technologies proposed to the City hospital under the label “AI” are, in fact, expert systems with advanced calculation software. Branding the products in this way is a strategy used by some companies to attract investment and/or obtain contracts. While an AI designation increases the market value of the technology, it does not necessarily increase the clinical value. For another manager, this labelling of AI products is also partly due to the organisation’s pressure on technology providers to integrate AI. This is a significant step for technology companies as, compared to traditional software, AI technologies require specific regulatory requirements, technical infrastructure, expertise, and resources.

Several participants raised emerging security issues specific to AI. This is not only about the security of the technology and infrastructure, but also about the security of the algorithm itself. The latter could be hacked and modified, which can have a direct clinical impact on the patient. According to a manager, being able to recombine data from different sources, AI technologies could easily re-identify individuals. On their side, technology providers pointed out that these security issues are mainly due to the City hospital’s obsolete systems and technology infrastructure. They underscore how their technologies conform to the best security and quality standards and norms on the market, and that unlike public organisations they have the best IT expertise. An industry respondent added that, since the customer is the guarantor of their added value on the market, they also regard data security as central to their reputation and brand image. If an incident occurs, the company could simply lose customers or even go bankrupt.

Some AI technologies need to run on an integrated technological platform or operating system (e.g., electronic health record -EHR-) that allows for optimal data flow and exchange between the different technological systems and organisational departments as well as across healthcare system organisations. Respondents agree that the City hospital’s departments generally have outdated and disparate systems and infrastructures that are frequently not interoperable. However, several managers, clinicians, and technology providers argue that this is a common problem for the whole healthcare system, as an integrated and interoperable EHR does not exist. In this regard, for a population of over 8 million people in Quebec, there are over 30 million patient identification cards. A patient may have several cards with a fragmented EHR in several organisations. Similarly, one interviewee stressed that the equipment used (e.g., scanner, magnetic resonance imaging -MRI) in the City hospital does not always meet the requirements for AI. In some situations, it is difficult to know where the data is, or how it is processed and collected by certain technologies or equipment. Problems with internet connection and data transmission via Wi-Fi are also reported.

There is a consensus that AI technologies need high-quality data. Both industry and organisation respondents highlighted that a significant amount of clinical-administrative data (e.g., handwritten clinical notes) and patient records are still scanned in portable document format (PDF), which is not usable for planned AI. For technology providers, the meaningful use of data, which raises the question of the purpose of the data collection, is missing within the organisation and should be given more consideration.

For its AI programme, the City hospital works with many specialised start-ups and small- and medium-sized enterprises (SU/SMEs). One such technology provider stresses that the survival of their company depends on their ability to seek liquidity in the financial market (e.g., venture capital). This means that they are necessarily accountable to their shareholders who may be looking for the fastest and most profitable exit events possible (i.e., when an investor sells his/her shares in a company to collect cash profits). This approach brings challenges for the City hospital in terms of working relationships, technology development, and continuity of care. For instance, SU/SMEs can be bought by multinationals or simply disappear (e.g., bankruptcy), or a company may stop a technology or cease to update it. According to a manager, the City hospital does not necessarily have the capacity to maintain these technologies on an ad hoc basis or replace them with others. Another interviewee added that sometimes the organisation has no guarantee of recovering data hosted or operated by these technology providers or their subcontractors (e.g., Cloud services).

The value proposition

Stakeholders interviewed have divergent definitions of what constitutes the perceived, anticipated and/or actual value of a technology and the parameters to be considered for measuring it (e.g., safety, efficacy, and effectiveness criteria). About 95% were still in development/experimentation or implementation.

Several technology providers mainly express the value of their technology in terms of its potential to improve healthcare and its efficiency. They pointed to significant consumption of resources by the healthcare system while at the same time being unable to meet the healthcare needs of the population. For these interviewees, AI can solve the problem whilst modernising the healthcare system. In this regard, for a supplier, to realise such value, the City hospital, and the healthcare system in general, must be willing to take some risks. He stressed that if the latter wait for AI to be perfect and risk-free before using it, the technology will never be integrated, and its value promise never delivered to the population.

A manager reported that many AI technologies in the City hospital were at a value promise stage (i.e., with anticipated, rather than actual value stage). Other interviewees consider that this value promise remains relatively speculative, based on vague projections and estimates. In this regard, from the organisation’s perspective, the perceived value of AI technologies is mainly about improved clinical quality and safety, and performance. The expectation to achieve this value is to have tailor-made AI technologies adapted to the setting, clinical contexts, and ways of working. However, focusing on tailored AI solutions can sometimes be a major constraint for technology providers. According to several interviewees, suppliers prefer to commercialise generic technologies that can be easily marketed elsewhere with minimum modification (plug-and-play). Several managers and clinicians added that the costs involved in implementing and adapting the technology to the local context are regularly underestimated by these suppliers. The latter often lack an understanding of the complexity of clinical practices. For example, one company stopped working with the City hospital because it considered that its clinical needs are too specific for the AI technology to be cost-effective.

Because of its status as a leading academic hospital, the City hospital is highly sought after by the AI industry. Several interviewees recognise that the organisation is used to showcase and legitimise the technology’s value proposition, hence its market value and potential for widespread commercialisation. A technology provider also reported that the organisation serves as a gateway to the healthcare systems of Quebec and other Canadian provinces. At the same time, according to organisation respondents, the City hospital benefits from media coverage, which gives it a competitive advantage in attracting talent and expertise. However, divergence over the actual added value of certain technologies may constitute a source of tension between senior management and clinical teams. Some AI technologies are likely to exacerbate workload and staff burnout (e.g., technologies intended for the optimisation of clinical-administrative processes). For a manager, since AI technologies are still considered over and above other priorities, their impact on the quality of work and clinicians’ satisfaction is not really taken into consideration in the organisation’s assessment of their value (e.g., flexibility, alignment with clinical-administrative workflows). He added that the City hospital has difficulty in moving the value of these innovations from the Triple Aim to the Quadruple Aim: “improving the patient experience, the population health and the quality of work and satisfaction of healthcare providers, and reducing costs” [ 49 ].

The organisation’s clinical-administrative data, which is used to develop and/or operate some AI technologies, may contain biases and may not be representative of the general population. For several interviewees, AI technologies may also not respond to the contextual realities and needs of some populations (e.g., indigenous, rural, or minority people). Patients and organisation respondents also pointed out that these populations are rarely involved in the design, development, and implementation of AI technologies within the City hospital. Several interviewees recognise that assessing the added value of AI technologies by population segment is essential, but very difficult to achieve.

The adopter system(s)

Interviewees overwhelmingly agree that certain AI technologies could have a direct impact on the patient-clinician relationship. Some progressive diseases require human care and support over time. For AI technologies designed to monitor chronic diseases, some patients fear being lost from sight by their healthcare providers. According to several patients, it is important to ensure that they always have the possibility of in-person meeting with their clinician. As a patient pointed out, technology could never understand their subjective experience with the disease better than the clinician. For this and another patient, listening and empathy are sometimes more important in a care pathway than medication and technology. They mentioned that the therapeutic relationship goes beyond the simple dimension of the disease.

According to a patient, some patients registered with the City hospital can have up to 5 technology applications, sometimes non-interoperable. Some of these technologies do not operate on older Apple- or Android-supported smartphones, making it hard for several patients to use them unless they upgrade their hardware. Technologies may also require access to patient-generated data at home. Patients, clinicians, and managers stressed that patients may not have the technology and equipment and/or a good internet connection, but also the social and cultural capital (e.g., literacy, family network) to fully benefit from the potential of these technologies. They recognise that these technologies could lead to additional costs and expenses for these patients. Even when they have the technology, they may need technical support at any time of the day (24/7) as the disease “has no working days”, as a patient notes. This support is not automatically provided by the organisation and not all patients have a family/friend network that can be mobilised when needed. Paradoxically, technology could exacerbate the disease burden for these patients.

Several respondents reported that the adoption and use of certain AI technologies typically requires a reorganisation, or even a redesign, of clinical practices, of the organisation of services, and of the modes of governance and control within the City hospital. According to clinicians and managers, these changes could be associated with a feeling of loss of professional autonomy, identities, values, and skills. In the words of a manager, AI technologies could cause an erosion of information asymmetry (in favour of the organisation and the MSSS) and challenge clinicians’ autonomy of practice. The erosion and reduction of the scope of expertise due to the replacement of part of the clinical activity by AI was also pointed. However, several respondents relativised these fears, stressing that it is rather the clinicians trained in AI (e.g., clinician-informatician, clinician-data scientist) who will replace the others. This new expertise will have to be institutionalised and valued. This could imply a revision of the boundaries of professional jurisdictions (e.g., reserved acts) and of certain negotiated orders and privileges, and therefore of powers (e.g., nurse vs. general practitioner; general practitioner vs. specialist physician). Managers and technology providers pointed out that a technology that provides real added value for patients will never be integrated into practice if clinicians perceive it as a threat to them.

It was reported that the effort to integrate AI within the City hospital is occurring in a context where clinicians are under great pressure with high workloads. Some emphasised that they have no time to waste on these technologies, particularly those imposed on them by senior management and/or industry. They also expressed a feeling of innovation fatigue. Managers and clinicians acknowledge that this lack of time, but also of engagement, has a negative impact on the success of technology training and promotion initiatives within the organisation, and therefore its subsequent adoption and use. In addition, clinicians involved in technology integration efforts are mainly volunteers (e.g., champions, super-users). As the contribution to innovation is not considered a clinical activity, it is not remunerated nor recognised in their performance indicators. According to several clinicians and managers, this point is a significant barrier to clinicians’ engagement, especially to embrace the necessary changes and adaptations, and to construct meaning and develop new identities with regards to AI.

There is agreement that the need for continuous monitoring and follow-up of some AI technologies in everyday clinical practice made the role of IT teams more critical to clinical practice. According to a manager, this is a major change as clinical and IT teams have historically evolved in silos. In this regard, it is difficult to align cultures and languages within the City hospital in the midst of developing AI technologies and services. For some clinicians, the increasing adoption of AI in their practice may make them dependent on IT teams (potentially conflicting with their autonomy of practice). To address this issue, an interviewee emphasised the importance of the presence of translators or boundary spanners with a hybrid clinical-IT profile to bridge and build a healthy collaborative space between clinical and IT teams. These translators could also act as a bridge between clinical teams and technology providers. The same respondent reported that such a role is already played by members of the City hospital’s Innovation Pole team and several clinicians.

Several managers and clinicians, acknowledge that the blind confidence and lack of critical distance could affect the use of certain AI technologies in clinical decision-making. In this regard, they see the problem of transparency and explainability of AI decisions (black box). According to an interviewee, the problems of data quality and bias are serious enough to be doubly vigilant on this point. A technology provider recognised the importance of clinicians being able to understand how the decision is made by the AI (e.g., parameters retained or excluded) and whether such a decision is right or wrong. To do so, clinicians may need technical support from AI experts, which the City hospital does not necessarily have. According to several respondents, it is difficult for public organisations to recruit AI experts, as the latter are more attracted by the private sector where working conditions and remuneration are very advantageous.

Embedding and adaptation over time

The City hospital’s IT systems are theoretically well secured for AI or associated technologies needed for its functioning. Indeed, any new technology for clinical-administrative use should meet strict criteria for safety and effectiveness. They should be licensed and/or authorised by the IT department or regulatory agencies. However, several managers and clinicians recognise that, once implemented, numerous technologies are not necessarily monitored and controlled over time. The result is a complex, fragmented, and non-interoperable technology environment that is difficult to manage and update, but also vulnerable to cyber-attacks. Some AI technologies are likely to dysfunction and/or operate and evolve awkwardly in such an environment, which could pose patient safety issues.

According to industry, clinicians, and managers, the lifecycle of AI technologies (i.e., the period during which they can function adequately without major upgrades and avoid replacement by new and better technologies) is often very short, and potentially only a few months. The City hospital should be able to upgrade its technology systems and equipment continuously. The costs can be significant. In this regard, equipment and devices (e.g., scanner, MRI) required for the functioning of certain AIs may be considered obsolete after only five years of use. The data they generate is no longer usable, which has a direct impact on their clinical reliability (e.g., ability to detect cancer). To remedy this problem, some technology providers offer to lease equipment. According to the latter, City hospital could then benefit from the latest equipment, with embedded AI, with no obligation to purchase. A technology provider explained that such a model involves the organisation to engage in service contracts over varying periods of time with the supplier. Such contracts usually include the implementation, maintenance, and upgrading of the equipment and associated technologies. The same respondent emphasised that this proximity model would also allow for a feedback process, necessary to adapt to the evolving needs and expectations of clinical teams. However, for several managers, this model raises concerns about the risk of locking the City hospital into a dependency relationship with a single supplier. They reported that this “chaining” could, among other things, increase the supplier’s control of the organisation’s data. To illustrate this point, an interviewee indicated that a technology provider has already “forced” the City hospital to pay for access to its own data (hosted/stored on the supplier’s servers). The same person reported that suppliers want to benefit from an annuity/rent, i.e., a continuous flow of money over time.

The wider system

A gap exists between those who call for a pragmatic approach (e.g., test-and-error, sandbox logic) and those who call for the consolidation of the precautionary principle (i.e., decision-makers adopt precautionary measures when scientific evidence about a human health or environmental hazard is uncertain and the stakes high) [ 50 ]. For several suppliers, the precautionary principle is a major obstacle to the integration of these technologies into the healthcare system. They stressed that regulation should be made more flexible, because zero risk does not exist in healthcare. An interviewee pointed out that the autonomous and evolving nature of some AI technologies will inevitably lead to failures and unforeseen incidents. Instead, lessons should be learned from these malfunctions and incidents to improve the technology. The Post-Market Approval/Post Market Surveillance model adopted in the USA was given as an example. This approach is rejected by other several managers and clinicians who consider that the lives and safety of patients cannot be subject to “hazardous test-and-error”.

Respondents are unanimous in stating that the authorisation, contracting, and financing process of AI technologies by the MSSS, which mainly focuses on the initial purchase price (capital equipment, which results in the procurement of technology with a fixed price, often the lowest, of which the organisation becomes the owner), is no longer adapted to the reality of AI technologies (Table  3 ). Firstly, many AIs operate with a “Software as a Service (SaaS)” business model. It is a monthly or yearly subscription for the organisation. According to technology providers, this model is justified by the fact that these technologies require continuous monitoring, control, and maintenance over time. Some respondents also called for the adoption of the “Value-Based Procurement (VBP)” business model. In this case, the suppliers are paid according to the value generated by their technology (e.g., 10% of the savings made over a patient’s entire care and service cycle). As these technologies are not cheap, there is a risk that they could be excluded from current tendering processes. According to several managers, the tender model does not consider the costs required for the implementation and adaptation of the technology to the local context. Examples where additional costs were required at the time of implementation, not initially foreseen, are relatively common. However, interviewees recognise that VBP is still difficult to implement. Because of the evolving nature of certain AIs, their value could change over time. Currently, it is difficult to ensure their continuous evaluation and monitoring due to the fragmentation of services and the lack of an integrated EHR, as well as trained and qualified human resources (e.g., collection, organisation, structuring, visualisation, and analysis of AI technology usage data), among other things.

According to several managers, the difficulty of acquiring certain AI technologies through the tendering process is another reason why the City hospital prioritises partnership contracts (e.g., co-development or serving as a testing ground) over service contracts (e.g., procurement of technology and/or associated services) with suppliers. In the words of a manager, as long as the organisation does not incur expenses (e.g., having the technology at no cost for a given period or forever) from its operating budgets, it does not have to justify its actions to the MSSS. This strategy also allows the City hospital to accelerate the integration of these technologies into its care and service offer by avoiding the complex bureaucratic process of the MSSS. However, some interviewees reported that partnership contracts do not always allow for the sustainable use of the technology beyond the free-of-charge period. In some situations, the organisation would have to incur expenses after this period and sign a service contract. It would then have to go through the tendering process again. If the latter is won by a different supplier, the initial technology should then be withdrawn, which condemns the City hospital to a kind of eternal restart.

Several technology providers argue that the tendering model is a barrier to entry into healthcare for SU/SMEs, although they could offer AI technologies with real added value. Unlike large companies, SU/SMEs do not have sufficient financial and marketing capacity to offer low prices.

Several respondents, both in the City hospital and industry, pointed out that the Act on the protection of personal information is also seen as a major obstacle to AI in the healthcare system. Typically, when a patient is treated in a public healthcare organisation, his/her consent does not include the secondary use of his/her data for research or other purposes. Legally, AI technologies developed or tested with this data cannot be used and/or commercialised, at least theoretically. According to an organisation interviewee, overcoming this barrier would entail considering that once a patient is treated in a public healthcare organisation, he/she automatically consents to the secondary use of his/her data for service improvement and research purposes. Several patients interviewed agree with this approach. However, they insisted that patients should always be able to withdraw their consent if they so want (opt-out).

Also concerning data, several interviewees highlighted the central role and necessity of Cloud services (e.g., data storage, exchange, and management) for optimal and effective use of AI technologies. According to a manager, Cloud services providers are mainly multi/transnational companies. The latter have servers and relay points all over the world, which means that data could travel across national borders. This challenges regulatory sovereignty. The same interviewee reported that Quebec legislation requires that data be hosted on servers located on its territory. However, the City hospital does not always have the levers to verify and ensure that the providers really respect this requirement. Nor does it always have the possibility of knowing whether an incident (e.g., security breach, data leakage) has occurred if the company does not communicate the information to it. In the words of another manager, “[The City hospital] does not always have the capacity to [ensure the security and reliability of the technologies], so it is forced to trust [the suppliers]”. In the same vein, it does not always have the levers and means to ensure that the technology provider has destroyed and/or deleted the dataset when requested to do so. In addition, according to another interviewee, the definition of responsibilities in the event of a patient harm incident is a not fully resolved issue yet. The latter highlighted that compensation could involve large sums of money that neither the supplier nor the City hospital would want to pay. In this regard, by simply being identified as a potential liable party in the event of an incident, the organisation or company could see the amount of its insurance contract increase considerably because of the risks involved.

Many AI technologies used in clinical decision making are considered as “Software as a Medical Device (SaMD)”. There is still no clear framework for their assessment and approval in Quebec and Canada. In addition, professional federations and colleges, and medical insurance bodies have not yet taken clear positions on their use in clinical practice. According to several interviewees, the absence of solid clinical practice guidelines, protocols, remuneration models, and professional responsibility frameworks limits the possibility of clinicians using these technologies. As an illustration, a manager pointed to the complexity of identifying responsibilities in the event of an AI error (e.g., misdiagnosis or mistreatment). Since certain technologies can decide autonomously, part of the responsibility of the clinician is transferred to them. For the same interviewee, numerous questions have yet to be answered: to what extent does the technology replace the clinician (totally or partially) or not? With the “black box” problem, AI does not always allow for tracing and understanding the decision-making process. Even when it is possible, technology providers might refuse to give access to their algorithm for commercial confidentiality and market competitiveness reasons. It is then difficult to know the nature and/or origin of the fault. Moreover, there is also the question of whether AI should imply an obligation of results, instead of the obligation of means to which clinicians are presently committed. According to another manager, technology providers prefer to classify their technologies outside the SaMD category. In this way, the clinician remains solely responsible in the event of harm. Then, the supplier avoids paying damages that may be substantial. Indeed, compared to a clinician’s error, which is usually limited to a single patient, an AI technology’s error could affect many patients. However, providers explained this choice by the fact that technology approval processes, such as SaMD, are time-consuming and very expensive.

Other regulatory constraints are pointed out by several interviewees. AI technologies never arrive ready for clinical use (plug-and-play). There is often adaptation and alignment work to be done. Some changes and/or adaptations are made informally (e.g., bricolage, workarounds) by clinicians. According to a clinician and a manager, these modifications are sometimes crucial in their decisions to use the technology or not. However, from a regulatory perspective, once licensed and authorised, a technology should not generally be modified, at least theoretically. Currently, any changes require the approval of the City hospital’s IT teams or of a governmental regulatory agency. Although justified in terms of financial and safety risks, there is a consensus among interviewees that this process is rigid, time consuming, and inadequate for the reality of AI. In this regard, updates to AI technologies should be quasi-automatic and continuous, in the spirit of how the iPhone works, often without human intervention. In the words of a clinician, any delay or blockage could have a direct impact on the diagnosis or treatment of patients.

According to a manager, aspects related to the organisations’ performance criteria and, therefore of their funding by the government are not yet fully defined for AI. In Quebec, the activity-based funding model is being deployed to complement the dominant historical budget model. This new model generally considers the activity of physicians (e.g., diagnosis, treatment, surgery), paid essentially on a fee-for-service basis, in the calculation of the budget the organisation will receive from the MSSS. The activity of other healthcare professionals, mainly salaried by the organisation (e.g., nurses), is not considered the same way (or only slightly) in these calculations. Numerous AI technologies intended for (or assisting in) diagnosis or treatment could be supervised by healthcare professionals other than physicians. The impact of this development on the funding of healthcare organisations remains unknown. In the same vein, the respondent highlighted the problem of the fragmentation of funding between medical, medico-social, and social services in Quebec. For example, some AI technologies have a clinical added value and are therefore covered by the MSSS. However, the latter does not cover other aspects such as the improvement of the patient’s quality of life (e.g., Quality-adjusted life year -QALY-). As a result, the City hospital could be required to solicit different departments, ministries and/or agencies to capture the different value components of the same AI technology.

According to several interviewees, funding from the federal government would have a direct impact on the integration of AI technologies into the City hospital. They report that federal programmes make it possible to fund expensive infrastructure projects, from several hundred thousand to several million CA$. However, implementation and sustainability are mainly under the responsibility of the Quebec MSSS because health falls under provincial authority in Canada. There is sometimes a gap between federal funding and provincial priorities. According to a manager, the Quebec MSSS does not automatically fund the implementation and sustainability of federally funded technologies. As a result, several technologies could eventually be abandoned. For another interviewee, one of the important limitations is that federal funding is often very targeted and specific to particular technologies and/or clinical areas. It does not provide sufficient flexibility for organisations to use it according to local needs and contingencies.

Lastly, several respondents recognise that inter-organisational collaboration for sharing expertise and experience is essential for AI. However, the fragmentation, lack of communication and coordination across public healthcare organisations make it difficult to establish such a collaborative environment. For example, according to a clinician, to develop AI technologies with real added value, it would be necessary to have access to large amounts of patient data. She explained that the way to do this, while competing with other technologies from other countries, is to pool the databases of different healthcare organisations in Quebec and Canada. Such an inter-organisational network is essential in the evaluation and approval process of AI technologies, as they are to be tested on data from different healthcare organisations (e.g., urban and rural hospitals, primary care clinics). For the same respondent, such multicentre testing would ensure reliability and effectiveness in different clinical and technological settings across the country.

Summary of key lessons

Our study aimed to generate a better understanding of the conditions that facilitate or constrain the integration of AI technologies in a large healthcare organisation in Canada. By analysing a rich corpus of data using the NASSS framework, the study highlights seven lessons:

Firstly, an organisational culture and leadership that creates favourable conditions for AI is essential as well as the presence of clinical champions who act as ambassadors for AI. This is a lever to attract clinical and/or technical talent and expertise, but also companies in the field. The strategic alignment of the organisation’s clinical-administrative processes and infrastructures with AI technologies remains a major challenge. A lack of alignment could lead to partial integration of technologies or their abandonment, resulting in innovation fatigue among clinical and administrative teams. In a context where clinicians are over-solicited, they should be given the time needed to integrate the change, but also develop the professional expertise and identities that AI could require. It is also important that the technologies proposed to them are supported by evidence of improvements in patient care and services as well as in their work conditions and quality. The integration of AI within a hospital also involves a multitude of stakeholders whose activities and actions should be coherent and synergistic. Communication is fundamental to clarify roles, responsibilities, and mandates and requires a horizontal structure capable of coordinating actions and shaping a consistent organisational story about AI. The technologies proposed by the industry should be filtered so that those that really meet the needs on the ground are prioritised.

Secondly, financial and other incentives are needed to encourage clinicians to experiment and adapt these technologies to their practices. Investments in the development of AI technologies have so far focused on specific complex pathologies that present a great burden to patients and their families as well as to the healthcare system. To address these pathologies, AI mainly exploits image analysis and/or signal quantification, which makes it easier for suppliers to develop technologies and introduce them more quickly to the market. Yet, the sensitivity of safety and data protection issues implies that the hospital hires a lawyer specialising in digital technologies (to ensure that contracts are properly made) and a Chief data officer (for adequate and consistent data governance). Upgrading IT systems and infrastructure and recruiting new expertise hence require planning for both initial and recurring investments and expenditures.

Thirdly, the interoperability of AI technologies and the organisation’s systems and infrastructure are major obstacles to their routine use. Some technologies need quasi-real time access to data, which requires an integrated platform to ensure optimal data circulation between different IT systems and departments of the organisation, or even other organisations involved in the patient’s treatment. The qualification of some advanced software as AI could have financial and legal implications for the organisation. In addition to traditional clinical safety issues, the AI algorithm itself could be hacked and modified, resulting in harm to patients. By recombining data from various sources, individuals could be easily re-identified. These technologies could also require high-tech equipment with very short lifecycles, which the organisation may not have. Furthermore, many AI technologies are driven by SU/SMEs that could disappear from the market at any time. Hence, organisations should have the capacity to maintain the technology on an ad hoc basis or find an alternative and be able to recover and/or ensure the deletion of data by the initial supplier.

Fourth, the definition of the value of AI technologies is far from consensual as well as the expectations regarding what they can or should do. The ability to measure this value is of considerable complexity given the great contrast between the value proposition stated by suppliers, and sometimes by managers, and the actual value to clinicians and patients. The value of AI is not self-evident. Indeed, even if it has shown great performance in a laboratory context, this may not materialise in the real-world context of care and services. The value of some AI technologies also contrasts with the risks they raise given their evolutionary and autonomous nature. There are trade-offs between the precautionary principle, the need for some risk tolerance, and its clinical potential. Moreover, clinical practice may require very specific AI technologies, whereas suppliers tend to prioritise plug-and-play technologies with a potential for widespread commercialisation. The global value of AI could vary widely depending on the balance of the changes and transformations it requires and what it actually provides. This value may also change over time. Evaluating and monitoring AI’s value on an ongoing basis requires resources and expertise the organisation may lack, especially in view of the (re)production of bias across sub-groups of the population.

Fifth, contrary to the rhetoric about their potential to humanise care, some AI technologies raise concerns about the patient-clinician relationship and, therefore, about quality of care. The risk of mechanisation of care and the difficulty of physically accessing healthcare providers is palpable. Digital literacy, technical support, and change management for clinicians and patients using these technologies are essential. For clinicians, AI technologies may imply redesigning clinical practice and service organisation, but also new governance and control strategies within the organisation. Although improbable, there is a real concern that AI could partially or totally replace the activity of clinicians. Hyper-dependence on technology raises concerns about the erosion of clinicians’ expertise and the risk of blind trust in the decisions made by AI. As a result, clinicians may worry about being subordinated to the IT teams that would play a central role in the production of care. This new reality highlights the central role of translators or boundary spanners in building bridges and trust between clinical and IT teams, but also with industry. On a larger scale, the technology-driven approach to AI could cause a deterioration in clinicians’ work conditions and quality.

Sixth, the evolving and self-learning nature of some AI technologies makes time critical, distinguishing them from previous licensed technologies that do not generally require a new approval review. IT teams should approve and validate any changes or adaptations, and this becomes difficult with some AI technologies that evolve autonomously and update themselves. Any delay or blockage could threaten the diagnostic or treatment quality of patients. Continuous monitoring and control over time is required to avoid malfunctions and incidents, but also to make the necessary improvements. In this regard, the increasingly short lifecycle of software and hardware challenges the technical and financial capacity of the organisation to adapt and evolve its systems, equipment, and infrastructure at the right pace. Evolutionary AI technologies create the need for close and sustainable relationships between the organisation and the technology providers, a new relationship that: 1) requires solid frameworks to identify and resolve conflicts of interest as they arise over time; and 2) must avoid lock-in and dependence upon a single provider.

Seventh, many socio-political, economic, and regulatory factors are decisive in the integration of AI technologies, which are mainly offered under SaaS and/or VBP business models. These models are in opposition to the current tender model in Quebec that emphasises the cheapest technology (capital equipment). The legal framework of the current model constitutes a barrier to entry for SU/SMEs, some with high value-added technologies. Established bureaucratic acquisition processes are inadequate for the very short lifecycle of AI technologies. Consent requirements for the use of patient data are misaligned with this new reality and are prompting consideration of an opt-out consent model. AI technologies increasing rely on Cloud services mainly offered by multinational companies with servers and relay points all over the world. Data governance is even more important as healthcare organisations and systems have limited resources and tools to ensure that data management and storage comply with applicable laws. Identifying liability in the event of harm could therefore be very complex. AI technologies classified as SaMD, on the other hand, have specific requirements for quality, efficiency, and clinical reliability. To date, the lack of reference technologies makes it difficult for regulatory agencies to assess and approve them. Established mechanisms and processes are not adapted to the complexity and very short lifecycle of AI. Ongoing evaluation and monitoring mechanisms in the real-world context seem necessary, but the high degree of uncertainty associated with them requires a balance between the precautionary principle and a laissez-faire integration in clinical routine. Beyond the lack of clear frameworks and directives from the MSSS and other regulatory bodies regarding the use of these technologies by clinicians, inter-organisational networks facilitating the sharing of expertise and experience are essential. The current context is characterised by fragmentation, and poor communication and coordination between organisations and government agencies, which hinders an integrated and coherent vision of AI at the healthcare system: provincial- and federal-level of governance.

Contribution to the existing literature

The results of this study contribute to knowledge in several ways. They shed a new and different light on the trend of recent years where the literature has mainly focused on the technical and promissory dimensions of AI. Our findings are consistent with those of Pumplun et al. (2021) and Petersson et al. (2022) who analysed implementation issues raised by AI technologies in healthcare in Germany and Sweden, respectively [ 3 , 51 ]. Studies on telehealth and EHR also reported results that corroborate ours on AI [ 26 , 31 , 32 , 34 , 52 , 53 , 54 , 55 , 56 , 57 , 58 ]. In this regard, several authors pointed out the major contrast between the techno-optimistic discourse on the performance and efficiency of technology and the reality of services that are difficult to transform [ 56 , 57 , 58 ]. These experiences have shown that the difficulties encountered in the deployment of digital technologies are mainly due to the historical lack of attention paid to the sociotechnical factors and conditions necessary for their integration into healthcare organisations and systems. Hence, our study adds to the growing literature that considers technology in a complex sociotechnical transformation perspective that requires not only technological but also human, clinical, professional, organisational, socio-political, economic, regulatory, legal, and cultural changes [ 27 , 40 , 41 , 56 , 59 , 60 , 61 ]. Very limited attention has been paid to this perspective in examining AI to date, whereas our study clarifies its contribution and indicates some avenues for future research (Table  4 ) [ 3 , 18 , 26 , 51 ].

From a theoretical standpoint, our study provides an original contribution to the literature on health innovations. It is one of the first to demonstrate that the NASSS framework is relevant for the analysis of the integration of AI technologies in healthcare organisations and systems [ 51 ]. The study contributes to the knowledge on the importance of a sociotechnical perspective to understand the complexity and unpredictability of transformations related to disruptive innovations such as AI [ 27 , 51 , 62 ].

Implication for practice and policy

Our study provides new insights for decision-making and practice on the conditions required but also on the pitfalls to be avoided to ensure successful integration of AI technologies into healthcare organisations and systems. It shows that the pitfalls of the technocentric vision of digital health of the last thirty years in Quebec (and elsewhere too) could easily be repeated with AI technologies, but this time with more profound repercussions [ 31 , 32 , 33 , 35 , 36 , 63 ]. As Matheny et al. (2020) highlighted: “Disconnects between reality and expectations have led to prior precipitous declines in use of the technology, termed AI winters, and another such event is possible, especially in health care” [ 64 ]. In this regard, the various stakeholders must be aware that AI is more an object of transformation at all levels of healthcare system governance, than a simple “intrinsically good/bad” tool. Its successful integration depends on several structural conditions, namely, appropriate: regulatory and governance frameworks; funding, business, and remuneration models; definition of the value proposition; management of conflicts of interest; governance of data; cybersecurity strategies; training and expertise, models of care and service delivery; inter-professional collaboration; and up-to-date infrastructure and equipment.

Specifically, AI highlights the importance of rethinking the collaboration between healthcare organisations and systems, on the one hand, and technology providers, on the other hand. Indeed, their interests sometimes represent competing financial and political objectives between which a difficult balance must be established [ 65 ]. Given their disruptive nature at all levels of the healthcare system, IA technologies could generate tensions and require trade-offs between perceptions, expectations, interests, and agendas that may be divergent or even antagonistic (ex. industry and venture capital, decision-makers, managers, clinicians, patients). These dynamics and power relations influence the trajectory of AI technologies in healthcare, either positively or negatively [ 59 , 66 ]. Thus, if healthcare organisations and systems are not sufficiently equipped and prepared, “the AI landscape risks being shaped by early established companies and decisions made with insufficient evaluations in place due to pressures to embrace technology” [ 67 ].

In addition, one of the fundamental issues remains the lack of digital literacy and culture, and AI technology skills among healthcare professionals [ 68 ]. Currently, initial and continuing training programmes do not sufficiently integrate these technologies into the expertise that trainees (e.g., physicians, nurses) need to achieve to be authorised to practice. As reported in our study, without appropriate training, clinicians are unlikely to adopt in an appropriate way these technologies. Indeed, training is required to adapt provider protocols, administrative workflows, pathways, and business processes [ 67 ]. According to Mistry (2019), for such change to take place, healthcare professionals will need:1) to have access to education content enabling them to learn new skills as AI users and work differently; 2) to be able to train AI systems themselves for setting them up to perform specified tasks, which implies knowing what data to select and its quality; 3) to develop abilities to interpret AI outputs, including a solid understanding of its limitations and bounds of function; and 4) to know “how the system learns and what constitutes appropriate use, so that ethical norms are upheld and any introduction of biases is avoided” [ 67 ].

Strengths and limitations

This study offers one of the first holistic and multilevel analyses of the complexity of the changes and transformations associated with the integration of AI technologies into clinical routine, beyond technical issues. It is also part of the few studies that go beyond looking at one single AI technology and delves into the organisational and systemic complexity of integrating multiple AI technologies concurrently.

However, the study has limitations. By its qualitative nature, it has a high level of internal validity, but the transferability (or generalisability) of its findings is limited to similar healthcare organisations and systems. In other contexts, it can increase the awareness of different stakeholders regarding the importance of taking better account of the sociotechnical dimension of AI. Healthcare organisations and systems can vary considerably, hence the importance of contextualising the results.

The number of interviewees ( n  = 29) is relatively low in view of the large number of AI technologies covered in this study. Although we made great efforts to include a wide range of stakeholders, several people were unable to participate due to the COVID-19 context. This is the case for women heading technology companies, whereas decision-makers, managers, and clinicians were unable to participate because of their direct involvement in the management of the pandemic. However, the people who participated, through their expertise and experience, provided us with rich data, necessary for a detailed understanding of the challenges of integrating AI in healthcare organisations and systems. The application of a rigorous research approach, guided by best methodological practices and an exhaustive theoretical framework, has reinforced the reliability of our results.

Conclusions

AI in healthcare is still in its infancy. There are huge expectations that it will provide answers to major contemporary challenges in healthcare organisations and systems. This is reflected in the funding it receives from governments, but also in the interest of the financial and venture capital sector. The COVID-19 pandemic was a test case for AI, and it did not fully deliver. However, the pandemic has served as an accelerator for its experimentation, for example, through the relaxation of regulatory requirements and less resistance from some stakeholders. AI represents as much a logistical, psychological, cultural, and philosophical change, particularly in terms of what it could and should do in healthcare organisations and systems. It is a “new era” that requires a real critical examination to learn from the many past experiences with the digitalisation of healthcare organisations and systems. With AI, the nature, scale and complexity of the changes and transformations are at such a level and intensity that the implications could be profound for society. At present, little is known about how such an announced revolution may take shape and under what conditions. This study provides a unique learning base for analysing AI technologies in healthcare organisations and systems from a sociotechnical perspective using the NASSS framework. It adds to the existing literature and can better inform decision-making towards the judicious, responsible, and sustainable integration of these technologies in healthcare organisations and systems.

Availability of data and materials

The data that support the findings of this study are available from the corresponding author (HA) upon reasonable request. The data are not publicly available due to information that could compromise the privacy of the research participants.

Abbreviations

• Artificial intelligence

Canadian Dollar

Coronavirus Disease 2019

Quebec’s Ministry of Health and Social Services Information Technology Division

Electronic Health Record

International Organization for Standardization

Information Technology

Act on Contracting by Public Bodies

Magnetic Resonance Imaging

Quebec’s Ministry of Health and Social Services

Non-Adoption, Abandonment, Scale-up, Spread, Sustainability

Picture Archiving and Communication System

Portable Document Format

Quality-Adjusted Life Year

Software as a Service

Software as a Medical Device

Start-ups and Small- and Medium-sized Enterprises

United States Dollar

United States of America

Value-Based Procurement

Organisation for Economic Co-operation and Development (OECD). Recommendation of the Council on Artificial Intelligence. OECD; 2019. https://legalinstruments.oecd.org/en/instruments/OECD-LEGAL-0449#mainText .

Alloghani M, Al-Jumeily D, Aljaaf A, Tan S, Khalaf M, Mustafina J. The application of artificial intelligence technology in healthcare: a systematic review. CCIS. 2020;1174:248–61.

Google Scholar  

Petersson L, Larsson I, Nygren JM, Nilsen P, Neher M, Reed JE, et al. Challenges to implementing artificial intelligence in healthcare: a qualitative interview study with healthcare leaders in Sweden. BMC Health Serv Res. 2022;22(1):1–16.

Article   Google Scholar  

Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019;25(1):44–56.

Article   CAS   PubMed   Google Scholar  

Abràmoff MD, Lavin PT, Birch M, Shah N, Folk JC. Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices. NPJ Digital Med. 2018;1(1):39.

Ching T, Himmelstein DS, Beaulieu-Jones BK, Kalinin AA, Do BT, Way GP, et al. Opportunities and obstacles for deep learning in biology and medicine. J R Soc Interface. 2018;15(141):20170387.

Article   PubMed   PubMed Central   Google Scholar  

van Leeuwen KG, de Rooij M, Schalekamp S, van Ginneken B, Rutten MJ. How does artificial intelligence in radiology improve efficiency and health outcomes? Pediatric Radiol. 2022;52(11):2087–93.

Benjamens S, Dhunnoo P, Meskó B. The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database. NPJ Digital Med. 2020;3(1):1–8.

Hamet P, Tremblay J. Artificial intelligence in medicine. Metabolism. 2017;10(01):11.

Jiang F, Jiang Y, Zhi H, Dong Y, Li H, Ma S, et al. Artificial intelligence in healthcare: past, present and future. Stroke Vasc Neurol. 2017;2(4):230–43.

Chen M, Decary M. Artificial intelligence in healthcare: an essential guide for health leaders. Healthc Manage Forum. 2020;33(1):10–8.  https://doi.org/10.1177/0840470419873123 .

Article   PubMed   Google Scholar  

Rajkomar A, Dean J, Kohane I. Machine learning in medicine. N Engl J Med. 2019;380(14):1347–58.

Miller DD, Brown EW. Artificial intelligence in medical practice: The question to the answer? Am J Med. 2018;131(2):129–33.

Dicuonzo G, Donofrio F, Fusco A, Shini M. Healthcare system: moving forward with artificial intelligence. Technovation. 2023;120:102510.

Bohr A, Memarzadeh K. The rise of artificial intelligence in healthcare applications. Artif Intell Healthc. 2020;Chap2:25–60.

Alami H, Rivard L, Lehoux P, Hoffman SJ, Cadeddu SBM, Savoldelli M, et al. Artificial intelligence in health care: laying the foundation for responsible, sustainable, and inclusive innovation in low- and middle-income countries. Glob Health. 2020;16(1):52.

Alami H, Lehoux P, Denis J-L, Motulsky A, Petitgand C, Savoldelli M, et al. Organizational readiness for artificial intelligence in health care: insights for decision-making and practice. J Heal Organ Manag. 2020;35(1):106–14.

Alami H, Lehoux P, Auclair Y, de Guise M, Gagnon M-P, Shaw J, et al. Artificial intelligence and health technology assessment: anticipating a new level of complexity. J Med Internet Res. 2020;22(7):e17707.

Sharon T. When digital health meets digital capitalism, how many common goods are at stake? Big Data Soc. 2018;5(2):2053951718819032.

Liu X, Faes L, Kale AU, Wagner SK, Fu DJ, Bruynseels A, et al. A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis. Lancet Digital Health. 2019;1(6):e271–97.

Bullock J, Luccioni A, Pham KH, Lam CS, Luengo-Oroz M. Mapping the landscape of artificial intelligence applications against COVID-19. J Artif Intell Res. 2020;19(69):807–45.

Naudé W. Artificial intelligence vs COVID-19: limitations, constraints and pitfalls. Ai Soc. 2020;35(3):761–5.

Heaven WD. Hundreds of AI tools have been built to catch covid. None of them helped. MIT Technology Review; 2021. https://www.technologyreview.com/2021/07/30/1030329/machine-learning-ai-failed-covid-hospital-diagnosis-pandemic/ .

Wynants L, Van Calster B, Collins GS, Riley RD, Heinze G, Schuit E, et al. Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal. Br Med J. 2020;7:369.

Roberts M, Driggs D, Thorpe M, Gilbey J, Yeung M, Ursprung S, et al. Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans. Nat Machine Intell. 2021;3(3):199–217.

Lebcir R, Hill T, Atun R, Cubric M. Stakeholders’ views on the organisational factors affecting application of artificial intelligence in healthcare: a scoping review protocol. BMJ Open. 2021;11(3):e044074.

Greenhalgh T, Wherton J, Papoutsi C, Lynch J, Hughes G, A'Court C, et al. Beyond adoption: a new framework for theorizing and evaluating nonadoption, abandonment, and challenges to the scale-up, spread, and sustainability of health and care technologies. J Med Int Res. 2017;19(11):e8775.

Skaria R, Satam P, Khalpey Z. Opportunities and challenges of disruptive innovation in medicine using artificial intelligence. Am J Med. 2020;133(6):e215–7.

Thompson RF, Valdes G, Fuller CD, Carpenter CM, Morin O, Aneja S, et al. Artificial intelligence in radiation oncology: a specialty-wide disruptive transformation? Radiother Oncol. 2018;129(3):421–6.

Rubeis G. The disruptive power of artificial intelligence. Ethical aspects of gerontechnology in elderly care. Arch Gerontol Geriatr. 2020;91:104186.

Alami H, Gagnon M-P, Fortin J-P. Some multidimensional unintended consequences of telehealth utilization: a multi-project evaluation synthesis. Int J Health Policy Manag. 2019;8(6):337.

Alami H, Fortin J-P, Gagnon M-P, Pollender H, Têtu B, Tanguay F. The challenges of a complex and innovative telehealth project: a qualitative evaluation of the eastern Quebec Telepathology network. Int J Health Policy Manag. 2018;7(5):421.

Alami H, Fortin J-P, Gagnon M-P, Lamothe L, Ahmed MAA, Roy D. Cadre stratégique pour soutenir l’évaluation des projets complexes et innovants en santé numérique. Sante Publique. 2020;32(2):221–8.

Alami H, Gagnon M-P, Wootton R, Fortin J-P, Zanaboni P. Exploring factors associated with the uneven utilization of telemedicine in Norway: a mixed methods study. BMC Med Inform Decis Mak. 2017;17(1):180.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Alami H, Lamothe L, Fortin J-P, Gagnon M-P. L’implantation de la télésanté et la pérennité de son utilisation au Canada : quelques leçons à retenir. Eur Res Telemed. 2016;5(4):105–17.

Alami H, Shaw S-E, Fortin J-P, Savoldelli M, Fleet R, Têtu B. The ‘wrong pocket’problem as a barrier to the integration of telehealth in health organisations and systems. Digital Health. 2023;9:1–7.

Gremyr A, Gäre BA, Greenhalgh T, Malm U, Thor J, Andersson A-C. Using complexity assessment to inform the development and deployment of a digital dashboard for schizophrenia care: case study. J Med Internet Res. 2020;22(4):e15521.

Greenhalgh T, Maylor H, Shaw S, Wherton J, Papoutsi C, Betton V, et al. The NASSS-CAT tools for understanding, guiding, monitoring, and researching technology implementation projects in health and social care: protocol for an evaluation study in real-world settings. JMIR Res Protoc. 2020;9(5):e16861.

Berg M. Patient care information systems and health care work: a sociotechnical approach. Int J Med Inform. 1999;55(2):87–101.

Papoutsi C, Wherton J, Shaw S, Greenhalgh T. Explaining the mixed findings of a randomised controlled trial of telehealth with centralised remote support for heart failure: multi-site qualitative study using the NASSS framework. Trials. 2020;21(1):1–15.

Shaw J, Rudzicz F, Jamieson T, Goldfarb A. Artificial intelligence and the implementation challenge. J Med Internet Res. 2019;21(7):e13659.

Yin RK. Case study research and applications. Thousand Oaks CA: Sage; 2018.

Alami H, Rivard L, Lehoux P, Ahmed MAA, Fortin J-P, Fleet R. Integrating environmental considerations in digital health technology assessment and procurement: Stakeholders’ perspectives. Digital Health. 2023;9:1–17.

Miles MB, Huberman AM, Saldaña J. Qualitative data analysis: a methods sourcebook. 3rd: ed. Thousand Oaks, CA: Sage; 2014.

Morse JM. Designing funded qualitative research. Handbook of Qualitative Research. 1994.

Farmer T, Robinson K, Elliott SJ, Eyles J. Developing and implementing a triangulation protocol for qualitative health research. Qual Health Res. 2006;16(3):377–94.

De PP. l’analyse qualitative en général et de l’analyse thématique en particulier. Rec Qual. 1996;15:179–94.

Overcash JA. Narrative research: a review of methodology and relevance to clinical practice. Crit Rev Oncol Hematol. 2003;48(2):179–84.

Bodenheimer T, Sinsky C. From triple to quadruple aim: care of the patient requires care of the provider. Ann Fam Med. 2014;12(6):573–6.

Bourguignon D. The precautionary principle: definitions, applications and governance. Policy Commons. 2015. https://policycommons.net/artifacts/1334548/the-precautionary-principle/1940163/ .

Pumplun L, Fecho M, Wahl N, Peters F, Buxmann P. Adoption of machine learning systems for medical diagnostics in clinics: qualitative interview study. J Med Internet Res. 2021;23(10):e29301.

Alami H, Lehoux P, Gagnon M-P, Fortin J-P, Fleet R, Ahmed MAA. Rethinking the electronic health record through the quadruple aim: time to align its value with the health system. BMC Med Inform Decis Mak. 2020;20(1):1–5.

Alami H, Gagnon M-P, Fortin J-P, Kouri R. La télémédecine au Québec: état de la situation des considérations légales, juridiques et déontologiques. La Rec Eur Téléméd. 2015;4(2):33–43.

Alami H, Lehoux P, Attieh R, Fortin J-P, Fleet R, Niang M, et al. A “not so quiet” revolution: systemic benefits and challenges of telehealth in the context of COVID-19 in Quebec (Canada). Front Digit Health. 2021;10(3):721898.

Alami H, Gagnon MP, Fortin JP. Telehealth in light of cloud computing: clinical, technological, regulatory and policy issues. J Int Soc Telemed eHealth. 2016;4(e5):1–7.

Shaw S, Hughes G, Wherton J, Moore L, Rosen R, Papoutsi C, et al. Achieving spread, scale up and sustainability of video consulting services during the Covid-19 pandemic? Findings from a comparative case study of policy implementation in England, Wales, Scotland and Northern Ireland. Front Digital Health. 2021;3:754319.

Greenhalgh T, Shaw S, Wherton J, Vijayaraghavan S, Morris J, Bhattacharya S, et al. Real-world implementation of video outpatient consultations at macro, meso, and micro levels: mixed-method study. J Med Internet Res. 2018;20(4):e9897.

Shaw S, Wherton J, Vijayaraghavan S, Morris J, Bhattacharya S, Hanson P, et al. Advantages and limitations of virtual online consultations in a NHS acute trust: the VOCAL mixed-methods study. Health Serv Del Res. 2018;6(21):1–36.

Cresswell K, Hernández AD, Williams R, Sheikh A. Key challenges and opportunities for cloud technology in health care: semistructured interview study. JMIR Hum Factors. 2022;9(1):e31246.

Greenhalgh T, Rosen R, Shaw SE, Byng R, Faulkner S, Finlay T, et al. Planning and evaluating remote consultation services: a new conceptual framework incorporating complexity and practical ethics. Front Digital Health. 2021;103:726095.

James HM, Papoutsi C, Wherton J, Greenhalgh T, Shaw SE. Spread, scale-up, and sustainability of video consulting in health care: systematic review and synthesis guided by the NASSS framework. J Med Internet Res. 2021;23(1):e23775.

Papoutsi C, Wherton J, Shaw S, Morrison C, Greenhalgh T. Putting the social back into sociotechnical: Case studies of co-design in digital health. J Am Med Inform Assoc. 2021;28(2):284–93.

Alami H, Lehoux P, Shaw S-E, Papoutsi C, Rybczynska-Bunt S, Fortin J-P. Virtual care and the inverse care law: Implications for policy, practice, research, public and patients. Int J Environ Res Public Health. 2022;19(17):10591.

Matheny M-E, Whicher D, Israni STD. Artificial intelligence in health care: a report from the national academy of medicine. J Am Med Assoc. 2020;323(6):509–10.

Lehoux P, Daudelin G, Denis J-L, Miller F-A. A concurrent analysis of three institutions that transform health technology-based ventures: economic policy, capital investment, and market approval. Rev Policy Res. 2017;34(5):636–59.

Cennamo C, Santaló J. Generativity tension and value creation in platform ecosystems. Organ Sci. 2019;30(3):617–41.

Mistry P. Artificial intelligence in primary care. Br J Gen Pract. 2019;69(686):422–3.

Alami H, Gagnon M-P, Ahmed MAA, Fortin J-P. Digital health: cybersecurity is a value creation lever, not only a source of expenditure. Health Policy Technol. 2019;8(4):319–21.

Download references

Acknowledgements

We thank the interviewees and the City hospital personnel for their availability throughout the study, even in the midst of the COVID-19 pandemic. The findings and conclusions presented in the text are those of the authors. They do not necessarily reflect the position of their organisations.

HA was supported by the In Fieri research programme (led by P), the International Observatory on the Societal Impacts of Artificial Intelligence and Digital Technologies, and the Institute for Data Valorization (IVADO), (Canada).

Author information

Authors and affiliations.

Department of Health Management, Evaluation and Policy, School of Public Health, University of Montreal, P.O. Box 6128, Branch Centre-Ville, Montreal, QC, H3C 3J7, Canada

Hassane Alami & Pascale Lehoux

Center for Public Health Research of the University of Montreal, Montreal, QC, Canada

Institute for Data Valorization (IVADO), Montreal, QC, Canada

Hassane Alami

Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK

Hassane Alami, Chrysanthi Papoutsi & Sara E. Shaw

Faculty of Medicine, Laval University, Quebec, QC, Canada

Richard Fleet & Jean-Paul Fortin

VITAM Research Centre on Sustainable Health, Faculty of Medicine, Laval University, Quebec, QC, Canada

You can also search for this author in PubMed   Google Scholar

Contributions

HA and PL conceived and designed the study plan. HA and PL were responsible for data collection, analysis, and interpretation of results. HA, PL, CP, SES, RF and JPF were engaged in the drafting of the manuscript, and they all read and approved the final manuscript.

Corresponding author

Correspondence to Hassane Alami .

Ethics declarations

Ethics approval and consent to participate.

The study was approved by the City hospital Research Ethics Committee (Number: Comité d’éthique de la recherche- City hospital: 20.399). (Address is anonymised for confidentiality reasons). All methods were carried out in accordance with relevant guidelines and regulations. Informed consent was obtained from all subjects and/or their legal guardian(s).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Alami, H., Lehoux, P., Papoutsi, C. et al. Understanding the integration of artificial intelligence in healthcare organisations and systems through the NASSS framework: a qualitative study in a leading Canadian academic centre. BMC Health Serv Res 24 , 701 (2024). https://doi.org/10.1186/s12913-024-11112-x

Download citation

Received : 03 February 2023

Accepted : 14 May 2024

Published : 03 June 2024

DOI : https://doi.org/10.1186/s12913-024-11112-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Digital health
• Health organisation
• Health system
• Business models
• Implementation
• Innovation adoption

BMC Health Services Research

ISSN: 1472-6963

• General enquiries: [email protected]

Comment on “What resources do high school students activate to link energetic and structural changes in chemical reactions? – A qualitative study” by B. Pölloth, D. Diekemper and S. Schwarzer, Chem. Educ. Res. Pract. , 2023, 24 , 1153

First published on 9th December 2023

A recent study in Chemistry Education Research and Practice highlights the common pattern of student thinking known as ‘the octet framework’, and notes how it seems to relate to, but be inconsistent with, the octet rule: an idea commonly taught in introductory chemistry classes. The study noted the common feature of learners extending the octet rule into ‘a driving force’ for chemical change, but analysis also noted two other features of the alternative conceptual framework. It is argued here that these research findings reflect a key problem in chemistry education: one that the research community should prioritise for further investigation.

Introduction

Octets and student thinking.

Pölloth and colleagues’ argue that the octet rule is a canonical part of chemistry, which is therefore understandably included in elementary chemistry teaching, but that students’ use of the octet rule as found in their study, as a ‘driving force’ for chemical reaction, is invalid. The authors do not specify what they mean by the octet rule (that is, exactly what is being taught in introductory chemistry lessons in German high schools). As they are writing for a professional readership of chemistry educators, they can reasonably expect their readers to know what the ‘octet rule’ is, but their findings reflect previous research that the octet rule seems to be inappropriately applied to explain why chemical reactions occur, even when the reactants fit the rule as much as the products. Moreover, this is not an idiosyncratic notion offered by an outlier in research: in Pölloth and colleagues’ study “eleven [of 16] groups gave the same explanation for the driving force”. This seems to present a phenomenon worthy of further investigation: why do so many students seem to misunderstand/misapply this heuristic? It also raises the question of whether the teaching around this rule needs to be revisited . These are the points I will develop in this comment.

Alternative conceptions and frameworks

Terms such as alternative conception and alternative framework are often used (along with other terms such as misconception, intuitive theory, preconception, etc. ) synonymously in the literature ( Abimbola, 1988 ). However, it can be useful to distinguish between (i) discrete alternative conceptions (that can be represented in a single proposition) and (ii) more elaborated frameworks of ideas. So, the idea that ‘ the noble gases do not form compounds ’ can be considered a conception, although it generalises to a number of cases ( xenon does not form compounds , argon does not form compounds , etc. ). For a long time, when the term ‘inert gases’ was widely used, this particular conception was considered canonical, but now this would be considered an alternative conception. Other such alternative conceptions might be ‘ [all] acids are dangerous ’ and ‘ [all] metals are magnetic ’, or that ‘ elements are monatomic’ .

An alternative conceptual framework, when used in the sense suggested for the octet framework ( Taber, 1998 ), is of something more elaborated – a set of related conceptions (at least some of which are at odds with canonical science) that form a consistent and mutually reinforcing structure for thinking about some aspects of the natural world ( e.g. , see Fig. 1 ). In terms of the account of science offered by the physicist and philosopher of science Mario Bunge (2017/1998) , an alternative conceptual framework might be seen as standing in relation to an alternative conception in much the same way that a scientific theory relates to a single hypothesis.

A once active debate about the nature of learner thinking related to whether students’ alternative ideas at odds with scientific accounts could be considered ‘theory-like’ ( Driver, 1989 ) rather than just being isolated notions ( Claxton, 1993 ). This was seen as an important question as conceptual frameworks that make up an extended set of related and inter-linked ideas are likely to be more resistant to correction by teaching than discrete notions that are not embedded in a supporting network of associations. Given the extensive research-base now available it seems reasonable to state that learners’ alternative thinking about natural phenomena varies along this dimension such that it can sometimes b e, but is by no means always , theory-like. Indeed, this characterisation applies to people's thinking more generally.

Pölloth and colleagues draw upon the ‘resources’ perspective on learning and cognition ( diSessa, 1988 ) which sees much thinking as drawing from a repertoire of resources to construct transient conceptual ‘assemblages’ ( Brock et al. , 2023 ) for immediate purposes, in contrast to more permanent extensive conceptual frameworks. The development of stable and extensive conceptual structures is often associated with the acquisition of expertise in an area, and, so, with canonical thinking. The octet framework was however proposed as an example of a theory-like conceptual structure commonly acquired in introductory chemistry that is internally coherent, and yet inconsistent with several key areas of the higher grade chemistry curriculum ( i.e. , non-canonical). This ‘alternative framework’ is represented in Fig. 1 . † The core conception in this framework explains chemical processes as occurring to bring about octets or full outer shells; that is, in Pölloth and colleagues’ terms, seeing this as ‘a driving force’ for chemical reactions. This feature is highlighted with green shading in Fig. 1 .

The octet framework ‡ was proposed following an interview-based study undertaken in an English college (where students, c.16–19 years of age, progressed from a wide range of schools), and where

“students were found to commonly use the octet rule – a heuristic for identifying stable chemical species – as the basis of a principle to explain chemical reactions and chemical bonding: the full shells explanatory principle. From this perspective bonding “is done in order to try to achieve a stable structure, i.e., eight electrons in the outer shell of the atom”. All of the [study participants] used the octet rule as an explanatory principle at some point during the interviews, although the phrasing varied…”

( Taber, 1998 , pp. 600–601)

This clearly matches somewhat what was reported in Pölloth and colleagues’ German study (which of course is not only a different educational system, but one where students study in a different language of instruction). The octet framework included other aspects (common across the sample, although those interviewed did not necessarily demonstrate all of these features) as reflected in Fig. 1 . Two of these features, beyond the octet rule as a driving force, that are reflected in the data Pölloth and colleagues report to illustrate their analysis were:

• The assumption of initial atomicity

• Use of anthropomorphic language

Students make an assumption that reactants are always atomic

Fig. 2 shows a question from a diagnostic assessment tool included in a Royal Society of Chemistry resource ( Taber, 2002 ). This question asked about a parallel reaction to that used in the German study. Students given this question commonly explained the reaction in terms of the atoms obtaining full shells/fluorine acquiring eight electrons. Yet, as Fig. 2 shows, the question included the information that the reactants were initially molecular (H 2 , F 2 ). Despite this, the assumption of initial atomically was so strong that even when given this information as part of a question, students commonly gave an explanation that would only be valid for atomic reactants. This seems to be a widespread phenomenon, despite none of the reactions commonly studied in school chemistry (or beyond) being between atomised samples. This conception seems to be widely applied across chemical contexts, and seems to be tenacious. For example, students may explain the formation of sodium chloride in terms of an energetically non-feasible electron transfer from a discrete sodium atom to a discrete chlorine atom, even if they have prepared sodium chloride in the laboratory by neutralisation, starting with reagent solutions (of HCl, NaOH) that already contain the ions found in the product.

Anthropomorphic language

“ …it was very common for students to speak of atoms as if they were sentient actors in the molecular soap opera of chemistry…there were many suggestions that atoms wanted or needed to gain or lose electrons. Indeed this usage was ubiquitous in student comments, although alternatives included atoms preferring , liking , being eager , or having no wish for certain outcomes. When hydrogen bonding in hydrogen fluoride was considered one [participant] accused the fluorine of being greedy for ‘ trying to grab two electrons’ from different hydrogen atoms ”.

( Taber, 1998 , p. 603)

Pölloth and colleagues report students referring to atoms “ aiming for the eight electrons” and how a chlorine atom would not “ want to react with something that also has seven valence electrons [but rather] want to react with something that has one” (p. 1163). They found students equating stability with not ‘wanting’ to react, and inertness with being ‘very lazy’.

Anthropomorphic explanations are not valid in chemistry, so this raises the question of why they are so common among students. In their paper, Pölloth and colleagues consider the target models presented in the curriculum, and discuss the core and integrating role of energy as a key concept, yet they report than in their study they found that “students seldom refer to energy minimisation to reason on chemical reactivity” (p. 1166).

The suggestion of atoms ‘wanting’ or ‘needing’ or ‘trying to get’ octets or full shells as the basis of chemical explanations has been elicited from secondary students in various other national contexts such as Finland ( Joki and Aksela, 2018 ), Israel ( Zohar and Levy, 2019 ), Sweden ( Adbo, 2012 ) and Turkey ( Ünal et al. , 2010 ) and also at undergraduate level in the United States ( Nicoll, 2001 ; Wang and Barrow, 2013 ) and Australia ( Coll and Treagust, 2001 ) and even among postgraduate students in New Zealand ( Coll and Taylor, 2002 ; Coll and Treagust, 2003 ). This kind of language can offer the sense of an explanation, but does not amount to a scientific explanation as it relies upon the supposed desires of atoms rather than any natural cause. This makes such explanations teleological as they focus on an assumed desirable end-state without offering a mechanism for its attainment, and such pseudo-explanations are not only found in students’ explanations ( Taber and Watts, 2000 ), but also in textbooks assigned to students ( Talanquer, 2007 ).

Another learner is quoted (in translation) in Pölloth and colleagues’ paper as suggesting “if there aren’t eight electrons, a substance is very reactive because it strives for a stable state” (p. 1164). Students seem to readily come to equate stability with octet or full shell configurations.

The stability of the octet

The rule is limited. It does not help as much with the d-block elements. Copper forms compounds with the Cu + ion as well as with the Cu 2+ ion. It has many exceptions beyond the second period: compounds such as sulphates, PCl 5 , SF 6 , inter-halogen compounds, and so forth, with ‘expanded octets’, do not fit the rule. It would rule out any compounds of the inert gases. It is not an absolute guide even in period 2, as CO is stable enough to be a substance of significance, and there are relatively stable ‘electron deficient’ compounds such as BF 3 .

A major logical problem is that commonly students seem to reverse the idea of the rule: rather than just rule out unlikely species (Cl 2+ , CH 5 ), it may be used to rule in any species that fits the rule as being inherently stable. This feature is highlighted with mauve shading in Fig. 1 . So, it is common for students to think that chemically unlikely species such as Na 7− , Be 6− , and C 4+ , as well as Cl 11− ( i.e. , a species with a full outer shell, but not an octet), and even an excited atom such as Cl with electronic configuration 1.8.8, will be stable because they fit the criterion of an octet or full outer shell ( Taber, 2009 ). Students apply this without consideration of context. Na + is an ion commonly found stabilised in chemical systems such as lattices and hydrated in solution, but Na + is commonly assumed by learners to be inherently more stable than the neutral atom, such that a sodium atom would spontaneously emit an electron to obtain an octet configuration. Indeed, considering ionisation, neon and argon are commonly assumed to have the highest ionisation enthalpies in their periods because they have stable octet structures (when both fit the general patterns of increasing first ionisation enthalpy across the respective periods).

The belief that an Na + ion is intrinsically more stable than the sodium atom has also been found in secondary students in Finland ( Joki and Aksela, 2018 ) and among undergraduates in the U.S.A. who also thought the (chemically implausible) Na 7− anion would be more stable than the atom ( Wang and Barrow, 2013 ). Israeli secondary students have also been found to assume species with an outer shell octet will be the most stable ( Zohar and Levy, 2019 ).

The significance of the octet framework

One critical issue seems to be that students have typically already come to think that reactions occur in order to allow atoms to obtain octets or full shells (sometimes, but not always, the same thing) before they are provided with canonical conceptual tools ( e.g. , bond enthalpies) to learn the scientific accounts. It seems that ‘octet thinking’ comes to replace ‘the explanatory vacuum’ in introductory chemistry classes where no scientific rationale for why chemical reactions occur tends to be offered to students. The octet rule seems to be adopted/adapted as an explanatory principle in the absence of any taught alternative, and typically has several years to be consolidated in student thinking before students move on to more advanced courses where ideas such as bond enthalpies and energy minimisation are usually introduced. However, this can surely only be considered a partial explanation given that – as Pölloth and colleagues remind us – the octet rule should not have any bite as an explanation of reactions where the reactants fit the rule just as well as the products. That is, in just about all reactions met in introductory chemistry.

The source of the octet framework

Another potential source is spontaneously developed notions based on intuitions about the world – common conceptions about force and motion seem to be of this type ( diSessa, 1993 ). DiSessa (1993) has described how people develop what he termed ‘phenomenological primitives’ – features of cognition which reflect the preconscious recognition of common patterns in experience, and which come to be applied as intuitive elements of cognition across domains. These ‘p-prims’ are considered implicit knowledge elements that act as elementary resources to inform expectations and make sense of experience, and which may be automatically recruited in assembling more explicit conceptions ( Karmiloff-Smith, 1996 ), as for example in developing explanations of natural phenomena. This perspective on building up conceptual structures from spontaneously developed cognitive resources has been especially influential in physics education ( Hammer, 2000 ), the domain where diSessa (1993) has described a good many candidate p-prims; but is just as applicable in principle to other domains such as chemistry learning ( Taber and García Franco, 2010 ). P-prims are not domain specific, as they represent intuitions of generalisable patterns, so at least some of diSessa's candidate p-prims are likely to be of wide relevance. However, as diSessa's study was limited to asking students about college physics contexts, it also seems plausible that it would not have revealed any p-prims that are seldom applied in those particular contexts.

Joki and Aksela (2018) have mooted the suggestion that “ diSessa's (1993) p-prim of vacuums impel” may be related to the development of the octet framework. It is also possible that the degree to which the octet rule becomes widely adopted as an explanatory principle reflects the recruitment of a common p-prim not identified by diSessa from physics contexts, but which relates to “something about the ‘fullness’, or perhaps the symmetry, of the [full shell] pattern and marks it out as especially significant” ( Taber, 2008 , p. 1042).

It is not likely that learners commonly, spontaneously, intuit features of the molecular realm; but rather that certain p-prims are (without any conscious awareness) activated in sense-making where they seem to fit with what students are being taught about at this level. Vygostky's (1978) influential theory of learning distinguishes between (i) ideas that are developed spontaneously ( e.g. , in effect, intuitively) by the learner, and (ii) ideas that are acquired through inter-personal interactions (such as teaching) using symbolic language systems (text, diagram, gesture, etc. ): but also argues that extant conceptual ideas learned from others can only be made sense of, and internalised, in terms of existing conceptual resources.

That is, it is certainly possible to learn pre-packaged complex and abstract conceptual material, such as established scientific theories, but only when these can be understood through existing thinking that, directly or indirectly, has its ultimate origin in spontaneous conceptions. Although Vygotsky died (in 1934) long before the debate, referenced above, about whether alternative (non-canonical) patterns of thinking exhibited by science learners could be considered theory-like, he had already proposed a model which suggested that a person's ideas covered a spectrum of levels of abstraction and complexity, but were always, at base, ground in spontaneous notions. An expert's highly abstract and conceptual understanding of some domain differs from the novice's in the extent to which it has iteratively built, stage upon stage, away from the intuitive cognitive resources on which all human conceptualisation ultimately depends.

The ‘resources’ perspective informing Pölloth and colleagues’ work offers an explanation for why learners might interpret chemistry teaching in terms of existing general intuitions/expectations (“productive resources”, p. 1168) about the nature of the world, and this offers a plausible account for why teaching about the octet rule might be over-interpreted by learners. This could certainly explain the origin of the perception of the octet or full shell as ‘télos’, but seems insufficient to explain the widespread and tenacious nature of ‘octet framework thinking’. It might also be feasible that some students, on being taught the octet rule, spontaneously adopt it as the basis of a much more far-reaching explanatory principle, but it would seem incautious to assume this could explain why so many learners seem to acquire the more extensive alternative framework. Something which is not supposed to be taught (reactions occur so atoms can get octets/full outer shells) seems to be learnt much more widely, and retained and applied much more reliably, than many of the notions that are set out in the curriculum as target knowledge, and that are taught and regularly reinforced in classes.

The role of teaching in reinforcing ‘octet thinking’

Adbo (2012) reported that a course book used by Swedish upper secondary students was quite explicit in suggesting reactions took place because atoms strived for a noble gas configuration. Presentations suggesting that chemical reactions take place between atomic species ( e.g. , a carbon atom interacts with four discrete hydrogen atoms; a sodium atom isolated from the metallic lattice interacts with a lone chlorine atom) have been identified in school textbooks ( Taber, 2002 ; Bergqvist, 2017 ). The use of anthropomorphic language to discuss chemical processes has been reported in textbooks used by English ( Taber, 2002 ), Greek ( Tsaparlis et al. , 2018 ) and Swedish ( Bergqvist, 2017 ) secondary students, as well as by Swedish chemistry teachers themselves ( Bergqvist, 2017 ).

In her Swedish study, Bergqvist reported that

“ All the textbooks and teachers focused on individual atoms when presenting ionic, covalent, and polar covalent bonding…the octet rule was used explicitly or implicitly as a reason for bonding…Anthropomorphic descriptions were also common and used in many ways, both in textbooks and by teachers ”

( Bergqvist, 2017 , pp. 92–93)

Whether it transpires that the seemingly ubiquitous nature of ‘octet thinking’ is primarily the creative work of learners facing an explanatory vacuum, or largely derives from teachers and textbook authors doing their best to offer learners some kind of basis for explaining why chemistry occurs, research is indicated to find a solution to the core problem: i.e. , the lack of a teaching model of why chemical change occurs, which is both (a) accessible at the introductory level, and yet (b) suitable for developing into the accounts taught in more advanced classes. Without that, it seems likely that learners will continue to adopt ‘the octet rule as a driving force’ in the way Pölloth and colleagues found in their study.

Informing curriculum development

Pölloth and colleagues reiterate the well-rehearsed argument ( Jensen, 1995 ; Taber, 2001 ; Levy Nahum et al. , 2007 ; Tsaparlis et al. , 2018 ) that in teaching about bonding and structure and reactivity in introductory chemistry, it is important to focus on physical arguments – on charges, forces, energy – as the basis for explaining phenomena. Research suggests that it is not sufficient for such ideas to be adopted in isolation by particular teachers or for specific grades. Research undertaken in Finland suggests that even when introductory chemistry was taught according to a carefully designed scheme to avoid learners treating the octet rule as the basis for explaining chemical change ( Joki et al. , 2015 ), students can subsequently take up such thinking whilst studying subsequent chemistry courses ( Joki and Aksela, 2018 ). A detailed longitudinal case study of a student in England suggested that although ‘octet thinking’ found to be initially dominant on transition from secondary school became much less frequent during a two-year college course; octet thinking was again strongly represented in the individual's explanations of chemical phenomena several years after completing the course ( Taber, 2003 ). That students seem so wedded to this alternative way of thinking about chemistry, even after being taught more canonical principles, as Pölloth and colleagues report, is both a key problem in teaching chemistry and – I would suggest – a core phenomenon that it would be valuable for the chemistry education research community to understand better.

The importance of designing ongoing learning experiences around a limited number of core scientific ideas ( Key Stage 3 National Strategy, 2002 ) and of continuity across curriculum experiences is increasingly being recognised, as seen in studies to develop ‘learning progressions’ ( Alonzo and Gotwals, 2012 ). One example of such a curriculum initiative which has been extended from the undergraduate level ( Cooper et al. , 2012 ) to include the high school level ( Stowe et al. , 2019 ) is ‘CLUE’ (‘Chemistry, Life, the Universe, and Everything’), and such carefully designed curriculum contexts offer useful cases to explore the development of student thinking. If teaching in this area is explored in terms of learning progressions, one possible approach would be to consider whether the octet rule might be productive as a kind of intermediate notion ( Driver, 1989 ) that can be employed to build more advanced thinking. But learning progressions designed to structure curriculum need to be research-informed, and this would first require a better understanding of just how and why this particular idea becomes so readily and firmly recruited into the developing thinking of so many students.

In conclusion

Pölloth and colleagues’ study is a timely reminder that students commonly adopting (and so adapting) the octet rule as a driving force of chemistry is a well-recognised issue that the chemistry education research community has not yet been able to address. This new study should perhaps be seen as a ‘driving force’ for further research, firstly to better understand precisely how and why this phenomenon develops, and then to explore changes to curriculum and/or teaching practice to address this.

Conflicts of interest

• Abimbola I. O., (1988), The problem of terminology in the study of student conceptions in science, Sci. Educ. , 72 (2), 175–184.
• Adbo K., (2012), Relationships between models used for teaching chemistry and those expressed by students , Gothenburg, Sweden: Linnaeus University.
• Alonzo, A. C. and Gotwals, A. W. (ed.), (2012), Learning Progressions in Science: Current Challenges and Future Directions , Sense Publishers.
• Bergqvist A., (2017), Teaching and learning of chemical bonding models: Aspects of textbooks, students’ understanding and teachers’ professional knowledge , Karlstad, Sweden: Karlstad University.
• Brock R., Taber K. S. and Watts D. M., (2023), Assembly required: a microgenetic multiple case study of four students’ assemblages when learning about force, Int. J. Sci. Educ. , 1–21  DOI: 10.1080/09500693.2023.2269616 .
• Bunge M., (2017/1998), Philosophy of Science , Revised edn, Routledge, 1967.
• Claxton G., (1993), Minitheories: a preliminary model for learning science, in Black P. J. and Lucas A. M. (ed.), Children's Informal Ideas in Science , Routledge, pp. 45–61.
• Coll R. K. and Taylor N., (2002), Mental models in chemistry: senior chemistry students’ mental models of chemical bonding, Chem. Educ.: Res. Pract. Eur. , 3 (2), 175–184.
• Coll R. K. and Treagust D. F., (2001), Learners' mental models of chemical bonding, Res. Sci. Educ. , 31 (3), 357–382.
• Coll R. K. and Treagust D. F., (2003), Investigation of Secondary School, Undergraduate, and Graduate Learners’ Mental Models of Ionic Bonding, J. Res. Sci. Teach. , 40 (5), 464–486.
• Cooper M. M., Underwood S. M., Hilley C. Z. and Klymkowsky M. W., (2012), Development and Assessment of a Molecular Structure and Properties Learning Progression, J. Chem. Educ. , 89 (11), 1351–1357  DOI: 10.1021/ed300083a .
• Dhindsa H. S. and Treagust D. F., (2014), Prospective pedagogy for teaching chemical bonding for smart and sustainable learning, Chem. Educ. Res. Pract. , 15 (4), 435–446  10.1039/C4RP00059E .
• diSessa A. A., (1988), Knowledge in pieces, in Forman G. and Pufall P. (ed.), Constructivism in the Computer Age , Lawrence Erlbaum Publishers.
• diSessa A. A., (1993), Towards an epistemology of physics, Cogn. Instr. , 10 (2&3), 105–225.
• Driver R., (1989), Students’ conceptions and the learning of science, Int. J. Sci. Educ. , 11 (special issue), 481–490.
• Hammer D., (2000), Student resources for learning introductory physics, Am. J. Phys. , 68 (7-Physics Education Research Supplement), S52–S59.
• Jensen W. B., (1995), Logic, History and the Teaching of Chemistry, text of the Keynote Lectures, given at the 57th Annual Summer Conference of the New England Association of Chemistry Teachers, Sacred Heart University, Fairfield, Connecticut.
• Joki J. and Aksela M., (2018), The challenges of learning and teaching chemical bonding at different school levels using electrostatic interactions instead of the octet rule as a teaching model, Chem. Educ. Res. Pract. , 19 (3), 932–953  10.1039/C8RP00110C .
• Joki J., Lavonen J., Juuti K. and Aksela M., (2015), Coulombic interaction in Finnish middle school chemistry: a systemic perspective on students' conceptual structure of chemical bonding, Chem. Educ. Res. Pract. , 16 (4), 901–917  10.1039/C5RP00107B .
• Karmiloff-Smith A., (1996), Beyond Modularity: A developmental perspective on cognitive science , MIT Press.
• Key Stage 3 National Strategy, (2002), Framework for teaching science: years 7, 8 and 9 , London: Department for Education and Skills.
• Levy Nahum T., Mamlok-Naaman R., Hofstein A. and Krajcik J., (2007), Developing a new teaching approach for the chemical bonding concept aligned with current scientific and pedagogical knowledge, Sci. Educ. , 91 (4), 579–603  DOI: 10.1002/sce.20201 .
• Nicoll G., (2001), A report of undergraduates’ bonding misconceptions, Int. J. Sci. Educ. , 23 (7), 707–730.
• Palmer D., (1997), The effect of context on students’ reasoning about forces, Int. J. Sci. Educ. , 19 (16), 681–696  DOI: 10.1080/0950069970190605 .
• Pölloth B., Diekemper D. and Schwarzer S., (2023), What resources do high school students activate to link energetic and structural changes in chemical reactions? – A qualitative study, Chem. Educ. Res. Pract. , 24 (4), 1153–1173  10.1039/D3RP00068K .
• Solomon J., (1992), Getting to Know about Energy - in School and Society , Falmer Press.
• Stowe R. L., Herrington D. G., McKay R. L. and Cooper M. M., (2019), Adapting a core-idea centered undergraduate general chemistry curriculum for use in high school, J. Chem. Educ. , 96 (7), 1318–1326.
• Taber K. S., (1998), An alternative conceptual framework from chemistry education, Int. J. Sci. Educ. , 20 (5), 597–608.
• Taber K. S., (2001), Building the structural concepts of chemistry: some considerations from educational research, Chem. Educ.: Res. Pract. Eur. , 2 (2), 123–158  10.1039/B1RP90014E .
• Taber K. S., (2002), Chemical Misconceptions - Prevention, Diagnosis and Cure , Royal Society of Chemistry.
• Taber K. S., (2003), Lost without trace or not brought to mind? - a case study of remembering and forgetting of college science, Chemistry Education: Research and Practice , 4 (3), 249–277  10.1039/B3RP90016A .
• Taber K. S., (2008), Conceptual resources for learning science: Issues of transience and grain-size in cognition and cognitive structure, Int. J. Sci. Educ. , 30 (8), 1027–1053  DOI: 10.1080/09500690701485082 .
• Taber K. S., (2009), College students' conceptions of chemical stability: The widespread adoption of a heuristic rule out of context and beyond its range of application, Int. J. Sci. Educ. , 31 (10), 1333–1358  DOI: 10.1080/09500690801975594 .
• Taber K. S., (2013), A common core to chemical conceptions: learners' conceptions of chemical stability, change and bonding, in Tsaparlis G. and Sevian H. (ed.), Concepts of Matter in Science Education , Springer, pp. 391–418.
• Taber K. S. and García Franco A., (2010), Learning processes in chemistry: Drawing upon cognitive resources to learn about the particulate structure of matter, J. Learn. Sci. , 19 (1), 99–142.
• Taber K. S. and Watts M., (2000), Learners’ explanations for chemical phenomena, Chem. Educ.: Res. Pract. Eur. , 1 (3), 329–353.
• Talanquer V., (2007), Explanations and Teleology in Chemistry Education, Int. J. Sci. Educ. , 29 (7), 853–870  DOI: 10.1080/09500690601087632 .
• Tsaparlis G., Pappa E. T. and Byers B., (2018), Teaching and learning chemical bonding: research-based evidence for misconceptions and conceptual difficulties experienced by students in upper secondary schools and the effect of an enriched text, Chem. Educ. Res. Pract. , 19 (4), 1253–1269  10.1039/C8RP00035B .
• Ünal S., Coştu B. and Ayas A., (2010), Secondary school students’ misconceptions of covalent bonding, Journal of Turkish Sci. Educ. , 7 (2), 3–29.
• Vygotsky L. S., (1978), Mind in Society: The development of higher psychological processes , Harvard University Press.
• Wang C. Y. and Barrow L. H., (2013), Exploring conceptual frameworks of models of atomic structures and periodic variations, chemical bonding, and molecular shape and polarity: a comparison of undergraduate general chemistry students with high and low levels of content knowledge, Chem. Educ. Res. Pract. , 14 , 130–146.
• Watts M. and Zylbersztajn A., (1981), A survey of some children's ideas about force, Phys. Educ. , 16 (6), 360–365.
• Zohar A. R. and Levy S. T., (2019), Students' reasoning about chemical bonding: The lacuna of repulsion, J. Res. Sci. Teach. , 56 (7), 881–904  DOI: 10.1002/tea.21532 .