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What Is a Case Study?

Weighing the pros and cons of this method of research

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Cara Lustik is a fact-checker and copywriter.

Verywell / Colleen Tighe

• Pros and Cons

What Types of Case Studies Are Out There?

Where do you find data for a case study, how do i write a psychology case study.

A case study is an in-depth study of one person, group, or event. In a case study, nearly every aspect of the subject's life and history is analyzed to seek patterns and causes of behavior. Case studies can be used in many different fields, including psychology, medicine, education, anthropology, political science, and social work.

The point of a case study is to learn as much as possible about an individual or group so that the information can be generalized to many others. Unfortunately, case studies tend to be highly subjective, and it is sometimes difficult to generalize results to a larger population.

While case studies focus on a single individual or group, they follow a format similar to other types of psychology writing. If you are writing a case study, we got you—here are some rules of APA format to reference.  

At a Glance

A case study, or an in-depth study of a person, group, or event, can be a useful research tool when used wisely. In many cases, case studies are best used in situations where it would be difficult or impossible for you to conduct an experiment. They are helpful for looking at unique situations and allow researchers to gather a lot of˜ information about a specific individual or group of people. However, it's important to be cautious of any bias we draw from them as they are highly subjective.

What Are the Benefits and Limitations of Case Studies?

A case study can have its strengths and weaknesses. Researchers must consider these pros and cons before deciding if this type of study is appropriate for their needs.

One of the greatest advantages of a case study is that it allows researchers to investigate things that are often difficult or impossible to replicate in a lab. Some other benefits of a case study:

• Allows researchers to capture information on the 'how,' 'what,' and 'why,' of something that's implemented
• Gives researchers the chance to collect information on why one strategy might be chosen over another
• Permits researchers to develop hypotheses that can be explored in experimental research

On the other hand, a case study can have some drawbacks:

• It cannot necessarily be generalized to the larger population
• Cannot demonstrate cause and effect
• It may not be scientifically rigorous
• It can lead to bias

Researchers may choose to perform a case study if they want to explore a unique or recently discovered phenomenon. Through their insights, researchers develop additional ideas and study questions that might be explored in future studies.

It's important to remember that the insights from case studies cannot be used to determine cause-and-effect relationships between variables. However, case studies may be used to develop hypotheses that can then be addressed in experimental research.

Case Study Examples

There have been a number of notable case studies in the history of psychology. Much of  Freud's work and theories were developed through individual case studies. Some great examples of case studies in psychology include:

• Anna O : Anna O. was a pseudonym of a woman named Bertha Pappenheim, a patient of a physician named Josef Breuer. While she was never a patient of Freud's, Freud and Breuer discussed her case extensively. The woman was experiencing symptoms of a condition that was then known as hysteria and found that talking about her problems helped relieve her symptoms. Her case played an important part in the development of talk therapy as an approach to mental health treatment.
• Phineas Gage : Phineas Gage was a railroad employee who experienced a terrible accident in which an explosion sent a metal rod through his skull, damaging important portions of his brain. Gage recovered from his accident but was left with serious changes in both personality and behavior.
• Genie : Genie was a young girl subjected to horrific abuse and isolation. The case study of Genie allowed researchers to study whether language learning was possible, even after missing critical periods for language development. Her case also served as an example of how scientific research may interfere with treatment and lead to further abuse of vulnerable individuals.

Such cases demonstrate how case research can be used to study things that researchers could not replicate in experimental settings. In Genie's case, her horrific abuse denied her the opportunity to learn a language at critical points in her development.

This is clearly not something researchers could ethically replicate, but conducting a case study on Genie allowed researchers to study phenomena that are otherwise impossible to reproduce.

There are a few different types of case studies that psychologists and other researchers might use:

• Collective case studies : These involve studying a group of individuals. Researchers might study a group of people in a certain setting or look at an entire community. For example, psychologists might explore how access to resources in a community has affected the collective mental well-being of those who live there.
• Descriptive case studies : These involve starting with a descriptive theory. The subjects are then observed, and the information gathered is compared to the pre-existing theory.
• Explanatory case studies : These   are often used to do causal investigations. In other words, researchers are interested in looking at factors that may have caused certain things to occur.
• Exploratory case studies : These are sometimes used as a prelude to further, more in-depth research. This allows researchers to gather more information before developing their research questions and hypotheses .
• Instrumental case studies : These occur when the individual or group allows researchers to understand more than what is initially obvious to observers.
• Intrinsic case studies : This type of case study is when the researcher has a personal interest in the case. Jean Piaget's observations of his own children are good examples of how an intrinsic case study can contribute to the development of a psychological theory.

The three main case study types often used are intrinsic, instrumental, and collective. Intrinsic case studies are useful for learning about unique cases. Instrumental case studies help look at an individual to learn more about a broader issue. A collective case study can be useful for looking at several cases simultaneously.

The type of case study that psychology researchers use depends on the unique characteristics of the situation and the case itself.

There are a number of different sources and methods that researchers can use to gather information about an individual or group. Six major sources that have been identified by researchers are:

• Archival records : Census records, survey records, and name lists are examples of archival records.
• Direct observation : This strategy involves observing the subject, often in a natural setting . While an individual observer is sometimes used, it is more common to utilize a group of observers.
• Documents : Letters, newspaper articles, administrative records, etc., are the types of documents often used as sources.
• Interviews : Interviews are one of the most important methods for gathering information in case studies. An interview can involve structured survey questions or more open-ended questions.
• Participant observation : When the researcher serves as a participant in events and observes the actions and outcomes, it is called participant observation.
• Physical artifacts : Tools, objects, instruments, and other artifacts are often observed during a direct observation of the subject.

If you have been directed to write a case study for a psychology course, be sure to check with your instructor for any specific guidelines you need to follow. If you are writing your case study for a professional publication, check with the publisher for their specific guidelines for submitting a case study.

Here is a general outline of what should be included in a case study.

Section 1: A Case History

This section will have the following structure and content:

Background information : The first section of your paper will present your client's background. Include factors such as age, gender, work, health status, family mental health history, family and social relationships, drug and alcohol history, life difficulties, goals, and coping skills and weaknesses.

Description of the presenting problem : In the next section of your case study, you will describe the problem or symptoms that the client presented with.

Describe any physical, emotional, or sensory symptoms reported by the client. Thoughts, feelings, and perceptions related to the symptoms should also be noted. Any screening or diagnostic assessments that are used should also be described in detail and all scores reported.

Your diagnosis : Provide your diagnosis and give the appropriate Diagnostic and Statistical Manual code. Explain how you reached your diagnosis, how the client's symptoms fit the diagnostic criteria for the disorder(s), or any possible difficulties in reaching a diagnosis.

Section 2: Treatment Plan

This portion of the paper will address the chosen treatment for the condition. This might also include the theoretical basis for the chosen treatment or any other evidence that might exist to support why this approach was chosen.

• Cognitive behavioral approach : Explain how a cognitive behavioral therapist would approach treatment. Offer background information on cognitive behavioral therapy and describe the treatment sessions, client response, and outcome of this type of treatment. Make note of any difficulties or successes encountered by your client during treatment.
• Humanistic approach : Describe a humanistic approach that could be used to treat your client, such as client-centered therapy . Provide information on the type of treatment you chose, the client's reaction to the treatment, and the end result of this approach. Explain why the treatment was successful or unsuccessful.
• Psychoanalytic approach : Describe how a psychoanalytic therapist would view the client's problem. Provide some background on the psychoanalytic approach and cite relevant references. Explain how psychoanalytic therapy would be used to treat the client, how the client would respond to therapy, and the effectiveness of this treatment approach.
• Pharmacological approach : If treatment primarily involves the use of medications, explain which medications were used and why. Provide background on the effectiveness of these medications and how monotherapy may compare with an approach that combines medications with therapy or other treatments.

This section of a case study should also include information about the treatment goals, process, and outcomes.

When you are writing a case study, you should also include a section where you discuss the case study itself, including the strengths and limitiations of the study. You should note how the findings of your case study might support previous research. 

In your discussion section, you should also describe some of the implications of your case study. What ideas or findings might require further exploration? How might researchers go about exploring some of these questions in additional studies?

Need More Tips?

Here are a few additional pointers to keep in mind when formatting your case study:

• Never refer to the subject of your case study as "the client." Instead, use their name or a pseudonym.
• Read examples of case studies to gain an idea about the style and format.
• Remember to use APA format when citing references .

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

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach . BMC Med Res Methodol . 2011 Jun 27;11:100. doi:10.1186/1471-2288-11-100

Gagnon, Yves-Chantal.  The Case Study as Research Method: A Practical Handbook . Canada, Chicago Review Press Incorporated DBA Independent Pub Group, 2010.

Yin, Robert K. Case Study Research and Applications: Design and Methods . United States, SAGE Publications, 2017.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Understanding Case Study Method in Research: A Comprehensive Guide

Table of Contents

Have you ever wondered how researchers uncover the nuanced layers of individual experiences or the intricate workings of a particular event? One of the keys to unlocking these mysteries lies in the qualitative research focusing on a single subject in its real-life context.">case study method , a research strategy that might seem straightforward at first glance but is rich with complexity and insightful potential. Let’s dive into the world of case studies and discover why they are such a valuable tool in the arsenal of research methods.

What is a Case Study Method?

At its core, the case study method is a form of qualitative research that involves an in-depth, detailed examination of a single subject, such as an individual, group, organization, event, or phenomenon. It’s a method favored when the boundaries between phenomenon and context are not clearly evident, and where multiple sources of data are used to illuminate the case from various perspectives. This method’s strength lies in its ability to provide a comprehensive understanding of the case in its real-life context.

Historical Context and Evolution of Case Studies

Case studies have been around for centuries, with their roots in medical and psychological research. Over time, their application has spread to disciplines like sociology, anthropology, business, and education. The evolution of this method has been marked by a growing appreciation for qualitative data and the rich, contextual insights it can provide, which quantitative methods may overlook.

Characteristics of Case Study Research

What sets the case study method apart are its distinct characteristics:

• Intensive Examination: It provides a deep understanding of the case in question, considering the complexity and uniqueness of each case.
• Contextual Analysis: The researcher studies the case within its real-life context, recognizing that the context can significantly influence the phenomenon.
• Multiple Data Sources: Case studies often utilize various data sources like interviews, observations, documents, and reports, which provide multiple perspectives on the subject.
• Participant’s Perspective: This method often focuses on the perspectives of the participants within the case, giving voice to those directly involved.

Types of Case Studies

There are different types of case studies, each suited for specific research objectives:

• Exploratory: These are conducted before large-scale research projects to help identify questions, select measurement constructs, and develop hypotheses.
• Descriptive: These involve a detailed, in-depth description of the case, without attempting to determine cause and effect.
• Explanatory: These are used to investigate cause-and-effect relationships and understand underlying principles of certain phenomena.
• Intrinsic: This type is focused on the case itself because the case presents an unusual or unique issue.
• Instrumental: Here, the case is secondary to understanding a broader issue or phenomenon.
• Collective: These involve studying a group of cases collectively or comparably to understand a phenomenon, population, or general condition.

The Process of Conducting a Case Study

Conducting a case study involves several well-defined steps:

• Defining Your Case: What or who will you study? Define the case and ensure it aligns with your research objectives.
• Selecting Participants: If studying people, careful selection is crucial to ensure they fit the case criteria and can provide the necessary insights.
• Data Collection: Gather information through various methods like interviews, observations, and reviewing documents.
• Data Analysis: Analyze the collected data to identify patterns, themes, and insights related to your research question.
• Reporting Findings: Present your findings in a way that communicates the complexity and richness of the case study, often through narrative.

Case Studies in Practice: Real-world Examples

Case studies are not just academic exercises; they have practical applications in every field. For instance, in business, they can explore consumer behavior or organizational strategies. In psychology, they can provide detailed insight into individual behaviors or conditions. Education often uses case studies to explore teaching methods or learning difficulties.

Advantages of Case Study Research

While the case study method has its critics, it offers several undeniable advantages:

• Rich, Detailed Data: It captures data too complex for quantitative methods.
• Contextual Insights: It provides a better understanding of the phenomena in its natural setting.
• Contribution to Theory: It can generate and refine theory, offering a foundation for further research.

Limitations and Criticism

However, it’s important to acknowledge the limitations and criticisms:

• Generalizability : Findings from case studies may not be widely generalizable due to the focus on a single case.
• Subjectivity: The researcher’s perspective may influence the study, which requires careful reflection and transparency.
• Time-Consuming: They require a significant amount of time to conduct and analyze properly.

Concluding Thoughts on the Case Study Method

The case study method is a powerful tool that allows researchers to delve into the intricacies of a subject in its real-world environment. While not without its challenges, when executed correctly, the insights garnered can be incredibly valuable, offering depth and context that other methods may miss. Robert K\. Yin ’s advocacy for this method underscores its potential to illuminate and explain contemporary phenomena, making it an indispensable part of the researcher’s toolkit.

Reflecting on the case study method, how do you think its application could change with the advancements in technology and data analytics? Could such a traditional method be enhanced or even replaced in the future?

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Research Methods in Psychology

1 Introduction to Psychological Research – Objectives and Goals, Problems, Hypothesis and Variables

• Nature of Psychological Research
• The Context of Discovery
• Context of Justification
• Characteristics of Psychological Research
• Goals and Objectives of Psychological Research

2 Introduction to Psychological Experiments and Tests

• Independent and Dependent Variables
• Extraneous Variables
• Experimental and Control Groups
• Introduction of Test
• Types of Psychological Test
• Uses of Psychological Tests

3 Steps in Research

• Research Process
• Identification of the Problem
• Review of Literature
• Formulating a Hypothesis
• Identifying Manipulating and Controlling Variables
• Formulating a Research Design
• Constructing Devices for Observation and Measurement
• Sample Selection and Data Collection
• Data Analysis and Interpretation
• Hypothesis Testing
• Drawing Conclusion

4 Types of Research and Methods of Research

• Historical Research
• Descriptive Research
• Correlational Research
• Qualitative Research
• Ex-Post Facto Research
• True Experimental Research
• Quasi-Experimental Research

5 Definition and Description Research Design, Quality of Research Design

• Research Design
• Purpose of Research Design
• Design Selection
• Criteria of Research Design
• Qualities of Research Design

6 Experimental Design (Control Group Design and Two Factor Design)

• Experimental Design
• Control Group Design
• Two Factor Design

7 Survey Design

• Survey Research Designs
• Steps in Survey Design
• Structuring and Designing the Questionnaire
• Interviewing Methodology
• Data Analysis
• Final Report

8 Single Subject Design

• Single Subject Design: Definition and Meaning
• Phases Within Single Subject Design
• Requirements of Single Subject Design
• Characteristics of Single Subject Design
• Types of Single Subject Design
• Advantages of Single Subject Design
• Disadvantages of Single Subject Design

9 Observation Method

• Definition and Meaning of Observation
• Characteristics of Observation
• Types of Observation
• Advantages and Disadvantages of Observation
• Guides for Observation Method

10 Interview and Interviewing

• Definition of Interview
• Types of Interview
• Aspects of Qualitative Research Interviews
• Interview Questions
• Convergent Interviewing as Action Research
• Research Team

11 Questionnaire Method

• Definition and Description of Questionnaires
• Types of Questionnaires
• Purpose of Questionnaire Studies
• Designing Research Questionnaires
• The Methods to Make a Questionnaire Efficient
• The Types of Questionnaire to be Included in the Questionnaire
• Advantages and Disadvantages of Questionnaire
• When to Use a Questionnaire?

12 Case Study

• Definition and Description of Case Study Method
• Historical Account of Case Study Method
• Designing Case Study
• Requirements for Case Studies
• Guideline to Follow in Case Study Method
• Other Important Measures in Case Study Method
• Case Reports

13 Report Writing

• Purpose of a Report
• Writing Style of the Report
• Report Writing – the Do’s and the Don’ts
• Format for Report in Psychology Area
• Major Sections in a Report

14 Review of Literature

• Purposes of Review of Literature
• Sources of Review of Literature
• Types of Literature
• Writing Process of the Review of Literature
• Preparation of Index Card for Reviewing and Abstracting

15 Methodology

• Definition and Purpose of Methodology
• Participants (Sample)
• Apparatus and Materials

16 Result, Analysis and Discussion of the Data

• Definition and Description of Results
• Statistical Presentation
• Tables and Figures

17 Summary and Conclusion

• Summary Definition and Description
• Guidelines for Writing a Summary
• Writing the Summary and Choosing Words
• A Process for Paraphrasing and Summarising
• Summary of a Report
• Writing Conclusions

18 References in Research Report

• Reference List (the Format)
• References (Process of Writing)
• Reference List and Print Sources
• Electronic Sources
• Book on CD Tape and Movie
• Reference Specifications
• General Guidelines to Write References

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• Perspective
• Published: 22 November 2022

Single case studies are a powerful tool for developing, testing and extending theories

• Lyndsey Nickels   ORCID: orcid.org/0000-0002-0311-3524 1 , 2 ,
• Simon Fischer-Baum   ORCID: orcid.org/0000-0002-6067-0538 3 &
• Wendy Best   ORCID: orcid.org/0000-0001-8375-5916 4  

Nature Reviews Psychology volume  1 ,  pages 733–747 ( 2022 ) Cite this article

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• Neurological disorders

Psychology embraces a diverse range of methodologies. However, most rely on averaging group data to draw conclusions. In this Perspective, we argue that single case methodology is a valuable tool for developing and extending psychological theories. We stress the importance of single case and case series research, drawing on classic and contemporary cases in which cognitive and perceptual deficits provide insights into typical cognitive processes in domains such as memory, delusions, reading and face perception. We unpack the key features of single case methodology, describe its strengths, its value in adjudicating between theories, and outline its benefits for a better understanding of deficits and hence more appropriate interventions. The unique insights that single case studies have provided illustrate the value of in-depth investigation within an individual. Single case methodology has an important place in the psychologist’s toolkit and it should be valued as a primary research tool.

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The authors thank all of those pioneers of and advocates for single case study research who have mentored, inspired and encouraged us over the years, and the many other colleagues with whom we have discussed these issues.

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Nickels, L., Fischer-Baum, S. & Best, W. Single case studies are a powerful tool for developing, testing and extending theories. Nat Rev Psychol 1 , 733–747 (2022). https://doi.org/10.1038/s44159-022-00127-y

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What Is a Case Study in Psychology?

Categories Research Methods

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A case study is a research method used in psychology to investigate a particular individual, group, or situation in depth . It involves a detailed analysis of the subject, gathering information from various sources such as interviews, observations, and documents.

In a case study, researchers aim to understand the complexities and nuances of the subject under investigation. They explore the individual’s thoughts, feelings, behaviors, and experiences to gain insights into specific psychological phenomena. 

This type of research can provide great detail regarding a particular case, allowing researchers to examine rare or unique situations that may not be easily replicated in a laboratory setting. They offer a holistic view of the subject, considering various factors influencing their behavior or mental processes. 

By examining individual cases, researchers can generate hypotheses, develop theories, and contribute to the existing body of knowledge in psychology. Case studies are often utilized in clinical psychology, where they can provide valuable insights into the diagnosis, treatment, and outcomes of specific psychological disorders. 

Case studies offer a comprehensive and in-depth understanding of complex psychological phenomena, providing researchers with valuable information to inform theory, practice, and future research.

Table of Contents

Examples of Case Studies in Psychology

Case studies in psychology provide real-life examples that illustrate psychological concepts and theories. They offer a detailed analysis of specific individuals, groups, or situations, allowing researchers to understand psychological phenomena better. Here are a few examples of case studies in psychology: 

Phineas Gage

This famous case study explores the effects of a traumatic brain injury on personality and behavior. A railroad construction worker, Phineas Gage survived a severe brain injury that dramatically changed his personality.

This case study helped researchers understand the role of the frontal lobe in personality and social behavior. 

Little Albert

Conducted by behaviorist John B. Watson, the Little Albert case study aimed to demonstrate classical conditioning. In this study, a young boy named Albert was conditioned to fear a white rat by pairing it with a loud noise.

This case study provided insights into the process of fear conditioning and the impact of early experiences on behavior. 

Genie’s case study focused on a girl who experienced extreme social isolation and deprivation during her childhood. This study shed light on the critical period for language development and the effects of severe neglect on cognitive and social functioning. 

These case studies highlight the value of in-depth analysis and provide researchers with valuable insights into various psychological phenomena. By examining specific cases, psychologists can uncover unique aspects of human behavior and contribute to the field’s knowledge and understanding.

Types of Case Studies in Psychology

Psychology case studies come in various forms, each serving a specific purpose in research and analysis. Understanding the different types of case studies can help researchers choose the most appropriate approach. 

Descriptive Case Studies

These studies aim to describe a particular individual, group, or situation. Researchers use descriptive case studies to explore and document specific characteristics, behaviors, or experiences.

For example, a descriptive case study may examine the life and experiences of a person with a rare psychological disorder. 

Exploratory Case Studies

Exploratory case studies are conducted when there is limited existing knowledge or understanding of a particular phenomenon. Researchers use these studies to gather preliminary information and generate hypotheses for further investigation.

Exploratory case studies often involve in-depth interviews, observations, and analysis of existing data. 

Explanatory Case Studies

These studies aim to explain the causal relationship between variables or events. Researchers use these studies to understand why certain outcomes occur and to identify the underlying mechanisms or processes.

Explanatory case studies often involve comparing multiple cases to identify common patterns or factors. 

Instrumental Case Studies

Instrumental case studies focus on using a particular case to gain insights into a broader issue or theory. Researchers select cases that are representative or critical in understanding the phenomenon of interest.

Instrumental case studies help researchers develop or refine theories and contribute to the general knowledge in the field. 

By utilizing different types of case studies, psychologists can explore various aspects of human behavior and gain a deeper understanding of psychological phenomena. Each type of case study offers unique advantages and contributes to the overall body of knowledge in psychology.

How to Collect Data for a Case Study

There are a variety of ways that researchers gather the data they need for a case study. Some sources include:

• Directly observing the subject
• Collecting information from archival records
• Conducting interviews
• Examining artifacts related to the subject
• Examining documents that provide information about the subject

The way that this information is collected depends on the nature of the study itself

Prospective Research

In a prospective study, researchers observe the individual or group in question. These observations typically occur over a period of time and may be used to track the progress or progression of a phenomenon or treatment.

Retrospective Research

A retrospective case study involves looking back on a phenomenon. Researchers typically look at the outcome and then gather data to help them understand how the individual or group reached that point.

Benefits of a Case Study

Case studies offer several benefits in the field of psychology. They provide researchers with a unique opportunity to delve deep into specific individuals, groups, or situations, allowing for a comprehensive understanding of complex phenomena.

Case studies offer valuable insights that can inform theory development and practical applications by examining real-life examples. 

Complex Data

One of the key benefits of case studies is their ability to provide complex and detailed data. Researchers can gather in-depth information through various methods such as interviews, observations, and analysis of existing records.

This depth of data allows for a thorough exploration of the factors influencing behavior and the underlying mechanisms at play. 

Unique Data

Additionally, case studies allow researchers to study rare or unique cases that may not be easily replicated in experimental settings. This enables the examination of phenomena that are difficult to study through other psychology research methods . 

By focusing on specific cases, researchers can uncover patterns, identify causal relationships, and generate hypotheses for further investigation.

General Knowledge

Case studies can also contribute to the general knowledge of psychology by providing real-world examples that can be used to support or challenge existing theories. They offer a bridge between theory and practice, allowing researchers to apply theoretical concepts to real-life situations and vice versa. 

Case studies offer a range of benefits in psychology, including providing rich and detailed data, studying unique cases, and contributing to theory development. These benefits make case studies valuable in understanding human behavior and psychological phenomena.

Limitations of a Case Study

While case studies offer numerous benefits in the field of psychology, they also have certain limitations that researchers need to consider. Understanding these limitations is crucial for interpreting the findings and generalizing the results. 

Lack of Generalizability

One limitation of case studies is the issue of generalizability. Since case studies focus on specific individuals, groups, and situations, applying the findings to a larger population can be challenging. The unique characteristics and circumstances of the case may not be representative of the broader population, making it difficult to draw universal conclusions. 

Researcher bias is another possible limitation. The researcher’s subjective interpretation and personal beliefs can influence the data collection, analysis, and interpretation process. This bias can affect the objectivity and reliability of the findings, raising questions about the study’s validity. 

Case studies are often time-consuming and resource-intensive. They require extensive data collection, analysis, and interpretation, which can be lengthy. This can limit the number of cases that can be studied and may result in a smaller sample size, reducing the study’s statistical power. 

Case studies are retrospective in nature, relying on past events and experiences. This reliance on memory and self-reporting can introduce recall bias and inaccuracies in the data. Participants may forget or misinterpret certain details, leading to incomplete or unreliable information.

Despite these limitations, case studies remain a valuable research tool in psychology. By acknowledging and addressing these limitations, researchers can enhance the validity and reliability of their findings, contributing to a more comprehensive understanding of human behavior and psychological phenomena. 

While case studies have limitations, they remain valuable when researchers acknowledge and address these concerns, leading to more reliable and valid findings in psychology.

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Yin, Robert K. Case Study Research and Applications: Design and Methods . United States, SAGE Publications, 2017.

Case Study Research

• First Online: 29 September 2022

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• Robert E. White   ORCID: orcid.org/0000-0002-8045-164X 3 &
• Karyn Cooper 4  

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As a footnote to the previous chapter, there is such a beast known as the ethnographic case study. Ethnographic case study has found its way into this chapter rather than into the previous one because of grammatical considerations. Simply put, the “case study” part of the phrase is the noun (with “case” as an adjective defining what kind of study it is), while the “ethnographic” part of the phrase is an adjective defining the type of case study that is being conducted. As such, the case study becomes the methodology, while the ethnography part refers to a method, mode or approach relating to the development of the study.

The experiential account that we get from a case study or qualitative research of a similar vein is just so necessary. How things happen over time and the degree to which they are subject to personality and how they are only gradually perceived as tolerable or intolerable by the communities and the groups that are involved is so important. Robert Stake, University of Illinois, Urbana-Champaign

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A Case in Case Study Methodology

Christine Benedichte Meyer

Norwegian School of Economics and Business Administration

Meyer, C. B. (2001). A Case in Case Study Methodology. Field Methods 13 (4), 329-352.

The purpose of this article is to provide a comprehensive view of the case study process from the researcher’s perspective, emphasizing methodological considerations. As opposed to other qualitative or quantitative research strategies, such as grounded theory or surveys, there are virtually no specific requirements guiding case research. This is both the strength and the weakness of this approach. It is a strength because it allows tailoring the design and data collection procedures to the research questions. On the other hand, this approach has resulted in many poor case studies, leaving it open to criticism, especially from the quantitative field of research. This article argues that there is a particular need in case studies to be explicit about the methodological choices one makes. This implies discussing the wide range of decisions concerned with design requirements, data collection procedures, data analysis, and validity and reliability. The approach here is to illustrate these decisions through a particular case study of two mergers in the financial industry in Norway.

In the past few years, a number of books have been published that give useful guidance in conducting qualitative studies (Gummesson 1988; Cassell & Symon 1994; Miles & Huberman 1994; Creswell 1998; Flick 1998; Rossman & Rallis 1998; Bryman & Burgess 1999; Marshall & Rossman 1999; Denzin & Lincoln 2000). One approach often mentioned is the case study (Yin 1989). Case studies are widely used in organizational studies in the social science disciplines of sociology, industrial relations, and anthropology (Hartley 1994). Such a study consists of detailed investigation of one or more organizations, or groups within organizations, with a view to providing an analysis of the context and processes involved in the phenomenon under study.

As opposed to other qualitative or quantitative research strategies, such as grounded theory (Glaser and Strauss 1967) or surveys (Nachmias & Nachmias 1981), there are virtually no specific requirements guiding case research. Yin (1989) and Eisenhardt (1989) give useful insights into the case study as a research strategy, but leave most of the design decisions on the table. This is both the strength and the weakness of this approach. It is a strength because it allows tailoring the design and data collection procedures to the research questions. On the other hand, this approach has resulted in many poor case studies, leaving it open to criticism, especially from the quantitative field of research (Cook and Campbell 1979). The fact that the case study is a rather loose design implies that there are a number of choices that need to be addressed in a principled way.

Although case studies have become a common research strategy, the scope of methodology sections in articles published in journals is far too limited to give the readers a detailed and comprehensive view of the decisions taken in the particular studies, and, given the format of methodology sections, will remain so. The few books (Yin 1989, 1993; Hamel, Dufour, & Fortin 1993; Stake 1995) and book chapters on case studies (Hartley 1994; Silverman 2000) are, on the other hand, mainly normative and span a broad range of different kinds of case studies. One exception is Pettigrew (1990, 1992), who places the case study in the context of a research tradition (the Warwick process research).

Given the contextual nature of the case study and its strength in addressing contemporary phenomena in real-life contexts, I believe that there is a need for articles that provide a comprehensive overview of the case study process from the researcher’s perspective, emphasizing methodological considerations. This implies addressing the whole range of choices concerning specific design requirements, data collection procedures, data analysis, and validity and reliability.

WHY A CASE STUDY?

Case studies are tailor-made for exploring new processes or behaviors or ones that are little understood (Hartley 1994). Hence, the approach is particularly useful for responding to how and why questions about a contemporary set of events (Leonard-Barton 1990). Moreover, researchers have argued that certain kinds of information can be difficult or even impossible to tackle by means other than qualitative approaches such as the case study (Sykes 1990). Gummesson (1988:76) argues that an important advantage of case study research is the opportunity for a holistic view of the process: “The detailed observations entailed in the case study method enable us to study many different aspects, examine them in relation to each other, view the process within its total environment and also use the researchers’ capacity for ‘verstehen.’ ”

The contextual nature of the case study is illustrated in Yin’s (1993:59) definition of a case study as an empirical inquiry that “investigates a contemporary phenomenon within its real-life context and addresses a situation in which the boundaries between phenomenon and context are not clearly evident.”

The key difference between the case study and other qualitative designs such as grounded theory and ethnography (Glaser & Strauss 1967; Strauss & Corbin 1990; Gioia & Chittipeddi 1991) is that the case study is open to the use of theory or conceptual categories that guide the research and analysis of data. In contrast, grounded theory or ethnography presupposes that theoretical perspectives are grounded in and emerge from firsthand data. Hartley (1994) argues that without a theoretical framework, the researcher is in severe danger of providing description without meaning. Gummesson (1988) says that a lack of preunderstanding will cause the researcher to spend considerable time gathering basic information. This preunderstanding may arise from general knowledge such as theories, models, and concepts or from specific knowledge of institutional conditions and social patterns. According to Gummesson, the key is not to require researchers to have split but dual personalities: “Those who are able to balance on a razor’s edge using their pre-understanding without being its slave” (p. 58).

DESCRIPTION OF THE ILLUSTRATIVE STUDY

The study that will be used for illustrative purposes is a comparative and longitudinal case study of organizational integration in mergers and acquisitions taking place in Norway. The study had two purposes: (1) to identify contextual factors and features of integration that facilitated or impeded organizational integration, and (2) to study how the three dimensions of organizational integration (integration of tasks, unification of power, and integration of cultures and identities) interrelated and evolved over time. Examples of contextual factors were relative power, degree of friendliness, and economic climate. Integration features included factors such as participation, communication, and allocation of positions and functions.

Mergers and acquisitions are inherently complex. Researchers in the field have suggested that managers continuously underestimate the task of integrating the merging organizations in the postintegration process (Haspeslaph & Jemison 1991). The process of organizational integration can lead to sharp interorganizational conflict as the different top management styles, organizational and work unit cultures, systems, and other aspects of organizational life come into contact (Blake & Mounton 1985; Schweiger & Walsh 1990; Cartwright & Cooper 1993). Furthermore, cultural change in mergers and acquisitions is compounded by additional uncertainties, ambiguities, and stress inherent in the combination process (Buono & Bowditch 1989).

I focused on two combinations: one merger and one acquisition. The first case was a merger between two major Norwegian banks, Bergen Bank and DnC (to be named DnB), that started in the late 1980s. The second case was a study of a major acquisition in the insurance industry (i.e., Gjensidige’s acquisition of Forenede), that started in the early 1990s. Both combinations aimed to realize operational synergies though merging the two organizations into one entity. This implied disruption of organizational boundaries and threat to the existing power distribution and organizational cultures.

The study of integration processes in mergers and acquisitions illustrates the need to find a design that opens for exploration of sensitive issues such as power struggles between the two merging organizations. Furthermore, the inherent complexity in the integration process, involving integration of tasks, unification of power, and cultural integration stressed the need for in-depth study of the phenomenon over time. To understand the cultural integration process, the design also had to be linked to the past history of the two organizations.

DESIGN DECISIONS

In the introduction, I stressed that a case is a rather loose design that requires that a number of design choices be made. In this section, I go through the most important choices I faced in the study of organizational integration in mergers and acquisitions. These include: (1) selection of cases; (2) sampling time; (3) choosing business areas, divisions, and sites; and (4) selection of and choices regarding data collection procedures, interviews, documents, and observation.

Selection of Cases

There are several choices involved in selecting cases. First, there is the question of how many cases to include. Second, one must sample cases and decide on a unit of analysis. I will explore these issues subsequently.

Single or Multiple Cases

Case studies can involve single or multiple cases. The problem of single cases is limitations in generalizability and several information-processing biases (Eisenhardt 1989).

One way to respond to these biases is by applying a multi-case approach (Leonard-Barton 1990). Multiple cases augment external validity and help guard against observer biases. Moreover, multi-case sampling adds confidence to findings. By looking at a range of similar and contrasting cases, we can understand a single-case finding, grounding it by specifying how and where and, if possible, why it behaves as it does. (Miles & Huberman 1994)

Given these limitations of the single case study, it is desirable to include more than one case study in the study. However, the desire for depth and a pluralist perspective and tracking the cases over time implies that the number of cases must be fairly few. I chose two cases, which clearly does not support generalizability any more than does one case, but allows for comparison and contrast between the cases as well as a deeper and richer look at each case.

Originally, I planned to include a third case in the study. Due to changes in management during the initial integration process, my access to the case was limited and I left this case entirely. However, a positive side effect was that it allowed a deeper investigation of the two original cases and in hindsight turned out to be a good decision.

Sampling Cases

The logic of sampling cases is fundamentally different from statistical sampling. The logic in case studies involves theoretical sampling, in which the goal is to choose cases that are likely to replicate or extend the emergent theory or to fill theoretical categories and provide examples for polar types (Eisenhardt 1989). Hence, whereas quantitative sampling concerns itself with representativeness, qualitative sampling seeks information richness and selects the cases purposefully rather than randomly (Crabtree and Miller 1992).

The choice of cases was guided by George (1979) and Pettigrew’s (1990) recommendations. The aim was to find cases that matched the three dimensions in the dependent variable and provided variation in the contextual factors, thus representing polar cases.

To match the choice of outcome variable, organizational integration, I chose cases in which the purpose was to fully consolidate the merging parties’ operations. A full consolidation would imply considerable disruption in the organizational boundaries and would be expected to affect the task-related, political, and cultural features of the organizations. As for the contextual factors, the two cases varied in contextual factors such as relative power, friendliness, and economic climate. The DnB merger was a friendly combination between two equal partners in an unfriendly economic climate. Gjensidige’s acquisition of Forenede was, in contrast, an unfriendly and unbalanced acquisition in a friendly economic climate.

Unit of Analysis

Another way to respond to researchers’ and respondents’ biases is to have more than one unit of analysis in each case (Yin 1993). This implies that, in addition to developing contrasts between the cases, researchers can focus on contrasts within the cases (Hartley 1994). In case studies, there is a choice of a holistic or embedded design (Yin 1989). A holistic design examines the global nature of the phenomenon, whereas an embedded design also pays attention to subunit(s).

I used an embedded design to analyze the cases (i.e., within each case, I also gave attention to subunits and subprocesses). In both cases, I compared the combination processes in the various divisions and local networks. Moreover, I compared three distinct change processes in DnB: before the merger, during the initial combination, and two years after the merger. The overall and most important unit of analysis in the two cases was, however, the integration process.

Sampling Time

According to Pettigrew (1990), time sets a reference for what changes can be seen and how those changes are explained. When conducting a case study, there are several important issues to decide when sampling time. The first regards how many times data should be collected, while the second concerns when to enter the organizations. There is also a need to decide whether to collect data on a continuous basis or in distinct periods.

Number of data collections. I studied the process by collecting real time and retrospective data at two points in time, with one-and-a-half- and two-year intervals in the two cases. Collecting data twice had some interesting implications for the interpretations of the data. During the first data collection in the DnB study, for example, I collected retrospective data about the premerger and initial combination phase and real-time data about the second step in the combination process.

Although I gained a picture of how the employees experienced the second stage of the combination process, it was too early to assess the effects of this process at that stage. I entered the organization two years later and found interesting effects that I had not anticipated the first time. Moreover, it was interesting to observe how people’s attitudes toward the merger processes changed over time to be more positive and less emotional.

When to enter the organizations. It would be desirable to have had the opportunity to collect data in the precombination processes. However, researchers are rarely given access in this period due to secrecy. The emphasis in this study was to focus on the postcombination process. As such, the precombination events were classified as contextual factors. This implied that it was most important to collect real-time data after the parties had been given government approval to merge or acquire. What would have been desirable was to gain access earlier in the postcombination process. This was not possible because access had to be negotiated. Due to the change of CEO in the middle of the merger process and the need for renegotiating access, this took longer than expected.

Regarding the second case, I was restricted by the time frame of the study. In essence, I had to choose between entering the combination process as soon as governmental approval was given, or entering the organization at a later stage. In light of the previous studies in the field that have failed to go beyond the initial two years, and given the need to collect data about the cultural integration process, I chose the latter strategy. And I decided to enter the organizations at two distinct periods of time rather than on a continuous basis.

There were several reasons for this approach, some methodological and some practical. First, data collection on a continuous basis would have required use of extensive observation that I didn’t have access to, and getting access to two data collections in DnB was difficult in itself. Second, I had a stay abroad between the first and second data collection in Gjensidige. Collecting data on a continuous basis would probably have allowed for better mapping of the ongoing integration process, but the contrasts between the two different stages in the integration process that I wanted to elaborate would probably be more difficult to detect. In Table 1 I have listed the periods of time in which I collected data in the two combinations.

Sampling Business Areas, Divisions, and Sites

Even when the cases for a study have been chosen, it is often necessary to make further choices within each case to make the cases researchable. The most important criteria that set the boundaries for the study are importance or criticality, relevance, and representativeness. At the time of the data collection, my criteria for making these decisions were not as conscious as they may appear here. Rather, being restricted by time and my own capacity as a researcher, I had to limit the sites and act instinctively. In both cases, I decided to concentrate on the core businesses (criticality criterion) and left out the business units that were only mildly affected by the integration process (relevance criterion). In the choice of regional offices, I used the representativeness criterion as the number of offices widely exceeded the number of sites possible to study. In making these choices, I relied on key informants in the organizations.

SELECTION OF DATA COLLECTION PROCEDURES

The choice of data collection procedures should be guided by the research question and the choice of design. The case study approach typically combines data collection methods such as archives, interviews, questionnaires, and observations (Yin 1989). This triangulated methodology provides stronger substantiation of constructs and hypotheses. However, the choice of data collection methods is also subject to constraints in time, financial resources, and access.

I chose a combination of interviews, archives, and observation, with main emphasis on the first two. Conducting a survey was inappropriate due to the lack of established concepts and indicators. The reason for limited observation, on the other hand, was due to problems in obtaining access early in the study and time and resource constraints. In addition to choosing among several different data collection methods, there are a number of choices to be made for each individual method.

When relying on interviews as the primary data collection method, the issue of building trust between the researcher and the interviewees becomes very important. I addressed this issue by several means. First, I established a procedure of how to approach the interviewees. In most cases, I called them first, then sent out a letter explaining the key features of the project and outlining the broad issues to be addressed in the interview. In this letter, the support from the institution’s top management was also communicated. In most cases, the top management’s support of the project was an important prerequisite for the respondent’s input. Some interviewees did, however, fear that their input would be open to the top management without disguising the information source. Hence, it became important to communicate how I intended to use and store the information.

To establish trust, I also actively used my preunderstanding of the context in the first case and the phenomenon in the second case. As I built up an understanding of the cases, I used this information to gain confidence. The active use of my preunderstanding did, however, pose important challenges in not revealing too much of the research hypotheses and in balancing between asking open-ended questions and appearing knowledgeable.

There are two choices involved in conducting interviews. The first concerns the sampling of interviewees. The second is that you must decide on issues such as the structure of the interviews, use of tape recorder, and involvement of other researchers.

Sampling Interviewees

Following the desire for detailed knowledge of each case and for grasping different participant’s views the aim was, in line with Pettigrew (1990), to apply a pluralist view by describing and analyzing competing versions of reality as seen by actors in the combination processes.

I used four criteria for sampling informants. First, I drew informants from populations representing multiple perspectives. The first data collection in DnB was primarily focused on the top management level. Moreover, most middle managers in the first data collection were employed at the head offices, either in Bergen or Oslo. In the second data collection, I compensated for this skew by including eight local middle managers in the sample. The difference between the number of employees interviewed in DnB and Gjensidige was primarily due to the fact that Gjensidige has three unions, whereas DnB only has one. The distribution of interviewees is outlined in Table 2 .

The second criterion was to use multiple informants. According to Glick et al. (1990), an important advantage of using multiple informants is that the validity of information provided by one informant can be checked against that provided by other informants. Moreover, the validity of the data used by the researcher can be enhanced by resolving the discrepancies among different informants’ reports. Hence, I selected multiple respondents from each perspective.

Third, I focused on key informants who were expected to be knowledgeable about the combination process. These people included top management members, managers, and employees involved in the integration project. To validate the information from these informants, I also used a fourth criterion by selecting managers and employees who had been affected by the process but who were not involved in the project groups.

Structured versus unstructured. In line with the explorative nature of the study, the goal of the interviews was to see the research topic from the perspective of the interviewee, and to understand why he or she came to have this particular perspective. To meet this goal, King (1994:15) recommends that one have “a low degree of structure imposed on the interviewer, a preponderance of open questions, a focus on specific situations and action sequences in the world of the interviewee rather than abstractions and general opinions.” In line with these recommendations, the collection of primary data in this study consists of unstructured interviews.

Using tape recorders and involving other researchers. The majority of the interviews were tape-recorded, and I could thus concentrate fully on asking questions and responding to the interviewees’ answers. In the few interviews that were not tape-recorded, most of which were conducted in the first phase of the DnB-study, two researchers were present. This was useful as we were both able to discuss the interviews later and had feedback on the role of an interviewer.

In hindsight, however, I wish that these interviews had been tape-recorded to maintain the level of accuracy and richness of data. Hence, in the next phases of data collection, I tape-recorded all interviews, with two exceptions (people who strongly opposed the use of this device). All interviews that were tape-recorded were transcribed by me in full, which gave me closeness and a good grasp of the data.

When organizations merge or make acquisitions, there are often a vast number of documents to choose from to build up an understanding of what has happened and to use in the analyses. Furthermore, when firms make acquisitions or merge, they often hire external consultants, each of whom produces more documents. Due to time constraints, it is seldom possible to collect and analyze all these documents, and thus the researcher has to make a selection.

The choice of documentation was guided by my previous experience with merger and acquisition processes and the research question. Hence, obtaining information on the postintegration process was more important than gaining access to the due-diligence analysis. As I learned about the process, I obtained more documents on specific issues. I did not, however, gain access to all the documents I asked for, and, in some cases, documents had been lost or shredded.

The documents were helpful in a number of ways. First, and most important, they were used as inputs to the interview guide and saved me time, because I did not have to ask for facts in the interviews. They were also useful for tracing the history of the organizations and statements made by key people in the organizations. Third, the documents were helpful in counteracting the biases of the interviews. A list of the documents used in writing the cases is shown in Table 3 .

Observation

The major strength of direct observation is that it is unobtrusive and does not require direct interaction with participants (Adler and Adler 1994). Observation produces rigor when it is combined with other methods. When the researcher has access to group processes, direct observation can illuminate the discrepancies between what people said in the interviews and casual conversations and what they actually do (Pettigrew 1990).

As with interviews, there are a number of choices involved in conducting observations. Although I did some observations in the study, I used interviews as the key data collection source. Discussion in this article about observations will thus be somewhat limited. Nevertheless, I faced a number of choices in conducting observations, including type of observation, when to enter, how much observation to conduct, and which groups to observe.

The are four ways in which an observer may gather data: (1) the complete participant who operates covertly, concealing any intention to observe the setting; (2) the participant-as-observer, who forms relationships and participates in activities, but makes no secret of his or her intentions to observe events; (3) the observer-as-participant, who maintains only superficial contact with the people being studied; and (4) the complete observer, who merely stands back and eavesdrops on the proceedings (Waddington 1994).

In this study, I used the second and third ways of observing. The use of the participant-as-observer mode, on which much ethnographic research is based, was rather limited in the study. There were two reasons for this. First, I had limited time available for collecting data, and in my view interviews made more effective use of this limited time than extensive participant observation. Second, people were rather reluctant to let me observe these political and sensitive processes until they knew me better and felt I could be trusted. Indeed, I was dependent on starting the data collection before having built sufficient trust to observe key groups in the integration process. Nevertheless, Gjensidige allowed me to study two employee seminars to acquaint me with the organization. Here I admitted my role as an observer but participated fully in the activities. To achieve variation, I chose two seminars representing polar groups of employees.

As observer-as-participant, I attended a top management meeting at the end of the first data collection in Gjensidige and observed the respondents during interviews and in more informal meetings, such as lunches. All these observations gave me an opportunity to validate the data from the interviews. Observing the top management group was by far the most interesting and rewarding in terms of input.

Both DnB and Gjensidige started to open up for more extensive observation when I was about to finish the data collection. By then, I had built up the trust needed to undertake this approach. Unfortunately, this came a little late for me to take advantage of it.

DATA ANALYSIS

Published studies generally describe research sites and data-collection methods, but give little space to discuss the analysis (Eisenhardt 1989). Thus, one cannot follow how a researcher arrives at the final conclusions from a large volume of field notes (Miles and Huberman 1994).

In this study, I went through the stages by which the data were reduced and analyzed. This involved establishing the chronology, coding, writing up the data according to phases and themes, introducing organizational integration into the analysis, comparing the cases, and applying the theory. I will discuss these phases accordingly.

The first step in the analysis was to establish the chronology of the cases. To do this, I used internal and external documents. I wrote the chronologies up and included appendices in the final report.

The next step was to code the data into phases and themes reflecting the contextual factors and features of integration. For the interviews, this implied marking the text with a specific phase and a theme, and grouping the paragraphs on the same theme and phase together. I followed the same procedure in organizing the documents.

I then wrote up the cases using phases and themes to structure them. Before starting to write up the cases, I scanned the information on each theme, built up the facts and filled in with perceptions and reactions that were illustrative and representative of the data.

The documents were primarily useful in establishing the facts, but they also provided me with some perceptions and reactions that were validated in the interviews. The documents used included internal letters and newsletters as well as articles from the press. The interviews were less factual, as intended, and gave me input to assess perceptions and reactions. The limited observation was useful to validate the data from the interviews. The result of this step was two descriptive cases.

To make each case more analytical, I introduced the three dimensions of organizational integration—integration of tasks, unification of power, and cultural integration—into the analysis. This helped to focus the case and to develop a framework that could be used to compare the cases. The cases were thus structured according to phases, organizational integration, and themes reflecting the factors and features in the study.

I took all these steps to become more familiar with each case as an individual entity. According to Eisenhardt (1989:540), this is a process that “allows the unique patterns of each case to emerge before the investigators push to generalise patterns across cases. In addition it gives investigators a rich familiarity with each case which, in turn, accelerates cross-case comparison.”

The comparison between the cases constituted the next step in the analysis. Here, I used the categories from the case chapters, filled in the features and factors, and compared and contrasted the findings. The idea behind cross-case searching tactics is to force investigators to go beyond initial impressions, especially through the use of structural and diverse lenses on the data. These tactics improve the likelihood of accurate and reliable theory, that is, theory with a close fit to the data (Eisenhardt 1989).

As a result, I had a number of overall themes, concepts, and relationships that had emerged from the within-case analysis and cross-case comparisons. The next step was to compare these emergent findings with theory from the organizational field of mergers and acquisitions, as well as other relevant perspectives.

This method of generalization is known as analytical generalization. In this approach, a previously developed theory is used as a template with which to compare the empirical results of the case study (Yin 1989). This comparison of emergent concepts, theory, or hypotheses with the extant literature involves asking what it is similar to, what it contradicts, and why. The key to this process is to consider a broad range of theory (Eisenhardt 1989). On the whole, linking emergent theory to existent literature enhances the internal validity, generalizability, and theoretical level of theory-building from case research.

According to Eisenhardt (1989), examining literature that conflicts with the emergent literature is important for two reasons. First, the chance of neglecting conflicting findings is reduced. Second, “conflicting results forces researchers into a more creative, frame-breaking mode of thinking than they might otherwise be able to achieve” (p. 544). Similarly, Eisenhardt (1989) claims that literature discussing similar findings is important because it ties together underlying similarities in phenomena not normally associated with each other. The result is often a theory with a stronger internal validity, wider generalizability, and a higher conceptual level.

The analytical generalization in the study included exploring and developing the concepts and examining the relationships between the constructs. In carrying out this analytical generalization, I acted on Eisenhardt’s (1989) recommendation to use a broad range of theory. First, I compared and contrasted the findings with the organizational stream on mergers and acquisition literature. Then I discussed other relevant literatures, including strategic change, power and politics, social justice, and social identity theory to explore how these perspectives could contribute to the understanding of the findings. Finally, I discussed the findings that could not be explained either by the merger and acquisition literature or the four theoretical perspectives.

In every scientific study, questions are raised about whether the study is valid and reliable. The issues of validity and reliability in case studies are just as important as for more deductive designs, but the application is fundamentally different.

VALIDITY AND RELIABILITY

The problems of validity in qualitative studies are related to the fact that most qualitative researchers work alone in the field, they focus on the findings rather than describe how the results were reached, and they are limited in processing information (Miles and Huberman 1994).

Researchers writing about qualitative methods have questioned whether the same criteria can be used for qualitative and quantitative studies (Kirk & Miller 1986; Sykes 1990; Maxwell 1992). The problem with the validity criteria suggested in qualitative research is that there is little consistency across the articles as each author suggests a new set of criteria.

One approach in examining validity and reliability is to apply the criteria used in quantitative research. Hence, the criteria to be examined here are objectivity/intersubjectivity, construct validity, internal validity, external validity, and reliability.

Objectivity/Intersubjectivity

The basic issue of objectivity can be framed as one of relative neutrality and reasonable freedom from unacknowledged research biases (Miles & Huberman 1994). In a real-time longitudinal study, the researcher is in danger of losing objectivity and of becoming too involved with the organization, the people, and the process. Hence, Leonard-Barton (1990) claims that one may be perceived as, and may even become, an advocate rather than an observer.

According to King (1994), however, qualitative research, in seeking to describe and make sense of the world, does not require researchers to strive for objectivity and distance themselves from research participants. Indeed, to do so would make good qualitative research impossible, as the interviewer’s sensitivity to subjective aspects of his or her relationship with the interviewee is an essential part of the research process (King 1994:31).

This does not imply, however, that the issue of possible research bias can be ignored. It is just as important as in a structured quantitative interview that the findings are not simply the product of the researcher’s prejudices and prior experience. One way to guard against this bias is for the researcher to explicitly recognize his or her presuppositions and to make a conscious effort to set these aside in the analysis (Gummesson 1988). Furthermore, rival conclusions should be considered (Miles & Huberman 1994).

My experience from the first phase of the DnB study was that it was difficult to focus the questions and the analysis of the data when the research questions were too vague and broad. As such, developing a framework before collecting the data for the study was useful in guiding the collection and analysis of data. Nevertheless, it was important to be open-minded and receptive to new and surprising data. In the DnB study, for example, the positive effect of the reorganization process on the integration of cultures came as a complete surprise to me and thus needed further elaboration.

I also consciously searched for negative evidence and problems by interviewing outliers (Miles & Huberman 1994) and asking problem-oriented questions. In Gjensidige, the first interviews with the top management revealed a much more positive perception of the cultural integration process than I had expected. To explore whether this was a result of overreliance on elite informants, I continued posing problem-oriented questions to outliers and people at lower levels in the organization. Moreover, I told them about the DnB study to be explicit about my presuppositions.

Another important issue when assessing objectivity is whether other researchers can trace the interpretations made in the case studies, or what is called intersubjectivity. To deal with this issue, Miles & Huberman (1994) suggest that: (1) the study’s general methods and procedures should be described in detail, (2) one should be able to follow the process of analysis, (3) conclusions should be explicitly linked with exhibits of displayed data, and (4) the data from the study should be made available for reanalysis by others.

In response to these requirements, I described the study’s data collection procedures and processing in detail. Then, the primary data were displayed in the written report in the form of quotations and extracts from documents to support and illustrate the interpretations of the data. Because the study was written up in English, I included the Norwegian text in a separate appendix. Finally, all the primary data from the study were accessible for a small group of distinguished researchers.

Construct Validity

Construct validity refers to whether there is substantial evidence that the theoretical paradigm correctly corresponds to observation (Kirk & Miller 1986). In this form of validity, the issue is the legitimacy of the application of a given concept or theory to established facts.

The strength of qualitative research lies in the flexible and responsive interaction between the interviewer and the respondents (Sykes 1990). Thus, meaning can be probed, topics covered easily from a number of angles, and questions made clear for respondents. This is an advantage for exploring the concepts (construct or theoretical validity) and the relationships between them (internal validity). Similarly, Hakim (1987) says the great strength of qualitative research is the validity of data obtained because individuals are interviewed in sufficient detail for the results to be taken as true, correct, and believable reports of their views and experiences.

Construct validity can be strengthened by applying a longitudinal multicase approach, triangulation, and use of feedback loops. The advantage of applying a longitudinal approach is that one gets the opportunity to test sensitivity of construct measures to the passage of time. Leonard-Barton (1990), for example, found that one of her main constructs, communicability, varied across time and relative to different groups of users. Thus, the longitudinal study aided in defining the construct more precisely. By using more than one case study, one can validate stability of construct across situations (Leonard-Barton 1990). Since my study only consists of two case studies, the opportunity to test stability of constructs across cases is somewhat limited. However, the use of more than one unit of analysis helps to overcome this limitation.

Construct validity is strengthened by the use of multiple sources of evidence to build construct measures, which define the construct and distinguish it from other constructs. These multiple sources of evidence can include multiple viewpoints within and across the data sources. My study responds to these requirements in its sampling of interviewees and uses of multiple data sources.

Use of feedback loops implies returning to interviewees with interpretations and developing theory and actively seeking contradictions in data (Crabtree & Miller 1992; King 1994). In DnB, the written report had to be approved by the bank’s top management after the first data collection. Apart from one minor correction, the bank had no objections to the established facts. In their comments on my analysis, some of the top managers expressed the view that the political process had been overemphasized, and that the CEO’s role in initiating a strategic process was undervalued. Hence, an important objective in the second data collection was to explore these comments further. Moreover, the report was not as positive as the management had hoped for, and negotiations had to be conducted to publish the report. The result of these negotiations was that publication of the report was postponed one-and-a-half years.

The experiences from the first data collection in the DnB had some consequences. I was more cautious and brought up the problems of confidentiality and the need to publish at the outset of the Gjensidige study. Also, I had to struggle to get access to the DnB case for the second data collection and some of the information I asked for was not released. At Gjensidige, I sent a preliminary draft of the case chapter to the corporation’s top management for comments, in addition to having second interviews with a small number of people. Beside testing out the factual description, these sessions gave me the opportunity to test out the theoretical categories established as a result of the within-case analysis.

Internal Validity

Internal validity concerns the validity of the postulated relationships among the concepts. The main problem of internal validity as a criterion in qualitative research is that it is often not open to scrutiny. According to Sykes (1990), the researcher can always provide a plausible account and, with careful editing, may ensure its coherence. Recognition of this problem has led to calls for better documentation of the processes of data collection, the data itself, and the interpretative contribution of the researcher. The discussion of how I met these requirements was outlined in the section on objectivity/subjectivity above.

However, there are some advantages in using qualitative methods, too. First, the flexible and responsive methods of data collection allow cross-checking and amplification of information from individual units as it is generated. Respondents’ opinions and understandings can be thoroughly explored. The internal validity results from strategies that eliminate ambiguity and contradiction, filling in detail and establishing strong connections in data.

Second, the longitudinal study enables one to track cause and effect. Moreover, it can make one aware of intervening variables (Leonard-Barton 1990). Eisenhardt (1989:542) states, “Just as hypothesis testing research an apparent relationship may simply be a spurious correlation or may reflect the impact of some third variable on each of the other two. Therefore, it is important to discover the underlying reasons for why the relationship exists.”

Generalizability

According to Mitchell (1983), case studies are not based on statistical inference. Quite the contrary, the inferring process turns exclusively on the theoretically necessary links among the features in the case study. The validity of the extrapolation depends not on the typicality or representativeness of the case but on the cogency of the theoretical reasoning. Hartley (1994:225) claims, “The detailed knowledge of the organization and especially the knowledge about the processes underlying the behaviour and its context can help to specify the conditions under which behaviour can be expected to occur. In other words, the generalisation is about theoretical propositions not about populations.”

Generalizability is normally based on the assumption that this theory may be useful in making sense of similar persons or situations (Maxwell 1992). One way to increase the generalizability is to apply a multicase approach (Leonard-Barton 1990). The advantage of this approach is that one can replicate the findings from one case study to another. This replication logic is similar to that used on multiple experiments (Yin 1993).

Given the choice of two case studies, the generalizability criterion is not supported in this study. Through the discussion of my choices, I have tried to show that I had to strike a balance between the need for depth and mapping changes over time and the number of cases. In doing so, I deliberately chose to provide a deeper and richer look at each case, allowing the reader to make judgments about the applicability rather than making a case for generalizability.

Reliability

Reliability focuses on whether the process of the study is consistent and reasonably stable over time and across researchers and methods (Miles & Huberman 1994). In the context of qualitative research, reliability is concerned with two questions (Sykes 1990): Could the same study carried out by two researchers produce the same findings? and Could a study be repeated using the same researcher and respondents to yield the same findings?

The problem of reliability in qualitative research is that differences between replicated studies using different researchers are to be expected. However, while it may not be surprising that different researchers generate different findings and reach different conclusions, controlling for reliability may still be relevant. Kirk and Miller’s (1986:311) definition takes into account the particular relationship between the researcher’s orientation, the generation of data, and its interpretation:

For reliability to be calculated, it is incumbent on the scientific investigator to document his or her procedure. This must be accomplished at such a level of abstraction that the loci of decisions internal to the project are made apparent. The curious public deserves to know how the qualitative researcher prepares him or herself for the endeavour, and how the data is collected and analysed.

The study addresses these requirements by discussing my point of departure regarding experience and framework, the sampling and data collection procedures, and data analysis.

Case studies often lack academic rigor and are, as such, regarded as inferior to more rigorous methods where there are more specific guidelines for collecting and analyzing data. These criticisms stress that there is a need to be very explicit about the choices one makes and the need to justify them.

One reason why case studies are criticized may be that researchers disagree about the definition and the purpose of carrying out case studies. Case studies have been regarded as a design (Cook and Campbell 1979), as a qualitative methodology (Cassell and Symon 1994), as a particular data collection procedure (Andersen 1997), and as a research strategy (Yin 1989). Furthermore, the purpose for carrying out case studies is unclear. Some regard case studies as supplements to more rigorous qualitative studies to be carried out in the early stage of the research process; others claim that it can be used for multiple purposes and as a research strategy in its own right (Gummesson 1988; Yin 1989). Given this unclear status, researchers need to be very clear about their interpretation of the case study and the purpose of carrying out the study.

This article has taken Yin’s (1989) definition of the case study as a research strategy as a starting point and argued that the choice of the case study should be guided by the research question(s). In the illustrative study, I used a case study strategy because of a need to explore sensitive, ill-defined concepts in depth, over time, taking into account the context and history of the mergers and the existing knowledge about the phenomenon. However, the choice of a case study strategy extended rather than limited the number of decisions to be made. In Schramm’s (1971, cited in Yin 1989:22–23) words, “The essence of a case study, the central tendency among all types of case study, is that it tries to illuminate a decision or set of decisions, why they were taken, how they were implemented, and with what result.”

Hence, the purpose of this article has been to illustrate the wide range of decisions that need to be made in the context of a particular case study and to discuss the methodological considerations linked to these decisions. I argue that there is a particular need in case studies to be explicit about the methodological choices one makes and that these choices can be best illustrated through a case study of the case study strategy.

As in all case studies, however, there are limitations to the generalizability of using one particular case study for illustrative purposes. As such, the strength of linking the methodological considerations to a specific context and phenomenon also becomes a weakness. However, I would argue that the questions raised in this article are applicable to many case studies, but that the answers are very likely to vary. The design choices are shown in Table 4 . Hence, researchers choosing a longitudinal, comparative case study need to address the same set of questions with regard to design, data collection procedures, and analysis, but they are likely to come up with other conclusions, given their different research questions.

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Christine Benedichte Meyer is an associate professor in the Department of Strategy and Management in the Norwegian School of Economics and Business Administration, Bergen-Sandviken, Norway. Her research interests are mergers and acquisitions, strategic change, and qualitative research. Recent publications include: “Allocation Processes in Mergers and Acquisitions: An Organisational Justice Perspective” (British Journal of Management 2001) and “Motives for Acquisitions in the Norwegian Financial Industry” (CEMS Business Review 1997).

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White, R.E., Cooper, K. (2022). Case Study Research. In: Qualitative Research in the Post-Modern Era. Springer, Cham. https://doi.org/10.1007/978-3-030-85124-8_7

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Common Methodologies in GSEP Research

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Common Methodologies found in Graduate Psych Research

Welcome, 

This guide aims to provide an overview of various research methodologies most frequently encountered in graduate psychology research studies.

Methodologies

1. Experimental Methodology:

The experimental method involves manipulating one variable (independent variable) to observe the effect it has on another variable (dependent variable), while controlling for extraneous variables. It is used to establish cause-and-effect relationships between variables in controlled laboratory settings.

Key Concepts: Randomization, Control Group, Experimental Group, Internal Validity.

2. Survey Methodology:

Description: Surveys involve collecting data from a sample of individuals through questionnaires or interviews, with the aim of generalizing the findings to a larger population. It is commonly used in psychology to gather information on attitudes, behaviors, and opinions from diverse populations.

Key Concepts: Sampling Techniques, Questionnaire Design, Reliability, Validity.

3. Observational Methodology:

Description: Observational studies involve systematically observing and recording behavior in naturalistic settings without intervening or manipulating variables. This method is used to study behavior in real-world contexts, offering insights into naturally occurring phenomena.

Key Concepts: Participant Observation, Non-Participant Observation, Ethnography, Observer Bias.

4. Case Study Methodology:

Description: Case studies involve in-depth examination of a single individual, group, or phenomenon, utilizing various data sources such as interviews, observations, and archival records. Case studies are valuable for exploring complex or rare phenomena in-depth, providing detailed insights into specific cases.

Key Concepts: Rich Description, Longitudinal Analysis, Generalization.

5. Correlational Methodology:

Description: Correlational studies examine the relationship between two or more variables without manipulating them, focusing on the extent and direction of their association. This method identifies patterns and associations between variables, informing predictions and further research directions.

Key Concepts: Correlation Coefficient, Directionality, Third Variable Problem.

6. Qualitative Methodology:

Description: Qualitative research focuses on understanding and interpreting subjective experiences, meanings, and social processes through methods such as interviews, focus groups, and textual analysis. The qualitative method provides nuanced insights into individuals' perspectives, cultural contexts, and social phenomena, often used in exploratory or theory-building research.

Key Concepts: Thematic Analysis, Grounded Theory, Reflexivity, Saturation.

7. Mixed Methods:

Description: Mixed methods research combines qualitative and quantitative approaches within a single study, allowing researchers to triangulate findings, enhance validity, and gain comprehensive understanding. Mixed methods offer the flexibility to address complex research questions by leveraging the strengths of both qualitative and quantitative methodologies.

Key Concepts: Integration, Sequential Design, Convergence, Expansion.

8. Quantitative Methodology:

Description: Quantitative research involves collecting and analyzing numerical data to test hypotheses, identify patterns, and quantify relationships between variables using statistical techniques. This method is widely used in psychology to investigate relationships, trends, and causal effects through numerical data analysis.

Key Concepts: Hypothesis Testing, Descriptive Statistics, Inferential Statistics, Measurement Scales.

9. Longitudinal Methodology:

Description: Longitudinal studies involve collecting data from the same participants over an extended period, allowing researchers to observe changes and trajectories of variables over time. Longitudinal studies are used to investigate developmental processes, life transitions, and long-term effects of interventions or treatments in psychology.

Key Concepts: Panel Designs, Cohort Studies, Attrition, Retention Strategies. 

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Research Methods In Psychology

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

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Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Research methods in psychology are systematic procedures used to observe, describe, predict, and explain behavior and mental processes. They include experiments, surveys, case studies, and naturalistic observations, ensuring data collection is objective and reliable to understand and explain psychological phenomena.

Hypotheses are statements about the prediction of the results, that can be verified or disproved by some investigation.

There are four types of hypotheses :

• Null Hypotheses (H0 ) – these predict that no difference will be found in the results between the conditions. Typically these are written ‘There will be no difference…’
• Alternative Hypotheses (Ha or H1) – these predict that there will be a significant difference in the results between the two conditions. This is also known as the experimental hypothesis.
• One-tailed (directional) hypotheses – these state the specific direction the researcher expects the results to move in, e.g. higher, lower, more, less. In a correlation study, the predicted direction of the correlation can be either positive or negative.
• Two-tailed (non-directional) hypotheses – these state that a difference will be found between the conditions of the independent variable but does not state the direction of a difference or relationship. Typically these are always written ‘There will be a difference ….’

All research has an alternative hypothesis (either a one-tailed or two-tailed) and a corresponding null hypothesis.

Once the research is conducted and results are found, psychologists must accept one hypothesis and reject the other. 

So, if a difference is found, the Psychologist would accept the alternative hypothesis and reject the null.  The opposite applies if no difference is found.

Sampling techniques

Sampling is the process of selecting a representative group from the population under study.

A sample is the participants you select from a target population (the group you are interested in) to make generalizations about.

Representative means the extent to which a sample mirrors a researcher’s target population and reflects its characteristics.

Generalisability means the extent to which their findings can be applied to the larger population of which their sample was a part.

• Volunteer sample : where participants pick themselves through newspaper adverts, noticeboards or online.
• Opportunity sampling : also known as convenience sampling , uses people who are available at the time the study is carried out and willing to take part. It is based on convenience.
• Random sampling : when every person in the target population has an equal chance of being selected. An example of random sampling would be picking names out of a hat.
• Systematic sampling : when a system is used to select participants. Picking every Nth person from all possible participants. N = the number of people in the research population / the number of people needed for the sample.
• Stratified sampling : when you identify the subgroups and select participants in proportion to their occurrences.
• Snowball sampling : when researchers find a few participants, and then ask them to find participants themselves and so on.
• Quota sampling : when researchers will be told to ensure the sample fits certain quotas, for example they might be told to find 90 participants, with 30 of them being unemployed.

Experiments always have an independent and dependent variable .

• The independent variable is the one the experimenter manipulates (the thing that changes between the conditions the participants are placed into). It is assumed to have a direct effect on the dependent variable.
• The dependent variable is the thing being measured, or the results of the experiment.

Operationalization of variables means making them measurable/quantifiable. We must use operationalization to ensure that variables are in a form that can be easily tested.

For instance, we can’t really measure ‘happiness’, but we can measure how many times a person smiles within a two-hour period. 

By operationalizing variables, we make it easy for someone else to replicate our research. Remember, this is important because we can check if our findings are reliable.

Extraneous variables are all variables which are not independent variable but could affect the results of the experiment.

It can be a natural characteristic of the participant, such as intelligence levels, gender, or age for example, or it could be a situational feature of the environment such as lighting or noise.

Demand characteristics are a type of extraneous variable that occurs if the participants work out the aims of the research study, they may begin to behave in a certain way.

For example, in Milgram’s research , critics argued that participants worked out that the shocks were not real and they administered them as they thought this was what was required of them. 

Extraneous variables must be controlled so that they do not affect (confound) the results.

Randomly allocating participants to their conditions or using a matched pairs experimental design can help to reduce participant variables. 

Situational variables are controlled by using standardized procedures, ensuring every participant in a given condition is treated in the same way

Experimental Design

Experimental design refers to how participants are allocated to each condition of the independent variable, such as a control or experimental group.

• Independent design ( between-groups design ): each participant is selected for only one group. With the independent design, the most common way of deciding which participants go into which group is by means of randomization. 
• Matched participants design : each participant is selected for only one group, but the participants in the two groups are matched for some relevant factor or factors (e.g. ability; sex; age).
• Repeated measures design ( within groups) : each participant appears in both groups, so that there are exactly the same participants in each group.
• The main problem with the repeated measures design is that there may well be order effects. Their experiences during the experiment may change the participants in various ways.
• They may perform better when they appear in the second group because they have gained useful information about the experiment or about the task. On the other hand, they may perform less well on the second occasion because of tiredness or boredom.
• Counterbalancing is the best way of preventing order effects from disrupting the findings of an experiment, and involves ensuring that each condition is equally likely to be used first and second by the participants.

If we wish to compare two groups with respect to a given independent variable, it is essential to make sure that the two groups do not differ in any other important way. 

Experimental Methods

All experimental methods involve an iv (independent variable) and dv (dependent variable)..

• Field experiments are conducted in the everyday (natural) environment of the participants. The experimenter still manipulates the IV, but in a real-life setting. It may be possible to control extraneous variables, though such control is more difficult than in a lab experiment.
• Natural experiments are when a naturally occurring IV is investigated that isn’t deliberately manipulated, it exists anyway. Participants are not randomly allocated, and the natural event may only occur rarely.

Case studies are in-depth investigations of a person, group, event, or community. It uses information from a range of sources, such as from the person concerned and also from their family and friends.

Many techniques may be used such as interviews, psychological tests, observations and experiments. Case studies are generally longitudinal: in other words, they follow the individual or group over an extended period of time. 

Case studies are widely used in psychology and among the best-known ones carried out were by Sigmund Freud . He conducted very detailed investigations into the private lives of his patients in an attempt to both understand and help them overcome their illnesses.

Case studies provide rich qualitative data and have high levels of ecological validity. However, it is difficult to generalize from individual cases as each one has unique characteristics.

Correlational Studies

Correlation means association; it is a measure of the extent to which two variables are related. One of the variables can be regarded as the predictor variable with the other one as the outcome variable.

Correlational studies typically involve obtaining two different measures from a group of participants, and then assessing the degree of association between the measures. 

The predictor variable can be seen as occurring before the outcome variable in some sense. It is called the predictor variable, because it forms the basis for predicting the value of the outcome variable.

Relationships between variables can be displayed on a graph or as a numerical score called a correlation coefficient.

• If an increase in one variable tends to be associated with an increase in the other, then this is known as a positive correlation .
• If an increase in one variable tends to be associated with a decrease in the other, then this is known as a negative correlation .
• A zero correlation occurs when there is no relationship between variables.

After looking at the scattergraph, if we want to be sure that a significant relationship does exist between the two variables, a statistical test of correlation can be conducted, such as Spearman’s rho.

The test will give us a score, called a correlation coefficient . This is a value between 0 and 1, and the closer to 1 the score is, the stronger the relationship between the variables. This value can be both positive e.g. 0.63, or negative -0.63.

A correlation between variables, however, does not automatically mean that the change in one variable is the cause of the change in the values of the other variable. A correlation only shows if there is a relationship between variables.

Correlation does not always prove causation, as a third variable may be involved. 

Interview Methods

Interviews are commonly divided into two types: structured and unstructured.

A fixed, predetermined set of questions is put to every participant in the same order and in the same way. 

Responses are recorded on a questionnaire, and the researcher presets the order and wording of questions, and sometimes the range of alternative answers.

The interviewer stays within their role and maintains social distance from the interviewee.

There are no set questions, and the participant can raise whatever topics he/she feels are relevant and ask them in their own way. Questions are posed about participants’ answers to the subject

Unstructured interviews are most useful in qualitative research to analyze attitudes and values.

Though they rarely provide a valid basis for generalization, their main advantage is that they enable the researcher to probe social actors’ subjective point of view. 

Questionnaire Method

Questionnaires can be thought of as a kind of written interview. They can be carried out face to face, by telephone, or post.

The choice of questions is important because of the need to avoid bias or ambiguity in the questions, ‘leading’ the respondent or causing offense.

• Open questions are designed to encourage a full, meaningful answer using the subject’s own knowledge and feelings. They provide insights into feelings, opinions, and understanding. Example: “How do you feel about that situation?”
• Closed questions can be answered with a simple “yes” or “no” or specific information, limiting the depth of response. They are useful for gathering specific facts or confirming details. Example: “Do you feel anxious in crowds?”

Its other practical advantages are that it is cheaper than face-to-face interviews and can be used to contact many respondents scattered over a wide area relatively quickly.

Observations

There are different types of observation methods :

• Covert observation is where the researcher doesn’t tell the participants they are being observed until after the study is complete. There could be ethical problems or deception and consent with this particular observation method.
• Overt observation is where a researcher tells the participants they are being observed and what they are being observed for.
• Controlled : behavior is observed under controlled laboratory conditions (e.g., Bandura’s Bobo doll study).
• Natural : Here, spontaneous behavior is recorded in a natural setting.
• Participant : Here, the observer has direct contact with the group of people they are observing. The researcher becomes a member of the group they are researching.  
• Non-participant (aka “fly on the wall): The researcher does not have direct contact with the people being observed. The observation of participants’ behavior is from a distance

Pilot Study

A pilot  study is a small scale preliminary study conducted in order to evaluate the feasibility of the key s teps in a future, full-scale project.

A pilot study is an initial run-through of the procedures to be used in an investigation; it involves selecting a few people and trying out the study on them. It is possible to save time, and in some cases, money, by identifying any flaws in the procedures designed by the researcher.

A pilot study can help the researcher spot any ambiguities (i.e. unusual things) or confusion in the information given to participants or problems with the task devised.

Sometimes the task is too hard, and the researcher may get a floor effect, because none of the participants can score at all or can complete the task – all performances are low.

The opposite effect is a ceiling effect, when the task is so easy that all achieve virtually full marks or top performances and are “hitting the ceiling”.

Research Design

In cross-sectional research , a researcher compares multiple segments of the population at the same time

Sometimes, we want to see how people change over time, as in studies of human development and lifespan. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time.

In cohort studies , the participants must share a common factor or characteristic such as age, demographic, or occupation. A cohort study is a type of longitudinal study in which researchers monitor and observe a chosen population over an extended period.

Triangulation means using more than one research method to improve the study’s validity.

Reliability

Reliability is a measure of consistency, if a particular measurement is repeated and the same result is obtained then it is described as being reliable.

• Test-retest reliability :  assessing the same person on two different occasions which shows the extent to which the test produces the same answers.
• Inter-observer reliability : the extent to which there is an agreement between two or more observers.

Meta-Analysis

A meta-analysis is a systematic review that involves identifying an aim and then searching for research studies that have addressed similar aims/hypotheses.

This is done by looking through various databases, and then decisions are made about what studies are to be included/excluded.

Strengths: Increases the conclusions’ validity as they’re based on a wider range.

Weaknesses: Research designs in studies can vary, so they are not truly comparable.

Peer Review

A researcher submits an article to a journal. The choice of the journal may be determined by the journal’s audience or prestige.

The journal selects two or more appropriate experts (psychologists working in a similar field) to peer review the article without payment. The peer reviewers assess: the methods and designs used, originality of the findings, the validity of the original research findings and its content, structure and language.

Feedback from the reviewer determines whether the article is accepted. The article may be: Accepted as it is, accepted with revisions, sent back to the author to revise and re-submit or rejected without the possibility of submission.

The editor makes the final decision whether to accept or reject the research report based on the reviewers comments/ recommendations.

Peer review is important because it prevent faulty data from entering the public domain, it provides a way of checking the validity of findings and the quality of the methodology and is used to assess the research rating of university departments.

Peer reviews may be an ideal, whereas in practice there are lots of problems. For example, it slows publication down and may prevent unusual, new work being published. Some reviewers might use it as an opportunity to prevent competing researchers from publishing work.

Some people doubt whether peer review can really prevent the publication of fraudulent research.

The advent of the internet means that a lot of research and academic comment is being published without official peer reviews than before, though systems are evolving on the internet where everyone really has a chance to offer their opinions and police the quality of research.

Types of Data

• Quantitative data is numerical data e.g. reaction time or number of mistakes. It represents how much or how long, how many there are of something. A tally of behavioral categories and closed questions in a questionnaire collect quantitative data.
• Qualitative data is virtually any type of information that can be observed and recorded that is not numerical in nature and can be in the form of written or verbal communication. Open questions in questionnaires and accounts from observational studies collect qualitative data.
• Primary data is first-hand data collected for the purpose of the investigation.
• Secondary data is information that has been collected by someone other than the person who is conducting the research e.g. taken from journals, books or articles.

Validity means how well a piece of research actually measures what it sets out to, or how well it reflects the reality it claims to represent.

Validity is whether the observed effect is genuine and represents what is actually out there in the world.

• Concurrent validity is the extent to which a psychological measure relates to an existing similar measure and obtains close results. For example, a new intelligence test compared to an established test.
• Face validity : does the test measure what it’s supposed to measure ‘on the face of it’. This is done by ‘eyeballing’ the measuring or by passing it to an expert to check.
• Ecological validit y is the extent to which findings from a research study can be generalized to other settings / real life.
• Temporal validity is the extent to which findings from a research study can be generalized to other historical times.

Features of Science

• Paradigm – A set of shared assumptions and agreed methods within a scientific discipline.
• Paradigm shift – The result of the scientific revolution: a significant change in the dominant unifying theory within a scientific discipline.
• Objectivity – When all sources of personal bias are minimised so not to distort or influence the research process.
• Empirical method – Scientific approaches that are based on the gathering of evidence through direct observation and experience.
• Replicability – The extent to which scientific procedures and findings can be repeated by other researchers.
• Falsifiability – The principle that a theory cannot be considered scientific unless it admits the possibility of being proved untrue.

Statistical Testing

A significant result is one where there is a low probability that chance factors were responsible for any observed difference, correlation, or association in the variables tested.

If our test is significant, we can reject our null hypothesis and accept our alternative hypothesis.

If our test is not significant, we can accept our null hypothesis and reject our alternative hypothesis. A null hypothesis is a statement of no effect.

In Psychology, we use p < 0.05 (as it strikes a balance between making a type I and II error) but p < 0.01 is used in tests that could cause harm like introducing a new drug.

A type I error is when the null hypothesis is rejected when it should have been accepted (happens when a lenient significance level is used, an error of optimism).

A type II error is when the null hypothesis is accepted when it should have been rejected (happens when a stringent significance level is used, an error of pessimism).

Ethical Issues

• Informed consent is when participants are able to make an informed judgment about whether to take part. It causes them to guess the aims of the study and change their behavior.
• To deal with it, we can gain presumptive consent or ask them to formally indicate their agreement to participate but it may invalidate the purpose of the study and it is not guaranteed that the participants would understand.
• Deception should only be used when it is approved by an ethics committee, as it involves deliberately misleading or withholding information. Participants should be fully debriefed after the study but debriefing can’t turn the clock back.
• All participants should be informed at the beginning that they have the right to withdraw if they ever feel distressed or uncomfortable.
• It causes bias as the ones that stayed are obedient and some may not withdraw as they may have been given incentives or feel like they’re spoiling the study. Researchers can offer the right to withdraw data after participation.
• Participants should all have protection from harm . The researcher should avoid risks greater than those experienced in everyday life and they should stop the study if any harm is suspected. However, the harm may not be apparent at the time of the study.
• Confidentiality concerns the communication of personal information. The researchers should not record any names but use numbers or false names though it may not be possible as it is sometimes possible to work out who the researchers were.

Psychology Case Study Examples: A Deep Dive into Real-life Scenarios

Peeling back the layers of the human mind is no easy task, but psychology case studies can help us do just that. Through these detailed analyses, we’re able to gain a deeper understanding of human behavior, emotions, and cognitive processes. I’ve always found it fascinating how a single person’s experience can shed light on broader psychological principles.

Over the years, psychologists have conducted numerous case studies—each with their own unique insights and implications. These investigations range from Phineas Gage’s accidental lobotomy to Genie Wiley’s tragic tale of isolation. Such examples not only enlighten us about specific disorders or occurrences but also continue to shape our overall understanding of psychology .

As we delve into some noteworthy examples , I assure you’ll appreciate how varied and intricate the field of psychology truly is. Whether you’re a budding psychologist or simply an eager learner, brace yourself for an intriguing exploration into the intricacies of the human psyche.

Understanding Psychology Case Studies

Diving headfirst into the world of psychology, it’s easy to come upon a valuable tool used by psychologists and researchers alike – case studies. I’m here to shed some light on these fascinating tools.

Psychology case studies, for those unfamiliar with them, are in-depth investigations carried out to gain a profound understanding of the subject – whether it’s an individual, group or phenomenon. They’re powerful because they provide detailed insights that other research methods might miss.

Let me share a few examples to clarify this concept further:

• One notable example is Freud’s study on Little Hans. This case study explored a 5-year-old boy’s fear of horses and related it back to Freud’s theories about psychosexual stages.
• Another classic example is Genie Wiley (a pseudonym), a feral child who was subjected to severe social isolation during her early years. Her heartbreaking story provided invaluable insights into language acquisition and critical periods in development.

You see, what sets psychology case studies apart is their focus on the ‘why’ and ‘how’. While surveys or experiments might tell us ‘what’, they often don’t dig deep enough into the inner workings behind human behavior.

It’s important though not to take these psychology case studies at face value. As enlightening as they can be, we must remember that they usually focus on one specific instance or individual. Thus, generalizing findings from single-case studies should be done cautiously.

To illustrate my point using numbers: let’s say we have 1 million people suffering from condition X worldwide; if only 20 unique cases have been studied so far (which would be quite typical for rare conditions), then our understanding is based on just 0.002% of the total cases! That’s why multiple sources and types of research are vital when trying to understand complex psychological phenomena fully.

In the grand scheme of things, psychology case studies are just one piece of the puzzle – albeit an essential one. They provide rich, detailed data that can form the foundation for further research and understanding. As we delve deeper into this fascinating field, it’s crucial to appreciate all the tools at our disposal – from surveys and experiments to these insightful case studies.

Importance of Case Studies in Psychology

I’ve always been fascinated by the human mind, and if you’re here, I bet you are too. Let’s dive right into why case studies play such a pivotal role in psychology.

One of the key reasons they matter so much is because they provide detailed insights into specific psychological phenomena. Unlike other research methods that might use large samples but only offer surface-level findings, case studies allow us to study complex behaviors, disorders, and even treatments at an intimate level. They often serve as a catalyst for new theories or help refine existing ones.

To illustrate this point, let’s look at one of psychology’s most famous case studies – Phineas Gage. He was a railroad construction foreman who survived a severe brain injury when an iron rod shot through his skull during an explosion in 1848. The dramatic personality changes he experienced after his accident led to significant advancements in our understanding of the brain’s role in personality and behavior.

Moreover, it’s worth noting that some rare conditions can only be studied through individual cases due to their uncommon nature. For instance, consider Genie Wiley – a girl discovered at age 13 having spent most of her life locked away from society by her parents. Her tragic story gave psychologists valuable insights into language acquisition and critical periods for learning.

Finally yet importantly, case studies also have practical applications for clinicians and therapists. Studying real-life examples can inform treatment plans and provide guidance on how theoretical concepts might apply to actual client situations.

• Detailed insights: Case studies offer comprehensive views on specific psychological phenomena.
• Catalyst for new theories: Real-life scenarios help shape our understanding of psychology .
• Study rare conditions: Unique cases can offer invaluable lessons about uncommon disorders.
• Practical applications: Clinicians benefit from studying real-world examples.

In short (but without wrapping up), it’s clear that case studies hold immense value within psychology – they illuminate what textbooks often can’t, offering a more nuanced understanding of human behavior.

Different Types of Psychology Case Studies

Diving headfirst into the world of psychology, I can’t help but be fascinated by the myriad types of case studies that revolve around this subject. Let’s take a closer look at some of them.

Firstly, we’ve got what’s known as ‘Explanatory Case Studies’. These are often used when a researcher wants to clarify complex phenomena or concepts. For example, a psychologist might use an explanatory case study to explore the reasons behind aggressive behavior in children.

Second on our list are ‘Exploratory Case Studies’, typically utilized when new and unexplored areas of research come up. They’re like pioneers; they pave the way for future studies. In psychological terms, exploratory case studies could be conducted to investigate emerging mental health conditions or under-researched therapeutic approaches.

Next up are ‘Descriptive Case Studies’. As the name suggests, these focus on depicting comprehensive and detailed profiles about a particular individual, group, or event within its natural context. A well-known example would be Sigmund Freud’s analysis of “Anna O”, which provided unique insights into hysteria.

Then there are ‘Intrinsic Case Studies’, which delve deep into one specific case because it is intrinsically interesting or unique in some way. It’s sorta like shining a spotlight onto an exceptional phenomenon. An instance would be studying savants—individuals with extraordinary abilities despite significant mental disabilities.

Lastly, we have ‘Instrumental Case Studies’. These aren’t focused on understanding a particular case per se but use it as an instrument to understand something else altogether—a bit like using one puzzle piece to make sense of the whole picture!

So there you have it! From explanatory to instrumental, each type serves its own unique purpose and adds another intriguing layer to our understanding of human behavior and cognition.

Exploring Real-Life Psychology Case Study Examples

Let’s roll up our sleeves and delve into some real-life psychology case study examples. By digging deep, we can glean valuable insights from these studies that have significantly contributed to our understanding of human behavior and mental processes.

First off, let me share the fascinating case of Phineas Gage. This gentleman was a 19th-century railroad construction foreman who survived an accident where a large iron rod was accidentally driven through his skull, damaging his frontal lobes. Astonishingly, he could walk and talk immediately after the accident but underwent dramatic personality changes, becoming impulsive and irresponsible. This case is often referenced in discussions about brain injury and personality change.

Next on my list is Genie Wiley’s heart-wrenching story. She was a victim of severe abuse and neglect resulting in her being socially isolated until she was 13 years old. Due to this horrific experience, Genie couldn’t acquire language skills typically as other children would do during their developmental stages. Her tragic story offers invaluable insight into the critical periods for language development in children.

Then there’s ‘Little Hans’, a classic Freudian case that delves into child psychology. At just five years old, Little Hans developed an irrational fear of horses -or so it seemed- which Sigmund Freud interpreted as symbolic anxiety stemming from suppressed sexual desires towards his mother—quite an interpretation! The study gave us Freud’s Oedipus Complex theory.

Lastly, I’d like to mention Patient H.M., an individual who became amnesiac following surgery to control seizures by removing parts of his hippocampus bilaterally. His inability to form new memories post-operation shed light on how different areas of our brains contribute to memory formation.

Each one of these real-life psychology case studies gives us a unique window into understanding complex human behaviors better – whether it’s dissecting the role our brain plays in shaping personality or unraveling the mysteries of fear, language acquisition, and memory.

How to Analyze a Psychology Case Study

Diving headfirst into a psychology case study, I understand it can seem like an intimidating task. But don’t worry, I’m here to guide you through the process.

First off, it’s essential to go through the case study thoroughly. Read it multiple times if needed. Each reading will likely reveal new information or perspectives you may have missed initially. Look out for any patterns or inconsistencies in the subject’s behavior and make note of them.

Next on your agenda should be understanding the theoretical frameworks that might be applicable in this scenario. Is there a cognitive-behavioral approach at play? Or does psychoanalysis provide better insights? Comparing these theories with observed behavior and symptoms can help shed light on underlying psychological issues.

Now, let’s talk data interpretation. If your case study includes raw data like surveys or diagnostic tests results, you’ll need to analyze them carefully. Here are some steps that could help:

• Identify what each piece of data represents
• Look for correlations between different pieces of data
• Compute statistics (mean, median, mode) if necessary
• Use graphs or charts for visual representation

Keep in mind; interpreting raw data requires both statistical knowledge and intuition about human behavior.

Finally, drafting conclusions is key in analyzing a psychology case study. Based on your observations, evaluations of theoretical approaches and interpretations of any given data – what do you conclude about the subject’s mental health status? Remember not to jump to conclusions hastily but instead base them solidly on evidence from your analysis.

In all this journey of analysis remember one thing: every person is unique and so are their experiences! So while theories and previous studies guide us, they never define an individual completely.

Applying Lessons from Psychology Case Studies

Let’s dive into how we can apply the lessons learned from psychology case studies. If you’ve ever studied psychology, you’ll know that case studies offer rich insights. They shed light on human behavior, mental health issues, and therapeutic techniques. But it’s not just about understanding theory. It’s also about implementing these valuable lessons in real-world situations.

One of the most famous psychological case studies is Phineas Gage’s story. This 19th-century railroad worker survived a severe brain injury which dramatically altered his personality. From this study, we gained crucial insight into how different brain areas are responsible for various aspects of our personality and behavior.

• Lesson: Recognizing that damage to specific brain areas can result in personality changes, enabling us to better understand certain mental conditions.

Sigmund Freud’s work with a patient known as ‘Anna O.’ is another landmark psychology case study. Anna displayed what was then called hysteria – symptoms included hallucinations and disturbances in speech and physical coordination – which Freud linked back to repressed memories of traumatic events.

• Lesson: The importance of exploring an individual’s history for understanding their current psychological problems – a principle at the heart of psychoanalysis.

Then there’s Genie Wiley’s case – a girl who suffered extreme neglect resulting in impaired social and linguistic development. Researchers used her tragic circumstances as an opportunity to explore theories around language acquisition and socialization.

• Lesson: Reinforcing the critical role early childhood experiences play in shaping cognitive development.

Lastly, let’s consider the Stanford Prison Experiment led by Philip Zimbardo examining how people conform to societal roles even when they lead to immoral actions.

• Lesson: Highlighting that situational forces can drastically impact human behavior beyond personal characteristics or morality.

These examples demonstrate that psychology case studies aren’t just academic exercises isolated from daily life. Instead, they provide profound lessons that help us make sense of complex human behaviors, mental health issues, and therapeutic strategies. By understanding these studies, we’re better equipped to apply their lessons in our own lives – whether it’s navigating personal relationships, working with diverse teams at work or even self-improvement.

Challenges and Critiques of Psychological Case Studies

Delving into the world of psychological case studies, it’s not all rosy. Sure, they offer an in-depth understanding of individual behavior and mental processes. Yet, they’re not without their share of challenges and criticisms.

One common critique is the lack of generalizability. Each case study is unique to its subject. We can’t always apply what we learn from one person to everyone else. I’ve come across instances where results varied dramatically between similar subjects, highlighting the inherent unpredictability in human behavior.

Another challenge lies within ethical boundaries. Often, sensitive information surfaces during these studies that could potentially harm the subject if disclosed improperly. To put it plainly, maintaining confidentiality while delivering a comprehensive account isn’t always easy.

Distortion due to subjective interpretations also poses substantial difficulties for psychologists conducting case studies. The researcher’s own bias may color their observations and conclusions – leading to skewed outcomes or misleading findings.

Moreover, there’s an ongoing debate about the scientific validity of case studies because they rely heavily on qualitative data rather than quantitative analysis. Some argue this makes them less reliable or objective when compared with other research methods such as experiments or surveys.

To summarize:

• Lack of generalizability
• Ethical dilemmas concerning privacy
• Potential distortion through subjective interpretation
• Questions about scientific validity

While these critiques present significant challenges, they do not diminish the value that psychological case studies bring to our understanding of human behavior and mental health struggles.

Conclusion: The Impact of Case Studies in Understanding Human Behavior

Case studies play a pivotal role in shedding light on human behavior. Throughout this article, I’ve discussed numerous examples that illustrate just how powerful these studies can be. Yet it’s the impact they have on our understanding of human psychology where their true value lies.

Take for instance the iconic study of Phineas Gage. It was through his tragic accident and subsequent personality change that we began to grasp the profound influence our frontal lobes have on our behavior. Without such a case study, we might still be in the dark about this crucial aspect of our neurology.

Let’s also consider Genie, the feral child who showed us the critical importance of social interaction during early development. Her heartbreaking story underscores just how vital appropriate nurturing is for healthy mental and emotional growth.

Here are some key takeaways from these case studies:

• Our brain structure significantly influences our behavior.
• Social interaction during formative years is vital for normal psychological development.
• Studying individual cases can reveal universal truths about human nature.

What stands out though, is not merely what these case studies teach us individually but collectively. They remind us that each person constitutes a unique combination of various factors—biological, psychological, and environmental—that shape their behavior.

One cannot overstate the significance of case studies in psychology—they are more than mere stories or isolated incidents; they’re windows into the complexities and nuances of human nature itself.

In wrapping up, I’d say that while statistics give us patterns and trends to understand groups, it’s these detailed narratives offered by case studies that help us comprehend individuals’ unique experiences within those groups—making them an invaluable part of psychological research.

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2.2 Approaches to Research

Learning objectives.

By the end of this section, you will be able to:

• Describe the different research methods used by psychologists
• Discuss the strengths and weaknesses of case studies, naturalistic observation, surveys, and archival research
• Compare longitudinal and cross-sectional approaches to research
• Compare and contrast correlation and causation

There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it. Some methods rely on observational techniques. Other approaches involve interactions between the researcher and the individuals who are being studied—ranging from a series of simple questions to extensive, in-depth interviews—to well-controlled experiments.

Each of these research methods has unique strengths and weaknesses, and each method may only be appropriate for certain types of research questions. For example, studies that rely primarily on observation produce incredible amounts of information, but the ability to apply this information to the larger population is somewhat limited because of small sample sizes. Survey research, on the other hand, allows researchers to easily collect data from relatively large samples. While this allows for results to be generalized to the larger population more easily, the information that can be collected on any given survey is somewhat limited and subject to problems associated with any type of self-reported data. Some researchers conduct archival research by using existing records. While this can be a fairly inexpensive way to collect data that can provide insight into a number of research questions, researchers using this approach have no control on how or what kind of data was collected. All of the methods described thus far are correlational in nature. This means that researchers can speak to important relationships that might exist between two or more variables of interest. However, correlational data cannot be used to make claims about cause-and-effect relationships.

Correlational research can find a relationship between two variables, but the only way a researcher can claim that the relationship between the variables is cause and effect is to perform an experiment. In experimental research, which will be discussed later in this chapter, there is a tremendous amount of control over variables of interest. While this is a powerful approach, experiments are often conducted in artificial settings. This calls into question the validity of experimental findings with regard to how they would apply in real-world settings. In addition, many of the questions that psychologists would like to answer cannot be pursued through experimental research because of ethical concerns.

Clinical or Case Studies

In 2011, the New York Times published a feature story on Krista and Tatiana Hogan, Canadian twin girls. These particular twins are unique because Krista and Tatiana are conjoined twins, connected at the head. There is evidence that the two girls are connected in a part of the brain called the thalamus, which is a major sensory relay center. Most incoming sensory information is sent through the thalamus before reaching higher regions of the cerebral cortex for processing.

Link to Learning

Watch this CBC video about Krista's and Tatiana's lives to learn more.

The implications of this potential connection mean that it might be possible for one twin to experience the sensations of the other twin. For instance, if Krista is watching a particularly funny television program, Tatiana might smile or laugh even if she is not watching the program. This particular possibility has piqued the interest of many neuroscientists who seek to understand how the brain uses sensory information.

These twins represent an enormous resource in the study of the brain, and since their condition is very rare, it is likely that as long as their family agrees, scientists will follow these girls very closely throughout their lives to gain as much information as possible (Dominus, 2011).

Over time, it has become clear that while Krista and Tatiana share some sensory experiences and motor control, they remain two distinct individuals, which provides invaluable insight for researchers interested in the mind and the brain (Egnor, 2017).

In observational research, scientists are conducting a clinical or case study when they focus on one person or just a few individuals. Indeed, some scientists spend their entire careers studying just 10–20 individuals. Why would they do this? Obviously, when they focus their attention on a very small number of people, they can gain a precious amount of insight into those cases. The richness of information that is collected in clinical or case studies is unmatched by any other single research method. This allows the researcher to have a very deep understanding of the individuals and the particular phenomenon being studied.

If clinical or case studies provide so much information, why are they not more frequent among researchers? As it turns out, the major benefit of this particular approach is also a weakness. As mentioned earlier, this approach is often used when studying individuals who are interesting to researchers because they have a rare characteristic. Therefore, the individuals who serve as the focus of case studies are not like most other people. If scientists ultimately want to explain all behavior, focusing attention on such a special group of people can make it difficult to generalize any observations to the larger population as a whole. Generalizing refers to the ability to apply the findings of a particular research project to larger segments of society. Again, case studies provide enormous amounts of information, but since the cases are so specific, the potential to apply what’s learned to the average person may be very limited.

Naturalistic Observation

If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances are that almost everyone in the classroom will raise their hand, but do you think hand washing after every trip to the restroom is really that universal?

This is very similar to the phenomenon mentioned earlier in this chapter: many individuals do not feel comfortable answering a question honestly. But if we are committed to finding out the facts about hand washing, we have other options available to us.

Suppose we send a classmate into the restroom to actually watch whether everyone washes their hands after using the restroom. Will our observer blend into the restroom environment by wearing a white lab coat, sitting with a clipboard, and staring at the sinks? We want our researcher to be inconspicuous—perhaps standing at one of the sinks pretending to put in contact lenses while secretly recording the relevant information. This type of observational study is called naturalistic observation : observing behavior in its natural setting. To better understand peer exclusion, Suzanne Fanger collaborated with colleagues at the University of Texas to observe the behavior of preschool children on a playground. How did the observers remain inconspicuous over the duration of the study? They equipped a few of the children with wireless microphones (which the children quickly forgot about) and observed while taking notes from a distance. Also, the children in that particular preschool (a “laboratory preschool”) were accustomed to having observers on the playground (Fanger, Frankel, & Hazen, 2012).

It is critical that the observer be as unobtrusive and as inconspicuous as possible: when people know they are being watched, they are less likely to behave naturally. If you have any doubt about this, ask yourself how your driving behavior might differ in two situations: In the first situation, you are driving down a deserted highway during the middle of the day; in the second situation, you are being followed by a police car down the same deserted highway ( Figure 2.7 ).

It should be pointed out that naturalistic observation is not limited to research involving humans. Indeed, some of the best-known examples of naturalistic observation involve researchers going into the field to observe various kinds of animals in their own environments. As with human studies, the researchers maintain their distance and avoid interfering with the animal subjects so as not to influence their natural behaviors. Scientists have used this technique to study social hierarchies and interactions among animals ranging from ground squirrels to gorillas. The information provided by these studies is invaluable in understanding how those animals organize socially and communicate with one another. The anthropologist Jane Goodall , for example, spent nearly five decades observing the behavior of chimpanzees in Africa ( Figure 2.8 ). As an illustration of the types of concerns that a researcher might encounter in naturalistic observation, some scientists criticized Goodall for giving the chimps names instead of referring to them by numbers—using names was thought to undermine the emotional detachment required for the objectivity of the study (McKie, 2010).

The greatest benefit of naturalistic observation is the validity , or accuracy, of information collected unobtrusively in a natural setting. Having individuals behave as they normally would in a given situation means that we have a higher degree of ecological validity, or realism, than we might achieve with other research approaches. Therefore, our ability to generalize the findings of the research to real-world situations is enhanced. If done correctly, we need not worry about people or animals modifying their behavior simply because they are being observed. Sometimes, people may assume that reality programs give us a glimpse into authentic human behavior. However, the principle of inconspicuous observation is violated as reality stars are followed by camera crews and are interviewed on camera for personal confessionals. Given that environment, we must doubt how natural and realistic their behaviors are.

The major downside of naturalistic observation is that they are often difficult to set up and control. In our restroom study, what if you stood in the restroom all day prepared to record people’s hand washing behavior and no one came in? Or, what if you have been closely observing a troop of gorillas for weeks only to find that they migrated to a new place while you were sleeping in your tent? The benefit of realistic data comes at a cost. As a researcher you have no control of when (or if) you have behavior to observe. In addition, this type of observational research often requires significant investments of time, money, and a good dose of luck.

Sometimes studies involve structured observation. In these cases, people are observed while engaging in set, specific tasks. An excellent example of structured observation comes from Strange Situation by Mary Ainsworth (you will read more about this in the chapter on lifespan development). The Strange Situation is a procedure used to evaluate attachment styles that exist between an infant and caregiver. In this scenario, caregivers bring their infants into a room filled with toys. The Strange Situation involves a number of phases, including a stranger coming into the room, the caregiver leaving the room, and the caregiver’s return to the room. The infant’s behavior is closely monitored at each phase, but it is the behavior of the infant upon being reunited with the caregiver that is most telling in terms of characterizing the infant’s attachment style with the caregiver.

Another potential problem in observational research is observer bias . Generally, people who act as observers are closely involved in the research project and may unconsciously skew their observations to fit their research goals or expectations. To protect against this type of bias, researchers should have clear criteria established for the types of behaviors recorded and how those behaviors should be classified. In addition, researchers often compare observations of the same event by multiple observers, in order to test inter-rater reliability : a measure of reliability that assesses the consistency of observations by different observers.

Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally ( Figure 2.9 ). Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.

Surveys allow researchers to gather data from larger samples than may be afforded by other research methods . A sample is a subset of individuals selected from a population , which is the overall group of individuals that the researchers are interested in. Researchers study the sample and seek to generalize their findings to the population. Generally, researchers will begin this process by calculating various measures of central tendency from the data they have collected. These measures provide an overall summary of what a typical response looks like. There are three measures of central tendency: mode, median, and mean. The mode is the most frequently occurring response, the median lies at the middle of a given data set, and the mean is the arithmetic average of all data points. Means tend to be most useful in conducting additional analyses like those described below; however, means are very sensitive to the effects of outliers, and so one must be aware of those effects when making assessments of what measures of central tendency tell us about a data set in question.

There is both strength and weakness of the survey in comparison to case studies. By using surveys, we can collect information from a larger sample of people. A larger sample is better able to reflect the actual diversity of the population, thus allowing better generalizability. Therefore, if our sample is sufficiently large and diverse, we can assume that the data we collect from the survey can be generalized to the larger population with more certainty than the information collected through a case study. However, given the greater number of people involved, we are not able to collect the same depth of information on each person that would be collected in a case study.

Another potential weakness of surveys is something we touched on earlier in this chapter: People don't always give accurate responses. They may lie, misremember, or answer questions in a way that they think makes them look good. For example, people may report drinking less alcohol than is actually the case.

Any number of research questions can be answered through the use of surveys. One real-world example is the research conducted by Jenkins, Ruppel, Kizer, Yehl, and Griffin (2012) about the backlash against the US Arab-American community following the terrorist attacks of September 11, 2001. Jenkins and colleagues wanted to determine to what extent these negative attitudes toward Arab-Americans still existed nearly a decade after the attacks occurred. In one study, 140 research participants filled out a survey with 10 questions, including questions asking directly about the participant’s overt prejudicial attitudes toward people of various ethnicities. The survey also asked indirect questions about how likely the participant would be to interact with a person of a given ethnicity in a variety of settings (such as, “How likely do you think it is that you would introduce yourself to a person of Arab-American descent?”). The results of the research suggested that participants were unwilling to report prejudicial attitudes toward any ethnic group. However, there were significant differences between their pattern of responses to questions about social interaction with Arab-Americans compared to other ethnic groups: they indicated less willingness for social interaction with Arab-Americans compared to the other ethnic groups. This suggested that the participants harbored subtle forms of prejudice against Arab-Americans, despite their assertions that this was not the case (Jenkins et al., 2012).

Archival Research

Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research . Archival research relies on looking at past records or data sets to look for interesting patterns or relationships.

For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and calculate how long it took them to complete their degrees, as well as course loads, grades, and extracurricular involvement. Archival research could provide important information about who is most likely to complete their education, and it could help identify important risk factors for struggling students ( Figure 2.10 ).

In comparing archival research to other research methods, there are several important distinctions. For one, the researcher employing archival research never directly interacts with research participants. Therefore, the investment of time and money to collect data is considerably less with archival research. Additionally, researchers have no control over what information was originally collected. Therefore, research questions have to be tailored so they can be answered within the structure of the existing data sets. There is also no guarantee of consistency between the records from one source to another, which might make comparing and contrasting different data sets problematic.

Longitudinal and Cross-Sectional Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again at age 40.

Another approach is cross-sectional research. In cross-sectional research , a researcher compares multiple segments of the population at the same time. Using the dietary habits example above, the researcher might directly compare different groups of people by age. Instead of studying a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old individuals. While cross-sectional research requires a shorter-term investment, it is also limited by differences that exist between the different generations (or cohorts) that have nothing to do with age per se, but rather reflect the social and cultural experiences of different generations of individuals that make them different from one another.

To illustrate this concept, consider the following survey findings. In recent years there has been significant growth in the popular support of same-sex marriage. Many studies on this topic break down survey participants into different age groups. In general, younger people are more supportive of same-sex marriage than are those who are older (Jones, 2013). Does this mean that as we age we become less open to the idea of same-sex marriage, or does this mean that older individuals have different perspectives because of the social climates in which they grew up? Longitudinal research is a powerful approach because the same individuals are involved in the research project over time, which means that the researchers need to be less concerned with differences among cohorts affecting the results of their study.

Often longitudinal studies are employed when researching various diseases in an effort to understand particular risk factors. Such studies often involve tens of thousands of individuals who are followed for several decades. Given the enormous number of people involved in these studies, researchers can feel confident that their findings can be generalized to the larger population. The Cancer Prevention Study-3 (CPS-3) is one of a series of longitudinal studies sponsored by the American Cancer Society aimed at determining predictive risk factors associated with cancer. When participants enter the study, they complete a survey about their lives and family histories, providing information on factors that might cause or prevent the development of cancer. Then every few years the participants receive additional surveys to complete. In the end, hundreds of thousands of participants will be tracked over 20 years to determine which of them develop cancer and which do not.

Clearly, this type of research is important and potentially very informative. For instance, earlier longitudinal studies sponsored by the American Cancer Society provided some of the first scientific demonstrations of the now well-established links between increased rates of cancer and smoking (American Cancer Society, n.d.) ( Figure 2.11 ).

As with any research strategy, longitudinal research is not without limitations. For one, these studies require an incredible time investment by the researcher and research participants. Given that some longitudinal studies take years, if not decades, to complete, the results will not be known for a considerable period of time. In addition to the time demands, these studies also require a substantial financial investment. Many researchers are unable to commit the resources necessary to see a longitudinal project through to the end.

Research participants must also be willing to continue their participation for an extended period of time, and this can be problematic. People move, get married and take new names, get ill, and eventually die. Even without significant life changes, some people may simply choose to discontinue their participation in the project. As a result, the attrition rates, or reduction in the number of research participants due to dropouts, in longitudinal studies are quite high and increase over the course of a project. For this reason, researchers using this approach typically recruit many participants fully expecting that a substantial number will drop out before the end. As the study progresses, they continually check whether the sample still represents the larger population, and make adjustments as necessary.

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• Authors: Rose M. Spielman, William J. Jenkins, Marilyn D. Lovett
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• Book title: Psychology 2e
• Publication date: Apr 22, 2020
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• Open access
• Published: 30 April 2024

Application and value of anxiety and depression scale in patients with functional dyspepsia

• Yejiao Ruan 1   na1 ,
• Hao Lin 1   na1 ,
• Xinru Lu 1 ,
• Yiying Lin 1 ,
• Jian Sun 1 ,
• Cengqi Xu 2 ,
• Lingjun Zhou 2 ,
• Zhenzhai Cai 1 &
• Xiaoyan Chen 1  

BMC Psychology volume  12 , Article number:  244 ( 2024 ) Cite this article

Metrics details

Patients with functional dyspepsia (FD) cannot be assessed for their mental health using a suitable and practical measure. The purpose of the study is to investigate the usefulness of several anxiety and depression scales in patients with FD, offering recommendations for clinical identification and therapy.

From September 2021 to September 2022, patients were sought and selected. The psychological symptoms were assessed using ten depression or anxiety questionnaires. The receiver operating characteristic (ROC) curve, Spearman analysis, Pearson correlation analysis, and single factor analysis were applied.

Prospective analysis was performed on 142 healthy individuals and 113 patients with FD. In the case group, anxiety and depression symptoms were more common than in the control group, and the 10 scales showed strong validity and reliability. HAMD had the strongest connection with the PHQ-9 score on the depression scale (0.83). The score correlation between SAS and HAMA on the anxiety analysis scale was the greatest at 0.77. The PHQ-9, SAS, HAMD, and HAMA measures performed exceptionally well in detecting FD with anxiety or depression symptoms (AUC = 0.72, 0.70, 0.70, 0.77, and 0.77, respectively).

Conclusions

PHQ-9, SAS, HAMD, and HAMA scales have good application performance in FD patients. They can assist gastroenterologists in evaluating anxiety and depression symptoms, and provide reference and guidance for subsequent treatment.

Peer Review reports

One of the most common functional gastrointestinal disorders is functional dyspepsia (FD) [ 1 , 2 ]. According to ROME criteria, population-based studies reported that the overall global pooled prevalence of FD in adults from 1990 to 2022 was 8.4%, which was even higher in developing countries (9.0%) [ 3 ]. Low cure rates, frequent flare-ups, and persistent symptoms are all characteristics of FD that impair patients’ quality of life and cause a greater financial healthcare burden which reaches $1.84 billion per year in the USA [ 4 , 5 , 6 ]. Existing studies have demonstrated that FD is strongly correlated with psychological and mental factors [ 7 , 8 ]. However, there are currently few ways to identify FD patients who have psychiatric issues, and psychological assessments can offer a scientifically valid basis for detection [ 9 ]. More than 10 different psychological assessment scale subtypes are currently employed in clinical assessments of psychological disorders, none of which are determined as the golden standards in clinical practice yet due to the lack of systematic research [ 10 ]. Investigating useful psychological assessments for the early detection of anxiety and depression symptoms in gastrointestinal patients is crucial. This study examined and compared the effectiveness of various psychological measures used with FD patients to offer a clinical foundation for the selection of suitable evaluation instruments for the clinical practice of doctors. It may help to further enhance the quick recognition, diagnosis, and treatment of FD by medical doctors as well as enhance the clinical prognosis of FD patients.

Materials and methods

Study population.

From September 2022 to March 2023, the researchers prospectively gathered pertinent data from outpatients and healthy individuals receiving physical examinations at the Second Affiliated Hospital of Wenzhou Medical University. Rome IV criteria were used to diagnose patients with functional dyspepsia, and the healthy individuals who completed physical tests in the hospital during the same period made up the control group.

Inclusion criteria

Inclusion criteria were: aged 18–80; originating in the gastroduodenal region, except for organic, systemic, or metabolic diseases that could explain the symptoms, containing at least 1 of the following 4 symptoms (upper abdominal pain, epigastric burning sensation, postprandial fullness, and early satiety), with a disease duration of more than 6 months, and symptoms have occurred in the past 3 months. In all cases, endoscopy was performed to exclude organic disease.

Exclusion criteria

Exclusion criteria were: pregnant or lactating; history of any other diagnosed gastrointestinal disorders which can explain dyspeptic symptoms, such as esophagitis, gastritis, ulcer disease, etc.; history of severe major abdominal surgery; history of psychotic disorders or other severe psychiatric disorders; history of other severe organic disorders, such as pancreaticobiliary disease, metabolic disease or liver dysfunction; currently using drugs with proven gastrointestinal adverse effects, such as steroids or nonsteroidal anti-inflammatory drugs; or declined to participate in this study.

All study participants gave a written informed agreement allowing their data to be recorded and utilized in the study, and the study was carried out with the Ethics Committee of the Second Affiliated Hospital of Wenzhou Medical University’s clearance. The study adhered to the confidentiality of patient information concept, and the completed questionnaire was immediately collected.

Related scales

Hamilton Anxiety Rating Scale (HAMA): Compiled by Hamilton in 1959, it includes 14 items, all of which are rated on a 5-point scale from 0 to 4 [ 11 ].

Hamilton Depression Rating Scale (HAMD): Developed by Hamilton in 1960, it is divided into three versions. A 24-item version was used in this study [ 12 ].

Self-Rating Anxiety Scale (SAS): Prepared by William WK Zung, contains 20 items, divided into 4 grades [ 13 ].

Self-Rating Depression Scale (SDS): It is a self-rating scale with 20 items and divided into 4 grades. The prototype is the depression scale compiled by WKZung (1965) [ 14 ].

Patient Health Questionnaire 9(PHQ-9): It is a 9-item scale based on the DSM-IV diagnostic criteria, using a 4-point scoring method of 0 to 3 points [ 15 ].

The 7-item Generalized Anxiety Disorder Scale (GAD-7): Developed by Spizer et al. (2006), there are 7 items in total, and it is a 4-point rating on a scale of 0–3 [ 16 ].

The 90s four-question questionnaire of depression (D90-4): The subjects were asked to answer four questions within the 90s, and depression could be quickly screened according to the answers.

The 90s four-question questionnaire for anxiety (A90-4): The subjects were asked to answer four questions within the 90s, and anxiety could be quickly screened according to the answers.

General Hospital Anxiety and Depression Scale (HADS): The HADS consists of 14 items to calculate the patient’s composite score, seven of which are anxiety-related (HADS-D) and the other seven are depression-related (HADS-A) [ 17 ].

Data collection

Following completion of the baseline personal information questionnaire, participants were given the SDS, HAMD, HADS-D, PHQ-9, and D90-4 depression measures as well as the SAS, HAMA, HADS-A, GAD-7, and A90-4 anxiety scales. The patients voluntarily filled out the self-rated scales after being explained by experienced researchers. Individually, both subjects and professionally trained researchers evaluated the clinician-rated scales. For the same patient, all scales were required to be completed in one day and there shouldn’t be more than a 30-minute gap between the filling times of two scales to prevent cross-talk between them and patient boredom from having too many scales.

Statistic analysis

All statistical analyses were performed by SPSS 22.0. Continuous variables with normal distribution are expressed as mean standard deviation, and those with an abnormal distribution are expressed as median (upper and lower quartiles). Frequencies and percentages are used to represent categorical variables. Comparisons between groups were performed using the χ2 test and t test. Both Spearman and Pearson correlation analysis were used to perform the correlation analysis. GraphPad software was used to construct the receiver operating characteristic (ROC) curves for each of the 10 scales. The threshold for statistical significance was set at p  < 0.05.

Patient characteristics

This study examined 305 instances in total, and it only included the 255 individuals who fully completed the ten-item measure. The average age was 39.5 ± 11.1, and there were 114 females and 141 males. The case group consisted of 142 people with an average age of 38.2 ± 11.4 years, while the normal control group had 142 people with an average age of 41.1 ± 10.5 years. While there was no statistical difference in the gender ratio between the two groups ( p  > 0.05), the proportion of senior-year rent samples in the control group was higher than that in the case group (age > 40 years). Details can be found in Table  1 .

Reliability and validity tests

Overall, the validity and reliability of all five anxiety and depression scores were adequate. With the exception of D90-4 and A90-4, all scales demonstrated adequate internal consistency, with Cronbach’s alpha values for the four depression scales ranging from 0.71 to 0.87 and the four anxiety scales from 0.70 to 0.90. Except for the D90-4 and A90-4, the scales fared satisfactorily in terms of validity. The four depression scales had Spearman-Brown values greater than 0.80, whereas the four anxiety scales had values greater than 0.85. In general, the scales D90-4 reliability (0.68), validity (0.65), and A90-4 reliability (0.68) performed well. Details are provided in Tables  2 and 3 .

Analysis of depression levels in FD patients

142 FD patients were assessed using the HAMD scale, and depression symptoms were shown to account for 41.5% (59/142), with severe depression symptoms (HAMD score > 24) accounting for 11.3% (16/142). In the control group, the percentage of depressed patients was 9.7%(11/113) and 2.7%(3/113) of patients with severe depression symptoms. The differences in the prevalence of depression symptoms between the two groups were statistically significant ( p  < 0.05). Besides, 61.3%, 36.6%, and 56.3% of FD patients were detected with depression symptoms by the SDS, HADS-D, and PHQ-9 self-rated scales, which were significantly higher than those in the control group, and the differences were statistically significant ( p  < 0.05), as shown in Table  4 .

In addition to displaying a greater prevalence, FD patients also had higher levels of depression. With a mean score of 47.95 ± 1.00 on the SDS, 7.62 ± 0.64 on the HAMD, 2.95 ± 0.35 on the PHQ-9, and 0.82 ± 0.10 on the D90-4, FD patients considerably outperformed healthy controls on most depression scales, as shown in Fig.  1 ; Table  4 . There were significant differences in HAMD and PHQ-9 scores between groups based on age and gender ( p  < 0.05). In comparison to the younger age group, the older age group reported greater HAMD and PHQ-9 scores. The PHQ-9 and HAMD scores of the female group were higher than those of the male group.

Comparison of the scores of the two groups in the ten scales. *, <0.05; **, <0.01; ***, <0.001

Analysis of anxiety levels in FD patients

The five scales supported the fact that FD patients had higher levels of anxiety than the general population. The average SAS in the FD group score is 47.13 ± 0.88, HAMA is 5.72 ± 0.48, and GAD-7 is 4.84 ± 4.84. The distinction from the control group was statistically significant ( p  < 0.05). More information is available in Table  5 .

There were statistically significant variations in HAMA, GAD-7, and A90-4 scores between groups, as seen in Fig.  1 , according to age and gender. The elder group had higher HAMA, GAD-7, and A90-4 scores, while women had higher HAMA, GAD-7, and A90-4 scores than men. Statistics showed that the difference was significant ( p  < 0.05). In contrast, there was no scientifically significant variation in the SAS and HADS-A scores across age and gender groups ( p  > 0.05).

Comparative analysis of different scales

The dependability of the data was verified by the correlation index for all pairwise comparisons being greater than 0.5, as shown in Fig.  2 , which compared the scores of the five depression scales for correlation. PHQ-9 demonstrated the strongest association with the HAMD score of all of them, at 0.83. The score correlations between the five scales in the assessment of anxiety measures, as shown in Fig.  3 , ranged from 0.53 to 0.77, with the best score correlation occurring between SAS and HAMA and the relatively worst correlation being between A90-4 and GAD-7.

Correlation analysis of scores among five depression scales. Numbers represented the correlation(%). The correlation was reflected by the area and color depth of the pie chart

Correlation analysis of scores among five anxiety scales. Numbers represented the correlation(%). The correlation was reflected by the area and color depth of the pie chart

Assess patients with clinical FD by anxiety and depression scales

As shown in Fig.  4 , with the application of ROC curve analysis, the SDS, HAMD, HAMD, and SDS scales’ AUCs ranged from 0.56 to 0.72 ( p  < 0.05), while the SAS, HAMA, HADS-A, A904, and GAD-7 scales’ AUCs ranged from 0.67 to 0.77. Generally, the anxiety scales demonstrated a better capability to detect FD. The three best-performing scales were the PHQ-9 (AUC = 0.72, p  < 0.05), HAMD (AUC = 0.70, p  < 0.05), and HAMA (AUC = 0.77, p  < 0.05).

ROC curves for the correlation analysis between the scales and the diagnosis of FD. ( A ) ROC curve for the depression scale; ( B ) ROC curve for the anxiety scale

Recently, the significant role of psychosocial factors in functional dyspepsia has been acknowledged by mainstream researchers [ 18 ]. A significant association between anxiety, depression, and functional dyspepsia was also demonstrated by a meta-analysis from 2023 [ 19 ]. In our study, depression symptoms were shown to account for 41.5% of HAMD, 61.3% of SDS, 36.6% of HADS-D, and 56.3% of PHQ-9. The scores of anxiety symptoms were shown to account for 47.13 ± 0.88 by SAS, 5.72 ± 0.48 by HAMA, and 4.84 ± 4.84 by GAD-7. No matter the scale employed, the proportion of anxiety or depression symptoms in FD patients was considerably larger than in control groups, which is essentially in line with previous research. Additionally, FD patients experienced considerably more severe anxiety symptoms and despair than healthy controls. Our findings highlight the fact that individuals with FD experience more severe cases of anxiety and depression symptoms than people without FD, and they also point to a substantial association between FD and anxiety and depression symptoms. There is growing attention in how psychosocial variables affect the development and progress of FD. Functional gastrointestinal discomfort may be a somatic symptom of psychosomatic illnesses, which exacerbates the patients’ psychosomatic illnesses [ 10 , 20 ]. Bidirectional brain-gut communication is one of the proposed pathways [ 21 ]. These correlation investigations indicate that it might be beneficial to treat FD by quickly and accurately assessing the psychosomatic symptoms of FD patients [ 20 , 22 ]. The prognosis and regression of FD patients are impacted by the lack of objective criteria for assessing the psychological symptoms of FD patients in clinical practice and the lack of expertise in identifying and treating psychological illnesses among the majority of gastrointestinal practitioners. The two scales that psychiatrists use most frequently to identify bipolar disorder are the HAMD and HAMA. These two scales must be administered by psychiatric psychologists[ 23 ]. They will become biased and lose their effectiveness when non-professionals use them, which has a negative impact on non-psychiatrist practitioners and is harmful to the management and treatment of the illness.

There are currently more than 10 psychological evaluation scales used in clinical assessments of psychiatric illnesses in addition to HAMD and HAMA. It is challenging for gastroenterologists to screen patients for psychological disorders and is detrimental to the management and treatment of diseases since there is no relevant research on the effectiveness of various psychological evaluation samples used in digestive-related diseases. We evaluated and compared the score correlations, assessment consistency, reliability, and validity of the remaining four anxiety measures (SAS, HADS-A, GAD-7, and A90-4) and four depression scales (SDS, HADS-D, HPQ-9, and D90-4) in this study, which uses the author’s HAMA and HAMD as the standard. All of the measures we examined had strong associations. Patients with mental health issues can be assessed by choosing one of them. PHQ-9 demonstrated the strongest connection with HAMD (rs = 0.83, p  < 0.05) among all of the depression scores. The association between SAS and HAMA was the strongest among the anxiety scales (rs = 0.77, p  < 0.05). The clinician-rated measures used in psychiatric diagnosis are more consistently measured by the two scales, PHQ-9 and SAS, which seem to be simple to complete. We propose that doctors could early screen for anxiety and depression symptoms in FD patients using these two scales in addition to HAMA and HAMD.

Although the pooled prevalence of FD gradually decreased due to increasing medical level and improved life quality from 1990 to 2020 (12.4% [8.2–18.3] in 1990–2002 versus 7.3% [6.1–8.7] in 2013–2020) [ 3 ], FD-related health care operations are still imposing a significant financial burden on the healthcare system, whose global annual cost exceeds $18 billion [ 24 , 25 ]. After considering for something like the price of medical care, drug rehab, and time off work, the average annual cost per FD patient in the US is $699 [ 4 ]. Patients with FD who are depressed or anxious have more severe physical symptoms, require more medical care, and spend more time recovering from sickness [ 1 ]. This underlines how crucial it is to promptly recognize and detect FD patients who are depressed and anxious. By analyzing the ROC curves of the scales in FD patients and healthy groups, we discovered that all 10 scales under investigation showed a strong association among FD with depression and anxiety symptoms, with the PHQ-9 (AUC = 0.72), HAMD (AUC = 0.70), and HAMA (AUC = 0.77) scales being particularly capable of detecting FD. This suggests that detecting patients with anxiety and depression symptoms aids in FD patient diagnosis. The identification of FD in the population through the detection of patients with anxiety and depression symptoms is also useful, and the patient’s state is improved with the support of a gastroenterologist [ 26 , 27 , 28 ]. Consequently, there is to believe that early detection and treatment of such people will assist in halting the progression of the disease and preventing the disease from upgrading from a functional to an organic morbid symptom.

Numerous factors could have an impact on the original study outcomes. Due to the retrospective nature of this study, flaws like selection bias may be unavoidably introduced. Second, this study used a small number of participants and was done at a single center, both of which may have introduced some sample bias. To investigate these topics in greater depth, additional studies with numerous centers and sizable samples are required. Furthermore, it is still unclear what role mental aspects have in the pathophysiology and prognosis of FD patients, and more research is required to establish the causative link [ 29 , 30 , 31 ]. Perhaps the facts and recommendations from our study will help figure out the causes of FD and the way to manage it.

Functional dyspepsia patients are more prone than healthy people to experience both combined anxiety and depression symptoms, and their anxiety and depression symptoms are more severe. Ten psychological scales were used, and results in FD patients showed good correlations. The PHQ-9, SAS, HAMD, and HAMA scales all performed well in spotting FD when it was present with anxiety or depression symptoms. In order to assess anxiety and depression symptoms in patients, doctors might use the SAS and PHQ-9 scales as a guide and point of reference.

Data availability

The datasets generated for this study are available on request to the corresponding author.

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Acknowledgements

The authors would like to thank all participants who participated in the study.

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Yejiao Ruan and Hao Lin contributed equally to this work.

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The Second Affiliated Hospital & Yuying Children’s Hospital of Wenzhou Medical University, 1111 East Wenzhou Dadao, Longwan District, Wenzhou, 325000, Zhejiang, China

Yejiao Ruan, Hao Lin, Xinru Lu, Yiying Lin, Jian Sun, Zhenzhai Cai & Xiaoyan Chen

The Second Clinical Medical College, Wenzhou Medical University, Wenzhou, Zhejiang, China

Cengqi Xu & Lingjun Zhou

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Conceptualization and methodology, ZZ. C. and XY. C.; Investigation, YJ. R., H.L., and XR. L.; Validation, XY. C. and ZZ. C.; Data curation, XR.L., YY. L., JA. S., CQ. X. and LJ. Z.; Visualization, YJ. R. and XY. C.; Project administration, XY. C. and H. L.; Supervision, YJ. R.; Writing-original draft, YJ. R and H.L.; Writing-review and editing, XY. C.; All authors have read and agreed to the published version of the manuscript.

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Correspondence to Zhenzhai Cai or Xiaoyan Chen .

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Ruan, Y., Lin, H., Lu, X. et al. Application and value of anxiety and depression scale in patients with functional dyspepsia. BMC Psychol 12 , 244 (2024). https://doi.org/10.1186/s40359-024-01744-3

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Received : 23 March 2023

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DOI : https://doi.org/10.1186/s40359-024-01744-3

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