qualitative interview research topics

How to conduct qualitative interviews (tips and best practices)

Last updated

18 May 2023

Reviewed by

Miroslav Damyanov

However, conducting qualitative interviews can be challenging, even for seasoned researchers. Poorly conducted interviews can lead to inaccurate or incomplete data, significantly compromising the validity and reliability of your research findings.

When planning to conduct qualitative interviews, you must adequately prepare yourself to get the most out of your data. Fortunately, there are specific tips and best practices that can help you conduct qualitative interviews effectively.

• What is a qualitative interview?

A qualitative interview is a research technique used to gather in-depth information about people's experiences, attitudes, beliefs, and perceptions. Unlike a structured questionnaire or survey, a qualitative interview is a flexible, conversational approach that allows the interviewer to delve into the interviewee's responses and explore their insights and experiences.

In a qualitative interview, the researcher typically develops a set of open-ended questions that provide a framework for the conversation. However, the interviewer can also adapt to the interviewee's responses and ask follow-up questions to understand their experiences and views better.

• How to conduct interviews in qualitative research

Conducting interviews involves a well-planned and deliberate process to collect accurate and valid data. 

Here’s a step-by-step guide on how to conduct interviews in qualitative research, broken down into three stages:

1. Before the interview

The first step in conducting a qualitative interview is determining your research question . This will help you identify the type of participants you need to recruit . Once you have your research question, you can start recruiting participants by identifying potential candidates and contacting them to gauge their interest in participating in the study. 

After that, it's time to develop your interview questions. These should be open-ended questions that will elicit detailed responses from participants. You'll also need to get consent from the participants, ideally in writing, to ensure that they understand the purpose of the study and their rights as participants. Finally, choose a comfortable and private location to conduct the interview and prepare the interview guide.

2. During the interview

Start by introducing yourself and explaining the purpose of the study. Establish a rapport by putting the participants at ease and making them feel comfortable. Use the interview guide to ask the questions, but be flexible and ask follow-up questions to gain more insight into the participants' responses. 

Take notes during the interview, and ask permission to record the interview for transcription purposes. Be mindful of the time, and cover all the questions in the interview guide.

3. After the interview

Once the interview is over, transcribe the interview if you recorded it. If you took notes, review and organize them to make sure you capture all the important information. Then, analyze the data you collected by identifying common themes and patterns. Use the findings to answer your research question. 

Finally, debrief with the participants to thank them for their time, provide feedback on the study, and answer any questions they may have.

• What kinds of questions should you ask in a qualitative interview?

Qualitative interviews involve asking questions that encourage participants to share their experiences, opinions, and perspectives on a particular topic. These questions are designed to elicit detailed and nuanced responses rather than simple yes or no answers.

Effective questions in a qualitative interview are generally open-ended and non-leading. They avoid presuppositions or assumptions about the participant's experience and allow them to share their views in their own words. 

In customer research , you might ask questions such as:

What motivated you to choose our product/service over our competitors?

How did you first learn about our product/service?

Can you walk me through your experience with our product/service?

What improvements or changes would you suggest for our product/service?

Have you recommended our product/service to others, and if so, why?

The key is to ask questions relevant to the research topic and allow participants to share their experiences meaningfully and informally. 

• How to determine the right qualitative interview participants

Choosing the right participants for a qualitative interview is a crucial step in ensuring the success and validity of the research . You need to consider several factors to determine the right participants for a qualitative interview. These may include:

Relevant experiences : Participants should have experiences related to the research topic that can provide valuable insights.

Diversity : Aim to include diverse participants to ensure the study's findings are representative and inclusive.

Access : Identify participants who are accessible and willing to participate in the study.

Informed consent : Participants should be fully informed about the study's purpose, methods, and potential risks and benefits and be allowed to provide informed consent.

You can use various recruitment methods, such as posting ads in relevant forums, contacting community organizations or social media groups, or using purposive sampling to identify participants who meet specific criteria.

• How to make qualitative interview subjects comfortable

Making participants comfortable during a qualitative interview is essential to obtain rich, detailed data. Participants are more likely to share their experiences openly when they feel at ease and not judged. 

Here are some ways to make interview subjects comfortable:

Explain the purpose of the study

Start the interview by explaining the research topic and its importance. The goal is to give participants a sense of what to expect.

Create a comfortable environment

Conduct the interview in a quiet, private space where the participant feels comfortable. Turn off any unnecessary electronics that can create distractions. Ensure your equipment works well ahead of time. Arrive at the interview on time. If you conduct a remote interview, turn on your camera and mute all notetakers and observers.

Build rapport

Greet the participant warmly and introduce yourself. Show interest in their responses and thank them for their time.

Use open-ended questions

Ask questions that encourage participants to elaborate on their thoughts and experiences.

Listen attentively

Resist the urge to multitask . Pay attention to the participant's responses, nod your head, or make supportive comments to show you’re interested in their answers. Avoid interrupting them.

Avoid judgment

Show respect and don't judge the participant's views or experiences. Allow the participant to speak freely without feeling judged or ridiculed.

Offer breaks

If needed, offer breaks during the interview, especially if the topic is sensitive or emotional.

Creating a comfortable environment and establishing rapport with the participant fosters an atmosphere of trust and encourages open communication. This helps participants feel at ease and willing to share their experiences.

• How to analyze a qualitative interview

Analyzing a qualitative interview involves a systematic process of examining the data collected to identify patterns, themes, and meanings that emerge from the responses. 

Here are some steps on how to analyze a qualitative interview:

1. Transcription

The first step is transcribing the interview into text format to have a written record of the conversation. This step is essential to ensure that you can refer back to the interview data and identify the important aspects of the interview.

2. Data reduction

Once you’ve transcribed the interview, read through it to identify key themes, patterns, and phrases emerging from the data. This process involves reducing the data into more manageable pieces you can easily analyze.

The next step is to code the data by labeling sections of the text with descriptive words or phrases that reflect the data's content. Coding helps identify key themes and patterns from the interview data.

4. Categorization

After coding, you should group the codes into categories based on their similarities. This process helps to identify overarching themes or sub-themes that emerge from the data.

5. Interpretation

You should then interpret the themes and sub-themes by identifying relationships, contradictions, and meanings that emerge from the data. Interpretation involves analyzing the themes in the context of the research question .

6. Comparison

The next step is comparing the data across participants or groups to identify similarities and differences. This step helps to ensure that the findings aren’t just specific to one participant but can be generalized to the wider population.

7. Triangulation

To ensure the findings are valid and reliable, you should use triangulation by comparing the findings with other sources, such as observations or interview data.

8. Synthesis

The final step is synthesizing the findings by summarizing the key themes and presenting them clearly and concisely. This step involves writing a report that presents the findings in a way that is easy to understand, using quotes and examples from the interview data to illustrate the themes.

• Tips for transcribing a qualitative interview

Transcribing a qualitative interview is a crucial step in the research process. It involves converting the audio or video recording of the interview into written text. 

Here are some tips for transcribing a qualitative interview:

Use transcription software

Transcription software can save time and increase accuracy by automatically transcribing audio or video recordings.

Listen carefully

When manually transcribing, listen carefully to the recording to ensure clarity. Pause and rewind the recording as necessary.

Use appropriate formatting

Use a consistent format for transcribing, such as marking pauses, overlaps, and interruptions. Indicate non-verbal cues such as laughter, sighs, or changes in tone.

Edit for clarity

Edit the transcription to ensure clarity and readability. Use standard grammar and punctuation, correct misspellings, and remove filler words like "um" and "ah."

Proofread and edit

Verify the accuracy of the transcription by listening to the recording again and reviewing the notes taken during the interview.

Use timestamps

Add timestamps to the transcription to reference specific interview sections.

Transcribing a qualitative interview can be time-consuming, but it’s essential to ensure the accuracy of the data collected. Following these tips can produce high-quality transcriptions useful for analysis and reporting.

• Why are interview techniques in qualitative research effective?

Unlike quantitative research methods, which rely on numerical data, qualitative research seeks to understand the richness and complexity of human experiences and perspectives. 

Interview techniques involve asking open-ended questions that allow participants to express their views and share their stories in their own words. This approach can help researchers to uncover unexpected or surprising insights that may not have been discovered through other research methods.

Interview techniques also allow researchers to establish rapport with participants, creating a comfortable and safe space for them to share their experiences. This can lead to a deeper level of trust and candor, leading to more honest and authentic responses.

• What are the weaknesses of qualitative interviews?

Qualitative interviews are an excellent research approach when used properly, but they have their drawbacks. 

The weaknesses of qualitative interviews include the following:

Subjectivity and personal biases

Qualitative interviews rely on the researcher's interpretation of the interviewee's responses. The researcher's biases or preconceptions can affect how the questions are framed and how the responses are interpreted, which can influence results.

Small sample size

The sample size in qualitative interviews is often small, which can limit the generalizability of the results to the larger population.

Data quality

The quality of data collected during interviews can be affected by various factors, such as the interviewee's mood, the setting of the interview, and the interviewer's skills and experience.

Socially desirable responses

Interviewees may provide responses that they believe are socially acceptable rather than truthful or genuine.

Conducting qualitative interviews can be expensive, especially if the researcher must travel to different locations to conduct the interviews.

Time-consuming

The data analysis process can be time-consuming and labor-intensive, as researchers need to transcribe and analyze the data manually.

Despite these weaknesses, qualitative interviews remain a valuable research tool . You can take steps to mitigate the impact of these weaknesses by incorporating the perspectives of other researchers or participants in the analysis process, using multiple data sources , and critically analyzing your biases and assumptions.

Mastering the art of qualitative interviews is an essential skill for businesses looking to gain deep insights into their customers' needs , preferences, and behaviors. By following the tips and best practices outlined in this article, you can conduct interviews that provide you with rich data that you can use to make informed decisions about your products, services, and marketing strategies. 

Remember that effective communication, active listening, and proper analysis are critical components of successful qualitative interviews. By incorporating these practices into your customer research, you can gain a competitive edge and build stronger customer relationships.

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• Harvard Library
• Research Guides
• Faculty of Arts & Sciences Libraries

Library Support for Qualitative Research

• Interview Research
• Resources for Methodology
• Remote Research & Virtual Fieldwork

Resources for Research Interviewing

Nih-funded qualitative research.

• Oral History
• Data Management & Repositories
• Campus Access

Types of Interviews

• Engaging Participants

Interview Questions

• Conducting Interviews
• Transcription
• Coding and Analysis
• Managing & Finding Interview Data
• UX & Market Research Interviews

Textbooks, Guidebooks, and Handbooks  

• The Ethnographic Interview by James P. Spradley  “Spradley wrote this book for the professional and student who have never done ethnographic fieldwork (p. 231) and for the professional ethnographer who is interested in adapting the author’s procedures (p. iv). Part 1 outlines in 3 chapters Spradley’s version of ethnographic research, and it provides the background for Part 2 which consists of 12 guided steps (chapters) ranging from locating and interviewing an informant to writing an ethnography. Most of the examples come from the author’s own fieldwork among U.S. subcultures . . . Steps 6 and 8 explain lucidly how to construct a domain and a taxonomic analysis” (excerpted from book review by James D. Sexton, 1980).  
• Fundamentals of Qualitative Research by Johnny Saldana (Series edited by Patricia Leavy)  Provides a soup-to-nuts overview of the qualitative data collection process, including interviewing, participant observation, and other methods.  
• InterViews by Steinar Kvale  Interviewing is an essential tool in qualitative research and this introduction to interviewing outlines both the theoretical underpinnings and the practical aspects of the process. After examining the role of the interview in the research process, Steinar Kvale considers some of the key philosophical issues relating to interviewing: the interview as conversation, hermeneutics, phenomenology, concerns about ethics as well as validity, and postmodernism. Having established this framework, the author then analyzes the seven stages of the interview process - from designing a study to writing it up.  
• Practical Evaluation by Michael Quinn Patton  Surveys different interviewing strategies, from, a) informal/conversational, to b) interview guide approach, to c) standardized and open-ended, to d) closed/quantitative. Also discusses strategies for wording questions that are open-ended, clear, sensitive, and neutral, while supporting the speaker. Provides suggestions for probing and maintaining control of the interview process, as well as suggestions for recording and transcription.  
• The SAGE Handbook of Interview Research by Amir B. Marvasti (Editor); James A. Holstein (Editor); Jaber F. Gubrium (Editor); Karyn D. McKinney (Editor)  The new edition of this landmark volume emphasizes the dynamic, interactional, and reflexive dimensions of the research interview. Contributors highlight the myriad dimensions of complexity that are emerging as researchers increasingly frame the interview as a communicative opportunity as much as a data-gathering format. The book begins with the history and conceptual transformations of the interview, which is followed by chapters that discuss the main components of interview practice. Taken together, the contributions to The SAGE Handbook of Interview Research: The Complexity of the Craft encourage readers simultaneously to learn the frameworks and technologies of interviewing and to reflect on the epistemological foundations of the interview craft.  
• The SAGE Handbook of Online Research Methods by Nigel G. Fielding, Raymond M. Lee and Grant Blank (Editors) Bringing together the leading names in both qualitative and quantitative online research, this new edition is organised into nine sections: 1. Online Research Methods 2. Designing Online Research 3. Online Data Capture and Data Collection 4. The Online Survey 5. Digital Quantitative Analysis 6. Digital Text Analysis 7. Virtual Ethnography 8. Online Secondary Analysis: Resources and Methods 9. The Future of Online Social Research

ONLINE RESOURCES, COMMUNITIES, AND DATABASES  

• Interviews as a Method for Qualitative Research (video) This short video summarizes why interviews can serve as useful data in qualitative research.  
• Companion website to Bloomberg and Volpe's  Completing Your Qualitative Dissertation: A Road Map from Beginning to End,  4th ed Provides helpful templates and appendices featured in the book, as well as links to other useful dissertation resources.
• International Congress of Qualitative Inquiry Annual conference hosted by the International Center for Qualitative Inquiry at the University of Illinois at Urbana-Champaign, which aims to facilitate the development of qualitative research methods across a wide variety of academic disciplines, among other initiatives.  
• METHODSPACE ​​​​​​​​An online home of the research methods community, where practicing researchers share how to make research easier.  
• SAGE researchmethods ​​​​​​​Researchers can explore methods concepts to help them design research projects, understand particular methods or identify a new method, conduct their research, and write up their findings. A "methods map" facilitates finding content on methods.

The decision to conduct interviews, and the type of interviewing to use, should flow from, or align with, the methodological paradigm chosen for your study, whether that paradigm is interpretivist, critical, positivist, or participative in nature (or a combination of these).

Structured:

• Structured Interview. Entry in The SAGE Encyclopedia of Social Science Research Methodsby Floyd J. Fowler Jr., Editors: Michael S. Lewis-Beck; Alan E. Bryman; Tim Futing Liao (Editor)  A concise article noting standards, procedures, and recommendations for developing and testing structured interviews. For an example of structured interview questions, you may view the Current Population Survey, May 2008: Public Participation in the Arts Supplement (ICPSR 29641), Apr 15, 2011 at https://doi.org/10.3886/ICPSR29641.v1 (To see the survey questions, preview the user guide, which can be found under the "Data and Documentation" tab. Then, look for page 177 (attachment 8).

Semi-Structured:

• Semi-Structured Interview. Entry in The SAGE Encyclopedia of Qualitative Research Methodsby Lioness Ayres; Editor: Lisa M. Given  The semi-structured interview is a qualitative data collection strategy in which the researcher asks informants a series of predetermined but open-ended questions. The researcher has more control over the topics of the interview than in unstructured interviews, but in contrast to structured interviews or questionnaires that use closed questions, there is no fixed range of responses to each question.

Unstructured:

• Unstructured Interview. Entry in The SAGE Encyclopedia of Qualitative Research Methodsby Michael W. Firmin; Editor: Lisa M. Given  Unstructured interviews in qualitative research involve asking relatively open-ended questions of research participants in order to discover their percepts on the topic of interest. Interviews, in general, are a foundational means of collecting data when using qualitative research methods. They are designed to draw from the interviewee constructs embedded in his or her thinking and rationale for decision making. The researcher uses an inductive method in data gathering, regardless of whether the interview method is open, structured, or semi-structured. That is, the researcher does not wish to superimpose his or her own viewpoints onto the person being interviewed. Rather, inductively, the researcher wishes to understand the participant's perceptions, helping him or her to articulate percepts such that they will be understood clearly by the journal reader.

Genres and Uses

Focus groups:.

• "Focus Groups." Annual Review of Sociology 22 (1996): 129-1524.by David L. Morgan  Discusses the use of focus groups and group interviews as methods for gathering qualitative data used by sociologists and other academic and applied researchers. Focus groups are recommended for giving voice to marginalized groups and revealing the group effect on opinion formation.  
• Qualitative Research Methods: A Data Collector's Field Guide (See Module 4: "Focus Groups")by Mack, N., et al.  This field guide is based on an approach to doing team-based, collaborative qualitative research that has repeatedly proven successful in research projects sponsored by Family Health International (FHI) throughout the developing world. With its straightforward delivery of information on the main qualitative methods being used in public health research today, the guide speaks to the need for simple yet effective instruction on how to do systematic and ethically sound qualitative research. The aim of the guide is thus practical. In bypassing extensive discussion on the theoretical underpinnings of qualitative research, it distinguishes itself as a how-to guide to be used in the field.

In-Depth (typically One-on-One):

• A Practical Introduction to in-Depth Interviewingby Alan Morris  Are you new to qualitative research or a bit rusty and in need of some inspiration? Are you doing a research project involving in-depth interviews? Are you nervous about carrying out your interviews? This book will help you complete your qualitative research project by providing a nuts and bolts introduction to interviewing. With coverage of ethics, preparation strategies and advice for handling the unexpected in the field, this handy guide will help you get to grips with the basics of interviewing before embarking on your research. While recognising that your research question and the context of your research will drive your approach to interviewing, this book provides practical advice often skipped in traditional methods textbooks.  
• Qualitative Research Methods: A Data Collector's Field Guide (See Module 3: "In-Depth Interviews")by Mack, N., et al.  This field guide is based on an approach to doing team-based, collaborative qualitative research that has repeatedly proven successful in research projects sponsored by Family Health International (FHI) throughout the developing world. With its straightforward delivery of information on the main qualitative methods being used in public health research today, the guide speaks to the need for simple yet effective instruction on how to do systematic and ethically sound qualitative research. The aim of the guide is thus practical. In bypassing extensive discussion on the theoretical underpinnings of qualitative research, it distinguishes itself as a how-to guide to be used in the field.

Folklore Research and Oral Histories:

In addition to the following resource, see the  Oral History   page of this guide for helpful resources on Oral History interviewing.

American Folklife Center at the Library of Congress. Folklife and Fieldwork: A Layman’s Introduction to Field Techniques Interviews gathered for purposes of folklore research are similar to standard social science interviews in some ways, but also have a good deal in common with oral history approaches to interviewing. The focus in a folklore research interview is on documenting and trying to understand the interviewee's way of life relative to a culture or subculture you are studying. This guide includes helpful advice and tips for conducting fieldwork in folklore, such as tips for planning, conducting, recording, and archiving interviews.

An interdisciplinary scientific program within the Institute for Quantitative Social Science which encourages and facilitates research and instruction in the theory and practice of survey research. The primary mission of PSR is to provide survey research resources to enhance the quality of teaching and research at Harvard.

• Internet, Phone, Mail, and Mixed-Mode Surveysby Don A. Dillman; Jolene D. Smyth; Leah Melani Christian  The classic survey design reference, updated for the digital age. The new edition is thoroughly updated and revised, and covers all aspects of survey research. It features expanded coverage of mobile phones, tablets, and the use of do-it-yourself surveys, and Dillman's unique Tailored Design Method is also thoroughly explained. This new edition is complemented by copious examples within the text and accompanying website. It includes: Strategies and tactics for determining the needs of a given survey, how to design it, and how to effectively administer it. How and when to use mail, telephone, and Internet surveys to maximum advantage. Proven techniques to increase response rates. Guidance on how to obtain high-quality feedback from mail, electronic, and other self-administered surveys. Direction on how to construct effective questionnaires, including considerations of layout. The effects of sponsorship on the response rates of surveys. Use of capabilities provided by newly mass-used media: interactivity, presentation of aural and visual stimuli. The Fourth Edition reintroduces the telephone--including coordinating land and mobile.

User Experience (UX) and Marketing:

• See the  "UX & Market Research Interviews"  tab on this guide, above. May include  Focus Groups,  above.

Screening for Research Site Selection:

• Research interviews are used not only to furnish research data for theoretical analysis in the social sciences, but also to plan other kinds of studies. For example, interviews may allow researchers to screen appropriate research sites to conduct empirical studies (such as randomized controlled trials) in a variety of fields, from medicine to law. In contrast to interviews conducted in the course of social research, such interviews do not typically serve as the data for final analysis and publication.

ENGAGING PARTICIPANTS

Research ethics  .

• Human Subjects (IRB) The Committee on the Use of Human Subjects (CUHS) serves as the Institutional Review Board for the University area which includes the Cambridge and Allston campuses at Harvard. Find your IRB  contact person , or learn about  required ethics training.  You may also find the  IRB Lifecycle Guide  helpful. This is the preferred IRB portal for Harvard graduate students and other researchers. IRB forms can be downloaded via the  ESTR Library  (click on the "Templates and Forms" tab, then navigate to pages 2 and 3 to find the documents labelled with “HUA” for the Harvard University Area IRB. Nota bene: You may use these forms only if you submit your study to the Harvard University IRB). The IRB office can be reached through email at [email protected] or by telephone at (617) 496-2847.  
• Undergraduate Research Training Program (URTP) Portal The URTP at Harvard University is a comprehensive platform to create better prepared undergraduate researchers. The URTP is comprised of research ethics training sessions, a student-focused curriculum, and an online decision form that will assist students in determining whether their project requires IRB review. Students should examine the  URTP's guide for student researchers: Introduction to Human Subjects Research Protection.  
• Ethics reports From the Association of Internet Researchers (AoIR)  
• Respect, Beneficence, and Justice: QDR General Guidance for Human Participants If you are hoping to share your qualitative interview data in a repository after it has been collected, you will need to plan accordingly via informed consent, careful de-identification procedures, and data access controls. Consider  consulting with the Qualitative Research Support Group at Harvard Library  and consulting with  Harvard's Dataverse contacts  to help you think through all of the contingencies and processes.  
• "Conducting a Qualitative Child Interview: Methodological Considerations." Journal of Advanced Nursing 42/5 (2003): 434-441 by Kortesluoma, R., et al.  The purpose of this article is to illustrate the theoretical premises of child interviewing, as well as to describe some practical methodological solutions used during interviews. Factors that influence data gathered from children and strategies for taking these factors into consideration during the interview are also described.  
• "Crossing Cultural Barriers in Research Interviewing." Qualitative Social Work 63/3 (2007): 353-372 by Sands, R., et al.  This article critically examines a qualitative research interview in which cultural barriers between a white non-Muslim female interviewer and an African American Muslim interviewee, both from the USA, became evident and were overcome within the same interview.  
• Decolonizing Methodologies: Research and Indigenous Peoples by Linda Tuhiwai Smith  This essential volume explores intersections of imperialism and research - specifically, the ways in which imperialism is embedded in disciplines of knowledge and tradition as 'regimes of truth.' Concepts such as 'discovery' and 'claiming' are discussed and an argument presented that the decolonization of research methods will help to reclaim control over indigenous ways of knowing and being. The text includes case-studies and examples, and sections on new indigenous literature and the role of research in indigenous struggles for social justice.  

This resource, sponsored by University of Oregon Libraries, exemplifies the use of interviewing methodologies in research that foregrounds traditional knowledge. The methodology page summarizes the approach.

• Ethics: The Need to Tread Carefully. Chapter in A Practical Introduction to in-Depth Interviewing by Alan Morris  Pay special attention to the sections in chapter 2 on "How to prevent and respond to ethical issues arising in the course of the interview," "Ethics in the writing up of your interviews," and "The Ethics of Care."  
• Handbook on Ethical Issues in Anthropology by Joan Cassell (Editor); Sue-Ellen Jacobs (Editor)  This publication of the American Anthropological Association presents and discusses issues and sources on ethics in anthropology, as well as realistic case studies of ethical dilemmas. It is meant to help social science faculty introduce discussions of ethics in their courses. Some of the topics are relevant to interviews, or at least to studies of which interviews are a part. See chapters 3 and 4 for cases, with solutions and commentary, respectively.  
• Research Ethics from the Chanie Wenjack School for Indigenous Studies, Trent University  (Open Access) An overview of Indigenous research ethics and protocols from the across the globe.  
• Resources for Equity in Research Consult these resources for guidance on creating and incorporating equitable materials into public health research studies that entail community engagement.

The SAGE Handbook of Qualitative Research Ethics by Ron Iphofen (Editor); Martin Tolich (Editor)  This handbook is a much-needed and in-depth review of the distinctive set of ethical considerations which accompanies qualitative research. This is particularly crucial given the emergent, dynamic and interactional nature of most qualitative research, which too often allows little time for reflection on the important ethical responsibilities and obligations. Contributions from leading international researchers have been carefully organized into six key thematic sections: Part One: Thick Descriptions Of Qualitative Research Ethics; Part Two: Qualitative Research Ethics By Technique; Part Three: Ethics As Politics; Part Four: Qualitative Research Ethics With Vulnerable Groups; Part Five: Relational Research Ethics; Part Six: Researching Digitally. This Handbook is a one-stop resource on qualitative research ethics across the social sciences that draws on the lessons learned and the successful methods for surmounting problems - the tried and true, and the new.

RESEARCH COMPLIANCE AND PRIVACY LAWS

Research Compliance Program for FAS/SEAS at Harvard : The Faculty of Arts and Sciences (FAS), including the School of Engineering and Applied Sciences (SEAS), and the Office of the Vice Provost for Research (OVPR) have established a shared Research Compliance Program (RCP). An area of common concern for interview studies is international projects and collaboration . RCP is a resource to provide guidance on which international activities may be impacted by US sanctions on countries, individuals, or entities and whether licenses or other disclosure are required to ship or otherwise share items, technology, or data with foreign collaborators.

• Harvard Global Support Services (GSS) is for students, faculty, staff, and researchers who are studying, researching, or working abroad. Their services span safety and security, health, culture, outbound immigration, employment, financial and legal matters, and research center operations. These include travel briefings and registration, emergency response, guidance on international projects, and managing in-country operations.

Generative AI: Harvard-affiliated researchers should not enter data classified as confidential ( Level 2 and above ), including non-public research data, into publicly-available generative AI tools, in accordance with the University’s Information Security Policy. Information shared with generative AI tools using default settings is not private and could expose proprietary or sensitive information to unauthorized parties.

Privacy Laws: Be mindful of any potential privacy laws that may apply wherever you conduct your interviews. The General Data Protection Regulation is a high-profile example (see below):

• General Data Protection Regulation (GDPR) This Regulation lays down rules relating to the protection of natural persons with regard to the processing of personal data and rules relating to the free movement of personal data. It protects fundamental rights and freedoms of natural persons and in particular their right to the protection of personal data. The free movement of personal data within the Union shall be neither restricted nor prohibited for reasons connected with the protection of natural persons with regard to the processing of personal data. For a nice summary of what the GDPR requires, check out the GDPR "crash course" here .

SEEKING CONSENT  

If you would like to see examples of consent forms, ask your local IRB, or take a look at these resources:

• Model consent forms for oral history, suggested by the Centre for Oral History and Digital Storytelling at Concordia University  
• For NIH-funded research, see this  resource for developing informed consent language in research studies where data and/or biospecimens will be stored and shared for future use.

POPULATION SAMPLING

If you wish to assemble resources to aid in sampling, such as the USPS Delivery Sequence File, telephone books, or directories of organizations and listservs, please contact our  data librarian  or write to  [email protected] .

• Research Randomizer   A free web-based service that permits instant random sampling and random assignment. It also contains an interactive tutorial perfect for students taking courses in research methods.  
• Practical Tools for Designing and Weighting Survey Samples by Richard Valliant; Jill A. Dever; Frauke Kreuter  Survey sampling is fundamentally an applied field. The goal in this book is to put an array of tools at the fingertips of practitioners by explaining approaches long used by survey statisticians, illustrating how existing software can be used to solve survey problems, and developing some specialized software where needed. This book serves at least three audiences: (1) Students seeking a more in-depth understanding of applied sampling either through a second semester-long course or by way of a supplementary reference; (2) Survey statisticians searching for practical guidance on how to apply concepts learned in theoretical or applied sampling courses; and (3) Social scientists and other survey practitioners who desire insight into the statistical thinking and steps taken to design, select, and weight random survey samples. Several survey data sets are used to illustrate how to design samples, to make estimates from complex surveys for use in optimizing the sample allocation, and to calculate weights. Realistic survey projects are used to demonstrate the challenges and provide a context for the solutions. The book covers several topics that either are not included or are dealt with in a limited way in other texts. These areas include: sample size computations for multistage designs; power calculations related to surveys; mathematical programming for sample allocation in a multi-criteria optimization setting; nuts and bolts of area probability sampling; multiphase designs; quality control of survey operations; and statistical software for survey sampling and estimation. An associated R package, PracTools, contains a number of specialized functions for sample size and other calculations. The data sets used in the book are also available in PracTools, so that the reader may replicate the examples or perform further analyses.  
• Sampling: Design and Analysis by Sharon L. Lohr  Provides a modern introduction to the field of sampling. With a multitude of applications from a variety of disciplines, the book concentrates on the statistical aspects of taking and analyzing a sample. Overall, the book gives guidance on how to tell when a sample is valid or not, and how to design and analyze many different forms of sample surveys.  
• Sampling Techniques by William G. Cochran  Clearly demonstrates a wide range of sampling methods now in use by governments, in business, market and operations research, social science, medicine, public health, agriculture, and accounting. Gives proofs of all the theoretical results used in modern sampling practice. New topics in this edition include the approximate methods developed for the problem of attaching standard errors or confidence limits to nonlinear estimates made from the results of surveys with complex plans.  
• "Understanding the Process of Qualitative Data Collection" in Chapter 13 (pp. 103–1162) of 30 Essential Skills for the Qualitative Researcher by John W. Creswell  Provides practical "how-to" information for beginning researchers in the social, behavioral, and health sciences with many applied examples from research design, qualitative inquiry, and mixed methods.The skills presented in this book are crucial for a new qualitative researcher starting a qualitative project.  
• Survey Methodology by Robert M. Groves; Floyd J. Fowler; Mick P. Couper; James M. Lepkowski; Eleanor Singer; Roger Tourangeau; Floyd J. Fowler  coverage includes sampling frame evaluation, sample design, development of questionnaires, evaluation of questions, alternative modes of data collection, interviewing, nonresponse, post-collection processing of survey data, and practices for maintaining scientific integrity.

The way a qualitative researcher constructs and approaches interview questions should flow from, or align with, the methodological paradigm chosen for the study, whether that paradigm is interpretivist, critical, positivist, or participative in nature (or a combination of these).

Constructing Your Questions

Helpful texts:.

• "Developing Questions" in Chapter 4 (pp. 98–108) of Becoming Qualitative Researchers by Corrine Glesne  Ideal for introducing the novice researcher to the theory and practice of qualitative research, this text opens students to the diverse possibilities within this inquiry approach, while helping them understand how to design and implement specific research methods.  
• "Learning to Interview in the Social Sciences" Qualitative Inquiry, 9(4) 2003, 643–668 by Roulston, K., deMarrais, K., & Lewis, J. B. See especially the section on "Phrasing and Negotiating Questions" on pages 653-655 and common problems with framing questions noted on pages 659 - 660.  
• Qualitative Research Interviewing: Biographic Narrative and Semi-Structured Methods (See sections on “Lightly and Heavily Structured Depth Interviewing: Theory-Questions and Interviewer-Questions” and “Preparing for any Interviewing Sequence") by Tom Wengraf  Unique in its conceptual coherence and the level of practical detail, this book provides a comprehensive resource for those concerned with the practice of semi-structured interviewing, the most commonly used interview approach in social research, and in particular for in-depth, biographic narrative interviewing. It covers the full range of practices from the identification of topics through to strategies for writing up research findings in diverse ways.  
• "Scripting a Qualitative Purpose Statement and Research Questions" in Chapter 12 (pp. 93–102) of 30 Essential Skills for the Qualitative Researcher by John W. Creswell  Provides practical "how-to" information for beginning researchers in the social, behavioral, and health sciences with many applied examples from research design, qualitative inquiry, and mixed methods.The skills presented in this book are crucial for a new qualitative researcher starting a qualitative project.  
• Some Strategies for Developing Interview Guides for Qualitative Interviews by Sociology Department, Harvard University Includes general advice for conducting qualitative interviews, pros and cons of recording and transcription, guidelines for success, and tips for developing and phrasing effective interview questions.  
• Tip Sheet on Question Wording by Harvard University Program on Survey Research

Let Theory Guide You:

The quality of your questions depends on how you situate them within a wider body of knowledge. Consider the following advice:

A good literature review has many obvious virtues. It enables the investigator to define problems and assess data. It provides the concepts on which percepts depend. But the literature review has a special importance for the qualitative researcher. This consists of its ability to sharpen his or her capacity for surprise (Lazarsfeld, 1972b). The investigator who is well versed in the literature now has a set of expectations the data can defy. Counterexpectational data are conspicuous, readable, and highly provocative data. They signal the existence of unfulfilled theoretical assumptions, and these are, as Kuhn (1962) has noted, the very origins of intellectual innovation. A thorough review of the literature is, to this extent, a way to manufacture distance. It is a way to let the data of one's research project take issue with the theory of one's field.

McCracken, G. (1988), The Long Interview, Sage: Newbury Park, CA, p. 31

When drafting your interview questions, remember that everything follows from your central research question. Also, on the way to writing your "operationalized" interview questions, it's  helpful to draft broader, intermediate questions, couched in theory. Nota bene:  While it is important to know the literature well before conducting your interview(s), be careful not to present yourself to your research participant(s) as "the expert," which would be presumptuous and could be intimidating. Rather, the purpose of your knowledge is to make you a better, keener listener.

If you'd like to supplement what you learned about relevant theories through your coursework and literature review, try these sources:

• Annual Reviews   Review articles sum up the latest research in many fields, including social sciences, biomedicine, life sciences, and physical sciences. These are timely collections of critical reviews written by leading scientists.  
• HOLLIS - search for resources on theories in your field   Modify this example search by entering the name of your field in place of "your discipline," then hit search.  
• Oxford Bibliographies   Written and reviewed by academic experts, every article in this database is an authoritative guide to the current scholarship in a variety of fields, containing original commentary and annotations.  
• ProQuest Dissertations & Theses (PQDT)   Indexes dissertations and masters' theses from most North American graduate schools as well as some European universities. Provides full text for most indexed dissertations from 1990-present.  
• Very Short Introductions   Launched by Oxford University Press in 1995, Very Short Introductions offer concise introductions to a diverse range of subjects from Climate to Consciousness, Game Theory to Ancient Warfare, Privacy to Islamic History, Economics to Literary Theory.

CONDUCTING INTERVIEWS

Equipment and software:  .

• Lamont Library  loans microphones and podcast starter kits, which will allow you to capture audio (and you may record with software, such as Garage Band). 
• Cabot Library  loans digital recording devices, as well as USB microphones.

If you prefer to use your own device, you may purchase a small handheld audio recorder, or use your cell phone.

• Audio Capture Basics (PDF)  - Helpful instructions, courtesy of the Lamont Library Multimedia Lab.
• Getting Started with Podcasting/Audio:  Guidelines from Harvard Library's Virtual Media Lab for preparing your interviewee for a web-based recording (e.g., podcast, interview)
• ​ Camtasia Screen Recorder and Video Editor
• Zoom: Video Conferencing, Web Conferencing
• Visit the Multimedia Production Resources guide! Consult it to find and learn how to use audiovisual production tools, including: cameras, microphones, studio spaces, and other equipment at Cabot Science Library and Lamont Library.
• Try the virtual office hours offered by the Lamont Multimedia Lab!

TIPS FOR CONDUCTING INTERVIEWS

Quick handout:  .

• Research Interviewing Tips (Courtesy of Dr. Suzanne Spreadbury)

Remote Interviews:  

• For Online or Distant Interviews, See "Remote Research & Virtual Fieldwork" on this guide .  
• Deborah Lupton's Bibliography: Doing Fieldwork in a Pandemic

Seeking Consent:

Books and articles:  .

• "App-Based Textual Interviews: Interacting With Younger Generations in a Digitalized Social Reallity."International Journal of Social Research Methodology (12 June 2022). Discusses the use of texting platforms as a means to reach young people. Recommends useful question formulations for this medium.  
• "Learning to Interview in the Social Sciences." Qualitative Inquiry, 9(4) 2003, 643–668 by Roulston, K., deMarrais, K., & Lewis, J. B. See especially the section on "Phrasing and Negotiating Questions" on pages 653-655 and common problems with framing questions noted on pages 659-660.  
• "Slowing Down and Digging Deep: Teaching Students to Examine Interview Interaction in Depth." LEARNing Landscapes, Spring 2021 14(1) 153-169 by Herron, Brigette A. and Kathryn Roulston. Suggests analysis of videorecorded interviews as a precursor to formulating one's own questions. Includes helpful types of probes.  
• Using Interviews in a Research Project by Nigel Joseph Mathers; Nicholas J Fox; Amanda Hunn; Trent Focus Group.  A work pack to guide researchers in developing interviews in the healthcare field. Describes interview structures, compares face-to-face and telephone interviews. Outlines the ways in which different types of interview data can be analysed.  
• “Working through Challenges in Doing Interview Research.” International Journal of Qualitative Methods, (December 2011), 348–66 by Roulston, Kathryn.  The article explores (1) how problematic interactions identified in the analysis of focus group data can lead to modifications in research design, (2) an approach to dealing with reported data in representations of findings, and (3) how data analysis can inform question formulation in successive rounds of data generation. Findings from these types of examinations of interview data generation and analysis are valuable for informing both interview practice as well as research design.

Videos:  

The way a qualitative researcher transcribes interviews should flow from, or align with, the methodological paradigm chosen for the study, whether that paradigm is interpretivist, critical, positivist, or participative in nature (or a combination of these).

TRANSCRIPTION

Before embarking on a transcription project, it's worthwhile to invest in the time and effort necessary to capture good audio, which will make the transcription process much easier. If you haven't already done so, check out the  audio capture guidelines from Harvard Library's Virtual Media Lab , or  contact a media staff member  for customized recommendations. First and foremost, be mindful of common pitfalls by watching this short video that identifies  the most common errors to avoid!

SOFTWARE:  

• Adobe Premiere Pro Speech-To-Text  automatically generates transcripts and adds captions to your videos. Harvard affiliates can download Adobe Premiere in the Creative Cloud Suite.  
• GoTranscript  provides cost-effective human-generated transcriptions.  
• pyTranscriber  is an app for generating automatic transcription and/or subtitles for audio and video files. It uses the Google Cloud Speech-to-Text service, has a friendly graphical user interface, and is purported to work nicely with Chinese.   
• Otter  provides a new way to capture, store, search and share voice conversations, lectures, presentations, meetings, and interviews. The startup is based in Silicon Valley with a team of experienced Ph.Ds and engineers from Google, Facebook, Yahoo and Nuance (à la Dragon). Free accounts available. This is the software that  Zoom  uses to generate automated transcripts, so if you have access to a Zoom subscription, you have access to Otter transcriptions with it (applicable in several  languages ). As with any automated approach, be prepared to correct any errors after the fact, by hand.  
• Panopto  is available to Harvard affiliates and generates  ASR (automated speech recognition) captions . You may upload compatible audio files into it. As with any automatically generated transcription, you will need to make manual revisions. ASR captioning is available in several  languages . Panopto maintains robust security practices, including strong authentication measures and end-to-end encryption, ensuring your content remains private and protected.  
• REV.Com  allows you to record and transcribe any calls on the iPhone, both outgoing and incoming. It may be useful for recording phone interviews. Rev lets you choose whether you want an AI- or human-generated transcription, with a fast turnaround. Rev has Service Organization Controls Type II (SOC2) certification (a SOC2 cert looks at and verifies an organization’s processing integrity, privacy practices, and security safeguards).   
• Scribie Audio/Video Transcription  provides automated or manual transcriptions for a small fee. As with any transcription service, some revisions will be necessary after the fact, particularly for its automated transcripts.  
• Sonix  automatically transcribes, translates, and helps to organize audio and video files in over 40 languages. It's fast and affordable, with good accuracy. The free trial includes 30 minutes of free transcription.  
• TranscriptionWing  uses a human touch process to clean up machine-generated transcripts so that the content will far more accurately reflect your audio recording.   
• Whisper is a tool from OpenAI that facilitates transcription of sensitive audiovisual recordings (e.g., of research interviews) on your own device. Installation and use depends on your operating system and which version you install. Important Note: The Whisper API, where audio is sent to OpenAI to be processed by them and then sent back (usually through a programming language like Python) is NOT appropriate for sensitive data. The model should be downloaded with tools such as those described in this FAQ , so that audio is kept to your local machine. For assistance, contact James Capobianco .

EQUIPMENT:  

• Transcription pedals  are in circulation and available to borrow from the Circulation desk at Lamont, or use at Lamont Library's Media Lab on level B. For hand-transcribing your interviews, they work in conjunction with software such as  Express Scribe , which is loaded on Media Lab computers, or you may download for free on your own machine (Mac or PC versions; scroll down the downloads page for the latter). The pedals are plug-and-play USB, allow a wide range of playback speeds, and have 3 programmable buttons, which are typically set to rewind/play/fast-forward. Instructions are included in the bag that covers installation and set-up of the software, and basic use of the pedals.

NEED HELP?  

• Try the virtual office hours offered by the Lamont Multimedia Lab!    
• If you're creating podcasts, login to  Canvas  and check out the  Podcasting/Audio guide . 

Helpful Texts:  

• "Transcription as a Crucial Step of Data Analysis" in Chapter 5 of The SAGE Handbook of Qualitative Data Analysisby Uwe Flick (Editor)  Covers basic terminology for transcription, shares caveats for transcribers, and identifies components of vocal behavior. Provides notation systems for transcription, suggestions for transcribing turn-taking, and discusses new technologies and perspectives. Includes a bibliography for further reading.  
• "Transcribing the Oral Interview: Part Art, Part Science " on p. 10 of the Centre for Community Knowledge (CCK) newsletter: TIMESTAMPby Mishika Chauhan and Saransh Srivastav

QUALITATIVE DATA ANALYSIS

Software  .

• Free download available for Harvard Faculty of Arts and Sciences (FAS) affiliates
• Desktop access at Lamont Library Media Lab, 3rd floor
• Desktop access at Harvard Kennedy School Library (with HKS ID)
• Remote desktop access for Harvard affiliates from  IQSS Computer Labs . Email them at  [email protected] and ask for a new lab account and remote desktop access to NVivo.
• Virtual Desktop Infrastructure (VDI) access available to Harvard T.H. Chan School of Public Health affiliates

CODING AND THEMEING YOUR DATA

Data analysis methods should flow from, or align with, the methodological paradigm chosen for your study, whether that paradigm is interpretivist, critical, positivist, or participative in nature (or a combination of these). Some established methods include Content Analysis, Critical Analysis, Discourse Analysis, Gestalt Analysis, Grounded Theory Analysis, Interpretive Analysis, Narrative Analysis, Normative Analysis, Phenomenological Analysis, Rhetorical Analysis, and Semiotic Analysis, among others. The following resources should help you navigate your methodological options and put into practice methods for coding, themeing, interpreting, and presenting your data.

• Users can browse content by topic, discipline, or format type (reference works, book chapters, definitions, etc.). SRM offers several research tools as well: a methods map, user-created reading lists, a project planner, and advice on choosing statistical tests.  
• Abductive Coding: Theory Building and Qualitative (Re)Analysis by Vila-Henninger, et al.  The authors recommend an abductive approach to guide qualitative researchers who are oriented towards theory-building. They outline a set of tactics for abductive analysis, including the generation of an abductive codebook, abductive data reduction through code equations, and in-depth abductive qualitative analysis.  
• Analyzing and Interpreting Qualitative Research: After the Interview by Charles F. Vanover, Paul A. Mihas, and Johnny Saldana (Editors)   Providing insight into the wide range of approaches available to the qualitative researcher and covering all steps in the research process, the authors utilize a consistent chapter structure that provides novice and seasoned researchers with pragmatic, "how-to" strategies. Each chapter author introduces the method, uses one of their own research projects as a case study of the method described, shows how the specific analytic method can be used in other types of studies, and concludes with three questions/activities to prompt class discussion or personal study.   
• "Analyzing Qualitative Data." Theory Into Practice 39, no. 3 (2000): 146-54 by Margaret D. LeCompte   This article walks readers though rules for unbiased data analysis and provides guidance for getting organized, finding items, creating stable sets of items, creating patterns, assembling structures, and conducting data validity checks.  
• "Coding is Not a Dirty Word" in Chapter 1 (pp. 1–30) of Enhancing Qualitative and Mixed Methods Research with Technology by Shalin Hai-Jew (Editor)   Current discourses in qualitative research, especially those situated in postmodernism, represent coding and the technology that assists with coding as reductive, lacking complexity, and detached from theory. In this chapter, the author presents a counter-narrative to this dominant discourse in qualitative research. The author argues that coding is not necessarily devoid of theory, nor does the use of software for data management and analysis automatically render scholarship theoretically lightweight or barren. A lack of deep analytical insight is a consequence not of software but of epistemology. Using examples informed by interpretive and critical approaches, the author demonstrates how NVivo can provide an effective tool for data management and analysis. The author also highlights ideas for critical and deconstructive approaches in qualitative inquiry while using NVivo. By troubling the positivist discourse of coding, the author seeks to create dialogic spaces that integrate theory with technology-driven data management and analysis, while maintaining the depth and rigor of qualitative research.   
• The Coding Manual for Qualitative Researchers by Johnny Saldana   An in-depth guide to the multiple approaches available for coding qualitative data. Clear, practical and authoritative, the book profiles 32 coding methods that can be applied to a range of research genres from grounded theory to phenomenology to narrative inquiry. For each approach, Saldaña discusses the methods, origins, a description of the method, practical applications, and a clearly illustrated example with analytic follow-up. Essential reading across the social sciences.  
• Flexible Coding of In-depth Interviews: A Twenty-first-century Approach by Nicole M. Deterding and Mary C. Waters The authors suggest steps in data organization and analysis to better utilize qualitative data analysis technologies and support rigorous, transparent, and flexible analysis of in-depth interview data.  
• From the Editors: What Grounded Theory is Not by Roy Suddaby Walks readers through common misconceptions that hinder grounded theory studies, reinforcing the two key concepts of the grounded theory approach: (1) constant comparison of data gathered throughout the data collection process and (2) the determination of which kinds of data to sample in succession based on emergent themes (i.e., "theoretical sampling").  
• “Good enough” methods for life-story analysis, by Wendy Luttrell. In Quinn N. (Ed.), Finding culture in talk (pp. 243–268). Demonstrates for researchers of culture and consciousness who use narrative how to concretely document reflexive processes in terms of where, how and why particular decisions are made at particular stages of the research process.   
• The Ethnographic Interview by James P. Spradley  “Spradley wrote this book for the professional and student who have never done ethnographic fieldwork (p. 231) and for the professional ethnographer who is interested in adapting the author’s procedures (p. iv) ... Steps 6 and 8 explain lucidly how to construct a domain and a taxonomic analysis” (excerpted from book review by James D. Sexton, 1980). See also:  Presentation slides on coding and themeing your data, derived from Saldana, Spradley, and LeCompte Click to request access.  
• Qualitative Data Analysis by Matthew B. Miles; A. Michael Huberman   A practical sourcebook for researchers who make use of qualitative data, presenting the current state of the craft in the design, testing, and use of qualitative analysis methods. Strong emphasis is placed on data displays matrices and networks that go beyond ordinary narrative text. Each method of data display and analysis is described and illustrated.  
• "A Survey of Qualitative Data Analytic Methods" in Chapter 4 (pp. 89–138) of Fundamentals of Qualitative Research by Johnny Saldana   Provides an in-depth introduction to coding as a heuristic, particularly focusing on process coding, in vivo coding, descriptive coding, values coding, dramaturgical coding, and versus coding. Includes advice on writing analytic memos, developing categories, and themeing data.   
• "Thematic Networks: An Analytic Tool for Qualitative Research." Qualitative Research : QR, 1(3), 385–405 by Jennifer Attride-Stirling Details a technique for conducting thematic analysis of qualitative material, presenting a step-by-step guide of the analytic process, with the aid of an empirical example. The analytic method presented employs established, well-known techniques; the article proposes that thematic analyses can be usefully aided by and presented as thematic networks.  
• Using Thematic Analysis in Psychology by Virginia Braun and Victoria Clark Walks readers through the process of reflexive thematic analysis, step by step. The method may be adapted in fields outside of psychology as relevant. Pair this with One Size Fits All? What Counts as Quality Practice in Reflexive Thematic Analysis? by Virginia Braun and Victoria Clark

TESTING OR GENERATING THEORIES

The quality of your data analysis depends on how you situate what you learn within a wider body of knowledge. Consider the following advice:

Once you have coalesced around a theory, realize that a theory should  reveal  rather than  color  your discoveries. Allow your data to guide you to what's most suitable. Grounded theory  researchers may develop their own theory where current theories fail to provide insight.  This guide on Theoretical Models  from Alfaisal University Library provides a helpful overview on using theory.

MANAGING & FINDING INTERVIEW DATA

Managing your elicited interview data, general guidance:  .

• Research Data Management @ Harvard A reference guide with information and resources to help you manage your research data. See also: Harvard Research Data Security Policy , on the Harvard University Research Data Management website.  
• Data Management For Researchers: Organize, Maintain and Share Your Data for Research Success by Kristin Briney. A comprehensive guide for scientific researchers providing everything they need to know about data management and how to organize, document, use and reuse their data.  
• Open Science Framework (OSF) An open-source project management tool that makes it easy to collaborate within and beyond Harvard throughout a project's lifecycle. With OSF you can manage, store, and share documents, datasets, and other information with your research team. You can also publish your work to share it with a wider audience. Although data can be stored privately, because this platform is hosted on the Internet and designed with open access in mind, it is not a good choice for highly sensitive data.  
• Free cloud storage solutions for Harvard affiliates to consider include:  Google Drive ,  DropBox , or  OneDrive ( up to DSL3 )  

Data Confidentiality and Secure Handling:  

• Data Security Levels at Harvard - Research Data Examples This resource provided by Harvard Data Security helps you determine what level of access is appropriate for your data. Determine whether it should be made available for public use, limited to the Harvard community, or be protected as either "confidential and sensitive," "high risk," or "extremely sensitive." See also:  Harvard Data Classification Table  
• Harvard's Best Practices for Protecting Privacy and  Harvard Information Security Collaboration Tools Matrix Follow the nuts-and-bolts advice for privacy best practices at Harvard. The latter resource reveals the level of security that can be relied upon for a large number of technological tools and platforms used at Harvard to conduct business, such as email, Slack, Accellion Kiteworks, OneDrive/SharePoint, etc.  
• “Protecting Participant Privacy While Maintaining Content and Context: Challenges in Qualitative Data De‐identification and Sharing.” Proceedings of the ASIST Annual Meeting 57 (1) (2020): e415-420 by Myers, Long, and Polasek Presents an informed and tested protocol, based on the De-Identification guidelines published by the Qualitative Data Repository (QDR) at Syracuse University. Qualitative researchers may consult it to guide their data de-identification efforts.  
• QDS Qualitative Data Sharing Toolkit The Qualitative Data Sharing (QDS) project and its toolkit was funded by the NIH National Human Genome Research Institute (R01HG009351). It provides tools and resources to help researchers, especially those in the health sciences, share qualitative research data while protecting privacy and confidentiality. It offers guidance on preparing data for sharing through de-identification and access control. These health sciences research datasets in ICPSR's Qualitative Data Sharing (QDS) Project Series were de-identified using the QuaDS Software and the project’s QDS guidelines.  
• Table of De-Identification Techniques  
• Generative AI Harvard-affiliated researchers should not enter data classified as confidential ( Level 2 and above ), including non-public research data, into publicly-available generative AI tools, in accordance with the University’s Information Security Policy. Information shared with generative AI tools using default settings is not private and could expose proprietary or sensitive information to unauthorized parties.  
• Harvard Information Security Quick Reference Guide Storage guidelines, based on the data's security classification level (according to its IRB classification) is displayed on page 2, under "handling."  
• Email Encryption Harvard Microsoft 365 users can now send encrypted messages and files directly from the Outlook web or desktop apps. Encrypting an email adds an extra layer of security to the message and its attachments (up to 150MB), and means only the intended recipient (and their inbox delegates with full access) can view it. Message encryption in Outlook is approved for sending high risk ( level 4 ) data and below.  

Sharing Qualitative Data:  

• Repositories for Qualitative Data If you have cleared this intention with your IRB, secured consent from participants, and properly de-identified your data, consider sharing your interviews in one of the data repositories included in the link above. Depending on the nature of your research and the level of risk it may present to participants, sharing your interview data may not be appropriate. If there is any chance that sharing such data will be desirable, you will be much better off if you build this expectation into your plans from the beginning.  
• Guide for Sharing Qualitative Data at ICPSR The Inter-university Consortium for Political and Social Research (ICPSR) has created this resource for investigators planning to share qualitative data at ICPSR. This guide provides an overview of elements and considerations for archiving qualitative data, identifies steps for investigators to follow during the research life cycle to ensure that others can share and reuse qualitative data, and provides information about exemplars of qualitative data  

International Projects:

• Research Compliance Program for FAS/SEAS at Harvard The Faculty of Arts and Sciences (FAS), including the School of Engineering and Applied Sciences (SEAS), and the Office of the Vice Provost for Research (OVPR) have established a shared Research Compliance Program (RCP). An area of common concern for interview studies is international projects and collaboration . RCP is a resource to provide guidance on which international activities may be impacted by US sanctions on countries, individuals, or entities and whether licenses or other disclosure are required to ship or otherwise share items, technology, or data with foreign collaborators.

Finding Extant Interview Data

Finding journalistic interviews:  .

• Academic Search Premier This all-purpose database is great for finding articles from magazines and newspapers. In the Advanced Search, it allows you to specify "Document Type":  Interview.  
• Guide to Newspapers and Newspaper Indexes Use this guide created to Harvard Librarians to identify newspapers collections you'd like to search. To locate interviews, try adding the term  "interview"  to your search, or explore a database's search interface for options to  limit your search to interviews.  Nexis Uni  and  Factiva  are the two main databases for current news.   
• Listen Notes Search for podcast episodes at this podcast aggregator, and look for podcasts that include interviews. Make sure to vet the podcaster for accuracy and quality! (Listen Notes does not do much vetting.)  
• NPR  and  ProPublica  are two sites that offer high-quality long-form reporting, including journalistic interviews, for free.

Finding Oral History and Social Research Interviews:  

• To find oral histories, see the Oral History   page of this guide for helpful resources on Oral History interviewing.  
• Repositories for Qualitative Data It has not been a customary practice among qualitative researchers in the social sciences to share raw interview data, but some have made this data available in repositories, such as the ones listed on the page linked above. You may find published data from structured interview surveys (e.g., questionnaire-based computer-assisted telephone interview data), as well as some semi-structured and unstructured interviews.  
• If you are merely interested in studies interpreting data collected using interviews, rather than finding raw interview data, try databases like  PsycInfo ,  Sociological Abstracts , or  Anthropology Plus , among others. 

Finding Interviews in Archival Collections at Harvard Library:

In addition to the databases and search strategies mentioned under the  "Finding Oral History and Social Research Interviews" category above,  you may search for interviews and oral histories (whether in textual or audiovisual formats) held in archival collections at Harvard Library.

• HOLLIS searches all documented collections at Harvard, whereas HOLLIS for Archival Discovery searches only those with finding aids. Although HOLLIS for Archival Discovery covers less material, you may find it easier to parse your search results, especially when you wish to view results at the item level (within collections). Try these approaches:

Search in  HOLLIS :  

• To retrieve items available online, do an Advanced Search for  interview* OR "oral histor*" (in Subject), with Resource Type "Archives/Manuscripts," then refine your search by selecting "Online" under "Show Only" on the right of your initial result list.  Revise the search above by adding your topic in the Keywords or Subject field (for example:  African Americans ) and resubmitting the search.  
•  To enlarge your results set, you may also leave out the "Online" refinement; if you'd like to limit your search to a specific repository, try the technique of searching for  Code: Library + Collection on the "Advanced Search" page .   

Search in  HOLLIS for Archival Discovery :  

• To retrieve items available online, search for   interview* OR "oral histor*" limited to digital materials . Revise the search above by adding your topic (for example:  artist* ) in the second search box (if you don't see the box, click +).  
• To preview results by collection, search for  interview* OR "oral histor*" limited to collections . Revise the search above by adding your topic (for example:  artist* ) in the second search box (if you don't see the box, click +). Although this method does not allow you to isolate digitized content, you may find the refinement options on the right side of the screen (refine by repository, subject or names) helpful.  Once your select a given collection, you may search within it  (e.g., for your topic or the term interview).

UX & MARKET RESEARCH INTERVIEWS

Ux at harvard library  .

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• Interviewing Users: How to Uncover Compelling Insights by Steve Portigal; Grant McCracken (Foreword by)  Interviewing is a foundational user research tool that people assume they already possess. Everyone can ask questions, right? Unfortunately, that's not the case. Interviewing Users provides invaluable interviewing techniques and tools that enable you to conduct informative interviews with anyone. You'll move from simply gathering data to uncovering powerful insights about people.  
• Rapid Contextual Design by Jessamyn Wendell; Karen Holtzblatt; Shelley Wood  This handbook introduces Rapid CD, a fast-paced, adaptive form of Contextual Design. Rapid CD is a hands-on guide for anyone who needs practical guidance on how to use the Contextual Design process and adapt it to tactical projects with tight timelines and resources. Rapid Contextual Design provides detailed suggestions on structuring the project and customer interviews, conducting interviews, and running interpretation sessions. The handbook walks you step-by-step through organizing the data so you can see your key issues, along with visioning new solutions, storyboarding to work out the details, and paper prototype interviewing to iterate the design all with as little as a two-person team with only a few weeks to spare *Includes real project examples with actual customer data that illustrate how a CD project actually works.

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• Interview/Oral History Research for RSRA 298B: Master's Thesis Reading and Research (Spring 2023) Slideshow covers: Why Interviews?, Getting Context, Engaging Participants, Conducting the Interview, The Interview Guide, Note Taking, Transcription, File management, and Data Analysis.  
• Interview Skills From an online class on February 13, 2023:  Get set up for interview research. You will leave prepared to choose among the three types of interviewing methods, equipped to develop an interview schedule, aware of data management options and their ethical implications, and knowledgeable of technologies you can use to record and transcribe your interviews. This workshop complements Intro to NVivo, a qualitative data analysis tool useful for coding interview data.

NIH Data Management & Sharing Policy (DMSP) This policy, effective January 25, 2023, applies to all research, funded or conducted in whole or in part by NIH, that results in the generation of  scientific data , including NIH-funded qualitative research. Click here to see some examples of how the DMSP policy has been applied in qualitative research studies featured in the 2021 Qualitative Data Management Plan (DMP) Competition . As a resource for the community, NIH has developed a resource for developing informed consent language in research studies where data and/or biospecimens will be stored and shared for future use. It is important to note that the DMS Policy does NOT require that informed consent obtained from research participants must allow for broad sharing and the future use of data (either with or without identifiable private information). See the FAQ for more information.

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• Published: 15 September 2022

Interviews in the social sciences

• Eleanor Knott   ORCID: orcid.org/0000-0002-9131-3939 1 ,
• Aliya Hamid Rao   ORCID: orcid.org/0000-0003-0674-4206 1 ,
• Kate Summers   ORCID: orcid.org/0000-0001-9964-0259 1 &
• Chana Teeger   ORCID: orcid.org/0000-0002-5046-8280 1  

Nature Reviews Methods Primers volume  2 , Article number:  73 ( 2022 ) Cite this article

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• Interdisciplinary studies

In-depth interviews are a versatile form of qualitative data collection used by researchers across the social sciences. They allow individuals to explain, in their own words, how they understand and interpret the world around them. Interviews represent a deceptively familiar social encounter in which people interact by asking and answering questions. They are, however, a very particular type of conversation, guided by the researcher and used for specific ends. This dynamic introduces a range of methodological, analytical and ethical challenges, for novice researchers in particular. In this Primer, we focus on the stages and challenges of designing and conducting an interview project and analysing data from it, as well as strategies to overcome such challenges.

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Introduction.

In-depth interviews are a qualitative research method that follow a deceptively familiar logic of human interaction: they are conversations where people talk with each other, interact and pose and answer questions 1 . An interview is a specific type of interaction in which — usually and predominantly — a researcher asks questions about someone’s life experience, opinions, dreams, fears and hopes and the interview participant answers the questions 1 .

Interviews will often be used as a standalone method or combined with other qualitative methods, such as focus groups or ethnography, or quantitative methods, such as surveys or experiments. Although interviewing is a frequently used method, it should not be viewed as an easy default for qualitative researchers 2 . Interviews are also not suited to answering all qualitative research questions, but instead have specific strengths that should guide whether or not they are deployed in a research project. Whereas ethnography might be better suited to trying to observe what people do, interviews provide a space for extended conversations that allow the researcher insights into how people think and what they believe. Quantitative surveys also give these kinds of insights, but they use pre-determined questions and scales, privileging breadth over depth and often overlooking harder-to-reach participants.

In-depth interviews can take many different shapes and forms, often with more than one participant or researcher. For example, interviews might be highly structured (using an almost survey-like interview guide), entirely unstructured (taking a narrative and free-flowing approach) or semi-structured (using a topic guide ). Researchers might combine these approaches within a single project depending on the purpose of the interview and the characteristics of the participant. Whatever form the interview takes, researchers should be mindful of the dynamics between interviewer and participant and factor these in at all stages of the project.

In this Primer, we focus on the most common type of interview: one researcher taking a semi-structured approach to interviewing one participant using a topic guide. Focusing on how to plan research using interviews, we discuss the necessary stages of data collection. We also discuss the stages and thought-process behind analysing interview material to ensure that the richness and interpretability of interview material is maintained and communicated to readers. The Primer also tracks innovations in interview methods and discusses the developments we expect over the next 5–10 years.

We wrote this Primer as researchers from sociology, social policy and political science. We note our disciplinary background because we acknowledge that there are disciplinary differences in how interviews are approached and understood as a method.

Experimentation

Here we address research design considerations and data collection issues focusing on topic guide construction and other pragmatics of the interview. We also explore issues of ethics and reflexivity that are crucial throughout the research project.

Research design

Participant selection.

Participants can be selected and recruited in various ways for in-depth interview studies. The researcher must first decide what defines the people or social groups being studied. Often, this means moving from an abstract theoretical research question to a more precise empirical one. For example, the researcher might be interested in how people talk about race in contexts of diversity. Empirical settings in which this issue could be studied could include schools, workplaces or adoption agencies. The best research designs should clearly explain why the particular setting was chosen. Often there are both intrinsic and extrinsic reasons for choosing to study a particular group of people at a specific time and place 3 . Intrinsic motivations relate to the fact that the research is focused on an important specific social phenomenon that has been understudied. Extrinsic motivations speak to the broader theoretical research questions and explain why the case at hand is a good one through which to address them empirically.

Next, the researcher needs to decide which types of people they would like to interview. This decision amounts to delineating the inclusion and exclusion criteria for the study. The criteria might be based on demographic variables, like race or gender, but they may also be context-specific, for example, years of experience in an organization. These should be decided based on the research goals. Researchers should be clear about what characteristics would make an individual a candidate for inclusion in the study (and what would exclude them).

The next step is to identify and recruit the study’s sample . Usually, many more people fit the inclusion criteria than can be interviewed. In cases where lists of potential participants are available, the researcher might want to employ stratified sampling , dividing the list by characteristics of interest before sampling.

When there are no lists, researchers will often employ purposive sampling . Many researchers consider purposive sampling the most useful mode for interview-based research since the number of interviews to be conducted is too small to aim to be statistically representative 4 . Instead, the aim is not breadth, via representativeness, but depth via rich insights about a set of participants. In addition to purposive sampling, researchers often use snowball sampling . Both purposive and snowball sampling can be combined with quota sampling . All three types of sampling aim to ensure a variety of perspectives within the confines of a research project. A goal for in-depth interview studies can be to sample for range, being mindful of recruiting a diversity of participants fitting the inclusion criteria.

Study design

The total number of interviews depends on many factors, including the population studied, whether comparisons are to be made and the duration of interviews. Studies that rely on quota sampling where explicit comparisons are made between groups will require a larger number of interviews than studies focused on one group only. Studies where participants are interviewed over several hours, days or even repeatedly across years will tend to have fewer participants than those that entail a one-off engagement.

Researchers often stop interviewing when new interviews confirm findings from earlier interviews with no new or surprising insights (saturation) 4 , 5 , 6 . As a criterion for research design, saturation assumes that data collection and analysis are happening in tandem and that researchers will stop collecting new data once there is no new information emerging from the interviews. This is not always possible. Researchers rarely have time for systematic data analysis during data collection and they often need to specify their sample in funding proposals prior to data collection. As a result, researchers often draw on existing reports of saturation to estimate a sample size prior to data collection. These suggest between 12 and 20 interviews per category of participant (although researchers have reported saturation with samples that are both smaller and larger than this) 7 , 8 , 9 . The idea of saturation has been critiqued by many qualitative researchers because it assumes that meaning inheres in the data, waiting to be discovered — and confirmed — once saturation has been reached 7 . In-depth interview data are often multivalent and can give rise to different interpretations. The important consideration is, therefore, not merely how many participants are interviewed, but whether one’s research design allows for collecting rich and textured data that provide insight into participants’ understandings, accounts, perceptions and interpretations.

Sometimes, researchers will conduct interviews with more than one participant at a time. Researchers should consider the benefits and shortcomings of such an approach. Joint interviews may, for example, give researchers insight into how caregivers agree or debate childrearing decisions. At the same time, they may be less adaptive to exploring aspects of caregiving that participants may not wish to disclose to each other. In other cases, there may be more than one person interviewing each participant, such as when an interpreter is used, and so it is important to consider during the research design phase how this might shape the dynamics of the interview.

Data collection

Semi-structured interviews are typically organized around a topic guide comprised of an ordered set of broad topics (usually 3–5). Each topic includes a set of questions that form the basis of the discussion between the researcher and participant (Fig.  1 ). These topics are organized around key concepts that the researcher has identified (for example, through a close study of prior research, or perhaps through piloting a small, exploratory study) 5 .

a | Elaborated topics the researcher wants to cover in the interview and example questions. b | An example topic arc. Using such an arc, one can think flexibly about the order of topics. Considering the main question for each topic will help to determine the best order for the topics. After conducting some interviews, the researcher can move topics around if a different order seems to make sense.

Topic guide

One common way to structure a topic guide is to start with relatively easy, open-ended questions (Table  1 ). Opening questions should be related to the research topic but broad and easy to answer, so that they help to ease the participant into conversation.

After these broad, opening questions, the topic guide may move into topics that speak more directly to the overarching research question. The interview questions will be accompanied by probes designed to elicit concrete details and examples from the participant (see Table  1 ).

Abstract questions are often easier for participants to answer once they have been asked more concrete questions. In our experience, for example, questions about feelings can be difficult for some participants to answer, but when following probes concerning factual experiences these questions can become less challenging. After the main themes of the topic guide have been covered, the topic guide can move onto closing questions. At this stage, participants often repeat something they have said before, although they may sometimes introduce a new topic.

Interviews are especially well suited to gaining a deeper insight into people’s experiences. Getting these insights largely depends on the participants’ willingness to talk to the researcher. We recommend designing open-ended questions that are more likely to elicit an elaborated response and extended reflection from participants rather than questions that can be answered with yes or no.

Questions should avoid foreclosing the possibility that the participant might disagree with the premise of the question. Take for example the question: “Do you support the new family-friendly policies?” This question minimizes the possibility of the participant disagreeing with the premise of this question, which assumes that the policies are ‘family-friendly’ and asks for a yes or no answer. Instead, asking more broadly how a participant feels about the specific policy being described as ‘family-friendly’ (for example, a work-from-home policy) allows them to express agreement, disagreement or impartiality and, crucially, to explain their reasoning 10 .

For an uninterrupted interview that will last between 90 and 120 minutes, the topic guide should be one to two single-spaced pages with questions and probes. Ideally, the researcher will memorize the topic guide before embarking on the first interview. It is fine to carry a printed-out copy of the topic guide but memorizing the topic guide ahead of the interviews can often make the interviewer feel well prepared in guiding the participant through the interview process.

Although the topic guide helps the researcher stay on track with the broad areas they want to cover, there is no need for the researcher to feel tied down by the topic guide. For instance, if a participant brings up a theme that the researcher intended to discuss later or a point the researcher had not anticipated, the researcher may well decide to follow the lead of the participant. The researcher’s role extends beyond simply stating the questions; it entails listening and responding, making split-second decisions about what line of inquiry to pursue and allowing the interview to proceed in unexpected directions.

Optimizing the interview

The ideal place for an interview will depend on the study and what is feasible for participants. Generally, a place where the participant and researcher can both feel relaxed, where the interview can be uninterrupted and where noise or other distractions are limited is ideal. But this may not always be possible and so the researcher needs to be prepared to adapt their plans within what is feasible (and desirable for participants).

Another key tool for the interview is a recording device (assuming that permission for recording has been given). Recording can be important to capture what the participant says verbatim. Additionally, it can allow the researcher to focus on determining what probes and follow-up questions they want to pursue rather than focusing on taking notes. Sometimes, however, a participant may not allow the researcher to record, or the recording may fail. If the interview is not recorded we suggest that the researcher takes brief notes during the interview, if feasible, and then thoroughly make notes immediately after the interview and try to remember the participant’s facial expressions, gestures and tone of voice. Not having a recording of an interview need not limit the researcher from getting analytical value from it.

As soon as possible after each interview, we recommend that the researcher write a one-page interview memo comprising three key sections. The first section should identify two to three important moments from the interview. What constitutes important is up to the researcher’s discretion 9 . The researcher should note down what happened in these moments, including the participant’s facial expressions, gestures, tone of voice and maybe even the sensory details of their surroundings. This exercise is about capturing ethnographic detail from the interview. The second part of the interview memo is the analytical section with notes on how the interview fits in with previous interviews, for example, where the participant’s responses concur or diverge from other responses. The third part consists of a methodological section where the researcher notes their perception of their relationship with the participant. The interview memo allows the researcher to think critically about their positionality and practice reflexivity — key concepts for an ethical and transparent research practice in qualitative methodology 11 , 12 .

Ethics and reflexivity

All elements of an in-depth interview can raise ethical challenges and concerns. Good ethical practice in interview studies often means going beyond the ethical procedures mandated by institutions 13 . While discussions and requirements of ethics can differ across disciplines, here we focus on the most pertinent considerations for interviews across the research process for an interdisciplinary audience.

Ethical considerations prior to interview

Before conducting interviews, researchers should consider harm minimization, informed consent, anonymity and confidentiality, and reflexivity and positionality. It is important for the researcher to develop their own ethical sensitivities and sensibilities by gaining training in interview and qualitative methods, reading methodological and field-specific texts on interviews and ethics and discussing their research plans with colleagues.

Researchers should map the potential harm to consider how this can be minimized. Primarily, researchers should consider harm from the participants’ perspective (Box  1 ). But, it is also important to consider and plan for potential harm to the researcher, research assistants, gatekeepers, future researchers and members of the wider community 14 . Even the most banal of research topics can potentially pose some form of harm to the participant, researcher and others — and the level of harm is often highly context-dependent. For example, a research project on religion in society might have very different ethical considerations in a democratic versus authoritarian research context because of how openly or not such topics can be discussed and debated 15 .

The researcher should consider how they will obtain and record informed consent (for example, written or oral), based on what makes the most sense for their research project and context 16 . Some institutions might specify how informed consent should be gained. Regardless of how consent is obtained, the participant must be made aware of the form of consent, the intentions and procedures of the interview and potential forms of harm and benefit to the participant or community before the interview commences. Moreover, the participant must agree to be interviewed before the interview commences. If, in addition to interviews, the study contains an ethnographic component, it is worth reading around this topic (see, for example, Murphy and Dingwall 17 ). Informed consent must also be gained for how the interview will be recorded before the interview commences. These practices are important to ensure the participant is contributing on a voluntary basis. It is also important to remind participants that they can withdraw their consent at any time during the interview and for a specified period after the interview (to be decided with the participant). The researcher should indicate that participants can ask for anything shared to be off the record and/or not disseminated.

In terms of anonymity and confidentiality, it is standard practice when conducting interviews to agree not to use (or even collect) participants’ names and personal details that are not pertinent to the study. Anonymizing can often be the safer option for minimizing harm to participants as it is hard to foresee all the consequences of de-anonymizing, even if participants agree. Regardless of what a researcher decides, decisions around anonymity must be agreed with participants during the process of gaining informed consent and respected following the interview.

Although not all ethical challenges can be foreseen or planned for 18 , researchers should think carefully — before the interview — about power dynamics, participant vulnerability, emotional state and interactional dynamics between interviewer and participant, even when discussing low-risk topics. Researchers may then wish to plan for potential ethical issues, for example by preparing a list of relevant organizations to which participants can be signposted. A researcher interviewing a participant about debt, for instance, might prepare in advance a list of debt advice charities, organizations and helplines that could provide further support and advice. It is important to remember that the role of an interviewer is as a researcher rather than as a social worker or counsellor because researchers may not have relevant and requisite training in these other domains.

Box 1 Mapping potential forms of harm

Social: researchers should avoid causing any relational detriment to anyone in the course of interviews, for example, by sharing information with other participants or causing interview participants to be shunned or mistreated by their community as a result of participating.

Economic: researchers should avoid causing financial detriment to anyone, for example, by expecting them to pay for transport to be interviewed or to potentially lose their job as a result of participating.

Physical: researchers should minimize the risk of anyone being exposed to violence as a result of the research both from other individuals or from authorities, including police.

Psychological: researchers should minimize the risk of causing anyone trauma (or re-traumatization) or psychological anguish as a result of the research; this includes not only the participant but importantly the researcher themselves and anyone that might read or analyse the transcripts, should they contain triggering information.

Political: researchers should minimize the risk of anyone being exposed to political detriment as a result of the research, such as retribution.

Professional/reputational: researchers should minimize the potential for reputational damage to anyone connected to the research (this includes ensuring good research practices so that any researchers involved are not harmed reputationally by being involved with the research project).

The task here is not to map exhaustively the potential forms of harm that might pertain to a particular research project (that is the researcher’s job and they should have the expertise most suited to mapping such potential harms relative to the specific project) but to demonstrate the breadth of potential forms of harm.

Ethical considerations post-interview

Researchers should consider how interview data are stored, analysed and disseminated. If participants have been offered anonymity and confidentiality, data should be stored in a way that does not compromise this. For example, researchers should consider removing names and any other unnecessary personal details from interview transcripts, password-protecting and encrypting files and using pseudonyms to label and store all interview data. It is also important to address where interview data are taken (for example, across borders in particular where interview data might be of interest to local authorities) and how this might affect the storage of interview data.

Examining how the researcher will represent participants is a paramount ethical consideration both in the planning stages of the interview study and after it has been conducted. Dissemination strategies also need to consider questions of anonymity and representation. In small communities, even if participants are given pseudonyms, it might be obvious who is being described. Anonymizing not only the names of those participating but also the research context is therefore a standard practice 19 . With particularly sensitive data or insights about the participant, it is worth considering describing participants in a more abstract way rather than as specific individuals. These practices are important both for protecting participants’ anonymity but can also affect the ability of the researcher and others to return ethically to the research context and similar contexts 20 .

Reflexivity and positionality

Reflexivity and positionality mean considering the researcher’s role and assumptions in knowledge production 13 . A key part of reflexivity is considering the power relations between the researcher and participant within the interview setting, as well as how researchers might be perceived by participants. Further, researchers need to consider how their own identities shape the kind of knowledge and assumptions they bring to the interview, including how they approach and ask questions and their analysis of interviews (Box  2 ). Reflexivity is a necessary part of developing ethical sensibility as a researcher by adapting and reflecting on how one engages with participants. Participants should not feel judged, for example, when they share information that researchers might disagree with or find objectionable. How researchers deal with uncomfortable moments or information shared by participants is at their discretion, but they should consider how they will react both ahead of time and in the moment.

Researchers can develop their reflexivity by considering how they themselves would feel being asked these interview questions or represented in this way, and then adapting their practice accordingly. There might be situations where these questions are not appropriate in that they unduly centre the researchers’ experiences and worldview. Nevertheless, these prompts can provide a useful starting point for those beginning their reflexive journey and developing an ethical sensibility.

Reflexivity and ethical sensitivities require active reflection throughout the research process. For example, researchers should take care in interview memos and their notes to consider their assumptions, potential preconceptions, worldviews and own identities prior to and after interviews (Box  2 ). Checking in with assumptions can be a way of making sure that researchers are paying close attention to their own theoretical and analytical biases and revising them in accordance with what they learn through the interviews. Researchers should return to these notes (especially when analysing interview material), to try to unpack their own effects on the research process as well as how participants positioned and engaged with them.

Box 2 Aspects to reflect on reflexively

For reflexive engagement, and understanding the power relations being co-constructed and (re)produced in interviews, it is necessary to reflect, at a minimum, on the following.

Ethnicity, race and nationality, such as how does privilege stemming from race or nationality operate between the researcher, the participant and research context (for example, a researcher from a majority community may be interviewing a member of a minority community)

Gender and sexuality, see above on ethnicity, race and nationality

Social class, and in particular the issue of middle-class bias among researchers when formulating research and interview questions

Economic security/precarity, see above on social class and thinking about the researcher’s relative privilege and the source of biases that stem from this

Educational experiences and privileges, see above

Disciplinary biases, such as how the researcher’s discipline/subfield usually approaches these questions, possibly normalizing certain assumptions that might be contested by participants and in the research context

Political and social values

Lived experiences and other dimensions of ourselves that affect and construct our identity as researchers

In this section, we discuss the next stage of an interview study, namely, analysing the interview data. Data analysis may begin while more data are being collected. Doing so allows early findings to inform the focus of further data collection, as part of an iterative process across the research project. Here, the researcher is ultimately working towards achieving coherence between the data collected and the findings produced to answer successfully the research question(s) they have set.

The two most common methods used to analyse interview material across the social sciences are thematic analysis 21 and discourse analysis 22 . Thematic analysis is a particularly useful and accessible method for those starting out in analysis of qualitative data and interview material as a method of coding data to develop and interpret themes in the data 21 . Discourse analysis is more specialized and focuses on the role of discourse in society by paying close attention to the explicit, implicit and taken-for-granted dimensions of language and power 22 , 23 . Although thematic and discourse analysis are often discussed as separate techniques, in practice researchers might flexibly combine these approaches depending on the object of analysis. For example, those intending to use discourse analysis might first conduct thematic analysis as a way to organize and systematize the data. The object and intention of analysis might differ (for example, developing themes or interrogating language), but the questions facing the researcher (such as whether to take an inductive or deductive approach to analysis) are similar.

Preparing data

Data preparation is an important step in the data analysis process. The researcher should first determine what comprises the corpus of material and in what form it will it be analysed. The former refers to whether, for example, alongside the interviews themselves, analytic memos or observational notes that may have been taken during data collection will also be directly analysed. The latter refers to decisions about how the verbal/audio interview data will be transformed into a written form, making it suitable for processes of data analysis. Typically, interview audio recordings are transcribed to produce a written transcript. It is important to note that the process of transcription is one of transformation. The verbal interview data are transformed into a written transcript through a series of decisions that the researcher must make. The researcher should consider the effect of mishearing what has been said or how choosing to punctuate a sentence in a particular way will affect the final analysis.

Box  3 shows an example transcript excerpt from an interview with a teacher conducted by Teeger as part of her study of history education in post-apartheid South Africa 24 (Box  3 ). Seeing both the questions and the responses means that the reader can contextualize what the participant (Ms Mokoena) has said. Throughout the transcript the researcher has used square brackets, for example to indicate a pause in speech, when Ms Mokoena says “it’s [pause] it’s a difficult topic”. The transcription choice made here means that we see that Ms Mokoena has taken time to pause, perhaps to search for the right words, or perhaps because she has a slight apprehension. Square brackets are also included as an overt act of communication to the reader. When Ms Mokoena says “ja”, the English translation (“yes”) of the word in Afrikaans is placed in square brackets to ensure that the reader can follow the meaning of the speech.

Decisions about what to include when transcribing will be hugely important for the direction and possibilities of analysis. Researchers should decide what they want to capture in the transcript, based on their analytic focus. From a (post)positivist perspective 25 , the researcher may be interested in the manifest content of the interview (such as what is said, not how it is said). In that case, they may choose to transcribe intelligent verbatim . From a constructivist perspective 25 , researchers may choose to record more aspects of speech (including, for example, pauses, repetitions, false starts, talking over one another) so that these features can be analysed. Those working from this perspective argue that to recognize the interactional nature of the interview setting adequately and to avoid misinterpretations, features of interaction (pauses, overlaps between speakers and so on) should be preserved in transcription and therefore in the analysis 10 . Readers interested in learning more should consult Potter and Hepburn’s summary of how to present interaction through transcription of interview data 26 .

The process of analysing semi-structured interviews might be thought of as a generative rather than an extractive enterprise. Findings do not already exist within the interview data to be discovered. Rather, researchers create something new when analysing the data by applying their analytic lens or approach to the transcripts. At a high level, there are options as to what researchers might want to glean from their interview data. They might be interested in themes, whereby they identify patterns of meaning across the dataset 21 . Alternatively, they may focus on discourse(s), looking to identify how language is used to construct meanings and therefore how language reinforces or produces aspects of the social world 27 . Alternatively, they might look at the data to understand narrative or biographical elements 28 .

A further overarching decision to make is the extent to which researchers bring predetermined framings or understandings to bear on their data, or instead begin from the data themselves to generate an analysis. One way of articulating this is the extent to which researchers take a deductive approach or an inductive approach to analysis. One example of a truly inductive approach is grounded theory, whereby the aim of the analysis is to build new theory, beginning with one’s data 6 , 29 . In practice, researchers using thematic and discourse analysis often combine deductive and inductive logics and describe their process instead as iterative (referred to also as an abductive approach ) 30 , 31 . For example, researchers may decide that they will apply a given theoretical framing, or begin with an initial analytic framework, but then refine or develop these once they begin the process of analysis.

Box 3 Excerpt of interview transcript (from Teeger 24 )

Interviewer : Maybe you could just start by talking about what it’s like to teach apartheid history.

Ms Mokoena : It’s a bit challenging. You’ve got to accommodate all the kids in the class. You’ve got to be sensitive to all the racial differences. You want to emphasize the wrongs that were done in the past but you also want to, you know, not to make kids feel like it’s their fault. So you want to use the wrongs of the past to try and unite the kids …

Interviewer : So what kind of things do you do?

Ms Mokoena : Well I normally highlight the fact that people that were struggling were not just the blacks, it was all the races. And I give examples of the people … from all walks of life, all races, and highlight how they suffered as well as a result of apartheid, particularly the whites… . What I noticed, particularly my first year of teaching apartheid, I noticed that the black kids made the others feel responsible for what happened… . I had a lot of fights…. A lot of kids started hating each other because, you know, the others are white and the others were black. And they started saying, “My mother is a domestic worker because she was never allowed an opportunity to get good education.” …

Interviewer : I didn’t see any of that now when I was observing.

Ms Mokoena : … Like I was saying I think that because of the re-emphasis of the fact that, look, everybody did suffer one way or the other, they sort of got to see that it was everybody’s struggle … . They should now get to understand that that’s why we’re called a Rainbow Nation. Not everybody agreed with apartheid and not everybody suffered. Even all the blacks, not all blacks got to feel what the others felt . So ja [yes], it’s [pause] it’s a difficult topic, ja . But I think if you get the kids to understand why we’re teaching apartheid in the first place and you show the involvement of all races in all the different sides , then I think you have managed to teach it properly. So I think because of my inexperience then — that was my first year of teaching history — so I think I — maybe I over-emphasized the suffering of the blacks versus the whites [emphasis added].

Reprinted with permission from ref. 24 , Sage Publications.

From data to codes

Coding data is a key building block shared across many approaches to data analysis. Coding is a way of organizing and describing data, but is also ultimately a way of transforming data to produce analytic insights. The basic practice of coding involves highlighting a segment of text (this may be a sentence, a clause or a longer excerpt) and assigning a label to it. The aim of the label is to communicate some sort of summary of what is in the highlighted piece of text. Coding is an iterative process, whereby researchers read and reread their transcripts, applying and refining their codes, until they have a coding frame (a set of codes) that is applied coherently across the dataset and that captures and communicates the key features of what is contained in the data as it relates to the researchers’ analytic focus.

What one codes for is entirely contingent on the focus of the research project and the choices the researcher makes about the approach to analysis. At first, one might apply descriptive codes, summarizing what is contained in the interviews. It is rarely desirable to stop at this point, however, because coding is a tool to move from describing the data to interpreting the data. Suppose the researcher is pursuing some version of thematic analysis. In that case, it might be that the objects of coding are aspects of reported action, emotions, opinions, norms, relationships, routines, agreement/disagreement and change over time. A discourse analysis might instead code for different types of speech acts, tropes, linguistic or rhetorical devices. Multiple types of code might be generated within the same research project. What is important is that researchers are aware of the choices they are making in terms of what they are coding for. Moreover, through the process of refinement, the aim is to produce a set of discrete codes — in which codes are conceptually distinct, as opposed to overlapping. By using the same codes across the dataset, the researcher can capture commonalities across the interviews. This process of refinement involves relabelling codes and reorganizing how and where they are applied in the dataset.

From coding to analysis and writing

Data analysis is also an iterative process in which researchers move closer to and further away from the data. As they move away from the data, they synthesize their findings, thus honing and articulating their analytic insights. As they move closer to the data, they ground these insights in what is contained in the interviews. The link should not be broken between the data themselves and higher-order conceptual insights or claims being made. Researchers must be able to show evidence for their claims in the data. Figure  2 summarizes this iterative process and suggests the sorts of activities involved at each stage more concretely.

As well as going through steps 1 to 6 in order, the researcher will also go backwards and forwards between stages. Some stages will themselves be a forwards and backwards processing of coding and refining when working across different interview transcripts.

At the stage of synthesizing, there are some common quandaries. When dealing with a dataset consisting of multiple interviews, there will be salient and minority statements across different participants, or consensus or dissent on topics of interest to the researcher. A strength of qualitative interviews is that we can build in these nuances and variations across our data as opposed to aggregating them away. When exploring and reporting data, researchers should be asking how different findings are patterned and which interviews contain which codes, themes or tropes. Researchers should think about how these variations fit within the longer flow of individual interviews and what these variations tell them about the nature of their substantive research interests.

A further consideration is how to approach analysis within and across interview data. Researchers may look at one individual code, to examine the forms it takes across different participants and what they might be able to summarize about this code in the round. Alternatively, they might look at how a code or set of codes pattern across the account of one participant, to understand the code(s) in a more contextualized way. Further analysis might be done according to different sampling characteristics, where researchers group together interviews based on certain demographic characteristics and explore these together.

When it comes to writing up and presenting interview data, key considerations tend to rest on what is often termed transparency. When presenting the findings of an interview-based study, the reader should be able to understand and trace what the stated findings are based upon. This process typically involves describing the analytic process, how key decisions were made and presenting direct excerpts from the data. It is important to account for how the interview was set up and to consider the active part that the researcher has played in generating the data 32 . Quotes from interviews should not be thought of as merely embellishing or adding interest to a final research output. Rather, quotes serve the important function of connecting the reader directly to the underlying data. Quotes, therefore, should be chosen because they provide the reader with the most apt insight into what is being discussed. It is good practice to report not just on what participants said, but also on the questions that were asked to elicit the responses.

Researchers have increasingly used specialist qualitative data analysis software to organize and analyse their interview data, such as NVivo or ATLAS.ti. It is important to remember that such software is a tool for, rather than an approach or technique of, analysis. That said, software also creates a wide range of possibilities in terms of what can be done with the data. As researchers, we should reflect on how the range of possibilities of a given software package might be shaping our analytical choices and whether these are choices that we do indeed want to make.

Applications

This section reviews how and why in-depth interviews have been used by researchers studying gender, education and inequality, nationalism and ethnicity and the welfare state. Although interviews can be employed as a method of data collection in just about any social science topic, the applications below speak directly to the authors’ expertise and cutting-edge areas of research.

When it comes to the broad study of gender, in-depth interviews have been invaluable in shaping our understanding of how gender functions in everyday life. In a study of the US hedge fund industry (an industry dominated by white men), Tobias Neely was interested in understanding the factors that enable white men to prosper in the industry 33 . The study comprised interviews with 45 hedge fund workers and oversampled women of all races and men of colour to capture a range of experiences and beliefs. Tobias Neely found that practices of hiring, grooming and seeding are key to maintaining white men’s dominance in the industry. In terms of hiring, the interviews clarified that white men in charge typically preferred to hire people like themselves, usually from their extended networks. When women were hired, they were usually hired to less lucrative positions. In terms of grooming, Tobias Neely identifies how older and more senior men in the industry who have power and status will select one or several younger men as their protégés, to include in their own elite networks. Finally, in terms of her concept of seeding, Tobias Neely describes how older men who are hedge fund managers provide the seed money (often in the hundreds of millions of dollars) for a hedge fund to men, often their own sons (but not their daughters). These interviews provided an in-depth look into gendered and racialized mechanisms that allow white men to flourish in this industry.

Research by Rao draws on dozens of interviews with men and women who had lost their jobs, some of the participants’ spouses and follow-up interviews with about half the sample approximately 6 months after the initial interview 34 . Rao used interviews to understand the gendered experience and understanding of unemployment. Through these interviews, she found that the very process of losing their jobs meant different things for men and women. Women often saw job loss as being a personal indictment of their professional capabilities. The women interviewed often referenced how years of devaluation in the workplace coloured their interpretation of their job loss. Men, by contrast, were also saddened by their job loss, but they saw it as part and parcel of a weak economy rather than a personal failing. How these varied interpretations occurred was tied to men’s and women’s very different experiences in the workplace. Further, through her analysis of these interviews, Rao also showed how these gendered interpretations had implications for the kinds of jobs men and women sought to pursue after job loss. Whereas men remained tied to participating in full-time paid work, job loss appeared to be a catalyst pushing some of the women to re-evaluate their ties to the labour force.

In a study of workers in the tech industry, Hart used interviews to explain how individuals respond to unwanted and ambiguously sexual interactions 35 . Here, the researcher used interviews to allow participants to describe how these interactions made them feel and act and the logics of how they interpreted, classified and made sense of them 35 . Through her analysis of these interviews, Hart showed that participants engaged in a process she termed “trajectory guarding”, whereby they sought to monitor unwanted and ambiguously sexual interactions to avoid them from escalating. Yet, as Hart’s analysis proficiently demonstrates, these very strategies — which protect these workers sexually — also undermined their workplace advancement.

Drawing on interviews, these studies have helped us to understand better how gendered mechanisms, gendered interpretations and gendered interactions foster gender inequality when it comes to paid work. Methodologically, these studies illuminate the power of interviews to reveal important aspects of social life.

Nationalism and ethnicity

Traditionally, nationalism has been studied from a top-down perspective, through the lens of the state or using historical methods; in other words, in-depth interviews have not been a common way of collecting data to study nationalism. The methodological turn towards everyday nationalism has encouraged more scholars to go to the field and use interviews (and ethnography) to understand nationalism from the bottom up: how people talk about, give meaning, understand, navigate and contest their relation to nation, national identification and nationalism 36 , 37 , 38 , 39 . This turn has also addressed the gap left by those studying national and ethnic identification via quantitative methods, such as surveys.

Surveys can enumerate how individuals ascribe to categorical forms of identification 40 . However, interviews can question the usefulness of such categories and ask whether these categories are reflected, or resisted, by participants in terms of the meanings they give to identification 41 , 42 . Categories often pitch identification as a mutually exclusive choice; but identification might be more complex than such categories allow. For example, some might hybridize these categories or see themselves as moving between and across categories 43 . Hearing how people talk about themselves and their relation to nations, states and ethnicities, therefore, contributes substantially to the study of nationalism and national and ethnic forms of identification.

One particular approach to studying these topics, whether via everyday nationalism or alternatives, is that of using interviews to capture both articulations and narratives of identification, relations to nationalism and the boundaries people construct. For example, interviews can be used to gather self–other narratives by studying how individuals construct I–we–them boundaries 44 , including how participants talk about themselves, who participants include in their various ‘we’ groupings and which and how participants create ‘them’ groupings of others, inserting boundaries between ‘I/we’ and ‘them’. Overall, interviews hold great potential for listening to participants and understanding the nuances of identification and the construction of boundaries from their point of view.

Education and inequality

Scholars of social stratification have long noted that the school system often reproduces existing social inequalities. Carter explains that all schools have both material and sociocultural resources 45 . When children from different backgrounds attend schools with different material resources, their educational and occupational outcomes are likely to vary. Such material resources are relatively easy to measure. They are operationalized as teacher-to-student ratios, access to computers and textbooks and the physical infrastructure of classrooms and playgrounds.

Drawing on Bourdieusian theory 46 , Carter conceptualizes the sociocultural context as the norms, values and dispositions privileged within a social space 45 . Scholars have drawn on interviews with students and teachers (as well as ethnographic observations) to show how schools confer advantages on students from middle-class families, for example, by rewarding their help-seeking behaviours 47 . Focusing on race, researchers have revealed how schools can remain socioculturally white even as they enrol a racially diverse student population. In such contexts, for example, teachers often misrecognize the aesthetic choices made by students of colour, wrongly inferring that these students’ tastes in clothing and music reflect negative orientations to schooling 48 , 49 , 50 . These assessments can result in disparate forms of discipline and may ultimately shape educators’ assessments of students’ academic potential 51 .

Further, teachers and administrators tend to view the appropriate relationship between home and school in ways that resonate with white middle-class parents 52 . These parents are then able to advocate effectively for their children in ways that non-white parents are not 53 . In-depth interviews are particularly good at tapping into these understandings, revealing the mechanisms that confer privilege on certain groups of students and thereby reproduce inequality.

In addition, interviews can shed light on the unequal experiences that young people have within educational institutions, as the views of dominant groups are affirmed while those from disadvantaged backgrounds are delegitimized. For example, Teeger’s interviews with South African high schoolers showed how — because racially charged incidents are often framed as jokes in the broader school culture — Black students often feel compelled to ignore and keep silent about the racism they experience 54 . Interviews revealed that Black students who objected to these supposed jokes were coded by other students as serious or angry. In trying to avoid such labels, these students found themselves unable to challenge the racism they experienced. Interviews give us insight into these dynamics and help us see how young people understand and interpret the messages transmitted in schools — including those that speak to issues of inequality in their local school contexts as well as in society more broadly 24 , 55 .

The welfare state

In-depth interviews have also proved to be an important method for studying various aspects of the welfare state. By welfare state, we mean the social institutions relating to the economic and social wellbeing of a state’s citizens. Notably, using interviews has been useful to look at how policy design features are experienced and play out on the ground. Interviews have often been paired with large-scale surveys to produce mixed-methods study designs, therefore achieving both breadth and depth of insights.

In-depth interviews provide the opportunity to look behind policy assumptions or how policies are designed from the top down, to examine how these play out in the lives of those affected by the policies and whose experiences might otherwise be obscured or ignored. For example, the Welfare Conditionality project used interviews to critique the assumptions that conditionality (such as, the withdrawal of social security benefits if recipients did not perform or meet certain criteria) improved employment outcomes and instead showed that conditionality was harmful to mental health, living standards and had many other negative consequences 56 . Meanwhile, combining datasets from two small-scale interview studies with recipients allowed Summers and Young to critique assumptions around the simplicity that underpinned the design of Universal Credit in 2020, for example, showing that the apparently simple monthly payment design instead burdened recipients with additional money management decisions and responsibilities 57 .

Similarly, the Welfare at a (Social) Distance project used a mixed-methods approach in a large-scale study that combined national surveys with case studies and in-depth interviews to investigate the experience of claiming social security benefits during the COVID-19 pandemic. The interviews allowed researchers to understand in detail any issues experienced by recipients of benefits, such as delays in the process of claiming, managing on a very tight budget and navigating stigma and claiming 58 .

These applications demonstrate the multi-faceted topics and questions for which interviews can be a relevant method for data collection. These applications highlight not only the relevance of interviews, but also emphasize the key added value of interviews, which might be missed by other methods (surveys, in particular). Interviews can expose and question what is taken for granted and directly engage with communities and participants that might otherwise be ignored, obscured or marginalized.

Reproducibility and data deposition

There is a robust, ongoing debate about reproducibility in qualitative research, including interview studies. In some research paradigms, reproducibility can be a way of interrogating the rigour and robustness of research claims, by seeing whether these hold up when the research process is repeated. Some scholars have suggested that although reproducibility may be challenging, researchers can facilitate it by naming the place where the research was conducted, naming participants, sharing interview and fieldwork transcripts (anonymized and de-identified in cases where researchers are not naming people or places) and employing fact-checkers for accuracy 11 , 59 , 60 .

In addition to the ethical concerns of whether de-anonymization is ever feasible or desirable, it is also important to address whether the replicability of interview studies is meaningful. For example, the flexibility of interviews allows for the unexpected and the unforeseen to be incorporated into the scope of the research 61 . However, this flexibility means that we cannot expect reproducibility in the conventional sense, given that different researchers will elicit different types of data from participants. Sharing interview transcripts with other researchers, for instance, downplays the contextual nature of an interview.

Drawing on Bauer and Gaskell, we propose several measures to enhance rigour in qualitative research: transparency, grounding interpretations and aiming for theoretical transferability and significance 62 .

Researchers should be transparent when describing their methodological choices. Transparency means documenting who was interviewed, where and when (without requiring de-anonymization, for example, by documenting their characteristics), as well as the questions they were asked. It means carefully considering who was left out of the interviews and what that could mean for the researcher’s findings. It also means carefully considering who the researcher is and how their identity shaped the research process (integrating and articulating reflexivity into whatever is written up).

Second, researchers should ground their interpretations in the data. Grounding means presenting the evidence upon which the interpretation relies. Quotes and extracts should be extensive enough to allow the reader to evaluate whether the researcher’s interpretations are grounded in the data. At each step, researchers should carefully compare their own explanations and interpretations with alternative explanations. Doing so systematically and frequently allows researchers to become more confident in their claims. Here, researchers should justify the link between data and analysis by using quotes to justify and demonstrate the analytical point, while making sure the analytical point offers an interpretation of quotes (Box  4 ).

An important step in considering alternative explanations is to seek out disconfirming evidence 4 , 63 . This involves looking for instances where participants deviate from what the majority are saying and thus bring into question the theory (or explanation) that the researcher is developing. Careful analysis of such examples can often demonstrate the salience and meaning of what appears to be the norm (see Table  2 for examples) 54 . Considering alternative explanations and paying attention to disconfirming evidence allows the researcher to refine their own theories in respect of the data.

Finally, researchers should aim for theoretical transferability and significance in their discussions of findings. One way to think about this is to imagine someone who is not interested in the empirical study. Articulating theoretical transferability and significance usually takes the form of broadening out from the specific findings to consider explicitly how the research has refined or altered prior theoretical approaches. This process also means considering under what other conditions, aside from those of the study, the researcher thinks their theoretical revision would be supported by and why. Importantly, it also includes thinking about the limitations of one’s own approach and where the theoretical implications of the study might not hold.

Box 4 An example of grounding interpretations in data (from Rao 34 )

In an article explaining how unemployed men frame their job loss as a pervasive experience, Rao writes the following: “Unemployed men in this study understood unemployment to be an expected aspect of paid work in the contemporary United States. Robert, a white unemployed communications professional, compared the economic landscape after the Great Recession with the tragic events of September 11, 2001:

Part of your post-9/11 world was knowing people that died as a result of terrorism. The same thing is true with the [Great] Recession, right? … After the Recession you know somebody who was unemployed … People that really should be working.

The pervasiveness of unemployment rendered it normal, as Robert indicates.”

Here, the link between the quote presented and the analytical point Rao is making is clear: the analytical point is grounded in a quote and an interpretation of the quote is offered 34 .

Limitations and optimizations

When deciding which research method to use, the key question is whether the method provides a good fit for the research questions posed. In other words, researchers should consider whether interviews will allow them to successfully access the social phenomena necessary to answer their question(s) and whether the interviews will do so more effectively than other methods. Table  3 summarizes the major strengths and limitations of interviews. However, the accompanying text below is organized around some key issues, where relative strengths and weaknesses are presented alongside each other, the aim being that readers should think about how these can be balanced and optimized in relation to their own research.

Breadth versus depth of insight

Achieving an overall breadth of insight, in a statistically representative sense, is not something that is possible or indeed desirable when conducting in-depth interviews. Instead, the strength of conducting interviews lies in their ability to generate various sorts of depth of insight. The experiences or views of participants that can be accessed by conducting interviews help us to understand participants’ subjective realities. The challenge, therefore, is for researchers to be clear about why depth of insight is the focus and what we should aim to glean from these types of insight.

Naturalistic or artificial interviews

Interviews make use of a form of interaction with which people are familiar 64 . By replicating a naturalistic form of interaction as a tool to gather social science data, researchers can capitalize on people’s familiarity and expectations of what happens in a conversation. This familiarity can also be a challenge, as people come to the interview with preconceived ideas about what this conversation might be for or about. People may draw on experiences of other similar conversations when taking part in a research interview (for example, job interviews, therapy sessions, confessional conversations, chats with friends). Researchers should be aware of such potential overlaps and think through their implications both in how the aims and purposes of the research interview are communicated to participants and in how interview data are interpreted.

Further, some argue that a limitation of interviews is that they are an artificial form of data collection. By taking people out of their daily lives and asking them to stand back and pass comment, we are creating a distance that makes it difficult to use such data to say something meaningful about people’s actions, experiences and views. Other approaches, such as ethnography, might be more suitable for tapping into what people actually do, as opposed to what they say they do 65 .

Dynamism and replicability

Interviews following a semi-structured format offer flexibility both to the researcher and the participant. As the conversation develops, the interlocutors can explore the topics raised in much more detail, if desired, or pass over ones that are not relevant. This flexibility allows for the unexpected and the unforeseen to be incorporated into the scope of the research.

However, this flexibility has a related challenge of replicability. Interviews cannot be reproduced because they are contingent upon the interaction between the researcher and the participant in that given moment of interaction. In some research paradigms, replicability can be a way of interrogating the robustness of research claims, by seeing whether they hold when they are repeated. This is not a useful framework to bring to in-depth interviews and instead quality criteria (such as transparency) tend to be employed as criteria of rigour.

Accessing the private and personal

Interviews have been recognized for their strength in accessing private, personal issues, which participants may feel more comfortable talking about in a one-to-one conversation. Furthermore, interviews are likely to take a more personable form with their extended questions and answers, perhaps making a participant feel more at ease when discussing sensitive topics in such a context. There is a similar, but separate, argument made about accessing what are sometimes referred to as vulnerable groups, who may be difficult to make contact with using other research methods.

There is an associated challenge of anonymity. There can be types of in-depth interview that make it particularly challenging to protect the identities of participants, such as interviewing within a small community, or multiple members of the same household. The challenge to ensure anonymity in such contexts is even more important and difficult when the topic of research is of a sensitive nature or participants are vulnerable.

Increasingly, researchers are collaborating in large-scale interview-based studies and integrating interviews into broader mixed-methods designs. At the same time, interviews can be seen as an old-fashioned (and perhaps outdated) mode of data collection. We review these debates and discussions and point to innovations in interview-based studies. These include the shift from face-to-face interviews to the use of online platforms, as well as integrating and adapting interviews towards more inclusive methodologies.

Collaborating and mixing

Qualitative researchers have long worked alone 66 . Increasingly, however, researchers are collaborating with others for reasons such as efficiency, institutional incentives (for example, funding for collaborative research) and a desire to pool expertise (for example, studying similar phenomena in different contexts 67 or via different methods). Collaboration can occur across disciplines and methods, cases and contexts and between industry/business, practitioners and researchers. In many settings and contexts, collaboration has become an imperative 68 .

Cheek notes how collaboration provides both advantages and disadvantages 68 . For example, collaboration can be advantageous, saving time and building on the divergent knowledge, skills and resources of different researchers. Scholars with different theoretical or case-based knowledge (or contacts) can work together to build research that is comparative and/or more than the sum of its parts. But such endeavours also carry with them practical and political challenges in terms of how resources might actually be pooled, shared or accounted for. When undertaking such projects, as Morse notes, it is worth thinking about the nature of the collaboration and being explicit about such a choice, its advantages and its disadvantages 66 .

A further tension, but also a motivation for collaboration, stems from integrating interviews as a method in a mixed-methods project, whether with other qualitative researchers (to combine with, for example, focus groups, document analysis or ethnography) or with quantitative researchers (to combine with, for example, surveys, social media analysis or big data analysis). Cheek and Morse both note the pitfalls of collaboration with quantitative researchers: that quality of research may be sacrificed, qualitative interpretations watered down or not taken seriously, or tensions experienced over the pace and different assumptions that come with different methods and approaches of research 66 , 68 .

At the same time, there can be real benefits of such mixed-methods collaboration, such as reaching different and more diverse audiences or testing assumptions and theories between research components in the same project (for example, testing insights from prior quantitative research via interviews, or vice versa), as long as the skillsets of collaborators are seen as equally beneficial to the project. Cheek provides a set of questions that, as a starting point, can be useful for guiding collaboration, whether mixed methods or otherwise. First, Cheek advises asking all collaborators about their assumptions and understandings concerning collaboration. Second, Cheek recommends discussing what each perspective highlights and focuses on (and conversely ignores or sidelines) 68 .

A different way to engage with the idea of collaboration and mixed methods research is by fostering greater collaboration between researchers in the Global South and Global North, thus reversing trends of researchers from the Global North extracting knowledge from the Global South 69 . Such forms of collaboration also align with interview innovations, discussed below, that seek to transform traditional interview approaches into more participatory and inclusive (as part of participatory methodologies).

Digital innovations and challenges

The ongoing COVID-19 pandemic has centred the question of technology within interview-based fieldwork. Although conducting synchronous oral interviews online — for example, via Zoom, Skype or other such platforms — has been a method used by a small constituency of researchers for many years, it became (and remains) a necessity for many researchers wanting to continue or start interview-based projects while COVID-19 prevents face-to-face data collection.

In the past, online interviews were often framed as an inferior form of data collection for not providing the kinds of (often necessary) insights and forms of immersion face-to-face interviews allow 70 , 71 . Online interviews do tend to be more decontextualized than interviews conducted face-to-face 72 . For example, it is harder to recognize, engage with and respond to non-verbal cues 71 . At the same time, they broaden participation to those who might not have been able to access or travel to sites where interviews would have been conducted otherwise, for example people with disabilities. Online interviews also offer more flexibility in terms of scheduling and time requirements. For example, they provide more flexibility around precarious employment or caring responsibilities without having to travel and be away from home. In addition, online interviews might also reduce discomfort between researchers and participants, compared with face-to-face interviews, enabling more discussion of sensitive material 71 . They can also provide participants with more control, enabling them to turn on and off the microphone and video as they choose, for example, to provide more time to reflect and disconnect if they so wish 72 .

That said, online interviews can also introduce new biases based on access to technology 72 . For example, in the Global South, there are often urban/rural and gender gaps between who has access to mobile phones and who does not, meaning that some population groups might be overlooked unless researchers sample mindfully 71 . There are also important ethical considerations when deciding between online and face-to-face interviews. Online interviews might seem to imply lower ethical risks than face-to-face interviews (for example, they lower the chances of identification of participants or researchers), but they also offer more barriers to building trust between researchers and participants 72 . Interacting only online with participants might not provide the information needed to assess risk, for example, participants’ access to a private space to speak 71 . Just because online interviews might be more likely to be conducted in private spaces does not mean that private spaces are safe, for example, for victims of domestic violence. Finally, online interviews prompt further questions about decolonizing research and engaging with participants if research is conducted from afar 72 , such as how to include participants meaningfully and challenge dominant assumptions while doing so remotely.

A further digital innovation, modulating how researchers conduct interviews and the kinds of data collected and analysed, stems from the use and integration of (new) technology, such as WhatsApp text or voice notes to conduct synchronous or asynchronous oral or written interviews 73 . Such methods can provide more privacy, comfort and control to participants and make recruitment easier, allowing participants to share what they want when they want to, using technology that already forms a part of their daily lives, especially for young people 74 , 75 . Such technology is also emerging in other qualitative methods, such as focus groups, with similar arguments around greater inclusivity versus traditional offline modes. Here, the digital challenge might be higher for researchers than for participants if they are less used to such technology 75 . And while there might be concerns about the richness, depth and quality of written messages as a form of interview data, Gibson reports that the reams of transcripts that resulted from a study using written messaging were dense with meaning to be analysed 75 .

Like with online and face-to-face interviews, it is important also to consider the ethical questions and challenges of using such technology, from gaining consent to ensuring participant safety and attending to their distress, without cues, like crying, that might be more obvious in a face-to-face setting 75 , 76 . Attention to the platform used for such interviews is also important and researchers should be attuned to the local and national context. For example, in China, many platforms are neither legal nor available 76 . There, more popular platforms — like WeChat — can be highly monitored by the government, posing potential risks to participants depending on the topic of the interview. Ultimately, researchers should consider trade-offs between online and offline interview modalities, being attentive to the social context and power dynamics involved.

The next 5–10 years

Continuing to integrate (ethically) this technology will be among the major persisting developments in interview-based research, whether to offer more flexibility to researchers or participants, or to diversify who can participate and on what terms.

Pushing the idea of inclusion even further is the potential for integrating interview-based studies within participatory methods, which are also innovating via integrating technology. There is no hard and fast line between researchers using in-depth interviews and participatory methods; many who employ participatory methods will use interviews at the beginning, middle or end phases of a research project to capture insights, perspectives and reflections from participants 77 , 78 . Participatory methods emphasize the need to resist existing power and knowledge structures. They broaden who has the right and ability to contribute to academic knowledge by including and incorporating participants not only as subjects of data collection, but as crucial voices in research design and data analysis 77 . Participatory methods also seek to facilitate local change and to produce research materials, whether for academic or non-academic audiences, including films and documentaries, in collaboration with participants.

In responding to the challenges of COVID-19, capturing the fraught situation wrought by the pandemic and the momentum to integrate technology, participatory researchers have sought to continue data collection from afar. For example, Marzi has adapted an existing project to co-produce participatory videos, via participants’ smartphones in Medellin, Colombia, alongside regular check-in conversations/meetings/interviews with participants 79 . Integrating participatory methods into interview studies offers a route by which researchers can respond to the challenge of diversifying knowledge, challenging assumptions and power hierarchies and creating more inclusive and collaborative partnerships between participants and researchers in the Global North and South.

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Acknowledgements

The authors are grateful to the MY421 team and students for prompting how best to frame and communicate issues pertinent to in-depth interview studies.

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A pre-written interview outline for a semi-structured interview that provides both a topic structure and the ability to adapt flexibly to the content and context of the interview and the interaction between the interviewer and participant. Others may refer to the topic guide as an interview protocol.

Here we refer to the participants that take part in the study as the sample. Other researchers may refer to the participants as a participant group or dataset.

This involves dividing a population into smaller groups based on particular characteristics, for example, age or gender, and then sampling randomly within each group.

A sampling method where the guiding logic when deciding who to recruit is to achieve the most relevant participants for the research topic, in terms of being rich in information or insights.

Researchers ask participants to introduce the researcher to others who meet the study’s inclusion criteria.

Similar to stratified sampling, but participants are not necessarily randomly selected. Instead, the researcher determines how many people from each category of participants should be recruited. Recruitment can happen via snowball or purposive sampling.

A method for developing, analysing and interpreting patterns across data by coding in order to develop themes.

An approach that interrogates the explicit, implicit and taken-for-granted dimensions of language as well as the contexts in which it is articulated to unpack its purposes and effects.

A form of transcription that simplifies what has been said by removing certain verbal and non-verbal details that add no further meaning, such as ‘ums and ahs’ and false starts.

The analytic framework, theoretical approach and often hypotheses, are developed prior to examining the data and then applied to the dataset.

The analytic framework and theoretical approach is developed from analysing the data.

An approach that combines deductive and inductive components to work recursively by going back and forth between data and existing theoretical frameworks (also described as an iterative approach). This approach is increasingly recognized not only as a more realistic but also more desirable third alternative to the more traditional inductive versus deductive binary choice.

A theoretical apparatus that emphasizes the role of cultural processes and capital in (intergenerational) social reproduction.

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Knott, E., Rao, A.H., Summers, K. et al. Interviews in the social sciences. Nat Rev Methods Primers 2 , 73 (2022). https://doi.org/10.1038/s43586-022-00150-6

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Qualitative Research 101: Interviewing

5 Common Mistakes To Avoid When Undertaking Interviews

By: David Phair (PhD) and Kerryn Warren (PhD) | March 2022

Undertaking interviews is potentially the most important step in the qualitative research process. If you don’t collect useful, useable data in your interviews, you’ll struggle through the rest of your dissertation or thesis.  Having helped numerous students with their research over the years, we’ve noticed some common interviewing mistakes that first-time researchers make. In this post, we’ll discuss five costly interview-related mistakes and outline useful strategies to avoid making these.

Overview: 5 Interviewing Mistakes

• Not having a clear interview strategy /plan
• Not having good interview techniques /skills
• Not securing a suitable location and equipment
• Not having a basic risk management plan
• Not keeping your “ golden thread ” front of mind

1. Not having a clear interview strategy

The first common mistake that we’ll look at is that of starting the interviewing process without having first come up with a clear interview strategy or plan of action. While it’s natural to be keen to get started engaging with your interviewees, a lack of planning can result in a mess of data and inconsistency between interviews.

There are several design choices to decide on and plan for before you start interviewing anyone. Some of the most important questions you need to ask yourself before conducting interviews include:

• What are the guiding research aims and research questions of my study?
• Will I use a structured, semi-structured or unstructured interview approach?
• How will I record the interviews (audio or video)?
• Who will be interviewed and by whom ?
• What ethics and data law considerations do I need to adhere to?
• How will I analyze my data? 

Let’s take a quick look at some of these.

The core objective of the interviewing process is to generate useful data that will help you address your overall research aims. Therefore, your interviews need to be conducted in a way that directly links to your research aims, objectives and research questions (i.e. your “golden thread”). This means that you need to carefully consider the questions you’ll ask to ensure that they align with and feed into your golden thread. If any question doesn’t align with this, you may want to consider scrapping it.

Another important design choice is whether you’ll use an unstructured, semi-structured or structured interview approach . For semi-structured interviews, you will have a list of questions that you plan to ask and these questions will be open-ended in nature. You’ll also allow the discussion to digress from the core question set if something interesting comes up. This means that the type of information generated might differ a fair amount between interviews.

Contrasted to this, a structured approach to interviews is more rigid, where a specific set of closed questions is developed and asked for each interviewee in exactly the same order. Closed questions have a limited set of answers, that are often single-word answers. Therefore, you need to think about what you’re trying to achieve with your research project (i.e. your research aims) and decided on which approach would be best suited in your case.

It is also important to plan ahead with regards to who will be interviewed and how. You need to think about how you will approach the possible interviewees to get their cooperation, who will conduct the interviews, when to conduct the interviews and how to record the interviews. For each of these decisions, it’s also essential to make sure that all ethical considerations and data protection laws are taken into account.

Finally, you should think through how you plan to analyze the data (i.e., your qualitative analysis method) generated by the interviews. Different types of analysis rely on different types of data, so you need to ensure you’re asking the right types of questions and correctly guiding your respondents.

Simply put, you need to have a plan of action regarding the specifics of your interview approach before you start collecting data. If not, you’ll end up drifting in your approach from interview to interview, which will result in inconsistent, unusable data.

2. Not having good interview technique

While you’re generally not expected to become you to be an expert interviewer for a dissertation or thesis, it is important to practice good interview technique and develop basic interviewing skills .

Let’s go through some basics that will help the process along.

Firstly, before the interview , make sure you know your interview questions well and have a clear idea of what you want from the interview. Naturally, the specificity of your questions will depend on whether you’re taking a structured, semi-structured or unstructured approach, but you still need a consistent starting point . Ideally, you should develop an interview guide beforehand (more on this later) that details your core question and links these to the research aims, objectives and research questions.

Before you undertake any interviews, it’s a good idea to do a few mock interviews with friends or family members. This will help you get comfortable with the interviewer role, prepare for potentially unexpected answers and give you a good idea of how long the interview will take to conduct. In the interviewing process, you’re likely to encounter two kinds of challenging interviewees ; the two-word respondent and the respondent who meanders and babbles. Therefore, you should prepare yourself for both and come up with a plan to respond to each in a way that will allow the interview to continue productively.

To begin the formal interview , provide the person you are interviewing with an overview of your research. This will help to calm their nerves (and yours) and contextualize the interaction. Ultimately, you want the interviewee to feel comfortable and be willing to be open and honest with you, so it’s useful to start in a more casual, relaxed fashion and allow them to ask any questions they may have. From there, you can ease them into the rest of the questions.

As the interview progresses , avoid asking leading questions (i.e., questions that assume something about the interviewee or their response). Make sure that you speak clearly and slowly , using plain language and being ready to paraphrase questions if the person you are interviewing misunderstands. Be particularly careful with interviewing English second language speakers to ensure that you’re both on the same page.

Engage with the interviewee by listening to them carefully and acknowledging that you are listening to them by smiling or nodding. Show them that you’re interested in what they’re saying and thank them for their openness as appropriate. This will also encourage your interviewee to respond openly.

Need a helping hand?

3. Not securing a suitable location and quality equipment

Where you conduct your interviews and the equipment you use to record them both play an important role in how the process unfolds. Therefore, you need to think carefully about each of these variables before you start interviewing.

Poor location: A bad location can result in the quality of your interviews being compromised, interrupted, or cancelled. If you are conducting physical interviews, you’ll need a location that is quiet, safe, and welcoming . It’s very important that your location of choice is not prone to interruptions (the workplace office is generally problematic, for example) and has suitable facilities (such as water, a bathroom, and snacks).

If you are conducting online interviews , you need to consider a few other factors. Importantly, you need to make sure that both you and your respondent have access to a good, stable internet connection and electricity. Always check before the time that both of you know how to use the relevant software and it’s accessible (sometimes meeting platforms are blocked by workplace policies or firewalls). It’s also good to have alternatives in place (such as WhatsApp, Zoom, or Teams) to cater for these types of issues.

Poor equipment: Using poor-quality recording equipment or using equipment incorrectly means that you will have trouble transcribing, coding, and analyzing your interviews. This can be a major issue , as some of your interview data may go completely to waste if not recorded well. So, make sure that you use good-quality recording equipment and that you know how to use it correctly.

To avoid issues, you should always conduct test recordings before every interview to ensure that you can use the relevant equipment properly. It’s also a good idea to spot check each recording afterwards, just to make sure it was recorded as planned. If your equipment uses batteries, be sure to always carry a spare set.

4. Not having a basic risk management plan

Many possible issues can arise during the interview process. Not planning for these issues can mean that you are left with compromised data that might not be useful to you. Therefore, it’s important to map out some sort of risk management plan ahead of time, considering the potential risks, how you’ll minimize their probability and how you’ll manage them if they materialize.

Common potential issues related to the actual interview include cancellations (people pulling out), delays (such as getting stuck in traffic), language and accent differences (especially in the case of poor internet connections), issues with internet connections and power supply. Other issues can also occur in the interview itself. For example, the interviewee could drift off-topic, or you might encounter an interviewee who does not say much at all.

You can prepare for these potential issues by considering possible worst-case scenarios and preparing a response for each scenario. For instance, it is important to plan a backup date just in case your interviewee cannot make it to the first meeting you scheduled with them. It’s also a good idea to factor in a 30-minute gap between your interviews for the instances where someone might be late, or an interview runs overtime for other reasons. Make sure that you also plan backup questions that could be used to bring a respondent back on topic if they start rambling, or questions to encourage those who are saying too little.

In general, it’s best practice to plan to conduct more interviews than you think you need (this is called oversampling ). Doing so will allow you some room for error if there are interviews that don’t go as planned, or if some interviewees withdraw. If you need 10 interviews, it is a good idea to plan for 15. Likely, a few will cancel , delay, or not produce useful data.

5. Not keeping your golden thread front of mind

We touched on this a little earlier, but it is a key point that should be central to your entire research process. You don’t want to end up with pages and pages of data after conducting your interviews and realize that it is not useful to your research aims . Your research aims, objectives and research questions – i.e., your golden thread – should influence every design decision and should guide the interview process at all times. 

A useful way to avoid this mistake is by developing an interview guide before you begin interviewing your respondents. An interview guide is a document that contains all of your questions with notes on how each of the interview questions is linked to the research question(s) of your study. You can also include your research aims and objectives here for a more comprehensive linkage. 

You can easily create an interview guide by drawing up a table with one column containing your core interview questions . Then add another column with your research questions , another with expectations that you may have in light of the relevant literature and another with backup or follow-up questions . As mentioned, you can also bring in your research aims and objectives to help you connect them all together. If you’d like, you can download a copy of our free interview guide here .

Recap: Qualitative Interview Mistakes

In this post, we’ve discussed 5 common costly mistakes that are easy to make in the process of planning and conducting qualitative interviews.

To recap, these include:

If you have any questions about these interviewing mistakes, drop a comment below. Alternatively, if you’re interested in getting 1-on-1 help with your thesis or dissertation , check out our dissertation coaching service or book a free initial consultation with one of our friendly Grad Coaches.

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A Step-by-Step Guide for a Successful Qualitative Interview

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Key Takeaways: 

• Qualitative interviews provide in-depth insights from individual respondents, and are useful when follow-up or clarification is needed
• Clarity of objectives and audience is essential to gathering actionable insights from your qualitative research project
• Build a strong researcher-respondent relationship to elicit honest and engaged responses

Qualitative research uses in-depth interviews to gain rich non-numerical data from individuals. This data helps researchers understand concepts, opinions, and personal experiences. Interviews are an excellent method to discover the “why” behind people’s preferences or behaviors, but they require a thoughtful approach.

Continue reading as we explore use cases and define the steps to follow for a successful qualitative interview.

In this Article:

When Should I Use Qualitative Interviews? Conducting a Successful Qualitative Interview – Step by Step Guide

1. Determine Your Objective 2. Understand Your Audience 3. Design Appropriate Questions 4. Organize and Prepare for the Interview 5. Conduct the Interview 6. Transcribe and Analyze Responses 7. Learn, Adapt, and Evolve Your Interviews

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When Should I Use Qualitative Interviews?

Qualitative research is used to obtain context and describe underlying factors. It describes “how” and “why.”

Perhaps a business wants to understand what product features are most or least important to each target segment. They could ask:

“Between product A and product B, how would the features in each product influence your buying decision?”

This creates an opportunity for the respondent to reveal what features are personally important and unimportant for them. In an interview setting, researchers can go deeper into why these features are important, and how important each feature is in comparison to others.

Qualitative interviews are best when:

• You need in-depth insights
• You want answers to a range of follow-up questions, building on prior responses
• Your questions require significant explanation and reasoning
• You explore complex and confusing topics with respondents
• You want to understand what drives consumer decisions
• You want to hear the unique voice of your audience first-hand

Conducting a Successful Qualitative Interview – Step by Step Guide

Knowing when to use a qualitative interview is a great first step, but now you need to understand how best to conduct one. Our experts share a range of steps to follow as you embark on a qualitative interview and best practices for each.

1. Determine Your Objective

What are you trying to understand? The answer to this is critical in guiding your qualitative research process.

Some common examples:

• Understand consumer perceptions of products, services, or brand
• Reveal strengths and weaknesses in product or service portfolios
• Understand consumer buying behaviors
• Test the usability of a website or digital service
• Emotional reactions to packaging design and marketing assets

2. Understand Your Audience

Who is your target audience for this project? Have a clear understanding of who you need to hear from to meet your research objective.

Here are some examples of objectives, and the sample that is most suited to each:

• If you want to understand how existing customers perceive the quality of your products, you need a sample of existing customers.
• If you want to understand why consumers choose competitor products over yours, you need a sample of non-customers who buy products from your primary competitor.
• If you want to understand how the average person perceives your brand, you need a combination of existing customers, non-customers with awareness of your brand, and unaware non-customers.

3. Design Appropriate Questions

The questions you ask must align with the objectives of your research without being leading or introducing bias.

Here are some best practices when designing research questions:

• Keep questions open-ended. This increases the depth of insight obtained.
• Follow a structure. For instance, a tree diagram where every question has pre-determined follow-up questions based on anticipated answers. A planned structure increases the quality and validity of responses and reduces distractions.
• Design questions that simplify data collection and analysis. Format the responses collected to be compatible with your tools during data ingestion.
• Keep it simple. Focus on clarity when designing research questions to improve respondent understanding and engagement.

4. Organize and Prepare for the Interview

Relationships are essential to the interview process. Preparation beforehand helps build the respondent-researcher relationship. This relationship creates trust and elicits more honest and in-depth answers from participants. Here are some ways to prepare for an interview:

• Give respondents as much information as possible—such as question lists and question intent. Put this into an interview handbook to improve engagement and effectiveness.
• Conduct the interview in a suitable environment with minimal distractions and stressors.
• Have the necessary materials to record information.
• Interview yourself to identify and fix problems before you start interviewing others.

5. Conduct the Interview

With a structure in place, researchers have a clear plan of action throughout the interview.

During the interview, stay attuned to emotional reactions and body language with the following techniques:

• Create a relaxed atmosphere. Ask respondents about their lives, work, and passions to establish a connection.
• Give respondents your full attention. An engaged researcher encourages an engaged respondent. Plus, they gave up their personal time to help you out.
• Read body language. Is the respondent crossing their arms, looking down to the floor, or not making eye contact? These reactions may signal discomfort or anxiety, offering an opportunity to build rapport.
• Follow the questions but be flexible when listening. Deviations from the script may lead to unexpected and valuable insights.

6. Transcribe and Analyze Responses

Convert recorded audio responses to text. Decide early which tool or solution will work best for your needs.

Similarly, researchers may need to annotate video responses to describe behaviors and surrounding context before analysis; e.g., this person gritted their teeth during that response, that person’s vocal tone was anxious and uncertain, etc.

Transcribe responses into a format ready for analysis upon ingestion into your business intelligence tools.

7. Learn, Adapt, and Evolve Your Interviews

Each interview is an opportunity to improve the process. Take time after a project to evaluate how it went.

What did you learn about the process? Was it easy or confusing? Was the respondent comfortable or on edge? Did you get the responses you needed?

Scrutinize your interview approach. Look for ways to improve and innovate the process for better outcomes next time.

Now, you should have a good idea of when to use and how to approach qualitative interviews.

Sago has decades of experience across both quantitative and qualitative research. Our experts find interviews ideal for in-depth qualitative insights that guide new product and service development or improve market positioning for existing offerings. We offer both in-person facilities and online spaces to conduct qualitative interviews.

If you still have questions, get in touch with Sago for help with your next research project.

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Interviewing in Qualitative Research

• First Online: 14 December 2017

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• Svetlana Gudkova 4  

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The interview is one of the basic methods of data collection employed in the social sciences. It is worth noting that this method is not restricted solely to the qualitative research. Interviews have been actively taken advantage of by representatives of various scientific traditions. Both the supporters of the positivist paradigm and the interpretivist one use the technique of the interview to collect data even though the expectations and assumptions of researchers as well as the process of preparing the interview and the conclusion sphere differ fundamentally. The chapter presents different types of interviews employed by the researchers to collect the data in a qualitative research and discusses the process of preparation and conducting the interviews.

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Gudkova, S. (2018). Interviewing in Qualitative Research. In: Ciesielska, M., Jemielniak, D. (eds) Qualitative Methodologies in Organization Studies. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-65442-3_4

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Top 20 Qualitative Research Interview Questions & Answers

Master your responses to Qualitative Research related interview questions with our example questions and answers. Boost your chances of landing the job by learning how to effectively communicate your Qualitative Research capabilities.

Diving into the intricacies of human behavior, thoughts, and experiences is the lifeblood of qualitative research. As a professional in this nuanced field, you are well-versed in the art of gathering rich, descriptive data that can provide deep insights into complex issues. Now, as you prepare to take on new challenges in your career, it’s time to demonstrate not only your expertise in qualitative methodologies but also your ability to think critically and adapt to various research contexts.

Whether you’re interviewing for an academic position, a role within a market research firm, or any other setting where qualitative skills are prized, being prepared with thoughtful responses to potential interview questions can set you apart from other candidates. In this article, we will discuss some of the most common questions asked during interviews for qualitative research roles, offering guidance on how best to articulate your experience and approach to prospective employers.

Common Qualitative Research Interview Questions

1. how do you ensure the credibility of your data in qualitative research.

Ensuring credibility in qualitative research is crucial for the trustworthiness of the findings. By asking about methodological rigor, the interviewer is assessing a candidate’s understanding of strategies such as triangulation, member checking, and maintaining a detailed audit trail, which are essential for substantiating the integrity of qualitative data.

When responding to this question, you should articulate a multi-faceted approach to establishing credibility. Begin by highlighting your understanding of the importance of a well-defined research design and data collection strategy. Explain how you incorporate methods like triangulation, using multiple data sources or perspectives to confirm the consistency of the information obtained. Discuss your process for member checking—obtaining feedback on your findings from the participants themselves—to add another layer of validation. Mention your dedication to keeping a comprehensive audit trail, documenting all stages of the research process, which enables peer scrutiny and adds to the transparency of the study. Emphasize your ongoing commitment to reflexivity, where you continually examine your biases and influence on the research. Through this detailed explanation, you demonstrate a conscientious and systematic approach to safeguarding the credibility of your qualitative research.

Example: “ To ensure the credibility of data in qualitative research, I employ a rigorous research design that is both systematic and reflective. Initially, I establish clear protocols for data collection, which includes in-depth interviews, focus groups, and observations, ensuring that each method is well-suited to the research questions. To enhance the validity of the findings, I apply triangulation, drawing on various data sources, theoretical frameworks, and methodologies to cross-verify the information and interpretations.

During the analysis phase, member checking is a critical step, where I return to participants with a summary of the findings to validate the accuracy and resonance of the interpreted data with their experiences. This not only strengthens the credibility of the results but also enriches the data by incorporating participant insights. Furthermore, I maintain a comprehensive audit trail, meticulously documenting the research process, decisions made, and data transformations. This transparency allows for peer review and ensures that the research can be followed and critiqued by others in the field.

Lastly, reflexivity is integral to my practice. I continuously engage in self-reflection to understand and articulate my biases and assumptions and how they may influence the research process. By doing so, I can mitigate potential impacts on the data and interpretations, ensuring that the findings are a credible representation of the phenomenon under investigation.”

2. Describe a situation where you had to adapt your research methodology due to unforeseen challenges.

When unexpected variables arise, adaptability in research design is vital to maintain the integrity and validity of the study. This question seeks to assess a candidate’s problem-solving skills, flexibility, and resilience in the face of research challenges.

When responding, share a specific instance where you encountered a challenge that impacted your research methodology. Detail the nature of the challenge, the thought process behind your decision to adapt, the steps you took to revise your approach, and the outcome of those changes. Emphasize your critical thinking, your ability to consult relevant literature or peers if necessary, and how your adaptability contributed to the overall success or learning experience of the research project.

Example: “ In a recent qualitative study on community health practices, I encountered a significant challenge when the planned in-person interviews became unfeasible due to a sudden public health concern. The initial methodology was designed around face-to-face interactions to capture rich, detailed narratives. However, with participant safety as a priority, I quickly pivoted to remote data collection methods. After reviewing relevant literature on virtual qualitative research, I adapted the protocol to include video conferencing and phone interviews, ensuring I could still engage deeply with participants. This adaptation required a reevaluation of our ethical considerations, particularly around confidentiality and informed consent in digital formats.

The shift to remote interviews introduced concerns about potential biases, as the change might exclude individuals without access to the necessary technology. To mitigate this, I also offered the option of asynchronous voice recordings or email responses as a means to participate. This inclusive approach not only preserved the integrity of the study but also revealed an unexpected layer of data regarding digital literacy and access in the community. The study’s findings were robust, and the methodology adaptation was reflected upon in the final report, contributing to the discourse on the flexibility and resilience of qualitative research in dynamic contexts.”

3. What strategies do you employ for effective participant observation?

For effective participant observation, a balance between immersion and detachment is necessary to gather in-depth understanding without influencing the natural setting. This method allows the researcher to collect rich, contextual data that surveys or structured interviews might miss.

When responding to this question, highlight your ability to blend in with the participant group to minimize your impact on their behavior. Discuss your skills in active listening, detailed note-taking, and ethical considerations such as informed consent and maintaining confidentiality. Mention any techniques you use to reflect on your observations critically and how you ensure that your presence does not alter the dynamics of the group you are studying. It’s also effective to provide examples from past research where your participant observation led to valuable insights that informed your study’s findings.

Example: “ In participant observation, my primary strategy is to achieve a balance between immersion and detachment. I immerse myself in the environment to gain a deep understanding of the context and participants’ perspectives, while remaining sufficiently detached to observe and analyze behaviors and interactions objectively. To blend in, I adapt to the cultural norms and social cues of the group, which often involves a period of learning and adjustment to minimize my impact on their behavior.

Active listening is central to my approach, allowing me to capture the subtleties of communication beyond verbal exchanges. I complement this with meticulous note-taking, often employing a system of shorthand that enables me to record details without disrupting the flow of interaction. Ethically, I prioritize informed consent and confidentiality, ensuring participants are aware of my role and the study’s purpose. After observations, I engage in reflexive practice, critically examining my own biases and influence on the research setting. This reflexivity was instrumental in a past project where my awareness of my impact on group dynamics led to the discovery of underlying power structures that were not immediately apparent, significantly enriching the study’s findings.”

4. In what ways do you maintain ethical standards while conducting in-depth interviews?

Maintaining ethical standards during in-depth interviews involves respecting participant confidentiality, ensuring informed consent, and being sensitive to power dynamics. Ethical practice in this context is not only about adhering to institutional guidelines but also about fostering an environment where interviewees feel respected and understood.

When responding to this question, it’s vital to articulate a clear understanding of ethical frameworks such as confidentiality and informed consent. Describe specific strategies you employ, such as anonymizing data, obtaining consent through clear communication about the study’s purpose and the participant’s role, and ensuring the interviewee’s comfort and safety during the conversation. Highlight any training or certifications you’ve received in ethical research practices and give examples from past research experiences where you navigated ethical dilemmas successfully. This approach demonstrates your commitment to integrity in the research process and your ability to protect the well-being of your subjects.

Example: “ Maintaining ethical standards during in-depth interviews is paramount to the integrity of the research process. I ensure that all participants are fully aware of the study’s purpose, their role within it, and the ways in which their data will be used. This is achieved through a clear and comprehensive informed consent process. I always provide participants with the option to withdraw from the study at any point without penalty.

To safeguard confidentiality, I employ strategies such as anonymizing data and using secure storage methods. I am also attentive to the comfort and safety of interviewees, creating a respectful and non-threatening interview environment. In situations where sensitive topics may arise, I am trained to handle these with the necessary care and professionalism. For instance, in a past study involving vulnerable populations, I implemented additional privacy measures and worked closely with an ethics review board to navigate the complexities of the research context. My approach is always to prioritize the dignity and rights of the participants, adhering to ethical guidelines and best practices established in the field.”

5. How do you approach coding textual data without personal biases influencing outcomes?

When an interviewer poses a question about coding textual data free from personal biases, they are probing your ability to maintain objectivity and adhere to methodological rigor. This question tests your understanding of qualitative analysis techniques and your awareness of the researcher’s potential to skew data interpretation.

When responding, it’s essential to articulate your familiarity with established coding procedures such as open, axial, or thematic coding. Emphasize your systematic approach to data analysis, which might include multiple rounds of coding, peer debriefing, and maintaining a reflexive journal. Discuss the importance of bracketing your preconceptions during data analysis and how you would seek to validate your coding through methods such as triangulation or member checking. Your answer should convey a balance between a structured approach to coding and an openness to the data’s nuances, demonstrating your commitment to producing unbiased and trustworthy qualitative research findings.

Example: “ In approaching textual data coding, I adhere to a structured yet flexible methodology that mitigates personal bias. Initially, I engage in open coding to categorize data based on its manifest content, allowing patterns to emerge organically. This is followed by axial coding, where I explore connections between categories, and if applicable, thematic coding to identify overarching themes. Throughout this process, I maintain a reflexive journal to document my thought process and potential biases, ensuring transparency and self-awareness.

To ensure the reliability of my coding, I employ peer debriefing sessions, where colleagues scrutinize my coding decisions, challenging assumptions and offering alternative interpretations. This collaborative scrutiny helps to counteract any personal biases that might have crept into the analysis. Additionally, I utilize methods such as triangulation, comparing data across different sources, and member checking, soliciting feedback from participants on the accuracy of the coded data. These strategies collectively serve to validate the coding process and ensure that the findings are a credible representation of the data, rather than a reflection of my preconceptions.”

6. What is your experience with utilizing grounded theory in qualitative studies?

Grounded theory is a systematic methodology that operates almost in a reverse fashion from traditional research. Employers ask about your experience with grounded theory to assess your ability to conduct research that is flexible and adaptable to the data.

When responding, you should outline specific studies or projects where you’ve applied grounded theory. Discuss the nature of the data you worked with, the process of iterative data collection and analysis, and how you developed a theoretical framework as a result. Highlight any challenges you faced and how you overcame them, as well as the outcomes of your research. This will show your practical experience and your ability to engage deeply with qualitative data to extract meaningful theories and conclusions.

Example: “ In applying grounded theory to my qualitative studies, I have embraced its iterative approach to develop a theoretical framework grounded in empirical data. For instance, in a project exploring the coping mechanisms of individuals with chronic illnesses, I conducted in-depth interviews and focus groups, allowing the data to guide the research process. Through constant comparative analysis, I coded the data, identifying core categories and the relationships between them. This emergent coding process was central to refining and saturating the categories, ensuring the development of a robust theory that encapsulated the lived experiences of the participants.

Challenges such as data saturation and ensuring theoretical sensitivity were navigated by maintaining a balance between openness to the data and guiding research questions. The iterative nature of grounded theory facilitated the identification of nuanced coping strategies that were not initially apparent, leading to a theory that emphasized the dynamic interplay between personal agency and social support. The outcome was a substantive theory that not only provided a deeper understanding of the participants’ experiences but also had practical implications for designing support systems for individuals with chronic conditions.”

7. Outline the steps you take when conducting a thematic analysis.

Thematic analysis is a method used to identify, analyze, and report patterns within data, and it requires a systematic approach to ensure validity and reliability. This question assesses whether a candidate can articulate a clear, methodical process that will yield insightful findings from qualitative data.

When responding, you should outline a step-by-step process that begins with familiarization with the data, whereby you immerse yourself in the details, taking notes and highlighting initial ideas. Proceed to generating initial codes across the entire dataset, which involves organizing data into meaningful groups. Then, search for themes by collating codes into potential themes and gathering all data relevant to each potential theme. Review these themes to ensure they work in relation to the coded extracts and the entire dataset, refining them as necessary. Define and name themes, which entails developing a detailed analysis of each theme and determining the essence of what each theme is about. Finally, report the findings, weaving the analytic narrative with vivid examples, within the context of existing literature and the research questions. This methodical response not only showcases your technical knowledge but also demonstrates an organized thought process and the ability to communicate complex procedures clearly.

Example: “ In conducting a thematic analysis, I begin by thoroughly immersing myself in the data, which involves meticulously reading and re-reading the content to gain a deep understanding of its breadth and depth. During this stage, I make extensive notes and begin to mark initial ideas that strike me as potentially significant.

Following familiarization, I generate initial codes systematically across the entire dataset. This coding process is both reflective and interpretative, as it requires me to identify and categorize data segments that are pertinent to the research questions. These codes are then used to organize the data into meaningful groups.

Next, I search for themes by examining the codes and considering how they may combine to form overarching themes. This involves collating all the coded data relevant to each potential theme and considering the interrelationships between codes, themes, and different levels of themes, which may include sub-themes.

The subsequent step is to review these themes, checking them against the dataset to ensure they accurately represent the data. This may involve collapsing some themes into each other, splitting others, and refining the specifics of each theme. The essence of this iterative process is to refine the themes so that they tell a coherent story about the data.

Once the themes are satisfactorily developed, I define and name them. This involves a detailed analysis of each theme and determining what aspect of the data each theme captures. I aim to articulate the nuances within each theme, identifying the story that each tells about the data, and considering how this relates to the broader research questions and literature.

Lastly, I report the findings, weaving together the thematic analysis narrative. This includes selecting vivid examples that compellingly illustrate each theme, discussing how the themes interconnect, and situating them within the context of existing literature and the research questions. This final write-up is not merely about summarizing the data but about telling a story that provides insights into the research topic.”

8. When is it appropriate to use focus groups rather than individual interviews, and why?

Choosing between focus groups and individual interviews depends on the research goals and the nature of the information sought. Focus groups excel in exploring complex behaviors, attitudes, and experiences through the dynamic interaction of participants.

When responding to this question, articulate the strengths of both methods, matching them to specific research scenarios. For focus groups, emphasize your ability to facilitate lively, guided discussions that leverage group dynamics to elicit a breadth of perspectives. For individual interviews, highlight your skill in creating a safe, confidential space where participants can share detailed, personal experiences. Demonstrate strategic thinking by discussing how you would decide on the most suitable method based on the research question, participant characteristics, and the type of data needed to achieve your research objectives.

Example: “ Focus groups are particularly apt when the research question benefits from the interaction among participants, as the group dynamics can stimulate memories, ideas, and experiences that might not surface in one-on-one interviews. They are valuable for exploring the range of opinions or feelings about a topic, allowing researchers to observe consensus formation, the diversity of perspectives, and the reasoning behind attitudes. This method is also efficient for gathering a breadth of data in a limited timeframe. However, it’s crucial to ensure that the topic is suitable for discussion in a group setting and that participants are comfortable speaking in front of others.

Conversely, individual interviews are more appropriate when the subject matter is sensitive or requires deep exploration of personal experiences. They provide a private space for participants to share detailed and nuanced insights without the influence of others, which can be particularly important when discussing topics that may not be openly talked about in a group. The method allows for a tailored approach, where the interviewer can adapt questions based on the participant’s responses, facilitating a depth of understanding that is harder to achieve in a group setting. The decision between the two methods ultimately hinges on the specific needs of the research, the nature of the topic, and the goals of the study.”

9. Detail how you would validate findings from a case study research design.

In case study research, validation is paramount to ensure that interpretations and conclusions are credible. A well-validated case study reinforces the rigor of the research method and bolsters the transferability of its findings to other contexts.

When responding to this question, detail your process, which might include triangulation, where you corroborate findings with multiple data sources or perspectives; member checking, which involves sharing your interpretations with participants for their input; and seeking peer debriefing, where colleagues critique the process and findings. Explain how these methods contribute to the dependability and confirmability of your research, showing that you are not just collecting data but actively engaging with it to construct a solid, defensible narrative.

Example: “ In validating findings from a case study research design, I employ a multi-faceted approach to ensure the dependability and confirmability of the research. Triangulation is a cornerstone of my validation process, where I corroborate evidence from various data sources, such as interviews, observations, and documents. This method allows for cross-validation and helps in constructing a robust narrative by revealing consistencies and discrepancies in the data.

Member checking is another essential step in my process. By sharing my interpretations with participants, I not only honor their perspectives but also enhance the credibility of the findings. This iterative process ensures that the conclusions drawn are reflective of the participants’ experiences and not solely based on my own interpretations.

Lastly, peer debriefing serves as a critical checkpoint. By engaging colleagues who critique the research process and findings, I open the study to external scrutiny, which helps in mitigating any potential biases and enhances the study’s rigor. These colleagues act as devil’s advocates, challenging assumptions and conclusions, thereby strengthening the study’s validity. Collectively, these strategies form a comprehensive approach to validating case study research, ensuring that the findings are well-substantiated and trustworthy.”

10. What measures do you take to ensure the transferability of your qualitative research findings?

When asked about ensuring transferability, the interviewer is assessing your ability to articulate the relevance of your findings beyond the specific context of your study. They want to know if you can critically appraise your research design and methodology.

To respond effectively, you should discuss the thoroughness of your data collection methods, such as purposive sampling, to gather diverse perspectives that enhance the depth of the data. Explain your engagement with participants and the setting to ensure a rich understanding of the phenomenon under study. Highlight your detailed documentation of the research process, including your reflexivity, to allow others to follow your footsteps analytically. Finally, speak about how you communicate the boundaries of your research applicability and how you encourage readers to consider the transferability of findings to their contexts through clear and comprehensive descriptions of your study’s context, participants, and assumptions.

Example: “ In ensuring the transferability of my qualitative research findings, I prioritize a robust and purposive sampling strategy that captures a wide range of perspectives relevant to the research question. This approach not only enriches the data but also provides a comprehensive understanding of the phenomenon across varied contexts. By doing so, I lay a foundation for the findings to resonate with similar situations, allowing others to judge the applicability of the results to their own contexts.

I meticulously document the research process, including the setting, participant interactions, and my own reflexivity, to provide a transparent and detailed account of how conclusions were reached. This level of documentation serves as a roadmap for other researchers or practitioners to understand the intricacies of the study and evaluate the potential for transferability. Furthermore, I ensure that my findings are presented with a clear delineation of the context, including any cultural, temporal, or geographic nuances, and discuss the assumptions underpinning the study. By offering this rich, contextualized description, I invite readers to engage critically with the findings and assess their relevance to other settings, thus facilitating a responsible and informed application of the research outcomes.”

11. How do you determine when data saturation has been reached in your study?

Determining data saturation is crucial because it signals when additional data does not yield new insights, ensuring efficient use of resources without compromising the depth of understanding. This question is posed to assess a candidate’s experience and judgment in qualitative research.

When responding to this question, one should highlight their systematic approach to data collection and analysis. Discuss the iterative process of engaging with the data, constantly comparing new information with existing codes and themes. Explain how you monitor for emerging patterns and at what point these patterns become consistent and repeatable, indicating saturation. Mention any specific techniques or criteria you employ, such as the use of thematic analysis or constant comparison methods, and how you document the decision-making process to ensure transparency and validity in your research findings.

Example: “ In determining data saturation, I employ a rigorous and iterative approach to data collection and analysis. As I engage with the data, I continuously compare new information against existing codes and themes, carefully monitoring for the emergence of new patterns or insights. Saturation is approached when the data begins to yield redundant information, and no new themes or codes are emerging from the analysis.

I utilize techniques such as thematic analysis and constant comparison methods to ensure a systematic examination of the data. I document each step of the decision-making process, noting when additional data does not lead to new theme identification or when existing themes are fully fleshed out. This documentation not only serves as a checkpoint for determining saturation but also enhances the transparency and validity of the research findings. Through this meticulous process, I can confidently assert that data saturation has been achieved when the collected data offers a comprehensive understanding of the research phenomenon, with a rich and well-developed thematic structure that accurately reflects the research scope.”

12. Relate an instance where member checking significantly altered your research conclusions.

Member checking serves as a vital checkpoint to ensure accuracy, credibility, and resonance of the data with those it represents. It can reveal misunderstandings or even introduce new insights that substantially shift the study’s trajectory or outcomes.

When responding, candidates should recount a specific project where member checking made a pivotal difference in their findings. They should detail the initial conclusions, how the process of member checking was integrated, what feedback was received, and how it led to a re-evaluation or refinement of the research outcomes. This response showcases the candidate’s methodological rigor, flexibility in incorporating feedback, and dedication to producing research that authentically reflects the voices and experiences of the study’s participants.

Example: “ In a recent qualitative study on community responses to urban redevelopment, initial findings suggested broad support for the initiatives among residents. However, during the member checking phase, when participants reviewed and commented on the findings, a nuanced perspective emerged. Several participants highlighted that their apparent support was, in fact, resignation due to a lack of viable alternatives, rather than genuine enthusiasm for the redevelopment plans.

This feedback prompted a deeper dive into the data, revealing a pattern of resigned acceptance across a significant portion of the interviews. The conclusion was substantially revised to reflect this sentiment, emphasizing the complexity of community responses to redevelopment, which included both cautious optimism and skeptical resignation. This critical insight not only enriched the study’s validity but also had profound implications for policymakers interested in understanding the true sentiment of the affected communities.”

13. What are the key considerations when selecting a sample for phenomenological research?

The selection of a sample in phenomenological research is not about quantity but about the richness and relevance of the data that participants can provide. It requires an intimate knowledge of the research question and a deliberate choice to include participants who have experienced the phenomenon in question.

When responding to this question, it’s essential to emphasize the need for a purposeful sampling strategy that aims to capture a broad spectrum of perspectives on the phenomenon under study. Discuss the importance of sample diversity to ensure the findings are robust and reflect varied experiences. Mention the necessity of establishing clear criteria for participant selection and the willingness to adapt as the research progresses. Highlighting your commitment to ethical considerations, such as informed consent and the respectful treatment of participants’ information, will also demonstrate your thorough understanding of the nuances in qualitative sampling.

Example: “ In phenomenological research, the primary goal is to understand the essence of experiences concerning a particular phenomenon. Therefore, the key considerations for sample selection revolve around identifying individuals who have experienced the phenomenon of interest and can articulate their lived experiences. Purposeful sampling is essential to ensure that the participants chosen can provide rich, detailed accounts that contribute to a deep understanding of the phenomenon.

The diversity of the sample is also crucial. It is important to select participants who represent a range of perspectives within the phenomenon, not just a homogenous group. This might involve considering factors such as age, gender, socio-economic status, or other relevant characteristics that could influence their experiences. While the sample size in phenomenological studies is often small to allow for in-depth analysis, it is vital to ensure that the sample is varied enough to uncover a comprehensive understanding of the phenomenon.

Lastly, ethical considerations are paramount. Participants must give informed consent, understanding the nature of the study and their role in it. The researcher must also be prepared to handle sensitive information with confidentiality and respect, ensuring the participants’ well-being is prioritized throughout the study. Adapting the sample selection criteria as the study progresses is also important, as initial interviews may reveal additional nuances that require the inclusion of further varied perspectives to fully grasp the phenomenon.”

14. Which software tools do you prefer for qualitative data analysis, and for what reasons?

The choice of software tools for qualitative data analysis reflects a researcher’s approach to data synthesis and interpretation. It also indicates their proficiency with technology and their ability to leverage sophisticated features to deepen insights.

When responding, it’s essential to discuss specific features of the software tools you prefer, such as coding capabilities, ease of data management, collaborative features, or the ability to handle large datasets. Explain how these features have enhanced your research outcomes in the past. For example, you might highlight the use of NVivo for its robust coding structure that helped you organize complex data efficiently or Atlas.ti for its intuitive interface and visualization tools that made it easier to detect emerging patterns. Your response should demonstrate your analytical thought process and your commitment to rigorous qualitative analysis.

Example: “ In my qualitative research endeavors, I have found NVivo to be an invaluable tool, primarily due to its advanced coding capabilities and its ability to manage large and complex datasets effectively. The node structure in NVivo facilitates a hierarchical organization of themes, which streamlines the coding process and enhances the reliability of the data analysis. This feature was particularly beneficial in a recent project where the depth and volume of textual data required a robust system to ensure consistency and comprehensiveness in theme development.

Another tool I frequently utilize is Atlas.ti, which stands out for its user-friendly interface and powerful visualization tools. These features are instrumental in identifying and illustrating relationships between themes, thereby enriching the interpretive depth of the analysis. The network views in Atlas.ti have enabled me to construct clear visual representations of the data interconnections, which not only supported my analytical narrative but also facilitated stakeholder understanding and engagement. The combination of these tools, leveraging their respective strengths, has consistently augmented the quality and impact of my qualitative research outcomes.”

15. How do you handle discrepancies between participants’ words and actions in ethnographic research?

Ethnographic research hinges on the researcher’s ability to interpret both verbal and non-verbal data to draw meaningful conclusions. This question allows the interviewer to assess a candidate’s methodological rigor and analytical skills.

When responding, it’s essential to emphasize your systematic approach to reconciling such discrepancies. Discuss the importance of context, the use of triangulation to corroborate findings through multiple data sources, and the strategies you employ to interpret and integrate conflicting information. Highlight your commitment to ethical research practices, the ways you ensure participant understanding and consent, and your experience with reflective practice to mitigate researcher bias. Showcasing your ability to remain flexible and responsive to the data, while maintaining a clear analytical framework, will demonstrate your proficiency in qualitative research.

Example: “ In ethnographic research, discrepancies between participants’ words and actions are not only common but also a valuable source of insight. When I encounter such discrepancies, I first consider the context in which they occur, as it often holds the key to understanding the divergence. Cultural norms, social pressures, or even the presence of the researcher can influence participants’ behaviors and self-reporting. I employ triangulation, utilizing multiple data sources such as interviews, observations, and relevant documents to construct a more comprehensive understanding of the phenomena at hand.

I also engage in reflective practice to examine my own biases and assumptions that might influence data interpretation. By maintaining a stance of cultural humility and being open to the participants’ perspectives, I can better understand the reasons behind their actions and words. When integrating conflicting information, I look for patterns and themes that can reconcile the differences, often finding that they reveal deeper complexities within the social context being studied. Ethical research practices, including ensuring participant understanding and consent, are paramount throughout this process, as they help maintain the integrity of both the data and the relationships with participants.”

16. What role does reflexivity play in your research process?

Reflexivity is an ongoing self-assessment that ensures research findings are not merely a reflection of the researcher’s preconceptions, thereby increasing the credibility and authenticity of the work.

When responding, illustrate your understanding of reflexivity with examples from past research experiences. Discuss how you have actively engaged in reflexivity by questioning your assumptions, how this shaped your research design, and the methods you employed to ensure that your findings were informed by the data rather than your personal beliefs. Demonstrate your commitment to ethical research practice by highlighting how you’ve maintained an open dialogue with your participants and peers to challenge and refine your interpretations.

Example: “ Reflexivity is a cornerstone of my qualitative research methodology, as it allows me to critically examine my own influence on the research process and outcomes. In practice, I maintain a reflexive journal throughout the research process, documenting my preconceptions, emotional responses, and decision-making rationales. This ongoing self-analysis ensures that I remain aware of my potential biases and the ways in which my background and perspectives might shape the data collection and analysis.

For instance, in a recent ethnographic study, I recognized my own cultural assumptions could affect participant interactions. To mitigate this, I incorporated member checking and peer debriefing as integral parts of the research cycle. By actively seeking feedback on my interpretations from both participants and fellow researchers, I was able to challenge my initial readings of the data and uncover deeper, more nuanced insights. This reflexive approach not only enriched the research findings but also upheld the integrity and credibility of the study, fostering a more authentic and ethical representation of the participants’ experiences.”

17. Describe a complex qualitative dataset you’ve managed and how you navigated its challenges.

Managing a complex qualitative dataset requires meticulous organization, a strong grasp of research methods, and the ability to discern patterns and themes amidst a sea of words and narratives. This question evaluates the candidate’s analytical and critical thinking skills.

When responding to this question, you should focus on a specific project that exemplifies your experience with complex qualitative data. Outline the scope of the data, the methods you used for organization and analysis, and the challenges you encountered—such as data coding, thematic saturation, or ensuring reliability and validity. Discuss the strategies you implemented to address these challenges, such as iterative coding, member checking, or triangulation. By providing concrete examples, you demonstrate not only your technical ability but also your methodological rigor and dedication to producing insightful, credible research findings.

Example: “ In a recent project, I managed a complex qualitative dataset that comprised over 50 in-depth interviews, several focus groups, and field notes from participant observation. The data was rich with nuanced perspectives on community health practices, but it presented challenges in ensuring thematic saturation and maintaining a systematic approach to coding across multiple researchers.

To navigate these challenges, I employed a rigorous iterative coding process, utilizing NVivo software to facilitate organization and analysis. Initially, I conducted a round of open coding to identify preliminary themes, followed by axial coding to explore the relationships between these themes. As the dataset was extensive, I also implemented a strategy of constant comparison to refine and merge codes, ensuring thematic saturation was achieved. To enhance the reliability and validity of our findings, I organized regular peer debriefing sessions, where the research team could discuss and resolve discrepancies in coding and interpretation. Additionally, I conducted member checks with a subset of participants, which not only enriched the data but also validated our thematic constructs. This meticulous approach enabled us to develop a robust thematic framework that accurately reflected the complexity of the community’s health practices and informed subsequent policy recommendations.”

18. How do you integrate quantitative data to enhance the richness of a primarily qualitative study?

Integrating quantitative data with qualitative research can add a layer of objectivity, enhance validity, and offer a scalable dimension to the findings. This mixed-methods approach can help in identifying outliers or anomalies in qualitative data.

When responding to this question, a candidate should articulate their understanding of both qualitative and quantitative research methodologies. They should discuss specific techniques such as triangulation, where quantitative data serves as a corroborative tool for qualitative findings, or embedded analysis, where quantitative data provides a backdrop for deep qualitative exploration. The response should also include practical examples of past research scenarios where the candidate successfully merged both data types to strengthen their study, highlighting their ability to create a symbiotic relationship between numbers and narratives for richer, more robust research outcomes.

Example: “ Integrating quantitative data into a qualitative study can significantly enhance the depth and credibility of the research findings. In my experience, I employ triangulation to ensure that themes emerging from qualitative data are not only rich in context but also empirically grounded. For instance, in a study exploring patient satisfaction, while qualitative interviews might reveal nuanced patient experiences, quantitative satisfaction scores can be used to validate and quantify the prevalence of these experiences across a larger population.

Furthermore, I often use quantitative data as a formative tool to guide the qualitative inquiry. By initially analyzing patterns in quantitative data, I can identify areas that require a deeper understanding through qualitative methods. For example, if a survey indicates a trend in consumer behavior, follow-up interviews or focus groups can explore the motivations behind that trend. This embedded analysis approach ensures that qualitative findings are not only contextually informed but also quantitatively relevant, leading to a more comprehensive understanding of the research question.”

19. What is your rationale for choosing narrative inquiry over other qualitative methods in storytelling contexts?

Narrative inquiry delves into individual stories to find broader truths and patterns. This method captures the richness of how people perceive and make sense of their lives, revealing the interplay of various factors in shaping narratives.

When responding, articulate your understanding of narrative inquiry, emphasizing its strengths in capturing lived experiences and its ability to provide a detailed, insider’s view of a phenomenon. Highlight your knowledge of how narrative inquiry can uncover the nuances of storytelling, such as the role of language, emotions, and context, which are essential for a deep understanding of the subject matter. Demonstrate your ability to choose an appropriate research method based on the research question, objectives, and the nature of the data you aim to collect.

Example: “ Narrative inquiry is a powerful qualitative method that aligns exceptionally well with the exploration of storytelling contexts due to its focus on the richness of personal experience and the construction of meaning. By delving into individuals’ stories, narrative inquiry allows researchers to capture the complexities of lived experiences, which are often embedded with emotions, cultural values, and temporal elements that other methods may not fully grasp. The longitudinal nature of narrative inquiry, where stories can be collected and analyzed over time, also offers a dynamic perspective on how narratives evolve, intersect, and influence the storyteller’s identity and worldview.

In choosing narrative inquiry, one is committing to a methodological approach that honors the subjectivity and co-construction of knowledge between the researcher and participants. This approach is particularly adept at uncovering the layers of language use, symbolism, and the interplay of narratives with broader societal discourses. It is this depth and nuance that makes narrative inquiry the method of choice when the research aim is not just to catalog events but to understand the profound implications of storytelling on individual and collective levels. The method’s flexibility in accommodating different narrative forms – be it oral, written, or visual – further underscores its suitability for research that seeks to holistically capture the essence of storytelling within its natural context.”

20. How do you address potential power dynamics that may influence a participant’s responses during interviews?

Recognizing and mitigating the influence of power dynamics is essential to maintain the integrity of the data collected in qualitative research, ensuring that findings reflect the participants’ genuine perspectives.

When responding to this question, one should emphasize their awareness of such dynamics and articulate strategies to minimize their impact. This could include techniques like establishing rapport, using neutral language, ensuring confidentiality, and employing reflexivity—being mindful of one’s own influence on the conversation. Furthermore, demonstrating an understanding of how to create a safe space for open dialogue and acknowledging the importance of participant empowerment can convey a commitment to ethical and effective qualitative research practices.

Example: “ In addressing potential power dynamics, my approach begins with the conscious effort to create an environment of trust and safety. I employ active listening and empathetic engagement to establish rapport, which helps to level the conversational field. I am meticulous in using neutral, non-leading language to avoid inadvertently imposing my own assumptions or perspectives on participants. This is complemented by an emphasis on the voluntary nature of participation and the assurance of confidentiality, which together foster a space where participants feel secure in sharing their authentic experiences.

Reflexivity is a cornerstone of my practice; I continuously self-assess and acknowledge my positionality and its potential influence on the research process. By engaging in this critical self-reflection, I am better equipped to recognize and mitigate any power imbalances that may arise. Moreover, I strive to empower participants by validating their narratives and ensuring that the interview process is not just extractive but also offers them a platform to be heard and to contribute meaningfully to the research. This balanced approach not only enriches the data quality but also adheres to the ethical standards that underpin responsible qualitative research.”

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Qualitative Methods in Health Care Research

Vishnu renjith.

School of Nursing and Midwifery, Royal College of Surgeons Ireland - Bahrain (RCSI Bahrain), Al Sayh Muharraq Governorate, Bahrain

Renjulal Yesodharan

1 Department of Mental Health Nursing, Manipal College of Nursing Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India

Judith A. Noronha

2 Department of OBG Nursing, Manipal College of Nursing Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India

Elissa Ladd

3 School of Nursing, MGH Institute of Health Professions, Boston, USA

Anice George

4 Department of Child Health Nursing, Manipal College of Nursing Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India

Healthcare research is a systematic inquiry intended to generate robust evidence about important issues in the fields of medicine and healthcare. Qualitative research has ample possibilities within the arena of healthcare research. This article aims to inform healthcare professionals regarding qualitative research, its significance, and applicability in the field of healthcare. A wide variety of phenomena that cannot be explained using the quantitative approach can be explored and conveyed using a qualitative method. The major types of qualitative research designs are narrative research, phenomenological research, grounded theory research, ethnographic research, historical research, and case study research. The greatest strength of the qualitative research approach lies in the richness and depth of the healthcare exploration and description it makes. In health research, these methods are considered as the most humanistic and person-centered way of discovering and uncovering thoughts and actions of human beings.

Introduction

Healthcare research is a systematic inquiry intended to generate trustworthy evidence about issues in the field of medicine and healthcare. The three principal approaches to health research are the quantitative, the qualitative, and the mixed methods approach. The quantitative research method uses data, which are measures of values and counts and are often described using statistical methods which in turn aids the researcher to draw inferences. Qualitative research incorporates the recording, interpreting, and analyzing of non-numeric data with an attempt to uncover the deeper meanings of human experiences and behaviors. Mixed methods research, the third methodological approach, involves collection and analysis of both qualitative and quantitative information with an objective to solve different but related questions, or at times the same questions.[ 1 , 2 ]

In healthcare, qualitative research is widely used to understand patterns of health behaviors, describe lived experiences, develop behavioral theories, explore healthcare needs, and design interventions.[ 1 , 2 , 3 ] Because of its ample applications in healthcare, there has been a tremendous increase in the number of health research studies undertaken using qualitative methodology.[ 4 , 5 ] This article discusses qualitative research methods, their significance, and applicability in the arena of healthcare.

Qualitative Research

Diverse academic and non-academic disciplines utilize qualitative research as a method of inquiry to understand human behavior and experiences.[ 6 , 7 ] According to Munhall, “Qualitative research involves broadly stated questions about human experiences and realities, studied through sustained contact with the individual in their natural environments and producing rich, descriptive data that will help us to understand those individual's experiences.”[ 8 ]

Significance of Qualitative Research

The qualitative method of inquiry examines the 'how' and 'why' of decision making, rather than the 'when,' 'what,' and 'where.'[ 7 ] Unlike quantitative methods, the objective of qualitative inquiry is to explore, narrate, and explain the phenomena and make sense of the complex reality. Health interventions, explanatory health models, and medical-social theories could be developed as an outcome of qualitative research.[ 9 ] Understanding the richness and complexity of human behavior is the crux of qualitative research.

Differences between Quantitative and Qualitative Research

The quantitative and qualitative forms of inquiry vary based on their underlying objectives. They are in no way opposed to each other; instead, these two methods are like two sides of a coin. The critical differences between quantitative and qualitative research are summarized in Table 1 .[ 1 , 10 , 11 ]

Differences between quantitative and qualitative research

Qualitative Research Questions and Purpose Statements

Qualitative questions are exploratory and are open-ended. A well-formulated study question forms the basis for developing a protocol, guides the selection of design, and data collection methods. Qualitative research questions generally involve two parts, a central question and related subquestions. The central question is directed towards the primary phenomenon under study, whereas the subquestions explore the subareas of focus. It is advised not to have more than five to seven subquestions. A commonly used framework for designing a qualitative research question is the 'PCO framework' wherein, P stands for the population under study, C stands for the context of exploration, and O stands for the outcome/s of interest.[ 12 ] The PCO framework guides researchers in crafting a focused study question.

Example: In the question, “What are the experiences of mothers on parenting children with Thalassemia?”, the population is “mothers of children with Thalassemia,” the context is “parenting children with Thalassemia,” and the outcome of interest is “experiences.”

The purpose statement specifies the broad focus of the study, identifies the approach, and provides direction for the overall goal of the study. The major components of a purpose statement include the central phenomenon under investigation, the study design and the population of interest. Qualitative research does not require a-priori hypothesis.[ 13 , 14 , 15 ]

Example: Borimnejad et al . undertook a qualitative research on the lived experiences of women suffering from vitiligo. The purpose of this study was, “to explore lived experiences of women suffering from vitiligo using a hermeneutic phenomenological approach.” [ 16 ]

Review of the Literature

In quantitative research, the researchers do an extensive review of scientific literature prior to the commencement of the study. However, in qualitative research, only a minimal literature search is conducted at the beginning of the study. This is to ensure that the researcher is not influenced by the existing understanding of the phenomenon under the study. The minimal literature review will help the researchers to avoid the conceptual pollution of the phenomenon being studied. Nonetheless, an extensive review of the literature is conducted after data collection and analysis.[ 15 ]

Reflexivity

Reflexivity refers to critical self-appraisal about one's own biases, values, preferences, and preconceptions about the phenomenon under investigation. Maintaining a reflexive diary/journal is a widely recognized way to foster reflexivity. According to Creswell, “Reflexivity increases the credibility of the study by enhancing more neutral interpretations.”[ 7 ]

Types of Qualitative Research Designs

The qualitative research approach encompasses a wide array of research designs. The words such as types, traditions, designs, strategies of inquiry, varieties, and methods are used interchangeably. The major types of qualitative research designs are narrative research, phenomenological research, grounded theory research, ethnographic research, historical research, and case study research.[ 1 , 7 , 10 ]

Narrative research

Narrative research focuses on exploring the life of an individual and is ideally suited to tell the stories of individual experiences.[ 17 ] The purpose of narrative research is to utilize 'story telling' as a method in communicating an individual's experience to a larger audience.[ 18 ] The roots of narrative inquiry extend to humanities including anthropology, literature, psychology, education, history, and sociology. Narrative research encompasses the study of individual experiences and learning the significance of those experiences. The data collection procedures include mainly interviews, field notes, letters, photographs, diaries, and documents collected from one or more individuals. Data analysis involves the analysis of the stories or experiences through “re-storying of stories” and developing themes usually in chronological order of events. Rolls and Payne argued that narrative research is a valuable approach in health care research, to gain deeper insight into patient's experiences.[ 19 ]

Example: Karlsson et al . undertook a narrative inquiry to “explore how people with Alzheimer's disease present their life story.” Data were collected from nine participants. They were asked to describe about their life experiences from childhood to adulthood, then to current life and their views about the future life. [ 20 ]

Phenomenological research

Phenomenology is a philosophical tradition developed by German philosopher Edmond Husserl. His student Martin Heidegger did further developments in this methodology. It defines the 'essence' of individual's experiences regarding a certain phenomenon.[ 1 ] The methodology has its origin from philosophy, psychology, and education. The purpose of qualitative research is to understand the people's everyday life experiences and reduce it into the central meaning or the 'essence of the experience'.[ 21 , 22 ] The unit of analysis of phenomenology is the individuals who have had similar experiences of the phenomenon. Interviews with individuals are mainly considered for the data collection, though, documents and observations are also useful. Data analysis includes identification of significant meaning elements, textural description (what was experienced), structural description (how was it experienced), and description of 'essence' of experience.[ 1 , 7 , 21 ] The phenomenological approach is further divided into descriptive and interpretive phenomenology. Descriptive phenomenology focuses on the understanding of the essence of experiences and is best suited in situations that need to describe the lived phenomenon. Hermeneutic phenomenology or Interpretive phenomenology moves beyond the description to uncover the meanings that are not explicitly evident. The researcher tries to interpret the phenomenon, based on their judgment rather than just describing it.[ 7 , 21 , 22 , 23 , 24 ]

Example: A phenomenological study conducted by Cornelio et al . aimed at describing the lived experiences of mothers in parenting children with leukemia. Data from ten mothers were collected using in-depth semi-structured interviews and were analyzed using Husserl's method of phenomenology. Themes such as “pivotal moment in life”, “the experience of being with a seriously ill child”, “having to keep distance with the relatives”, “overcoming the financial and social commitments”, “responding to challenges”, “experience of faith as being key to survival”, “health concerns of the present and future”, and “optimism” were derived. The researchers reported the essence of the study as “chronic illness such as leukemia in children results in a negative impact on the child and on the mother.” [ 25 ]

Grounded Theory Research

Grounded theory has its base in sociology and propagated by two sociologists, Barney Glaser, and Anselm Strauss.[ 26 ] The primary purpose of grounded theory is to discover or generate theory in the context of the social process being studied. The major difference between grounded theory and other approaches lies in its emphasis on theory generation and development. The name grounded theory comes from its ability to induce a theory grounded in the reality of study participants.[ 7 , 27 ] Data collection in grounded theory research involves recording interviews from many individuals until data saturation. Constant comparative analysis, theoretical sampling, theoretical coding, and theoretical saturation are unique features of grounded theory research.[ 26 , 27 , 28 ] Data analysis includes analyzing data through 'open coding,' 'axial coding,' and 'selective coding.'[ 1 , 7 ] Open coding is the first level of abstraction, and it refers to the creation of a broad initial range of categories, axial coding is the procedure of understanding connections between the open codes, whereas selective coding relates to the process of connecting the axial codes to formulate a theory.[ 1 , 7 ] Results of the grounded theory analysis are supplemented with a visual representation of major constructs usually in the form of flow charts or framework diagrams. Quotations from the participants are used in a supportive capacity to substantiate the findings. Strauss and Corbin highlights that “the value of the grounded theory lies not only in its ability to generate a theory but also to ground that theory in the data.”[ 27 ]

Example: Williams et al . conducted a grounded theory research to explore the nature of relationship between the sense of self and the eating disorders. Data were collected form 11 women with a lifetime history of Anorexia Nervosa and were analyzed using the grounded theory methodology. Analysis led to the development of a theoretical framework on the nature of the relationship between the self and Anorexia Nervosa. [ 29 ]

Ethnographic research

Ethnography has its base in anthropology, where the anthropologists used it for understanding the culture-specific knowledge and behaviors. In health sciences research, ethnography focuses on narrating and interpreting the health behaviors of a culture-sharing group. 'Culture-sharing group' in an ethnography represents any 'group of people who share common meanings, customs or experiences.' In health research, it could be a group of physicians working in rural care, a group of medical students, or it could be a group of patients who receive home-based rehabilitation. To understand the cultural patterns, researchers primarily observe the individuals or group of individuals for a prolonged period of time.[ 1 , 7 , 30 ] The scope of ethnography can be broad or narrow depending on the aim. The study of more general cultural groups is termed as macro-ethnography, whereas micro-ethnography focuses on more narrowly defined cultures. Ethnography is usually conducted in a single setting. Ethnographers collect data using a variety of methods such as observation, interviews, audio-video records, and document reviews. A written report includes a detailed description of the culture sharing group with emic and etic perspectives. When the researcher reports the views of the participants it is called emic perspectives and when the researcher reports his or her views about the culture, the term is called etic.[ 7 ]

Example: The aim of the ethnographic study by LeBaron et al . was to explore the barriers to opioid availability and cancer pain management in India. The researchers collected data from fifty-nine participants using in-depth semi-structured interviews, participant observation, and document review. The researchers identified significant barriers by open coding and thematic analysis of the formal interview. [ 31 ]

Historical research

Historical research is the “systematic collection, critical evaluation, and interpretation of historical evidence”.[ 1 ] The purpose of historical research is to gain insights from the past and involves interpreting past events in the light of the present. The data for historical research are usually collected from primary and secondary sources. The primary source mainly includes diaries, first hand information, and writings. The secondary sources are textbooks, newspapers, second or third-hand accounts of historical events and medical/legal documents. The data gathered from these various sources are synthesized and reported as biographical narratives or developmental perspectives in chronological order. The ideas are interpreted in terms of the historical context and significance. The written report describes 'what happened', 'how it happened', 'why it happened', and its significance and implications to current clinical practice.[ 1 , 10 ]

Example: Lubold (2019) analyzed the breastfeeding trends in three countries (Sweden, Ireland, and the United States) using a historical qualitative method. Through analysis of historical data, the researcher found that strong family policies, adherence to international recommendations and adoption of baby-friendly hospital initiative could greatly enhance the breastfeeding rates. [ 32 ]

Case study research

Case study research focuses on the description and in-depth analysis of the case(s) or issues illustrated by the case(s). The design has its origin from psychology, law, and medicine. Case studies are best suited for the understanding of case(s), thus reducing the unit of analysis into studying an event, a program, an activity or an illness. Observations, one to one interviews, artifacts, and documents are used for collecting the data, and the analysis is done through the description of the case. From this, themes and cross-case themes are derived. A written case study report includes a detailed description of one or more cases.[ 7 , 10 ]

Example: Perceptions of poststroke sexuality in a woman of childbearing age was explored using a qualitative case study approach by Beal and Millenbrunch. Semi structured interview was conducted with a 36- year mother of two children with a history of Acute ischemic stroke. The data were analyzed using an inductive approach. The authors concluded that “stroke during childbearing years may affect a woman's perception of herself as a sexual being and her ability to carry out gender roles”. [ 33 ]

Sampling in Qualitative Research

Qualitative researchers widely use non-probability sampling techniques such as purposive sampling, convenience sampling, quota sampling, snowball sampling, homogeneous sampling, maximum variation sampling, extreme (deviant) case sampling, typical case sampling, and intensity sampling. The selection of a sampling technique depends on the nature and needs of the study.[ 34 , 35 , 36 , 37 , 38 , 39 , 40 ] The four widely used sampling techniques are convenience sampling, purposive sampling, snowball sampling, and intensity sampling.

Convenience sampling

It is otherwise called accidental sampling, where the researchers collect data from the subjects who are selected based on accessibility, geographical proximity, ease, speed, and or low cost.[ 34 ] Convenience sampling offers a significant benefit of convenience but often accompanies the issues of sample representation.

Purposive sampling

Purposive or purposeful sampling is a widely used sampling technique.[ 35 ] It involves identifying a population based on already established sampling criteria and then selecting subjects who fulfill that criteria to increase the credibility. However, choosing information-rich cases is the key to determine the power and logic of purposive sampling in a qualitative study.[ 1 ]

Snowball sampling

The method is also known as 'chain referral sampling' or 'network sampling.' The sampling starts by having a few initial participants, and the researcher relies on these early participants to identify additional study participants. It is best adopted when the researcher wishes to study the stigmatized group, or in cases, where findings of participants are likely to be difficult by ordinary means. Respondent ridden sampling is an improvised version of snowball sampling used to find out the participant from a hard-to-find or hard-to-study population.[ 37 , 38 ]

Intensity sampling

The process of identifying information-rich cases that manifest the phenomenon of interest is referred to as intensity sampling. It requires prior information, and considerable judgment about the phenomenon of interest and the researcher should do some preliminary investigations to determine the nature of the variation. Intensity sampling will be done once the researcher identifies the variation across the cases (extreme, average and intense) and picks the intense cases from them.[ 40 ]

Deciding the Sample Size

A-priori sample size calculation is not undertaken in the case of qualitative research. Researchers collect the data from as many participants as possible until they reach the point of data saturation. Data saturation or the point of redundancy is the stage where the researcher no longer sees or hears any new information. Data saturation gives the idea that the researcher has captured all possible information about the phenomenon of interest. Since no further information is being uncovered as redundancy is achieved, at this point the data collection can be stopped. The objective here is to get an overall picture of the chronicle of the phenomenon under the study rather than generalization.[ 1 , 7 , 41 ]

Data Collection in Qualitative Research

The various strategies used for data collection in qualitative research includes in-depth interviews (individual or group), focus group discussions (FGDs), participant observation, narrative life history, document analysis, audio materials, videos or video footage, text analysis, and simple observation. Among all these, the three popular methods are the FGDs, one to one in-depth interviews and the participant observation.

FGDs are useful in eliciting data from a group of individuals. They are normally built around a specific topic and are considered as the best approach to gather data on an entire range of responses to a topic.[ 42 Group size in an FGD ranges from 6 to 12. Depending upon the nature of participants, FGDs could be homogeneous or heterogeneous.[ 1 , 14 ] One to one in-depth interviews are best suited to obtain individuals' life histories, lived experiences, perceptions, and views, particularly while exporting topics of sensitive nature. In-depth interviews can be structured, unstructured, or semi-structured. However, semi-structured interviews are widely used in qualitative research. Participant observations are suitable for gathering data regarding naturally occurring behaviors.[ 1 ]

Data Analysis in Qualitative Research

Various strategies are employed by researchers to analyze data in qualitative research. Data analytic strategies differ according to the type of inquiry. A general content analysis approach is described herewith. Data analysis begins by transcription of the interview data. The researcher carefully reads data and gets a sense of the whole. Once the researcher is familiarized with the data, the researcher strives to identify small meaning units called the 'codes.' The codes are then grouped based on their shared concepts to form the primary categories. Based on the relationship between the primary categories, they are then clustered into secondary categories. The next step involves the identification of themes and interpretation to make meaning out of data. In the results section of the manuscript, the researcher describes the key findings/themes that emerged. The themes can be supported by participants' quotes. The analytical framework used should be explained in sufficient detail, and the analytic framework must be well referenced. The study findings are usually represented in a schematic form for better conceptualization.[ 1 , 7 ] Even though the overall analytical process remains the same across different qualitative designs, each design such as phenomenology, ethnography, and grounded theory has design specific analytical procedures, the details of which are out of the scope of this article.

Computer-Assisted Qualitative Data Analysis Software (CAQDAS)

Until recently, qualitative analysis was done either manually or with the help of a spreadsheet application. Currently, there are various software programs available which aid researchers to manage qualitative data. CAQDAS is basically data management tools and cannot analyze the qualitative data as it lacks the ability to think, reflect, and conceptualize. Nonetheless, CAQDAS helps researchers to manage, shape, and make sense of unstructured information. Open Code, MAXQDA, NVivo, Atlas.ti, and Hyper Research are some of the widely used qualitative data analysis software.[ 14 , 43 ]

Reporting Guidelines

Consolidated Criteria for Reporting Qualitative Research (COREQ) is the widely used reporting guideline for qualitative research. This 32-item checklist assists researchers in reporting all the major aspects related to the study. The three major domains of COREQ are the 'research team and reflexivity', 'study design', and 'analysis and findings'.[ 44 , 45 ]

Critical Appraisal of Qualitative Research

Various scales are available to critical appraisal of qualitative research. The widely used one is the Critical Appraisal Skills Program (CASP) Qualitative Checklist developed by CASP network, UK. This 10-item checklist evaluates the quality of the study under areas such as aims, methodology, research design, ethical considerations, data collection, data analysis, and findings.[ 46 ]

Ethical Issues in Qualitative Research

A qualitative study must be undertaken by grounding it in the principles of bioethics such as beneficence, non-maleficence, autonomy, and justice. Protecting the participants is of utmost importance, and the greatest care has to be taken while collecting data from a vulnerable research population. The researcher must respect individuals, families, and communities and must make sure that the participants are not identifiable by their quotations that the researchers include when publishing the data. Consent for audio/video recordings must be obtained. Approval to be in FGDs must be obtained from the participants. Researchers must ensure the confidentiality and anonymity of the transcripts/audio-video records/photographs/other data collected as a part of the study. The researchers must confirm their role as advocates and proceed in the best interest of all participants.[ 42 , 47 , 48 ]

Rigor in Qualitative Research

The demonstration of rigor or quality in the conduct of the study is essential for every research method. However, the criteria used to evaluate the rigor of quantitative studies are not be appropriate for qualitative methods. Lincoln and Guba (1985) first outlined the criteria for evaluating the qualitative research often referred to as “standards of trustworthiness of qualitative research”.[ 49 ] The four components of the criteria are credibility, transferability, dependability, and confirmability.

Credibility refers to confidence in the 'truth value' of the data and its interpretation. It is used to establish that the findings are true, credible and believable. Credibility is similar to the internal validity in quantitative research.[ 1 , 50 , 51 ] The second criterion to establish the trustworthiness of the qualitative research is transferability, Transferability refers to the degree to which the qualitative results are applicability to other settings, population or contexts. This is analogous to the external validity in quantitative research.[ 1 , 50 , 51 ] Lincoln and Guba recommend authors provide enough details so that the users will be able to evaluate the applicability of data in other contexts.[ 49 ] The criterion of dependability refers to the assumption of repeatability or replicability of the study findings and is similar to that of reliability in quantitative research. The dependability question is 'Whether the study findings be repeated of the study is replicated with the same (similar) cohort of participants, data coders, and context?'[ 1 , 50 , 51 ] Confirmability, the fourth criteria is analogous to the objectivity of the study and refers the degree to which the study findings could be confirmed or corroborated by others. To ensure confirmability the data should directly reflect the participants' experiences and not the bias, motivations, or imaginations of the inquirer.[ 1 , 50 , 51 ] Qualitative researchers should ensure that the study is conducted with enough rigor and should report the measures undertaken to enhance the trustworthiness of the study.

Conclusions

Qualitative research studies are being widely acknowledged and recognized in health care practice. This overview illustrates various qualitative methods and shows how these methods can be used to generate evidence that informs clinical practice. Qualitative research helps to understand the patterns of health behaviors, describe illness experiences, design health interventions, and develop healthcare theories. The ultimate strength of the qualitative research approach lies in the richness of the data and the descriptions and depth of exploration it makes. Hence, qualitative methods are considered as the most humanistic and person-centered way of discovering and uncovering thoughts and actions of human beings.

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How to Write Effective Qualitative Interview Questions

Qualitative interviewing is an effective technique to quickly understand more about a target user group. It is a key skill that any aspiring user researcher should develop. It is important to carefully craft the questions to ensure the sessions run efficiently and get the desired information. This article outlines best practice tips on creating effective session guides, ensuring your questions produce great results.

Don’t Ask Leading Questions

A leading question guides the respondent to a desired answer by implying that there is a correct answer. People tend to provide socially desirable answers, so if you ask a question that guides them, they will likely provide one that they believe you want to hear. Leading questions can be used by people to persuade someone. They should not be used when trying to uncover new information or understand an audience. They reduce the objectivity of the session, and therefore, reduce the reliability of the results.

Example: Leading: ‘Why would you prefer to use our product?’ Better: ‘What are your thoughts about using our product?

In the leading example, it implies that the respondent prefers the product and is enquiring as to why. The respondent may list a bunch of reasons that they like the product but may leave out crucial information where they believe the product could improve. Asking about their opinions and thoughts will provide them with a platform to discuss the product freely.

Example: Leading: Would you prefer to use the product to improve efficiencies or to gain an overview? Better: Why might you use this product?

In this example, the interviewer provides two reasons why someone might use a product. The interviewer may have only considered the two reasons why someone may use the product. Simply asking why they may use the product achieves the same goal, but also allows the respondent to consider other options.

To avoid leading questions, act as if you know nothing of the topic. Note down what you would ask if you have no information at all. Keep the questions simple, neutral and free from any words with connotations or emotions. It is also best to have an independent observer assess the topic, as it is easier for them to have an unbiased opinion on the matter.

Behavioural, Attitudinal

People often hold a belief that does not match with their behaviours. Using a mixture of attitudinal and behavioural questions uncovers what a person does, but also their thoughts about their actions. Attitudinal questions are used to understand their opinions and motivations. Behavioural questions are used to find out how a participant does something. It is best to utilise a mixture.

Example: Attitudinal: How often should you brush your teeth? Behavioural: How many times did you brush your teeth last week?

Try to keep all behavioural questions about the user’s past, as future behaviours are influenced by opinions and attitudes. It is best practice to repeat questions from a different angle. Don’t be afraid of users repeating themselves or going over a topic multiple times.

Ask Open-Ended Questions Instead of Closed Questions

Open-ended questions are ones that require more than one word to answer. Closed questions result in either a yes/no situation. Open-ended questions are used to find out people’s goals, motivations and pain points. They provide an opportunity for the participant to speak freely on the topic.

Example: Yes/No: Do you like coffee? Open: What are your thoughts on coffee?

Closed questions should be avoided unless you want to either clarify to gain more context to the user’s situation. Yes/No questions close down conversations and can be considered as quantitative. The following examples are both fine to use in an interview, as they will put other details into perspective.

Context: Do you drink coffee? Clarify: You mentioned you drink coffee, correct?

When creating your questionnaire, try and stick with ‘how’, ‘why’, ‘what’, ‘when’ and ‘where’ questions.

Don’t Use Double-Barreled Questions

Sometimes interviewers get excited and want to ask multiple things at once. Double-barreled questions touch on more than one topic. This can be overwhelming to answer, and respondents may either try to answer both at once or answer only one part of the question. If you want to ask something on multiple topics, it is best to split them into two different questions.

Example: Double-barreled: What do you like about coffee and new coffee products? Better: What do you like about coffee products?

It is normal in casual conversation to ask questions in such a manner. Interviewing is best when the questions are short and to the point, focusing on one topic.

Differentiate Between Quantitative and Qualitative Questions

Quantitative and qualitative questions both have their own strengths and weaknesses. Quantitative questions are typically reserved for surveys but can be used in interviewing to add some context and allow the interviewer to ask more follow-up questions. They mostly uncover ‘who’ and ‘what’. Qualitative questions will provide detailed information on the topic of interest, uncovering the ‘why’ and ‘how’.

Examples of quantitative questions:

• Numerical answers: How many coffees do you drink a day?
• Preferences: What type of coffee drink do you prefer?
• Single word answers: What brand of coffee do you drink?

It is not immediately obvious and clear-cut the quantitative nature of these questions. You can tell through the low complexity of data gathered. If you ask these questions to participants, you will get a straightforward answer. However, the issue is that the responses are not statistically valid, and require further investigation. You can better use your time in an in-depth one on one session asking qualitative questions such as:

Examples of qualitative questions:

• Recount your morning routine.
• Why do you prefer one brand over another?
• Why do you drink coffee everyday?

Shifting to why and how people do things, outlining goals, motivations, pain points and delights gives a much more in-depth perspective. These insights can be validated later through other techniques, but interviewing is the quickest and easiest way to gather them.

For qualitative interviewing, there are few clear best practices. Each interviewer has their own way of gathering information and forming questions. The tips above are there to guide you but are not definitive rules that one cannot break. I hope these help to elevate your interviewing process and gather better insights.

John Lassen

John started his career in market research and marketing where he constantly championed the experience of the users and customer journeys. John jumped into the profession of UX Research because of the ability to create products and understand users on a qualitative level. As an advocate of design thinking, he is constantly in touch with users, creating strategic outputs and reinforcing the business value of research.

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How to write qualitative research questions.

11 min read Here’s how to write effective qualitative research questions for your projects, and why getting it right matters so much.

What is qualitative research?

Qualitative research is a blanket term covering a wide range of research methods and theoretical framing approaches. The unifying factor in all these types of qualitative study is that they deal with data that cannot be counted. Typically this means things like people’s stories, feelings, opinions and emotions , and the meanings they ascribe to their experiences.

Qualitative study is one of two main categories of research, the other being quantitative research. Quantitative research deals with numerical data – that which can be counted and quantified, and which is mostly concerned with trends and patterns in large-scale datasets.

What are research questions?

Research questions are questions you are trying to answer with your research. To put it another way, your research question is the reason for your study, and the beginning point for your research design. There is normally only one research question per study, although if your project is very complex, you may have multiple research questions that are closely linked to one central question.

A good qualitative research question sums up your research objective. It’s a way of expressing the central question of your research, identifying your particular topic and the central issue you are examining.

Research questions are quite different from survey questions, questions used in focus groups or interview questions. A long list of questions is used in these types of study, as opposed to one central question. Additionally, interview or survey questions are asked of participants, whereas research questions are only for the researcher to maintain a clear understanding of the research design.

Research questions are used in both qualitative and quantitative research , although what makes a good research question might vary between the two.

In fact, the type of research questions you are asking can help you decide whether you need to take a quantitative or qualitative approach to your research project.

Discover the fundamentals of qualitative research

Quantitative vs. qualitative research questions

Writing research questions is very important in both qualitative and quantitative research, but the research questions that perform best in the two types of studies are quite different.

Quantitative research questions

Quantitative research questions usually relate to quantities, similarities and differences.

It might reflect the researchers’ interest in determining whether relationships between variables exist, and if so whether they are statistically significant. Or it may focus on establishing differences between things through comparison, and using statistical analysis to determine whether those differences are meaningful or due to chance.

• How much? This kind of research question is one of the simplest. It focuses on quantifying something. For example:

How many Yoruba speakers are there in the state of Maine?

• What is the connection?

This type of quantitative research question examines how one variable affects another.

For example:

How does a low level of sunlight affect the mood scores (1-10) of Antarctic explorers during winter?

• What is the difference? Quantitative research questions in this category identify two categories and measure the difference between them using numerical data.

Do white cats stay cooler than tabby cats in hot weather?

If your research question fits into one of the above categories, you’re probably going to be doing a quantitative study.

Qualitative research questions

Qualitative research questions focus on exploring phenomena, meanings and experiences.

Unlike quantitative research, qualitative research isn’t about finding causal relationships between variables. So although qualitative research questions might touch on topics that involve one variable influencing another, or looking at the difference between things, finding and quantifying those relationships isn’t the primary objective.

In fact, you as a qualitative researcher might end up studying a very similar topic to your colleague who is doing a quantitative study, but your areas of focus will be quite different. Your research methods will also be different – they might include focus groups, ethnography studies, and other kinds of qualitative study.

A few example qualitative research questions:

• What is it like being an Antarctic explorer during winter?
• What are the experiences of Yoruba speakers in the USA?
• How do white cat owners describe their pets?

Qualitative research question types

Marshall and Rossman (1989) identified 4 qualitative research question types, each with its own typical research strategy and methods.

• Exploratory questions

Exploratory questions are used when relatively little is known about the research topic. The process researchers follow when pursuing exploratory questions might involve interviewing participants, holding focus groups, or diving deep with a case study.

• Explanatory questions

With explanatory questions, the research topic is approached with a view to understanding the causes that lie behind phenomena. However, unlike a quantitative project, the focus of explanatory questions is on qualitative analysis of multiple interconnected factors that have influenced a particular group or area, rather than a provable causal link between dependent and independent variables.

• Descriptive questions

As the name suggests, descriptive questions aim to document and record what is happening. In answering descriptive questions , researchers might interact directly with participants with surveys or interviews, as well as using observational studies and ethnography studies that collect data on how participants interact with their wider environment.

• Predictive questions

Predictive questions start from the phenomena of interest and investigate what ramifications it might have in the future. Answering predictive questions may involve looking back as well as forward, with content analysis, questionnaires and studies of non-verbal communication (kinesics).

Why are good qualitative research questions important?

We know research questions are very important. But what makes them so essential? (And is that question a qualitative or quantitative one?)

Getting your qualitative research questions right has a number of benefits.

• It defines your qualitative research project Qualitative research questions definitively nail down the research population, the thing you’re examining, and what the nature of your answer will be.This means you can explain your research project to other people both inside and outside your business or organization. That could be critical when it comes to securing funding for your project, recruiting participants and members of your research team, and ultimately for publishing your results. It can also help you assess right the ethical considerations for your population of study.
• It maintains focus Good qualitative research questions help researchers to stick to the area of focus as they carry out their research. Keeping the research question in mind will help them steer away from tangents during their research or while they are carrying out qualitative research interviews. This holds true whatever the qualitative methods are, whether it’s a focus group, survey, thematic analysis or other type of inquiry.That doesn’t mean the research project can’t morph and change during its execution – sometimes this is acceptable and even welcome – but having a research question helps demarcate the starting point for the research. It can be referred back to if the scope and focus of the project does change.
• It helps make sure your outcomes are achievable

Because qualitative research questions help determine the kind of results you’re going to get, it helps make sure those results are achievable. By formulating good qualitative research questions in advance, you can make sure the things you want to know and the way you’re going to investigate them are grounded in practical reality. Otherwise, you may be at risk of taking on a research project that can’t be satisfactorily completed.

Developing good qualitative research questions

All researchers use research questions to define their parameters, keep their study on track and maintain focus on the research topic. This is especially important with qualitative questions, where there may be exploratory or inductive methods in use that introduce researchers to new and interesting areas of inquiry. Here are some tips for writing good qualitative research questions.

1. Keep it specific

Broader research questions are difficult to act on. They may also be open to interpretation, or leave some parameters undefined.

Strong example: How do Baby Boomers in the USA feel about their gender identity?

Weak example: Do people feel different about gender now?

2. Be original

Look for research questions that haven’t been widely addressed by others already.

Strong example: What are the effects of video calling on women’s experiences of work?

Weak example: Are women given less respect than men at work?

3. Make it research-worthy

Don’t ask a question that can be answered with a ‘yes’ or ‘no’, or with a quick Google search.

Strong example: What do people like and dislike about living in a highly multi-lingual country?

Weak example: What languages are spoken in India?

4. Focus your question

Don’t roll multiple topics or questions into one. Qualitative data may involve multiple topics, but your qualitative questions should be focused.

Strong example: What is the experience of disabled children and their families when using social services?

Weak example: How can we improve social services for children affected by poverty and disability?

4. Focus on your own discipline, not someone else’s

Avoid asking questions that are for the politicians, police or others to address.

Strong example: What does it feel like to be the victim of a hate crime?

Weak example: How can hate crimes be prevented?

5. Ask something researchable

Big questions, questions about hypothetical events or questions that would require vastly more resources than you have access to are not useful starting points for qualitative studies. Qualitative words or subjective ideas that lack definition are also not helpful.

Strong example: How do perceptions of physical beauty vary between today’s youth and their parents’ generation?

Weak example: Which country has the most beautiful people in it?

Related resources

Qualitative research design 12 min read, primary vs secondary research 14 min read, business research methods 12 min read, qualitative research interviews 11 min read, market intelligence 10 min read, marketing insights 11 min read, ethnographic research 11 min read, request demo.

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• Research Note
• Open access
• Published: 15 May 2024

Concepts of lines of therapy in cancer treatment: findings from an expert interview-based study

• Lisa Falchetto 1   na1 ,
• Bernd Bender 1 , 2   na1 ,
• Ian Erhard 1 , 2 ,
• Kim N. Zeiner 3 ,
• Jan A. Stratmann 11 ,
• Florestan J. Koll 4 ,
• Sebastian Wagner 11 ,
• Marcel Reiser 5 ,
• Khayal Gasimli 6 ,
• Angelika Stehle 7 ,
• Martin Voss 8 ,
• Olivier Ballo 11 ,
• Jörg Janne Vehreschild 1 , 9 , 10 &
• Daniel Maier 1 , 2  

BMC Research Notes volume  17 , Article number:  137 ( 2024 ) Cite this article

Metrics details

The concept of lines of therapy (LOT) in cancer treatment is often considered for decision making in tumor boards and clinical management, but lacks a common definition across medical specialties. The complexity and heterogeneity of malignancies and treatment modalities contribute to an inconsistent understanding of LOT among physicians. This study assesses the heterogeneity of understandings of the LOT concept, its major dimensions, and criteria from the perspective of physicians of different specialties with an oncological focus in Germany. Semi-structured expert interviews with nine physicians were conducted and evaluated using qualitative content analysis.

Most interviewees agreed that there is no single definition for LOT and found it difficult to explicate their understanding. A majority of experts stated that they had already encountered misunderstandings with colleagues regarding LOT and that they had problems with deciphering LOT from the medical records of their patients. Disagreement emerged about the roles of the following within the LOT concept: maintenance therapy, treatment intention, different therapy modalities, changing pharmaceutical agents, and therapy breaks. Respondents predominantly considered the same criteria as decisive for the definition of LOT as for a change in LOT (e.g., the occurrence of a progression event or tumor recurrence).

Peer Review reports

Introduction

While clinical oncology considers line of therapy (LOT) essential information for therapy planning, the field lacks a homogeneous understanding of the concept, as well as clear and consistent criteria for its classification [ 1 ]. Especially in real-world data-based research, it is often unclear whether a certain therapy is still part of an LOT; and often, conflicting interpretations lead to misunderstandings in information exchange about therapy progression [ 1 ]. Existing approaches, for standardizing the classification of LOT either focus on patterns proposed by guidelines (e.g., drug administration period, first-line termination) or on drug administration sequences [ 2 , 3 , 4 , 5 , 6 ]. However, other issues related to the LOT concept remain largely unclear. For example, the roles of maintenance therapies and local therapy modalities have not yet been discussed [ 1 ].

This expert-interview study aims to provide a better conceptual understanding of the defining criteria of LOT for solid and non-solid cancers. Therefore, it may contribute to identifying unclear aspects of the LOT concept and avoiding misunderstandings in communication about LOTs, especially between physicians of different medical disciplines. Concerning the rapidly developing field of real-world cancer research, data augmentation strategies and feature engineering require empirically validated concepts to obtain reliable evidence from observational data. More specifically, investigating the conceptual understanding of LOTs will help us build a rule-based framework for LOT classification within the Clinical Communication Platform of the German Cancer Consortium (DKTK).

The study’s target group was physicians from various specialties with an oncological focus, working in either university hospitals or private practice. Physicians from the University Hospital Frankfurt and private practices were contacted by e-mail. In total, nine were interviewed. Their varied specialties included neuro-oncology, pulmonology, hematology and medical oncology, urology, dermatology, and gynecological oncology, as well as one resident specialist in internal medicine with a focus on hematology and oncology. The interviewees’ professional experience ranged from 3.5 to 29 years and most had experience in treating both solid and non-solid malignancies.

Qualitative expert interviews [ 7 , 8 ] were conducted by posing open questions within a semi-structured framework [ 9 ]. An interview manual delineated this framework and was developed based on existing literature about oncological LOTs and associated concepts (see Additional File 1 ). Before the interviews, the interview manual was pre-tested with an experienced oncologist and adjusted accordingly. Each participant declared their consent before the interview. Confidentiality and anonymity of participants’ responses and information were assured. The first part of the interview manual asked about the interviewee’s underlying understanding of LOTs and the relevant criteria for their definition. Subsequently, questions concerning misunderstandings in interactions with colleagues were posed to determine whether there are frequent uncertainties in the use of the LOT concept and, if so, what reasons may underlie this situation. Next, the interviewer asked about how specific criteria, picked out of the literature, related to the definition of LOT. These included the influence of treatment intention, the role of maintenance therapy, and local therapies. Another focus of the interviews was how the interviewees judged the relationship of both changes in drug regimen and therapy breaks to the definition of LOT.

Data collection/conduct of interviews

The expert interviews were conducted between June 1 and July 17, 2022 via video conference and in German. They lasted between 10 and 25 minutes with an average duration of approximately 18 minutes. The interviews were recorded and transcribed using the ExpressScribe Pro software (Version 10.17).

Data analysis

The interviews were analyzed using methods of qualitative content analysis as described in Mayring [ 10 ] and the software MaxQDA Analytics Pro 2022 (release 22.2.0). A system for coding the interview material was developed based on literature research conducted before the interviews.

Since the interviews were conducted in German, we provide an English translation of selected quotes. Table  1 contains the main topics and sub-topics of the interview, as well as exemplary quotes from the interviewees.

LOT definition and misunderstandings

Most interviewees confirmed that there was no common understanding of LOT and that they had difficulties explicating their own understanding of the concept. Furthermore, four of the interviewees reported misunderstandings with colleagues regarding LOTs and seven reported that they experienced uncertainties in their clinical practice when defining an LOT. For instance, if care for a patient was delivered by multiple centers, misunderstandings concerning LOT progression frequently occurred, because involved persons lacked a common understanding:

“[…] when it comes to categorizing it somehow so that it is standardized and applicable across multiple centers, yes there existed discrepancies in the particular considerations.” (Expert interview (E)05).

Treatment intention

Six interviewees said that treatment intention (curative vs. palliative) is important in the choice of therapy. Consequently, treatment intention is also relevant to LOT planning. Three experts expressed that LOT is especially relevant and established in the palliative setting:

“With a curative therapy option, […] you shouldn’t have any progression under therapy, after all. So that’s why the definition [of the line of therapy] does differ somewhat – palliative versus curative.” (E03).

Maintenance therapy

Starting a maintenance therapy to control a tumor after chemotherapy was predominantly not considered an indicator for a change in LOT, since usually only part of the medication regimen is discontinued for maintenance, while the rest remains the same. However, interviewees also said that maintenance therapy can include an entirely new pharmaceutical agent, which would, in turn, complicate the delineation between LOT:

“Yes, that’s difficult, too. I would probably count maintenance therapy as part of that – if it’s sort of quasi-logically linked to the therapy that was administered before it. But if it’s a completely different type of substance now, then it becomes more difficult again.” (E03).

Local therapies vs. systemic therapies

Six of the physicians interviewed opined that a LOT can contain both local and systemic therapies. However, some participants stated that beginning a new local therapy would not lead to a change of LOT, in contrast to beginning a new systemic therapy. Meanwhile, in contrast to the other six, three physicians emphasized that only systemic therapies can constitute a LOT:

“In my opinion, the therapy line is primarily defined by the systemic therapies. The local therapies are rather something supplementary that is carried out additionally, or – as the case may be – primarily in addition to symptom relief. Local therapies can also be used to achieve a response, but are not usually mentioned as a line of therapy.” (E06).

Change of LOT

All interviewees said that the LOT must be changed if tumor progression or disease relapse occurs or if therapy response fails. Six interviewees considered the occurrence of adverse effects (e.g., severe toxicity) a significant criterion for the decision to change an LOT. Only three interviewees saw the addition of a new pharmaceutical agent as resulting in a change of LOT:

“Dropping an active substance, I would always see as being due to toxicity or at the patient’s request – so actually owed to toxicity. That is, I would never call that a new line of therapy, whereas the addition of a new agent – strictly speaking, it would have to be considered a new line of therapy, although it is also difficult in terms of definition.” (E09).

The other seven interviewees only considered the introduction of new pharmaceutical agents a change in LOT if the treatment intention changed as well, or if a recurrence or progression occurred. Only the replacement of one drug with another of the same class (e.g., cisplatin with carboplatin) was not considered a change of LOT by anyone.

Therapy breaks

There were also ambiguous opinions regarding the role of breaks in therapy for the classification of LOT. On the one hand, the length of the break was considered decisive, whereas on the other hand, it was said that the therapy following the break was more important. Additionally, some viewed breaks in therapy as important for the classification of LOT in the event of a relapse or progression:

“[…] In principle, if no recurrence has occurred and it is perhaps even the same substance […] then I would consider it one line of therapy, regardless of how long the break was.” (E01).

If the break was unplanned, it was considered a significantly more important criterion for a change in LOT than if it was part of the therapy concept.

The expert interviews in this study largely confirmed that there is no common understanding of the LOT concept or its defining criteria. The interview material suggests that individual backgrounds in differing medical disciplines may influence views on and understandings of LOT. This potential context dependency of the LOT concept also appears consistent with heterogeneous working definitions of LOT in different real-world studies of distinct cancer entities [ 1 , 11 , 12 ].

However, it appeared that a LOT was considered a therapeutic concept with start- and endpoints that is focused on systemic therapies, although it may also contain additional treatment modalities. If included in the LOT, such non-systemic modalities would be selected based on individual patient and disease characteristics, and terminated if certain events (e.g., tumor progression) occurred.

There was evident uncertainty about the role of adjuvant and maintenance therapy and whether they should be regarded as an LOT together with the preceding (systemic) therapy. Also, no prevailing opinion could be identified on the questions of whether treatment intention (curative vs. palliative) and therapy breaks were integral to defining LOTs. Furthermore, experts held differing opinions on which changes in the administered drug regimen would initiate a change in LOT.

In the literature, however, individual approaches for standardizing the criteria for a change in LOT exist in the following cases: the termination of a LOT is indicated in the event of treatment discontinuation, addition of a new, non-equivalent agent, interruption of treatment, clinical progression of the disease, or death of the patient [ 2 , 3 ]. The interviewees were also nearly unanimous on these criteria: all considered tumor progression and recurrence decisive for a change in LOT; six experts highlighted the occurrence of side effects or relevant toxicity; three mentioned the scheduled end of therapy; and one cited patients’ wishes. Only some of the interviewees considered a change in pharmaceutical regimen a factor in identifying a change in LOT, while replacement of one drug with another from the same class was not viewed as altering the LOT.

The interviews both identified tumor recurrence and progression as LOT-relevant events and raised questions about the nature of their role. Recurrence and progression during therapy breaks, as well as the length of the break and the treatment thereafter, were considered relevant factors for a change in LOT. In two interviews, although the participants initially identified recurrence and progression as indicators for a change in LOT, their further comments appeared to contradict this standpoint. This apparent inconsistency should be investigated in future research.

Seven interviewees considered treatment intention relevant to LOT. Predominantly, interviewees considered the adoption of maintenance therapy as a continuation of an ongoing LOT. However, it remains unclear whether changes in the dosage or interval of drug administration during maintenance therapy imply a change in LOT. Six interviewees said that both local and systemic therapy modalities should be included in characterizations of LOT, although previous research excluded local modalities [ 1 , 13 , 14 , 15 ].

While similar approaches to standardizing the duration of a LOT [ 2 ] and first-line therapy [ 2 , 3 ] exist, it is not clear whether the definition of LOT can be standardized across disciplines as well as tumor entities. Nevertheless, a cross-disciplinary standard definition of the LOT concept should be targeted.

Limitations

This study exhibits the following limitations:

Qualitative expert interviews were only feasible for a small sample ( n  = 9) of oncological experts, most of whom were located at a single center (eight out of nine). While the study delivers highly granular insights, this approach precludes generalization of the findings. Therefore, subsequent research must evaluate the qualitative insights leaned from this study in larger and more representative samples.

The interviewees had varying degrees of professional experience and different specialties, making direct comparisons of experience and assessments regarding oncological LOT difficult. However, this was intentional to obtain the widest possible range of assessments regarding the broad topic under investigation.

No triangulation in the form of using multiple and diverse data sources, perspectives, locations, or theories took place in conducting the study. Such methods can help to mitigate subjective bias resulting from the explicit focus on one’s own data [ 16 ].

Data availability

Details on the data and materials related to the study may be available upon reasonable request from Bernd Bender ([email protected]).

Abbreviations

German Cancer Consortium

• Expert interview

Line of therapy

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Acknowledgements

We would like to thank the expert physicians who participated in the interviews for their time and willingness to share their experiences and perspectives. Furthermore, we would like to thank the German Cancer Consortium’s Clinical Data Science Group for the support in realizing the study.

Open Access funding enabled and organized by Projekt DEAL. This research is partly funded by the German Cancer Consortium (DKTK).

Author information

Lisa Falchetto and Bernd Bender contributed equally to this work.

Authors and Affiliations

Institute for Digital Medicine and Clinical Data Science, Goethe University Frankfurt, Faculty of Medicine, Frankfurt, Germany

Lisa Falchetto, Bernd Bender, Ian Erhard, Jörg Janne Vehreschild & Daniel Maier

German Cancer Consortium (DKTK), partner site Frankfurt/Mainz and German Cancer Research Center (DKFZ), Heidelberg, Germany

Bernd Bender, Ian Erhard & Daniel Maier

Department for Dermatology, Venerology and Allergology, University Hospital Frankfurt, Frankfurt, Germany

Kim N. Zeiner

Department of Urology, University Hospital Frankfurt, Frankfurt, Germany

Florestan J. Koll

PIOH Praxis Internistischer Onkologie und Hämatologie, Cologne, Germany

Marcel Reiser

Clinic for Gynecology and Obstetrics, University Hospital Frankfurt, Frankfurt, Germany

Khayal Gasimli

Department for Internal Medicine 1, University Hospital Frankfurt, Frankfurt, Germany

Angelika Stehle

Department Neuro-Oncology, University Hospital Frankfurt, Frankfurt, Germany

Martin Voss

Department I of Internal Medicine, University Hospital of Cologne, Cologne, Germany

Jörg Janne Vehreschild

German Center for Infection Research (DZIF) partner site Bonn Cologne, Cologne, Germany

Medical Department 2 (Hematology/Oncology), Center for Internal Medicine, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt, Germany

Jan A. Stratmann, Sebastian Wagner & Olivier Ballo

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Contributions

BB, LF, and DM contributed to the writing of this article. LF and DM created the interview manual. LF conducted the interviews with the oncological experts and analyzed the interview material collected. DM and JJV were substantially involved in the conception of the study and in the acquisition of the interviewed experts. JJV also supported the piloting of the interview manual. IE edited the manuscript. KNZ, JAS, FJK, SW, MR, KG, AS, MV and OB participated in the study and provided the substantive statements and findings.

Corresponding author

Correspondence to Bernd Bender .

Ethics declarations

Ethics approval and consent to participate.

All subjects provided written informed consent to participate and this study was conducted according to all relevant ethical and regulatory guidelines. The project was approved by the ethics committee of the department of medicine of the Goethe University Frankfurt (ethical code number: 274/18).

Consent for publication

All interviewees permitted the use of the interview material and consented to publication.

Competing interests

Kim N. Zeiner (KNZ) received an honorarium for presentation from Bristol-Myers Squibb. Jan A. Stratmann (JAS) has personal fees from Boehringer Ingelheim, AstraZeneca, Roche, BMS, Amgen, LEO pharma, Novartis and Takeda. Florestan J. Koll (FJK) received grants from the German Cancer Aid and the German Cancer Consortium (DKTK). Marcel Reiser (MR) received consulting fees from Amgen, Abbvie, Stemline, Novartis and honoria from Roche. Jörg Janne Vehreschild (JJV) has personal fees from Merck / MSD, Gilead, Pfizer, Astellas Pharma, Basilea, German Centre for Infection Research (DZIF), University Hospital Freiburg/ Congress and Communication, Academy for Infectious Medicine, University Manchester, German Society for Infectious Diseases (DGI), Ärztekammer Nordrhein, University Hospital Aachen, Back Bay Strategies, German Society for Internal Medicine (DGIM), Shionogi, Molecular Health, Netzwerk Universitätsmedizin, Janssen, NordForsk, Biontech, APOGEPHA and grants from Merck / MSD, Gilead, Pfizer, Astellas Pharma, Basilea, German Centre for Infection Research (DZIF), German Federal Ministry of Education and Research (BMBF), Deutsches Zentrum für Luft- und Raumfahrt (DLR), University of Bristol, Rigshospitalet Copenhagen. Daniel Maier (DM) received speaker honoraria from Free University Berlin and travel compensation from IQVIA. Lisa Falchetto (LF), Bernd Bender (BB), Ian Erhard (IE), Sebastian Wagner (SW), Khayal Gasimli (KG), Angelika Stehle (AS), Martin Voss (MV) and Olivier Ballo (OB) have no competing interests.

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Additional file 1.

Interview manual with all instructions and questions.

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Falchetto, L., Bender, B., Erhard, I. et al. Concepts of lines of therapy in cancer treatment: findings from an expert interview-based study. BMC Res Notes 17 , 137 (2024). https://doi.org/10.1186/s13104-024-06789-6

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DOI : https://doi.org/10.1186/s13104-024-06789-6

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Patient medication management, understanding and adherence during the transition from hospital to outpatient care - a qualitative longitudinal study in polymorbid patients with type 2 diabetes

• Léa Solh Dost   ORCID: orcid.org/0000-0001-5767-1305 1 , 2 ,
• Giacomo Gastaldi   ORCID: orcid.org/0000-0001-6327-7451 3 &
• Marie P. Schneider   ORCID: orcid.org/0000-0002-7557-9278 1 , 2  

BMC Health Services Research volume  24 , Article number:  620 ( 2024 ) Cite this article

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Continuity of care is under great pressure during the transition from hospital to outpatient care. Medication changes during hospitalization may be poorly communicated and understood, compromising patient safety during the transition from hospital to home. The main aims of this study were to investigate the perspectives of patients with type 2 diabetes and multimorbidities on their medications from hospital discharge to outpatient care, and their healthcare journey through the outpatient healthcare system. In this article, we present the results focusing on patients’ perspectives of their medications from hospital to two months after discharge.

Patients with type 2 diabetes, with at least two comorbidities and who returned home after discharge, were recruited during their hospitalization. A descriptive qualitative longitudinal research approach was adopted, with four in-depth semi-structured interviews per participant over a period of two months after discharge. Interviews were based on semi-structured guides, transcribed verbatim, and a thematic analysis was conducted.

Twenty-one participants were included from October 2020 to July 2021. Seventy-five interviews were conducted. Three main themes were identified: (A) Medication management, (B) Medication understanding, and (C) Medication adherence, during three periods: (1) Hospitalization, (2) Care transition, and (3) Outpatient care. Participants had varying levels of need for medication information and involvement in medication management during hospitalization and in outpatient care. The transition from hospital to autonomous medication management was difficult for most participants, who quickly returned to their routines with some participants experiencing difficulties in medication adherence.

Conclusions

The transition from hospital to outpatient care is a challenging process during which discharged patients are vulnerable and are willing to take steps to better manage, understand, and adhere to their medications. The resulting tension between patients’ difficulties with their medications and lack of standardized healthcare support calls for interprofessional guidelines to better address patients’ needs, increase their safety, and standardize physicians’, pharmacists’, and nurses’ roles and responsibilities.

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Introduction

Continuity of patient care is characterized as the collaborative engagement between the patient and their physician-led care team in the ongoing management of healthcare, with the mutual objective of delivering high-quality and cost-effective medical care [ 1 ]. Continuity of care is under great pressure during the transition of care from hospital to outpatient care, with a risk of compromising patients’ safety [ 2 , 3 ]. The early post-discharge period is a high-risk and fragile transition: once discharged, one in five patients experience at least one adverse event during the first three weeks following discharge, and more than half of these adverse events are drug-related [ 4 , 5 ]. A retrospective study examining all discharged patients showed that adverse drug events (ADEs) account for up to 20% of 30-day hospital emergency readmissions [ 6 ]. During hospitalization, patients’ medications are generally modified, with an average of nearly four medication changes per patient [ 7 ]. Information regarding medications such as medication changes, the expected effect, side effects, and instructions for use are frequently poorly communicated to patients during hospitalization and at discharge [ 8 , 9 , 10 , 11 ]. Between 20 and 60% of discharged patients lack knowledge of their medications [ 12 , 13 ]. Consideration of patients’ needs and their active engagement in decision-making during hospitalization regarding their medications are often lacking [ 11 , 14 , 15 ]. This can lead to unsafe discharge and contribute to medication adherence difficulties, such as non-implementation of newly prescribed medications [ 16 , 17 ].

Patients with multiple comorbidities and polypharmacy are at higher risk of ADE [ 18 ]. Type 2 diabetes is one of the chronic health conditions most frequently associated with comorbidities and patients with type 2 diabetes often lack care continuum [ 19 , 20 , 21 ]. The prevalence of patients hospitalized with type 2 diabetes can exceed 40% [ 22 ] and these patients are at higher risk for readmission due to their comorbidities and their medications, such as insulin and oral hypoglycemic agents [ 23 , 24 , 25 ].

Interventions and strategies to improve patient care and safety at transition have shown mixed results worldwide in reducing cost, rehospitalization, ADE, and non-adherence [ 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ]. However, interventions that are patient-centered, with a patient follow-up and led by interprofessional healthcare teams showed promising results [ 34 , 35 , 36 ]. Most of these interventions have not been implemented routinely due to the extensive time to translate research into practice and the lack of hybrid implementation studies [ 37 , 38 , 39 , 40 , 41 ]. In addition, patient-reported outcomes and perspectives have rarely been considered, yet patients’ involvement is essential for seamless and integrated care [ 42 , 43 ]. Interprofessional collaboration in which patients are full members of the interprofessional team, is still in its infancy in outpatient care [ 44 ]. Barriers and facilitators regarding medications at the transition of care have been explored in multiple qualitative studies at one given time in a given setting (e.g., at discharge, one-month post-discharge) [ 8 , 45 , 46 , 47 , 48 ]. However, few studies have adopted a holistic methodology from the hospital to the outpatient setting to explore changes in patients’ perspectives over time [ 49 , 50 , 51 ]. Finally, little is known about whether, how, and when patients return to their daily routine following hospitalization and the impact of hospitalization weeks after discharge.

In Switzerland, continuity of care after hospital discharge is still poorly documented, both in terms of contextual analysis and interventional studies, and is mainly conducted in the hospital setting [ 31 , 35 , 52 , 53 , 54 , 55 , 56 ]. The first step of an implementation science approach is to perform a contextual analysis to set up effective interventions adapted to patients’ needs and aligned to healthcare professionals’ activities in a specific context [ 41 , 57 ]. Therefore, the main aims of this study were to investigate the perspectives of patients with type 2 diabetes and multimorbidities on their medications from hospital discharge to outpatient care, and on their healthcare journey through the outpatient healthcare system. In this article, we present the results focusing on patients’ perspectives of their medications from hospital to two months after discharge.

Study design

This qualitative longitudinal study, conducted from October 2020 to July 2021, used a qualitative descriptive methodology through four consecutive in-depth semi-structured interviews per participant at three, 10-, 30- and 60-days post-discharge, as illustrated in Fig.  1 . Longitudinal qualitative research is characterized by qualitative data collection at different points in time and focuses on temporality, such as time and change [ 58 , 59 ]. Qualitative descriptive studies aim to explore and describe the depth and complexity of human experiences or phenomena [ 60 , 61 , 62 ]. We focused our qualitative study on the 60 first days after discharge as this period is considered highly vulnerable and because studies often use 30- or 60-days readmission as an outcome measure [ 5 , 63 ].

This qualitative study follows the Consolidated Criteria for Reporting Qualitative Research (COREQ). Ethics committee approval was sought and granted by the Cantonal Research Ethics Commission, Geneva (CCER) (2020 − 01779).

Recruitment took place during participants’ hospitalization in the general internal medicine divisions at the Geneva University Hospitals in the canton of Geneva (500 000 inhabitants), Switzerland. Interviews took place at participants’ homes, in a private office at the University of Geneva, by telephone or by secure video call, according to participants’ preference. Informal caregivers could also participate alongside the participants.

Study flowchart

Researcher characteristics

All the researchers were trained in qualitative studies. The diabetologist and researcher (GG) who enrolled the patients in the study was involved directly or indirectly (advice asked to the Geneva University Hospital diabetes team of which he was a part) for most participants’ care during hospitalization. LS (Ph.D. student and community pharmacist) was unknown to participants and presented herself during hospitalization as a “researcher” and not as a healthcare professional to avoid any risk of influencing participants’ answers. This study was not interventional, and the interviewer (LS) invited participants to contact a healthcare professional for any questions related to their medication or medical issues.

Population and sampling strategy

Patients with type 2 diabetes were chosen as an example population to describe polypharmacy patients as these patients usually have several health issues and polypharmacy [ 20 , 22 , 25 ]. Inclusions criteria for the study were: adult patients with type 2 diabetes, with at least two other comorbidities, hospitalized for at least three days in a general internal medicine ward, with a minimum of one medication change during hospital stay, and who self-managed their medications once discharged home. Exclusion criteria were patients not reachable by telephone following discharge, unable to give consent (patients with schizophrenia, dementia, brain damage, or drug/alcohol misuse), and who could not communicate in French. A purposive sampling methodology was applied aiming to include participants with different ages, genders, types, and numbers of health conditions by listing participants’ characteristics in a double-entry table, available in Supplementary Material 1 , until thematic saturation was reached. Thematic saturation was considered achieved when no new code or theme emerged and new data repeated previously coded information [ 64 ]. The participants were identified if they were hospitalized in the ward dedicated to diabetes care or when the diabetes team was contacted for advice. The senior ward physician (GG) screened eligible patients and the interviewer (LS) obtained written consent before hospital discharge.

Data collection and instruments

Sociodemographic (age, gender, educational level, living arrangement) and clinical characteristics (reason for hospitalization, date of admission, health conditions, diabetes diagnosis, medications before and during hospitalization) were collected by interviewing participants before their discharge and by extracting participants’ data from electronic hospital files by GG and LS. Participants’ pharmacies were contacted with the participant’s consent to obtain medication records from the last three months if information regarding medications before hospitalization was missing in the hospital files.

Semi-structured interview guides for each interview (at three, 10-, 30- and 60-days post-discharge) were developed based on different theories and components of health behavior and medication adherence: the World Health Organization’s (WHO) five dimensions for adherence, the Information-Motivation-Behavioral skills model and the Social Cognitive Theory [ 65 , 66 , 67 ]. Each interview explored participants’ itinerary in the healthcare system and their perspectives on their medications. Regarding medications, the following themes were mentioned at each interview: changes in medications, patients’ understanding and implication; information on their medications, self-management of their medications, and patients’ medication adherence. Other aspects were mentioned in specific interviews: patients’ hospitalization and experience on their return home (interview 1), motivation (interviews 2 and 4), and patient’s feedback on the past two months (interview 4). Interview guides translated from French are available in Supplementary Material 2 . The participants completed self-reported and self-administrated questionnaires at different interviews to obtain descriptive information on different factors that may affect medication management and adherence: self-report questionnaires on quality of life (EQ-5D-5 L) [ 68 ], literacy (Schooling-Opinion-Support questionnaire) [ 69 ], medication adherence (Adherence Visual Analogue Scale, A-VAS) [ 70 ] and Belief in Medication Questionnaire (BMQ) [ 71 ] were administered to each participant at the end of selected interviews to address the different factors that may affect medication management and adherence as well as to determine a trend of determinants over time. The BMQ contains two subscores: Specific-Necessity and Specific-Concerns, addressing respectively their perceived needs for their medications, and their concerns about adverse consequences associated with taking their medication [ 72 ].

Data management

Informed consent forms, including consent to obtain health data, were securely stored in a private office at the University of Geneva. The participants’ identification key was protected by a password known only by MS and LS. Confidentiality was guaranteed by pseudonymization of participants’ information and audio-recordings were destroyed once analyzed. Sociodemographic and clinical characteristics, medication changes, and answers to questionnaires were securely collected by electronic case report forms (eCRFs) on RedCap®. Interviews were double audio-recorded and field notes were taken during interviews. Recorded interviews were manually transcribed verbatim in MAXQDA® (2018.2) by research assistants and LS and transcripts were validated for accuracy by LS. A random sample of 20% of questionnaires was checked for accuracy for the transcription from the paper questionnaires to the eCRFs. Recorded sequences with no link to the discussed topics were not transcribed and this was noted in the transcripts.

Data analysis

A descriptive statistical analysis of sociodemographic, clinical characteristics and self-reported questionnaire data was carried out. A thematic analysis of transcripts was performed, as described by Braun and Clarke [ 73 ], by following six steps: raw data was read, text segments related to the study objectives were identified, text segments to create new categories were identified, similar or redundant categories were reduced and a model that integrated all significant categories was created. The analysis was conducted in parallel with patient enrolment to ensure data saturation. To ensure the validity of the coding method, transcripts were double coded independently and discussed by the research team until similar themes were obtained. The research group developed and validated an analysis grid, with which LS coded systematically the transcriptions and met regularly with the research team to discuss questions on data analysis and to ensure the quality of coding. The analysis was carried out in French, and the verbatims of interest cited in the manuscript were translated and validated by a native English-speaking researcher to preserve the meaning.

In this analysis, we used the term “healthcare professionals” when more than one profession could be involved in participants’ medication management. Otherwise, when a specific healthcare professional was involved, we used the designated profession (e.g. physicians, pharmacists).

Patient and public involvement

During the development phase of the study, interview guides and questionnaires were reviewed for clarity and validity and adapted by two patient partners, with multiple health conditions and who experienced previously a hospital discharge. They are part of the HUG Patients Partners + 3P platform for research and patient and public involvement.

Interviews and participants’ descriptions

A total of 75 interviews were conducted with 21 participants. In total, 31 patients were contacted, seven refused to participate (four at the project presentation and three at consent), two did not enter the selection criteria at discharge and one was unreachable after discharge. Among the 21 participants, 15 participated in all interviews, four in three interviews, one in two interviews, and one in one interview, due to scheduling constraints. Details regarding interviews and participants characteristics are presented in Tables  1 and 2 .

The median length of time between hospital discharge and interviews 1,2,3 and 4 was 5 (IQR: 4–7), 14 (13-20), 35 (22-38), and 63 days (61-68), respectively. On average, by comparing medications at hospital admission and discharge, a median of 7 medication changes (IQR: 6–9, range:2;17) occurred per participant during hospitalization and a median of 7 changes (5–12) during the two months following discharge. Details regarding participants’ medications are described in Table  3 .

Patient self-reported adherence over the past week for their three most challenging medications are available in Supplementary Material 3 .

Qualitative analysis

We defined care transition as the period from discharge until the first medical appointment post-discharge, and outpatient care as the period starting after the first medical appointment. Data was organized into three key themes (A. Medication management, B. Medication understanding, and C. Medication adherence) divided into subthemes at three time points (1. Hospitalization, 2. Care transition and 3. Outpatient care). Figure  2 summarizes and illustrates the themes and subthemes with their influencing factors as bullet points.

Participants’ medication management, understanding and adherence during hospitalization, care transition and outpatient care

A. Medication management

A.1 medication management during hospitalization: medication management by hospital staff.

Medications during hospitalization were mainly managed by hospital healthcare professionals (i.e. nurses and physicians) with varying degrees of patient involvement: “At the hospital, they prepared the medications for me. […] I didn’t even know what the packages looked like.” Participant 22; interview 1 (P22.1) Some participants reported having therapeutic education sessions with specialized nurses and physicians, such as the explanation and demonstration of insulin injection and glucose monitoring. A patient reported that he was given the choice of several treatments and was involved in shared decision-making. Other participants had an active role in managing and optimizing dosages, such as rapid insulin, due to prior knowledge and use of medications before hospitalization.

A.2 Medication management at transition: obtaining the medication and initiating self-management

Once discharged, some participants had difficulties obtaining their medications at the pharmacy because some medications were not stored and had to be ordered, delaying medication initiation. To counter this problem upstream, a few participants were provided a 24-to-48-hour supply of medications at discharge. It was sometimes requested by the patient or suggested by the healthcare professionals but was not systematic. The transition from medication management by hospital staff to self-management was exhausting for most participants who were faced with a large amount of new information and changes in their medications: “ When I was in the hospital, I didn’t even realize all the changes. When I came back home, I took away the old medication packages and got out the new ones. And then I thought : « my God, all this…I didn’t know I had all these changes » ” P2.1 Written documentation, such as the discharge prescription or dosage labels on medication packages, was helpful in managing their medication at home. Most participants used weekly pill organizers to manage their medications, which were either already used before hospitalization or were introduced post-discharge. The help of a family caregiver in managing and obtaining medications was reported as a facilitator.

A.3 Medication management in outpatient care: daily self-management and medication burden

A couple of days or weeks after discharge, most participants had acquired a routine so that medication management was less demanding, but the medication burden varied depending on the participants. For some, medication management became a simple action well implemented in their routine (“It has become automatic” , P23.4), while for others, the number of medications and the fact that the medications reminded them of the disease was a heavy burden to bear on a daily basis (“ During the first few days after getting out of the hospital, I thought I was going to do everything right. In the end, well [laughs] it’s complicated. I ended up not always taking the medication, not monitoring the blood sugar” P12.2) To support medication self-management, some participants had written documentation such as treatment plans, medication lists, and pictures of their medication packages on their phones. Some participants had difficulties obtaining medications weeks after discharge as discharge prescriptions were not renewable and participants did not see their physician in time. Others had to visit multiple physicians to have their prescriptions updated. A few participants were faced with prescription or dispensing errors, such as prescribing or dispensing the wrong dosage, which affected medication management and decreased trust in healthcare professionals. In most cases, according to participants, the pharmacy staff worked in an interprofessional collaboration with physicians to provide new and updated prescriptions.

B. Medication understanding

B.1 medication understanding during hospitalization: new information and instructions.

The amount of information received during hospitalization varied considerably among participants with some reporting having received too much, while others saying they received too little information regarding medication changes, the reason for changes, or for introducing new medications: “They told me I had to take this medication all my life, but they didn’t tell me what the effects were or why I was taking it.” P5.3

Hospitalization was seen by some participants as a vulnerable and tiring period during which they were less receptive to information. Information and explanations were generally given verbally, making it complicated for most participants to recall it. Some participants reported that hospital staff was attentive to their needs for information and used communication techniques such as teach-back (a way of checking understanding by asking participants to say in their own words what they need to know or do about their health or medications). Some participants were willing to be proactive in the understanding of their medications while others were more passive, had no specific needs for information, and did not see how they could be engaged more.

B.2 Medication understanding at transition: facing medication changes

At hospital discharge, the most challenging difficulty for participants was to understand the changes made regarding their medications. For newly diagnosed participants, the addition of new medications was more difficult to understand, whereas, for experienced participants, changes in known medications such as dosage modification, changes within a therapeutic class, and generic substitutions were the most difficult to understand. Not having been informed about changes caused confusion and misunderstanding. Therefore, medication reconciliation done by the patient was time-consuming, especially for participants with multiple medications: “ They didn’t tell me at all that they had changed my treatment completely. They just told me : « We’ve changed a few things. But it was the whole treatment ». ” P2.3 Written information, such as the discharge prescription, the discharge report (brief letter summarizing information about the hospitalization, given to the patient at discharge), or the label on the medication box (written by the pharmacist with instructions on dosage) helped them find or recall information about their medications and diagnoses. However, technical terms were used in hospital documentations and were not always understandable. For example, this participant said: “ On the prescription of valsartan, they wrote: ‘resume in the morning once profile…’[once hypertension profile allows]… I don’t know what that means.” P8.1 In addition, some documents were incomplete, as mentioned by a patient who did not have the insulin dosage mentioned on the hospital prescription. Some participants sought help from healthcare professionals, such as pharmacists, hospital physicians, or general practitioners a few days after discharge to review medications, answer questions, or obtain additional information.

B.3 Medication understanding in the outpatient care: concerns and knowledge

Weeks after discharge, most participants had concerns about the long-term use of their medications, their usefulness, and the possible risk of interactions or side effects. Some participants also reported having some lack of knowledge regarding indications, names, or how the medication worked: “I don’t even know what Brilique® [ticagrelor, antiplatelet agent] is for. It’s for blood pressure, isn’t it?. I don’t know.” P11.4 According to participants, the main reasons for the lack of understanding were the lack of information at the time of prescribing and the large number of medications, making it difficult to search for information and remember it. Participants sought information from different healthcare professionals or by themselves, on package inserts, through the internet, or from family and friends. Others reported having had all the information needed or were not interested in having more information. In addition, participants with low medication literacy, such as non-native speakers or elderly people, struggled more with medication understanding and sought help from family caregivers or healthcare professionals, even weeks after discharge: “ I don’t understand French very well […] [The doctor] explained it very quickly…[…] I didn’t understand everything he was saying” P16.2

C. Medication adherence

C.2 medication adherence at transition: adopting new behaviors.

Medication adherence was not mentioned as a concern during hospitalization and a few participants reported difficulties in medication initiation once back home: “I have an injection of Lantus® [insulin] in the morning, but obviously, the first day [after discharge], I forgot to do it because I was not used to it.” P23.1 Participants had to quickly adopt new behaviors in the first few days after discharge, especially for participants with few medications pre-hospitalization. The use of weekly pill organizers, alarms and specific storage space were reported as facilitators to support adherence. One patient did not initiate one of his medications because he did not understand the medication indication, and another patient took her old medications because she was used to them. Moreover, most participants experienced their hospitalization as a turning point, a time when they focused on their health, thought about the importance of their medications, and discussed any new lifestyle or dietary measures that might be implemented.

C.3 Medication adherence in outpatient care: ongoing medication adherence

More medication adherence difficulties appeared a few weeks after hospital discharge when most participants reported nonadherence behaviors, such as difficulties implementing the dosage regimen, or intentionally discontinuing the medication and modifying the medication regimen on their initiative. Determinants positively influencing medication adherence were the establishment of a routine; organizing medications in weekly pill-organizers; organizing pocket doses (medications for a short period that participants take with them when away from home); seeking support from family caregivers; using alarm clocks; and using specific storage places. Reasons for nonadherence were changes in daily routine; intake times that were not convenient for the patient; the large number of medications; and poor knowledge of the medication or side effects. Healthcare professionals’ assistance for medication management, such as the help of home nurses or pharmacists for the preparation of weekly pill-organizers, was requested by participants or offered by healthcare professionals to support medication adherence: “ I needed [a home nurse] to put my pills in the pillbox. […] I felt really weak […] and I was making mistakes. So, I’m very happy [the doctor] offered me [home care]. […] I have so many medications.” P22.3 Some participants who experienced prehospitalization non-adherence were more aware of their non-adherence and implemented strategies, such as modifying the timing of intake: “I said to my doctor : « I forget one time out of two […], can I take them in the morning? » We looked it up and yes, I can take it in the morning.” P11.2 In contrast, some participants were still struggling with adherence difficulties that they had before hospitalization. Motivations for taking medications two months after discharge were to improve health, avoid complications, reduce symptoms, reduce the number of medications in the future or out of obligation: “ I force myself to take them because I want to get to the end of my diabetes, I want to reduce the number of pills as much as possible.” P14.2 After a few weeks post-hospitalization, for some participants, health and illness were no longer the priority because of other life imperatives (e.g., family or financial situation).

This longitudinal study provided a multi-faceted representation of how patients manage, understand, and adhere to their medications from hospital discharge to two months after discharge. Our findings highlighted the varying degree of participants’ involvement in managing their medications during their hospitalization, the individualized needs for information during and after hospitalization, the complicated transition from hospital to autonomous medication management, the adaptation of daily routines around medication once back home, and the adherence difficulties that surfaced in the outpatient care, with nonadherence prior to hospitalization being an indicator of the behavior after discharge. Finally, our results confirmed the lack of continuity in care and showed the lack of patient care standardization experienced by the participants during the transition from hospital to outpatient care.

This in-depth analysis of patients’ experiences reinforces common challenges identified in the existing literature such as the lack of personalized information [ 9 , 10 , 11 ], loss of autonomy during hospitalization [ 14 , 74 , 75 ], difficulties in obtaining medication at discharge [ 11 , 45 , 76 ] and challenges in understanding treatment modifications and generics substitution [ 11 , 32 , 77 , 78 ]. Some of these studies were conducted during patients’ hospitalization [ 10 , 75 , 79 ] or up to 12 months after discharge [ 80 , 81 ], but most studies focused on the few days following hospital discharge [ 9 , 11 , 14 , 82 ]. Qualitative studies on medications at transition often focused on a specific topic, such as medication information, or a specific moment in time, and often included healthcare professionals, which muted patients’ voices [ 9 , 10 , 11 , 47 , 49 ]. Our qualitative longitudinal methodology was interested in capturing the temporal dynamics, in-depth narratives, and contextual nuances of patients’ medication experiences during transitions of care [ 59 , 83 ]. This approach provided a comprehensive understanding of how patients’ perspectives and behaviors evolved over time, offering insights into the complex interactions of medication management, understanding and adherence, and turning points within their medication journeys. A qualitative longitudinal design was used by Fylan et al. to underline patients’ resilience in medication management during and after discharge, by Brandberg et al. to show the dynamic process of self-management during the 4 weeks post-discharge and by Lawton et al. to examine how patients with type 2 diabetes perceived their care after discharge over a period of four years [ 49 , 50 , 51 ]. Our study focused on the first two months following hospitalization and future studies should focus on following discharged and at-risk patients over a longer period, as “transitions of care do not comprise linear trajectories of patients’ movements, with a starting and finishing point. Instead, they are endless loops of movements” [ 47 ].

Our results provide a particularly thorough description of how participants move from a state of total dependency during hospitalization regarding their medication management to a sudden and complete autonomy after hospital discharge impacting medication management, understanding, and adherence in the first days after discharge for some participants. Several qualitative studies have described the lack of shared decision-making and the loss of patient autonomy during hospitalization, which had an impact on self-management and created conflicts with healthcare professionals [ 75 , 81 , 84 ]. Our study also highlights nuanced patient experiences, including varying levels of patient needs, involvement, and proactivity during hospitalization and outpatient care, and our results contribute to capturing different perspectives that contrast with some literature that often portrays patients as more passive recipients of care [ 14 , 15 , 74 , 75 ]. Shared decision-making and proactive medication are key elements as they contribute to a smoother transition and better outcomes for patients post-discharge [ 85 , 86 , 87 ].

Consistent with the literature, the study identifies some challenges in medication initiation post-discharge [ 16 , 17 , 88 ] but our results also describe how daily routine rapidly takes over, either solidifying adherence behavior or generating barriers to medication adherence. Participants’ nonadherence prior to hospitalization was a factor influencing participants’ adherence post-hospitalization and this association should be further investigated, as literature showed that hospitalized patients have high scores of non-adherence [ 89 ]. Mortel et al. showed that more than 20% of discharged patients stopped their medications earlier than agreed with the physician and 25% adapted their medication intake [ 90 ]. Furthermore, patients who self-managed their medications had a lower perception of the necessity of their medication than patients who received help, which could negatively impact medication adherence [ 91 ]. Although participants in our study had high BMQ scores for necessity and lower scores for concerns, some participants expressed doubts about the need for their medications and a lack of motivation a few weeks after discharge. Targeted pharmacy interventions for newly prescribed medications have been shown to improve medication adherence, and hospital discharge is an opportune moment to implement this service [ 92 , 93 ].

Many medication changes were made during the transition of care (a median number of 7 changes during hospitalization and 7 changes during the two months after discharge), especially medication additions during hospitalization and interruptions after hospitalization. While medication changes during hospitalization are well described, the many changes following discharge are less discussed [ 7 , 94 ]. A Danish study showed that approximately 65% of changes made during hospitalization were accepted by primary healthcare professionals but only 43% of new medications initiated during hospitalization were continued after discharge [ 95 ]. The numerous changes after discharge may be caused by unnecessary intensification of medications during hospitalization, delayed discharge letters, lack of standardized procedures, miscommunication, patient self-management difficulties, or in response to an acute situation [ 96 , 97 , 98 ]. During the transition of care, in our study, both new and experienced participants were faced with difficulties in managing and understanding medication changes, either for newly prescribed medication or changes in previous medications. Such difficulties corroborate the findings of the literature [ 9 , 10 , 47 ] and our results showed that the lack of understanding during hospitalization led to participants having questions about their medications, even weeks after discharge. Particular attention should be given to patients’ understanding of medication changes jointly by physicians, nurses and pharmacists during the transition of care and in the months that follow as medications are likely to undergo as many changes as during hospitalization.

Implication for practice and future research

The patients’ perspectives in this study showed, at a system level, that there was a lack of standardization in healthcare professional practices regarding medication dispensing and follow-up. For now, in Switzerland, there are no official guidelines on medication prescription and dispensation during the transition of care although some international guidelines have been developed for outpatient healthcare professionals [ 3 , 99 , 100 , 101 , 102 ]. Here are some suggestions for improvement arising from our results. Patients should be included as partners and healthcare professionals should systematically assess (i) previous medication adherence, (ii) patients’ desired level of involvement and (iii) their needs for information during hospitalization. Hospital discharge processes should be routinely implemented to standardize hospital discharge preparation, medication prescribing, and dispensing. Discharge from the hospital should be planned with community pharmacies to ensure that all medications are available and, if necessary, doses of medications should be supplied by the hospital to bridge the gap. A partnership with outpatient healthcare professionals, such as general practitioners, community pharmacists, and homecare nurses, should be set up for effective asynchronous interprofessional collaboration to consolidate patients’ medication management, knowledge, and adherence, as well as to monitor signs of deterioration or adverse drug events.

Future research should consolidate our first attempt to develop a framework to better characterize medication at the transition of care, using Fig. 2   as a starting point. Contextualized interventions, co-designed by health professionals, patients and stakeholders, should be tested in a hybrid implementation study to test the implementation and effectiveness of the intervention for the health system [ 103 ].

Limitations

This study has some limitations. First, the transcripts were validated for accuracy by the interviewer but not by a third party, which could have increased the robustness of the transcription. Nevertheless, the interviewer followed all methodological recommendations for transcription. Second, patient inclusion took place during the COVID-19 pandemic, which may have had an impact on patient care and the availability of healthcare professionals. Third, we cannot guarantee the accuracy of some participants’ medication history before hospitalization, even though we contacted the participants’ main pharmacy, as participants could have gone to different pharmacies to obtain their medications. Fourth, our findings may not be generalizable to other populations and other healthcare systems because some issues may be specific to multimorbid patients with type 2 diabetes or to the Swiss healthcare setting. Nevertheless, issues encountered by our participants regarding their medications correlate with findings in the literature. Fifth, only 15 out of 21 participants took part in all the interviews, but most participants took part in at least three interviews and data saturation was reached. Lastly, by its qualitative and longitudinal design, it is possible that the discussion during interviews and participants’ reflections between interviews influenced participants’ management, knowledge, and adherence, even though this study was observational, and no advice or recommendations were given by the interviewer during interviews.

Discharged patients are willing to take steps to better manage, understand, and adhere to their medications, yet they are also faced with difficulties in the hospital and outpatient care. Furthermore, extensive changes in medications not only occur during hospitalization but also during the two months following hospital discharge, for which healthcare professionals should give particular attention. The different degrees of patients’ involvement, needs and resources should be carefully considered to enable them to better manage, understand and adhere to their medications. At a system level, patients’ experiences revealed a lack of standardization of medication practices during the transition of care. The healthcare system should provide the ecosystem needed for healthcare professionals responsible for or involved in the management of patients’ medications during the hospital stay, discharge, and outpatient care to standardize their practices while considering the patient as an active partner.

Data availability

The anonymized quantitative survey datasets and the qualitative codes are available in French from the corresponding author on reasonable request.

Abbreviations

adverse drug events

Adherence Visual Analogue Scale

Belief in Medication Questionnaire

Consolidated Criteria for Reporting Qualitative Research

case report form

standard deviation

World Health Organization

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Acknowledgements

The authors would like to thank all the patients who took part in this study. We would also like to thank the Geneva University Hospitals Patients Partners + 3P platform as well as Mrs. Tourane Corbière and Mr. Joël Mermoud, patient partners, who reviewed interview guides for clarity and significance. We would like to thank Samuel Fabbi, Vitcoryavarman Koh, and Pierre Repiton for the transcriptions of the audio recordings.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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LS, GG, and MS conceptualized and designed the study. LS and GG screened and recruited participants. LS conducted the interviews. LS, GG, and MS performed data analysis and interpretation. LS drafted the manuscript and LS and MS worked on the different versions. MS and GG approved the final manuscript.

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Solh Dost, L., Gastaldi, G. & Schneider, M. Patient medication management, understanding and adherence during the transition from hospital to outpatient care - a qualitative longitudinal study in polymorbid patients with type 2 diabetes. BMC Health Serv Res 24 , 620 (2024). https://doi.org/10.1186/s12913-024-10784-9

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Factors associated with clinical nurse’s mental health: a qualitative study applying the social ecological model

• Qiang Yu 1   na1 ,
• Chongmei Huang 2 , 3   na1 ,
• Yusheng Tian 1 ,
• Jiaxin Yang 1 ,
• Xuting Li 1 ,
• Meng Ning 4 ,
• Zengyu Chen 4 ,
• Jiaqing He 1 &
• Yamin Li 1  

BMC Nursing volume  23 , Article number:  330 ( 2024 ) Cite this article

Metrics details

The prevalence of burnout, depression, and anxiety among Chinese nurses was 34%, 55.5%, and 41.8% respectively. Mental health problems have significant impacts on their personal well-being, work performance, patient care quality, and the overall healthcare system. Mental health is influenced by factors at multiple levels and their interactions.

This was a descriptive qualitative study using phenomenological approach. We recruited a total of 48 nurses from a tertiary hospital in Changsha, Hunan Province, China. Data were collected through focus group interviews. Audio-recorded data were transcribed and inductively analysed.

Four major themes with 13 subthemes were identified according to the social ecological model: (1) individual-level factors, including personality traits, sleep quality, workplace adaptability, and years of work experience; (2) interpersonal-level factors, encompassing interpersonal support and role conflict; (3) organization-level factors, such as organizational climate, organizational support, career plateau, and job control; and (4) social-level factors, which included compensation packages, social status, and legislative provision and policy.

Conclusions

Our study provides a nuanced understanding of the multifaceted factors influencing nurses’ mental health. Recognizing the interconnectedness of individual, interpersonal, organizational, and social elements is essential for developing targeted interventions and comprehensive strategies to promote and safeguard the mental well-being of nurses in clinical settings.

Trial and protocol registration

The larger study was registered with Chinese Clinical Trial Registry: ChiCTR2300072142 (05/06/2023) https://www.chictr.org.cn/showproj.html?proj=192676 .

Reporting method

This study is reported according to the Consolidated Criteria for Reporting Qualitative Research (COREQ).

Peer Review reports

The prevalence of mental health problem among clinical nurses is high. As the largest group of health systems, clinical nurses play a crucial role in promoting health and preventing disease [ 1 ]. Although they are trained to provide care for their patients, they rarely cared about themselves [ 1 ]. Clinical nurses are suffering from mental health problems, including stress, anxiety, depression, and burnout. A meta-analysis involving 45,539 nurses from 49 countries revealed that a global prevalence of burnout symptoms was 11.23% across various specialties [ 2 ]. In Australia, the prevalence of depression, anxiety and stress among nurses was 32.4%, 41.2% and 41.2%, respectively [ 1 ]. In Italy, the prevalence of generalized anxiety disorder among nurses is 50% [ 3 ].In Spain, 68% of nurses had depression, anxiety, insomnia and distress to some degree, and 38% of them had moderate or severe symptoms [ 4 ]. A survey of clinical nurses from 30 Chinese provinces indicated that the rates of burnout, depression, and anxiety was 34%, 55.5%, and 41.8%, respectively [ 5 ]. Mental health problems may compromise physical, mental, and social health and even increase suicide risk [ 6 ].

The mental health problems among clinical nurses affects their personal well-being, work performance, patient care quality, and the healthcare system. Remarkably, their mental health problems not only heighten the risk of physical conditions such as heart disease, chronic pain, gastrointestinal distress, and even mortality [ 7 ], but also correlate with absenteeism, intention to leave, and elevated turnover rates [ 8 , 9 ]. These increased turnover rates exacerbate the financial challenges faced by healthcare institutions [ 10 ]. The presence of one or more of these mental health problems can contribute to occupational mishaps, including medical errors [ 1 , 11 ], compromised work performance, and a pessimistic workplace demeanor [ 12 ]. Nurses with mental health problems are at 26–71% more likely to make medical errors [ 13 ]. Furthermore, their mental health may imperil the well-being of patients and the quality of health services [ 14 ]. Moreover, these challenges can contribute to reputation harm, diminished productivity, and decreased clinical efficacy of the hospital [ 15 ]. Therefore, it is necessary to identify factors associated with their mental health for developing and implementing targeted intervention.

Previous studies have identified several factors associated with clinical nurses’ mental health, with some limitations [ 16 ]. According to the social ecological model, mental health is affected by factors at multiple levels and interaction between factors. However, most studies explored factors at a single level or a single type of factors. For instance, studies focused on factors either at individual (psychological characteristics) [ 17 , 18 ], or interpersonal (e.g., social support) [ 19 , 20 , 21 ], organizational (e.g., workplace violence) [ 22 ], or societal level (e.g., social status) [ 23 , 24 ]. Therefore, these studies fail to offer a complete picture of factors at multiple levels and examine interactions between factors. Additionally, the majority of extant studies adopt quantitative design with standardized measurements, which may neglect the intricacies of personal experiences and the significance of context.

To fill aforementioned gap, our study is aimed to explore associated factors for mental health at all four socio-ecological levels and to understand the interactions between factors from the perspective of clinical nurses.

Study design

This study adopted a qualitative descriptive design with focus group interviews. Qualitative description design is widely used to gather insight from key informants about poorly understood healthcare questions [ 25 , 26 ]. The design was considered appropriate because this study aimed to obtain a detailed description of participants’ perceived influencing factors of mental health. Focus group interviews were used for data collection to encourage the free exchange of information and to yield richer data and deeper insights into the topic.

This study was conducted in a tertiary hospital in Changsha, Hunan Province, China. The hospital has 3000 nurses and 137 head nurses.

Participants

This study included clinical nurses and head nurses who were employed by the hospital for one year or over. They were recruited, using both convenience and purposive sampling between April to May 2023. The study was advertised through the existing network of the authors. Potential participants were approached by the authors via WeChat with an explanatory statement. The explanatory statement included a brief introduction of the study and invited potential participants to contact the first author directly to arrange the interview time and venue. Purposive sampling was used to obtain maximum variation, within participants’ characteristics including gender, years of work experience, clinical work area, and having an administrative position or not.

Data collection

We conducted seven focus groups (seven- eight participants in each group) in the meeting room of the hospital between April to May 2023. We introduced the purpose of the research and topics before conducting the group interview. The interview guide were developed based on the literature review, including following questions: (1) How about your mental health in daily work? (2) What are the factors influencing your mental health? (3) How does mental health affect your daily life? (4) When you felt down, what kind of coping strategies do you adopted? (5) What external factors (e.g., individual, interpersonal and environmental factors) are conducive to promoting your mental health? The interviews were conducted in Mandarin. The second author acted as a facilitator for focus groups, and she participated workshop in qualitative research as part of master course. The fourth author acted as a note taker who took field notes and observed the interaction within the groups. The duration of the focus group interviews ranged from 65 to 94 min (mean 81.5 min).

Data analysis

Preliminary data collection and data analysis were conducted simultaneously, which enabled collection to cease on reaching data saturation. All audio recordings were transcribed in Mandarin using Xunfei software, and the accuracy was verified by the first, third, and fifth authors. Then, all the data were input entered into excel for analysis. Three authors (the second, eighth, and ninth authors) independently coded the transcripts line by line and then deliberated to form a preliminary coding framework. Constant comparative analysis ensured consistent coding across transcripts. They developed a preliminary coding framework after coding the first three transcripts, refining it iteratively with subsequent transcripts. This was repeated with further transcripts, and the subthemes were refined and reduced in number by grouping codes together. Following the development of the final coding framework, the remaining transcripts remained open to new additions if needed.

Final themes were constructed using an inductive process. The social ecological model was used to group themes. This model was used to connect the findings with the literature and conceptual framework. The social ecological model [ 27 ] is used to describe multiple factors affecting mental health and explore healthcare behaviors [ 28 , 29 ], these factors grouped into four levels: intrapersonal, interpersonal, organizational and societal level. This model includes four levels: individual, interpersonal, organizational and societal. Individual level identifies biological, character traits and psychological factors. Interpersonal level examines communication and interaction with individuals in social networks. Organizational level contains resources obtained from organizations and through social interactions. Societal level focuses on factors that help create an atmosphere conducive to maintaining mental health.

The study’s rigor was established through meticulous attention to credibility, transferability, dependability, and confirmability [ 30 ]. Credibility was achieved by rigorously analyzing the data by the research team. Transferability was ensured by providing a comprehensive description of the study setting and detailed narratives of participant experiences. Additionally, dependability and confirmability were upheld through a meticulous audit of methodological decisions made by the research team throughout the study process.

Participant’s characteristics

Fifty nurses were invited to participate in this study, and two declined the invitation; the remaining 48 nurses completed the interview. More female nurse participated in the study ( n  = 37) rather than male ( n  = 5). The participants’ social demographic characteristics are presented in Table  1 .

Main findings

As shown shown in Fig. 1, factors associated with clinical nurses’ mental health were categorized four themes and 13 subthemes: (1) individual-level factors, (2) interpersonal-level factors, (3) organization-level factors, and (4) social-level factors.

Factors associated with clinical nurse’s mental health

Individual-level factors

Participants reported that their mental health could be impacted by personality traits (i.e., optimistic/negative life outlook), quality of sleep, workplace adaptability, and years of work experience. Some participants mentioned that adaptability was important for them to manage emotional and practical daily challenges in the face of rapidly changing and unpredictable circumstances.

When novice nurses take care of patients by themselves, they may experience increased stress, especially when patients’ condition changes suddenly during the night shift (F1P4).

Interpersonal-level factors

Participants perceived that interpersonal support and role conflict were associated with their mental health.

Interpersonal support

Our participants identified that interpersonal support was playing an important role in maintaining their mental health. They explained that talking to their families, friends, colleagues and supervisor were an effective way to relieve work stress.

I sought to the person I trust the most (my family) and talked all the unpleasant things with them when I felt very stressed (F3P3).

Role conflict

Participants mentioned that it was inevitable for them to experience role conflict (i.e., work-family conflict and work-school conflict) because of the demanding and challenging conditions of the job. They felt guilty when work pressures interfered with family responsibilities. Some participants identified that their emotional stress increased when their work interfered with their ability to meet the demands of their kids’ school. The demands of long study hours and early clinical hours caused stress among them and kept them from household responsibilities of cooking, cleaning, and spending time with children. Participants also felt that family support of their career choices helped their job performance.

. my father was diagnosed with lung cancer two years ago. He was resuscitated many times during his treatment. However, I was always busy working at the fever outpatient department and couldn’t spend much time with him. I still feel sad…(F7P4) .

Organization-level factors

Participants perceived that their mental health was influenced by the following four organizational-level factors, including (1) organization climate, (2) organization support, (3) career plateau, and (4) job control.

Organization climate

In this study, organization climate included emotional climate and workplace incivility. Participants perceived the importance of the emotional climate due to the transmissive nature of emotional states. It was easy to be infected by the negative emotions of colleagues, so that the entire department can generate or maintain a negative emotional climate, vice versa.

Some colleagues are always complaining, which affects others’ the mood (F3P4).

Most participates identified it was common for them to experience workplace incivility which came from their nurses, physicians, supervisors and patients. They felt disrespected, threatened reprimanded, and emotionally abused, which evoke negative emotions, such as anxiety, depression, exhaustion.

Organization support

Participants perceived that organization support (i.e., instrumental and emotional support) were related to job satisfaction and mental health. Participants identified various forms of instrumental support, including physical environment, sufficient human resource, task assistance, training opportunities and flexibility in work schedule. The support helped them to perform job roles, which also carried emotional meanings. Emotional support included listening to work concerns, allowing to vent emotions, and providing words of encouragement. The support provided socioemotional resources, involving affection, sympathy, understanding, acceptance, and recognition.

. we definitely don’t want our supervisor to scold us without getting the full picture (of the whole thing), and we really hope that supervisor investigate what really happened…(F7P2) .

Career plateau

Our participants, especially seniors frequently mentioned the challenge of double career plateau which includes hierarchical plateau and content plateau. They felt frustrated and even hopeless when they were experiencing a permanent end in career advancement. Some participants perceived little opportunity for vertical improvement because of the flattened pyramid shape within the hospital. Some participants expressed the concern about future professional recession because they have limited opportunities to master new skills.

Everyone think that our nurses don’t seem to have a future, especially the male nurses… only one or two nurses can really be head nurses (F2P1).

Job control

Many participates complained that they lack of control over work time and tasks. They had to extend their work time without compensation, leading to work-family conflicts. They felt exhausted and disgusted when they were asked to attend training and meetings immediately after night shifts. Additionally, some participants got annoyed by research tasks because they were not interested in it, and some participants felt incompetent at it because they did not receive relevant training.

we were asked to attend meetings and participate training and other activities after we finish our night shift. It’s really annoying (F7P5).

Social-level factors

Participants identified three social-level factors associated with the mental health, including (1) compensation package, (2) social status, and (3) legislative provision and policy.

Compensation package

Many participants were not satisfied with their compensation package. They indicated feelings of inadequate reward for their efforts and the level of responsibility, and unfairness of salary compared with doctors. Some participants felt unsafe because the institute did not buy pension insurance for them.

I did not have pension insurance, I feel stressed (laughing)… I reckon that as long as our profession enjoys good welfare and incentives…People will regard nursing as a valuable profession…(F2P8) .

Social status

Some participants perceived their social status as low, and it is common for them to receive discrimination from patients, relatives and doctors. Participants shared their experience of being viewed as servants by patients in the ward, which made them feel humiliated. They frankly voiced that their low social status, low salary and unsatisfactory professional image made them reluctant to recommend this career to others.

…In the eyes of most people, our status, ,are indeed low, they (patients) look down on us as if we were just waiters (F7P7)… .

Legislative provision and policy

Participants believe that legislative provision and supportive policy was an effective approach to improve social status and professional image.

How do you advocate for the rights of nurses? I believe the legal aspect is more important…(F5P4) .

To our knowledge, this is the first qualitative study which explored factors associated with mental health of clinical nurses by using socio-ecological model. The study advances the literature by emphasizing (1) the mental health is influenced by multi-level factors which include intrapersonal - (i.e., personality traits, quality of sleep, workplace adaptability, and years of work experience), interpersonal (i.e., interpersonal support and role conflict), organizational (i.e., organization climate, organization support, career plateau, and job control), and social-level factors (i.e., including compensation package, social status, and legislative provision and policy), (2) the interaction between factors, and (3) the reciprocal relationship between individuals’ mental health and their environments.

Consistent with the findings of previous research [ 31 , 32 , 33 , 34 , 35 ], our study found that nurses experience more work-to-family conflict than family-to-work conflict, leading to a feeling of stress and guilt. This may be because work and family life are mutually incompatible to some extent. Nurses experience high levels of physical, cognitive, and emotional demands due to the nature of the nursing profession. Meanwhile, most nurses are women, indicating a substantial number of dual-career or single-woman-headed households. They always are expected to take the primary responsibility for childcare and housework by themselves and society [ 36 ]. Therefore, they feel guilty when their work interferes with household duties and family responsibilities, or work detracts from quality time with their families. Notably, our study also found that organizational support (i.e., supportive working environment and flexibility in work schedule) and family support systems could help to mitigate work-family conflict. Consistently, organizational support has been identified as a valuable resource for fostering positive work attitudes and alleviating depressive symptoms [ 37 , 38 ].

Our study recognized the occurrence of double career plateau in nursing. This is because hierarchical and content plateau are closely connected. For example, the hierarchical plateau could lead to the content plateau. Nurse staff are more like to decrease their effort and consciously avoid holding more responsibilities due to the absence of promotion opportunities. Vice versa, nurse staff who are unable to expand their job expertise have limited opportunity for promotion. Notable, our study found that some nursing staff have initiated strategies to manage career plateau by improving academic qualifications. This finding was supported by previous evidence showing that more and more nurses are pursuing master’s and doctorates degrees [ 39 ]. Therefore, those nurses are more likely to experience role conflict and have compromised mental health [ 40 ]. Because they must navigate the added role of a student in addition to their professional career and family responsibilities within limited time and energy [ 41 ]. The career plateau not only leads to mental health problems (e.g.,depression, psychological stress, and burnout) but also exerts adverse effects on physical health. These effects manifest as irritability, outbursts, deteriorating service attitudes, confrontations with managers [ 42 ]. Nursing organizations and managers can address career plateau by providing more opportunities for advancement in nursing positions and titles and by establishing multi-dimensional career advancement pathways. For instance, implementing hierarchical management for nurses [ 43 ] can diversify career opportunities, motivate them, and ease the sense of professional stagnation, thereby alleviating mental health issues linked to career plateaus.

Our study found that nurses experience workplace uncivil acts from various sources, involving other nurses, physicians, supervisors, patients, and visitors. Consistently, evidence indicated that 65.7 − 90.4% of nurses were exposed to some degree of incivility. Previous studies have examined how this destructive behaviour affects organizational and individual outcomes, and which factors influence it [ 44 , 45 , 46 , 47 , 48 ]. Workplace incivility could cause emotional distress and productivity losses in nurses. This situation may be detrimental to patient safety and satisfaction. These negative outcomes could leads to financial strain on healthcare organizations [ 49 ]. Uncivil interactions within the healthcare team could be triggered by organizational and interpersonal factors, such as lack of support, heavy workload, inadequate personnel, and long working shifts. Particularly, these interactions negatively affect nurses who are the backbone of the team. Similarly, these factors were identified as risk factors of mental health of nurses in our study. We also found that support from other supervisors and coworkers could create healthy work environment, which is associated with improved mental health of nurses.

Strengths and limitations

A strength of this study was the use of the social ecological model as a theoretical framework. Contributory factors identified within each level of the framework were discussed by participants. This highlights that interventions developed around these contributory factors have the potential to improve clinical nurses’ mental health.

This study only recruited clinical nurses in one tertiary hospital, which may limits its generalizability. Our participants were recruited through the existing network of the author team, which may lead to selection bias.

This groundbreaking study has utilized the socio-ecological model to illuminate the intricate web of factors influencing the mental health of clinical nurses. The findings underscore the need for holistic interventions that address not only intrapersonal and interpersonal factors but also organizational and social-level factors to promote nurses’ well-being. By acknowledging the complexities of the nursing profession, healthcare organizations, managers, and policymakers can take proactive steps to create supportive environments, foster career development, and mitigate the adverse effects of workplace incivility. Ultimately, these efforts hold the promise of enhancing the mental health and overall job satisfaction of clinical nurses, which in turn contributes to improved patient care and healthcare system performance.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

The authors extend their sincere thanks to the research participants.

This study was supported by the grant of the 2023 Scientific Research Projects of the Chinese Nursing Association (Nurses’ mental health study, ID: ZHKY202306).

Author information

Qiang Yu and Chongmei Huang should be considered the joint first authors. Qiang Yu and Chongmei Huang made equal contributions to this manuscript.

Authors and Affiliations

Clinical Nursing Teaching and Research Section, The Second Xiangya Hospital, Central South University, Changsha, China

Qiang Yu, Yusheng Tian, Jiaxin Yang, Xuting Li, Jie Du, Jiaqing He & Yamin Li

School of Nursing, Ningxia Medical University, Yinchuan, China

Chongmei Huang

School of Nursing, Changsha Medical University, Changsha, China

Xiangya School of Nursing, Central South University, Changsha, China

Meng Ning & Zengyu Chen

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Contributions

YQ, HCM, TYS, YJX and LYM designed the study. HCM and YJX performed the interview. YQ, HCM, TYS, LXT, CZY, DJ and HJQ analyzed data. YQ, HCM, TYS, LXT, NM, CZY, DJ and HJQ did background researches, helped data transcriptions using software. YQ have drafted the manuscript. LYM supervised the research and revised the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Yamin Li .

Ethics declarations

Ethics approval and consent to participate.

The Ethics Committee of National Clinical Medical Research Center, Second Xiangya Hospital, Central South University approved this study (No.2023 − 0267). Formal written informed consent was obtained from each participant. Apart from the aim and pro-cedure of this study, nurses were also told that the participation wouldn’t affect them or their career, the whole interview would be audio-recorded and the anonymous records would only be used for this study. Besides, they were told about their rights to refuse to answer any question or withdraw at any time as well. With agreement to participant, they would sign an informed consent, after which they would be officially included in the study and interviewed. All methods were performed in accordance with the guidelines and regulations of the Declaration of Helsinki.

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The author(s) declare that they have no conflict of interests.

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Yu, Q., Huang, C., Tian, Y. et al. Factors associated with clinical nurse’s mental health: a qualitative study applying the social ecological model. BMC Nurs 23 , 330 (2024). https://doi.org/10.1186/s12912-024-02005-9

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Received : 28 December 2023

Accepted : 09 May 2024

Published : 16 May 2024

DOI : https://doi.org/10.1186/s12912-024-02005-9

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