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What Is a Case Study?

Weighing the pros and cons of this method of research

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."

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Home » Case Study – Methods, Examples and Guide

Case Study – Methods, Examples and Guide

Table of Contents

A case study is a research method that involves an in-depth examination and analysis of a particular phenomenon or case, such as an individual, organization, community, event, or situation.

It is a qualitative research approach that aims to provide a detailed and comprehensive understanding of the case being studied. Case studies typically involve multiple sources of data, including interviews, observations, documents, and artifacts, which are analyzed using various techniques, such as content analysis, thematic analysis, and grounded theory. The findings of a case study are often used to develop theories, inform policy or practice, or generate new research questions.

Types of Case Study

Types and Methods of Case Study are as follows:

Single-Case Study

A single-case study is an in-depth analysis of a single case. This type of case study is useful when the researcher wants to understand a specific phenomenon in detail.

For Example , A researcher might conduct a single-case study on a particular individual to understand their experiences with a particular health condition or a specific organization to explore their management practices. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a single-case study are often used to generate new research questions, develop theories, or inform policy or practice.

Multiple-Case Study

A multiple-case study involves the analysis of several cases that are similar in nature. This type of case study is useful when the researcher wants to identify similarities and differences between the cases.

For Example, a researcher might conduct a multiple-case study on several companies to explore the factors that contribute to their success or failure. The researcher collects data from each case, compares and contrasts the findings, and uses various techniques to analyze the data, such as comparative analysis or pattern-matching. The findings of a multiple-case study can be used to develop theories, inform policy or practice, or generate new research questions.

Exploratory Case Study

An exploratory case study is used to explore a new or understudied phenomenon. This type of case study is useful when the researcher wants to generate hypotheses or theories about the phenomenon.

For Example, a researcher might conduct an exploratory case study on a new technology to understand its potential impact on society. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as grounded theory or content analysis. The findings of an exploratory case study can be used to generate new research questions, develop theories, or inform policy or practice.

Descriptive Case Study

A descriptive case study is used to describe a particular phenomenon in detail. This type of case study is useful when the researcher wants to provide a comprehensive account of the phenomenon.

For Example, a researcher might conduct a descriptive case study on a particular community to understand its social and economic characteristics. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a descriptive case study can be used to inform policy or practice or generate new research questions.

Instrumental Case Study

An instrumental case study is used to understand a particular phenomenon that is instrumental in achieving a particular goal. This type of case study is useful when the researcher wants to understand the role of the phenomenon in achieving the goal.

For Example, a researcher might conduct an instrumental case study on a particular policy to understand its impact on achieving a particular goal, such as reducing poverty. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of an instrumental case study can be used to inform policy or practice or generate new research questions.

Case Study Data Collection Methods

Here are some common data collection methods for case studies:

Interviews involve asking questions to individuals who have knowledge or experience relevant to the case study. Interviews can be structured (where the same questions are asked to all participants) or unstructured (where the interviewer follows up on the responses with further questions). Interviews can be conducted in person, over the phone, or through video conferencing.

Observations

Observations involve watching and recording the behavior and activities of individuals or groups relevant to the case study. Observations can be participant (where the researcher actively participates in the activities) or non-participant (where the researcher observes from a distance). Observations can be recorded using notes, audio or video recordings, or photographs.

Documents can be used as a source of information for case studies. Documents can include reports, memos, emails, letters, and other written materials related to the case study. Documents can be collected from the case study participants or from public sources.

Surveys involve asking a set of questions to a sample of individuals relevant to the case study. Surveys can be administered in person, over the phone, through mail or email, or online. Surveys can be used to gather information on attitudes, opinions, or behaviors related to the case study.

Artifacts are physical objects relevant to the case study. Artifacts can include tools, equipment, products, or other objects that provide insights into the case study phenomenon.

How to conduct Case Study Research

Conducting a case study research involves several steps that need to be followed to ensure the quality and rigor of the study. Here are the steps to conduct case study research:

• Define the research questions: The first step in conducting a case study research is to define the research questions. The research questions should be specific, measurable, and relevant to the case study phenomenon under investigation.
• Select the case: The next step is to select the case or cases to be studied. The case should be relevant to the research questions and should provide rich and diverse data that can be used to answer the research questions.
• Collect data: Data can be collected using various methods, such as interviews, observations, documents, surveys, and artifacts. The data collection method should be selected based on the research questions and the nature of the case study phenomenon.
• Analyze the data: The data collected from the case study should be analyzed using various techniques, such as content analysis, thematic analysis, or grounded theory. The analysis should be guided by the research questions and should aim to provide insights and conclusions relevant to the research questions.
• Draw conclusions: The conclusions drawn from the case study should be based on the data analysis and should be relevant to the research questions. The conclusions should be supported by evidence and should be clearly stated.
• Validate the findings: The findings of the case study should be validated by reviewing the data and the analysis with participants or other experts in the field. This helps to ensure the validity and reliability of the findings.
• Write the report: The final step is to write the report of the case study research. The report should provide a clear description of the case study phenomenon, the research questions, the data collection methods, the data analysis, the findings, and the conclusions. The report should be written in a clear and concise manner and should follow the guidelines for academic writing.

Examples of Case Study

Here are some examples of case study research:

• The Hawthorne Studies : Conducted between 1924 and 1932, the Hawthorne Studies were a series of case studies conducted by Elton Mayo and his colleagues to examine the impact of work environment on employee productivity. The studies were conducted at the Hawthorne Works plant of the Western Electric Company in Chicago and included interviews, observations, and experiments.
• The Stanford Prison Experiment: Conducted in 1971, the Stanford Prison Experiment was a case study conducted by Philip Zimbardo to examine the psychological effects of power and authority. The study involved simulating a prison environment and assigning participants to the role of guards or prisoners. The study was controversial due to the ethical issues it raised.
• The Challenger Disaster: The Challenger Disaster was a case study conducted to examine the causes of the Space Shuttle Challenger explosion in 1986. The study included interviews, observations, and analysis of data to identify the technical, organizational, and cultural factors that contributed to the disaster.
• The Enron Scandal: The Enron Scandal was a case study conducted to examine the causes of the Enron Corporation’s bankruptcy in 2001. The study included interviews, analysis of financial data, and review of documents to identify the accounting practices, corporate culture, and ethical issues that led to the company’s downfall.
• The Fukushima Nuclear Disaster : The Fukushima Nuclear Disaster was a case study conducted to examine the causes of the nuclear accident that occurred at the Fukushima Daiichi Nuclear Power Plant in Japan in 2011. The study included interviews, analysis of data, and review of documents to identify the technical, organizational, and cultural factors that contributed to the disaster.

Application of Case Study

Case studies have a wide range of applications across various fields and industries. Here are some examples:

Business and Management

Case studies are widely used in business and management to examine real-life situations and develop problem-solving skills. Case studies can help students and professionals to develop a deep understanding of business concepts, theories, and best practices.

Case studies are used in healthcare to examine patient care, treatment options, and outcomes. Case studies can help healthcare professionals to develop critical thinking skills, diagnose complex medical conditions, and develop effective treatment plans.

Case studies are used in education to examine teaching and learning practices. Case studies can help educators to develop effective teaching strategies, evaluate student progress, and identify areas for improvement.

Social Sciences

Case studies are widely used in social sciences to examine human behavior, social phenomena, and cultural practices. Case studies can help researchers to develop theories, test hypotheses, and gain insights into complex social issues.

Law and Ethics

Case studies are used in law and ethics to examine legal and ethical dilemmas. Case studies can help lawyers, policymakers, and ethical professionals to develop critical thinking skills, analyze complex cases, and make informed decisions.

Purpose of Case Study

The purpose of a case study is to provide a detailed analysis of a specific phenomenon, issue, or problem in its real-life context. A case study is a qualitative research method that involves the in-depth exploration and analysis of a particular case, which can be an individual, group, organization, event, or community.

The primary purpose of a case study is to generate a comprehensive and nuanced understanding of the case, including its history, context, and dynamics. Case studies can help researchers to identify and examine the underlying factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and detailed understanding of the case, which can inform future research, practice, or policy.

Case studies can also serve other purposes, including:

• Illustrating a theory or concept: Case studies can be used to illustrate and explain theoretical concepts and frameworks, providing concrete examples of how they can be applied in real-life situations.
• Developing hypotheses: Case studies can help to generate hypotheses about the causal relationships between different factors and outcomes, which can be tested through further research.
• Providing insight into complex issues: Case studies can provide insights into complex and multifaceted issues, which may be difficult to understand through other research methods.
• Informing practice or policy: Case studies can be used to inform practice or policy by identifying best practices, lessons learned, or areas for improvement.

Advantages of Case Study Research

There are several advantages of case study research, including:

• In-depth exploration: Case study research allows for a detailed exploration and analysis of a specific phenomenon, issue, or problem in its real-life context. This can provide a comprehensive understanding of the case and its dynamics, which may not be possible through other research methods.
• Rich data: Case study research can generate rich and detailed data, including qualitative data such as interviews, observations, and documents. This can provide a nuanced understanding of the case and its complexity.
• Holistic perspective: Case study research allows for a holistic perspective of the case, taking into account the various factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and comprehensive understanding of the case.
• Theory development: Case study research can help to develop and refine theories and concepts by providing empirical evidence and concrete examples of how they can be applied in real-life situations.
• Practical application: Case study research can inform practice or policy by identifying best practices, lessons learned, or areas for improvement.
• Contextualization: Case study research takes into account the specific context in which the case is situated, which can help to understand how the case is influenced by the social, cultural, and historical factors of its environment.

Limitations of Case Study Research

There are several limitations of case study research, including:

• Limited generalizability : Case studies are typically focused on a single case or a small number of cases, which limits the generalizability of the findings. The unique characteristics of the case may not be applicable to other contexts or populations, which may limit the external validity of the research.
• Biased sampling: Case studies may rely on purposive or convenience sampling, which can introduce bias into the sample selection process. This may limit the representativeness of the sample and the generalizability of the findings.
• Subjectivity: Case studies rely on the interpretation of the researcher, which can introduce subjectivity into the analysis. The researcher’s own biases, assumptions, and perspectives may influence the findings, which may limit the objectivity of the research.
• Limited control: Case studies are typically conducted in naturalistic settings, which limits the control that the researcher has over the environment and the variables being studied. This may limit the ability to establish causal relationships between variables.
• Time-consuming: Case studies can be time-consuming to conduct, as they typically involve a detailed exploration and analysis of a specific case. This may limit the feasibility of conducting multiple case studies or conducting case studies in a timely manner.
• Resource-intensive: Case studies may require significant resources, including time, funding, and expertise. This may limit the ability of researchers to conduct case studies in resource-constrained settings.

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• What Is a Case Study? | Definition, Examples & Methods

What Is a Case Study? | Definition, Examples & Methods

Published on May 8, 2019 by Shona McCombes . Revised on November 20, 2023.

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

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

Table of contents

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

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

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

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

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

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

TipIf your research is more practical in nature and aims to simultaneously investigate an issue as you solve it, consider conducting action research instead.

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

Example of an outlying case studyIn the 1960s the town of Roseto, Pennsylvania was discovered to have extremely low rates of heart disease compared to the US average. It became an important case study for understanding previously neglected causes of heart disease.

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

Example of a representative case studyIn the 1920s, two sociologists used Muncie, Indiana as a case study of a typical American city that supposedly exemplified the changing culture of the US at the time.

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

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

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

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

Example of a mixed methods case studyFor a case study of a wind farm development in a rural area, you could collect quantitative data on employment rates and business revenue, collect qualitative data on local people’s perceptions and experiences, and analyze local and national media coverage of the development.

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

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

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

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

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

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

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Case Study Research Method in Psychology

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On This Page:

Case studies are in-depth investigations of a person, group, event, or community. Typically, data is gathered from various sources using several methods (e.g., observations & interviews).

The case study research method originated in clinical medicine (the case history, i.e., the patient’s personal history). In psychology, case studies are often confined to the study of a particular individual.

The information is mainly biographical and relates to events in the individual’s past (i.e., retrospective), as well as to significant events that are currently occurring in his or her everyday life.

The case study is not a research method, but researchers select methods of data collection and analysis that will generate material suitable for case studies.

Freud (1909a, 1909b) conducted very detailed investigations into the private lives of his patients in an attempt to both understand and help them overcome their illnesses.

This makes it clear that the case study is a method that should only be used by a psychologist, therapist, or psychiatrist, i.e., someone with a professional qualification.

There is an ethical issue of competence. Only someone qualified to diagnose and treat a person can conduct a formal case study relating to atypical (i.e., abnormal) behavior or atypical development.

 Famous Case Studies

• Anna O – One of the most famous case studies, documenting psychoanalyst Josef Breuer’s treatment of “Anna O” (real name Bertha Pappenheim) for hysteria in the late 1800s using early psychoanalytic theory.
• Little Hans – A child psychoanalysis case study published by Sigmund Freud in 1909 analyzing his five-year-old patient Herbert Graf’s house phobia as related to the Oedipus complex.
• Bruce/Brenda – Gender identity case of the boy (Bruce) whose botched circumcision led psychologist John Money to advise gender reassignment and raise him as a girl (Brenda) in the 1960s.
• Genie Wiley – Linguistics/psychological development case of the victim of extreme isolation abuse who was studied in 1970s California for effects of early language deprivation on acquiring speech later in life.
• Phineas Gage – One of the most famous neuropsychology case studies analyzes personality changes in railroad worker Phineas Gage after an 1848 brain injury involving a tamping iron piercing his skull.

Clinical Case Studies

• Studying the effectiveness of psychotherapy approaches with an individual patient
• Assessing and treating mental illnesses like depression, anxiety disorders, PTSD
• Neuropsychological cases investigating brain injuries or disorders

Child Psychology Case Studies

• Studying psychological development from birth through adolescence
• Cases of learning disabilities, autism spectrum disorders, ADHD
• Effects of trauma, abuse, deprivation on development

Types of Case Studies

• Explanatory case studies : Used to explore causation in order to find underlying principles. Helpful for doing qualitative analysis to explain presumed causal links.
• Exploratory case studies : Used to explore situations where an intervention being evaluated has no clear set of outcomes. It helps define questions and hypotheses for future research.
• Descriptive case studies : Describe an intervention or phenomenon and the real-life context in which it occurred. It is helpful for illustrating certain topics within an evaluation.
• Multiple-case studies : Used to explore differences between cases and replicate findings across cases. Helpful for comparing and contrasting specific cases.
• Intrinsic : Used to gain a better understanding of a particular case. Helpful for capturing the complexity of a single case.
• Collective : Used to explore a general phenomenon using multiple case studies. Helpful for jointly studying a group of cases in order to inquire into the phenomenon.

Where Do You Find Data for a Case Study?

There are several places to find data for a case study. The key is to gather data from multiple sources to get a complete picture of the case and corroborate facts or findings through triangulation of evidence. Most of this information is likely qualitative (i.e., verbal description rather than measurement), but the psychologist might also collect numerical data.

1. Primary sources

• Interviews – Interviewing key people related to the case to get their perspectives and insights. The interview is an extremely effective procedure for obtaining information about an individual, and it may be used to collect comments from the person’s friends, parents, employer, workmates, and others who have a good knowledge of the person, as well as to obtain facts from the person him or herself.
• Observations – Observing behaviors, interactions, processes, etc., related to the case as they unfold in real-time.
• Documents & Records – Reviewing private documents, diaries, public records, correspondence, meeting minutes, etc., relevant to the case.

2. Secondary sources

• News/Media – News coverage of events related to the case study.
• Academic articles – Journal articles, dissertations etc. that discuss the case.
• Government reports – Official data and records related to the case context.
• Books/films – Books, documentaries or films discussing the case.

3. Archival records

Searching historical archives, museum collections and databases to find relevant documents, visual/audio records related to the case history and context.

Public archives like newspapers, organizational records, photographic collections could all include potentially relevant pieces of information to shed light on attitudes, cultural perspectives, common practices and historical contexts related to psychology.

4. Organizational records

Organizational records offer the advantage of often having large datasets collected over time that can reveal or confirm psychological insights.

Of course, privacy and ethical concerns regarding confidential data must be navigated carefully.

However, with proper protocols, organizational records can provide invaluable context and empirical depth to qualitative case studies exploring the intersection of psychology and organizations.

• Organizational/industrial psychology research : Organizational records like employee surveys, turnover/retention data, policies, incident reports etc. may provide insight into topics like job satisfaction, workplace culture and dynamics, leadership issues, employee behaviors etc.
• Clinical psychology : Therapists/hospitals may grant access to anonymized medical records to study aspects like assessments, diagnoses, treatment plans etc. This could shed light on clinical practices.
• School psychology : Studies could utilize anonymized student records like test scores, grades, disciplinary issues, and counseling referrals to study child development, learning barriers, effectiveness of support programs, and more.

How do I Write a Case Study in Psychology?

Follow specified case study guidelines provided by a journal or your psychology tutor. General components of clinical case studies include: background, symptoms, assessments, diagnosis, treatment, and outcomes. Interpreting the information means the researcher decides what to include or leave out. A good case study should always clarify which information is the factual description and which is an inference or the researcher’s opinion.

1. Introduction

• Provide background on the case context and why it is of interest, presenting background information like demographics, relevant history, and presenting problem.
• Compare briefly to similar published cases if applicable. Clearly state the focus/importance of the case.

2. Case Presentation

• Describe the presenting problem in detail, including symptoms, duration,and impact on daily life.
• Include client demographics like age and gender, information about social relationships, and mental health history.
• Describe all physical, emotional, and/or sensory symptoms reported by the client.
• Use patient quotes to describe the initial complaint verbatim. Follow with full-sentence summaries of relevant history details gathered, including key components that led to a working diagnosis.
• Summarize clinical exam results, namely orthopedic/neurological tests, imaging, lab tests, etc. Note actual results rather than subjective conclusions. Provide images if clearly reproducible/anonymized.
• Clearly state the working diagnosis or clinical impression before transitioning to management.

3. Management and Outcome

• Indicate the total duration of care and number of treatments given over what timeframe. Use specific names/descriptions for any therapies/interventions applied.
• Present the results of the intervention,including any quantitative or qualitative data collected.
• For outcomes, utilize visual analog scales for pain, medication usage logs, etc., if possible. Include patient self-reports of improvement/worsening of symptoms. Note the reason for discharge/end of care.

4. Discussion

• Analyze the case, exploring contributing factors, limitations of the study, and connections to existing research.
• Analyze the effectiveness of the intervention,considering factors like participant adherence, limitations of the study, and potential alternative explanations for the results.
• Identify any questions raised in the case analysis and relate insights to established theories and current research if applicable. Avoid definitive claims about physiological explanations.
• Offer clinical implications, and suggest future research directions.

5. Additional Items

• Thank specific assistants for writing support only. No patient acknowledgments.
• References should directly support any key claims or quotes included.
• Use tables/figures/images only if substantially informative. Include permissions and legends/explanatory notes.
• Provides detailed (rich qualitative) information.
• Provides insight for further research.
• Permitting investigation of otherwise impractical (or unethical) situations.

Case studies allow a researcher to investigate a topic in far more detail than might be possible if they were trying to deal with a large number of research participants (nomothetic approach) with the aim of ‘averaging’.

Because of their in-depth, multi-sided approach, case studies often shed light on aspects of human thinking and behavior that would be unethical or impractical to study in other ways.

Research that only looks into the measurable aspects of human behavior is not likely to give us insights into the subjective dimension of experience, which is important to psychoanalytic and humanistic psychologists.

Case studies are often used in exploratory research. They can help us generate new ideas (that might be tested by other methods). They are an important way of illustrating theories and can help show how different aspects of a person’s life are related to each other.

The method is, therefore, important for psychologists who adopt a holistic point of view (i.e., humanistic psychologists ).

Limitations

• Lacking scientific rigor and providing little basis for generalization of results to the wider population.
• Researchers’ own subjective feelings may influence the case study (researcher bias).
• Difficult to replicate.
• Time-consuming and expensive.
• The volume of data, together with the time restrictions in place, impacted the depth of analysis that was possible within the available resources.

Because a case study deals with only one person/event/group, we can never be sure if the case study investigated is representative of the wider body of “similar” instances. This means the conclusions drawn from a particular case may not be transferable to other settings.

Because case studies are based on the analysis of qualitative (i.e., descriptive) data , a lot depends on the psychologist’s interpretation of the information she has acquired.

This means that there is a lot of scope for Anna O , and it could be that the subjective opinions of the psychologist intrude in the assessment of what the data means.

For example, Freud has been criticized for producing case studies in which the information was sometimes distorted to fit particular behavioral theories (e.g., Little Hans ).

This is also true of Money’s interpretation of the Bruce/Brenda case study (Diamond, 1997) when he ignored evidence that went against his theory.

Breuer, J., & Freud, S. (1895).  Studies on hysteria . Standard Edition 2: London.

Curtiss, S. (1981). Genie: The case of a modern wild child .

Diamond, M., & Sigmundson, K. (1997). Sex Reassignment at Birth: Long-term Review and Clinical Implications. Archives of Pediatrics & Adolescent Medicine , 151(3), 298-304

Freud, S. (1909a). Analysis of a phobia of a five year old boy. In The Pelican Freud Library (1977), Vol 8, Case Histories 1, pages 169-306

Freud, S. (1909b). Bemerkungen über einen Fall von Zwangsneurose (Der “Rattenmann”). Jb. psychoanal. psychopathol. Forsch ., I, p. 357-421; GW, VII, p. 379-463; Notes upon a case of obsessional neurosis, SE , 10: 151-318.

Harlow J. M. (1848). Passage of an iron rod through the head.  Boston Medical and Surgical Journal, 39 , 389–393.

Harlow, J. M. (1868).  Recovery from the Passage of an Iron Bar through the Head .  Publications of the Massachusetts Medical Society. 2  (3), 327-347.

Money, J., & Ehrhardt, A. A. (1972).  Man & Woman, Boy & Girl : The Differentiation and Dimorphism of Gender Identity from Conception to Maturity. Baltimore, Maryland: Johns Hopkins University Press.

Money, J., & Tucker, P. (1975). Sexual signatures: On being a man or a woman.

Further Information

• Case Study Approach
• Case Study Method
• Enhancing the Quality of Case Studies in Health Services Research
• “We do things together” A case study of “couplehood” in dementia
• Using mixed methods for evaluating an integrative approach to cancer care: a case study

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

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

Research question

• Conceptual framework
• Conceptual vs. theoretical framework

Data collection

• Qualitative research methods
• Focus groups
• Observational research

What is a case study?

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

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

Case studies

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

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

Definition of a case study

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

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

Characteristics of case studies

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

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

The role of case studies in research

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

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

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

What is the purpose of a case study?

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

Why use case studies in qualitative research?

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

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

The explanatory, exploratory, and descriptive roles of case studies

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

The impact of case studies on knowledge development

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

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

Types of case studies

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

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

Exploratory case studies

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

Descriptive case studies

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

Explanatory case studies

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

Intrinsic, instrumental, and collective case studies

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

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

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

Critical information systems research

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

Health research

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

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

Asthma research studies

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

Other fields

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

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

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

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

Propositions

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

Units of analysis

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

Argumentation

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

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

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

Defining the research question

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

Selecting and defining the case

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

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

Developing a detailed case study protocol

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

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

Collecting data

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

Analyzing and interpreting data

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

Writing the case study report

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

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

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

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

Observations

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

Documents and artifacts

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

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

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

Ensuring the quality of data collection

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

Data analysis

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

Organizing the data

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

Categorizing and coding the data

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

Identifying patterns and themes

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

Interpreting the data

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

Verification of the data

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

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

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

Benefits include the following:

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

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

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

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

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Organizing Your Social Sciences Research Assignments

• Annotated Bibliography
• Analyzing a Scholarly Journal Article
• Group Presentations
• Dealing with Nervousness
• Using Visual Aids
• Grading Someone Else's Paper
• Types of Structured Group Activities
• Group Project Survival Skills
• Leading a Class Discussion
• Multiple Book Review Essay
• Reviewing Collected Works
• Writing a Case Analysis Paper
• Writing a Case Study
• About Informed Consent
• Writing Field Notes
• Writing a Policy Memo
• Writing a Reflective Paper
• Writing a Research Proposal
• Generative AI and Writing
• Acknowledgments

A case study research paper examines a person, place, event, condition, phenomenon, or other type of subject of analysis in order to extrapolate  key themes and results that help predict future trends, illuminate previously hidden issues that can be applied to practice, and/or provide a means for understanding an important research problem with greater clarity. A case study research paper usually examines a single subject of analysis, but case study papers can also be designed as a comparative investigation that shows relationships between two or more subjects. The methods used to study a case can rest within a quantitative, qualitative, or mixed-method investigative paradigm.

Case Studies. Writing@CSU. Colorado State University; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010 ; “What is a Case Study?” In Swanborn, Peter G. Case Study Research: What, Why and How? London: SAGE, 2010.

How to Approach Writing a Case Study Research Paper

General information about how to choose a topic to investigate can be found under the " Choosing a Research Problem " tab in the Organizing Your Social Sciences Research Paper writing guide. Review this page because it may help you identify a subject of analysis that can be investigated using a case study design.

However, identifying a case to investigate involves more than choosing the research problem . A case study encompasses a problem contextualized around the application of in-depth analysis, interpretation, and discussion, often resulting in specific recommendations for action or for improving existing conditions. As Seawright and Gerring note, practical considerations such as time and access to information can influence case selection, but these issues should not be the sole factors used in describing the methodological justification for identifying a particular case to study. Given this, selecting a case includes considering the following:

• The case represents an unusual or atypical example of a research problem that requires more in-depth analysis? Cases often represent a topic that rests on the fringes of prior investigations because the case may provide new ways of understanding the research problem. For example, if the research problem is to identify strategies to improve policies that support girl's access to secondary education in predominantly Muslim nations, you could consider using Azerbaijan as a case study rather than selecting a more obvious nation in the Middle East. Doing so may reveal important new insights into recommending how governments in other predominantly Muslim nations can formulate policies that support improved access to education for girls.
• The case provides important insight or illuminate a previously hidden problem? In-depth analysis of a case can be based on the hypothesis that the case study will reveal trends or issues that have not been exposed in prior research or will reveal new and important implications for practice. For example, anecdotal evidence may suggest drug use among homeless veterans is related to their patterns of travel throughout the day. Assuming prior studies have not looked at individual travel choices as a way to study access to illicit drug use, a case study that observes a homeless veteran could reveal how issues of personal mobility choices facilitate regular access to illicit drugs. Note that it is important to conduct a thorough literature review to ensure that your assumption about the need to reveal new insights or previously hidden problems is valid and evidence-based.
• The case challenges and offers a counter-point to prevailing assumptions? Over time, research on any given topic can fall into a trap of developing assumptions based on outdated studies that are still applied to new or changing conditions or the idea that something should simply be accepted as "common sense," even though the issue has not been thoroughly tested in current practice. A case study analysis may offer an opportunity to gather evidence that challenges prevailing assumptions about a research problem and provide a new set of recommendations applied to practice that have not been tested previously. For example, perhaps there has been a long practice among scholars to apply a particular theory in explaining the relationship between two subjects of analysis. Your case could challenge this assumption by applying an innovative theoretical framework [perhaps borrowed from another discipline] to explore whether this approach offers new ways of understanding the research problem. Taking a contrarian stance is one of the most important ways that new knowledge and understanding develops from existing literature.
• The case provides an opportunity to pursue action leading to the resolution of a problem? Another way to think about choosing a case to study is to consider how the results from investigating a particular case may result in findings that reveal ways in which to resolve an existing or emerging problem. For example, studying the case of an unforeseen incident, such as a fatal accident at a railroad crossing, can reveal hidden issues that could be applied to preventative measures that contribute to reducing the chance of accidents in the future. In this example, a case study investigating the accident could lead to a better understanding of where to strategically locate additional signals at other railroad crossings so as to better warn drivers of an approaching train, particularly when visibility is hindered by heavy rain, fog, or at night.
• The case offers a new direction in future research? A case study can be used as a tool for an exploratory investigation that highlights the need for further research about the problem. A case can be used when there are few studies that help predict an outcome or that establish a clear understanding about how best to proceed in addressing a problem. For example, after conducting a thorough literature review [very important!], you discover that little research exists showing the ways in which women contribute to promoting water conservation in rural communities of east central Africa. A case study of how women contribute to saving water in a rural village of Uganda can lay the foundation for understanding the need for more thorough research that documents how women in their roles as cooks and family caregivers think about water as a valuable resource within their community. This example of a case study could also point to the need for scholars to build new theoretical frameworks around the topic [e.g., applying feminist theories of work and family to the issue of water conservation].

Eisenhardt, Kathleen M. “Building Theories from Case Study Research.” Academy of Management Review 14 (October 1989): 532-550; Emmel, Nick. Sampling and Choosing Cases in Qualitative Research: A Realist Approach . Thousand Oaks, CA: SAGE Publications, 2013; Gerring, John. “What Is a Case Study and What Is It Good for?” American Political Science Review 98 (May 2004): 341-354; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Seawright, Jason and John Gerring. "Case Selection Techniques in Case Study Research." Political Research Quarterly 61 (June 2008): 294-308.

Structure and Writing Style

The purpose of a paper in the social sciences designed around a case study is to thoroughly investigate a subject of analysis in order to reveal a new understanding about the research problem and, in so doing, contributing new knowledge to what is already known from previous studies. In applied social sciences disciplines [e.g., education, social work, public administration, etc.], case studies may also be used to reveal best practices, highlight key programs, or investigate interesting aspects of professional work.

In general, the structure of a case study research paper is not all that different from a standard college-level research paper. However, there are subtle differences you should be aware of. Here are the key elements to organizing and writing a case study research paper.

I.  Introduction

As with any research paper, your introduction should serve as a roadmap for your readers to ascertain the scope and purpose of your study . The introduction to a case study research paper, however, should not only describe the research problem and its significance, but you should also succinctly describe why the case is being used and how it relates to addressing the problem. The two elements should be linked. With this in mind, a good introduction answers these four questions:

• What is being studied? Describe the research problem and describe the subject of analysis [the case] you have chosen to address the problem. Explain how they are linked and what elements of the case will help to expand knowledge and understanding about the problem.
• Why is this topic important to investigate? Describe the significance of the research problem and state why a case study design and the subject of analysis that the paper is designed around is appropriate in addressing the problem.
• What did we know about this topic before I did this study? Provide background that helps lead the reader into the more in-depth literature review to follow. If applicable, summarize prior case study research applied to the research problem and why it fails to adequately address the problem. Describe why your case will be useful. If no prior case studies have been used to address the research problem, explain why you have selected this subject of analysis.
• How will this study advance new knowledge or new ways of understanding? Explain why your case study will be suitable in helping to expand knowledge and understanding about the research problem.

Each of these questions should be addressed in no more than a few paragraphs. Exceptions to this can be when you are addressing a complex research problem or subject of analysis that requires more in-depth background information.

II.  Literature Review

The literature review for a case study research paper is generally structured the same as it is for any college-level research paper. The difference, however, is that the literature review is focused on providing background information and  enabling historical interpretation of the subject of analysis in relation to the research problem the case is intended to address . This includes synthesizing studies that help to:

• Place relevant works in the context of their contribution to understanding the case study being investigated . This would involve summarizing studies that have used a similar subject of analysis to investigate the research problem. If there is literature using the same or a very similar case to study, you need to explain why duplicating past research is important [e.g., conditions have changed; prior studies were conducted long ago, etc.].
• Describe the relationship each work has to the others under consideration that informs the reader why this case is applicable . Your literature review should include a description of any works that support using the case to investigate the research problem and the underlying research questions.
• Identify new ways to interpret prior research using the case study . If applicable, review any research that has examined the research problem using a different research design. Explain how your use of a case study design may reveal new knowledge or a new perspective or that can redirect research in an important new direction.
• Resolve conflicts amongst seemingly contradictory previous studies . This refers to synthesizing any literature that points to unresolved issues of concern about the research problem and describing how the subject of analysis that forms the case study can help resolve these existing contradictions.
• Point the way in fulfilling a need for additional research . Your review should examine any literature that lays a foundation for understanding why your case study design and the subject of analysis around which you have designed your study may reveal a new way of approaching the research problem or offer a perspective that points to the need for additional research.
• Expose any gaps that exist in the literature that the case study could help to fill . Summarize any literature that not only shows how your subject of analysis contributes to understanding the research problem, but how your case contributes to a new way of understanding the problem that prior research has failed to do.
• Locate your own research within the context of existing literature [very important!] . Collectively, your literature review should always place your case study within the larger domain of prior research about the problem. The overarching purpose of reviewing pertinent literature in a case study paper is to demonstrate that you have thoroughly identified and synthesized prior studies in relation to explaining the relevance of the case in addressing the research problem.

III.  Method

In this section, you explain why you selected a particular case [i.e., subject of analysis] and the strategy you used to identify and ultimately decide that your case was appropriate in addressing the research problem. The way you describe the methods used varies depending on the type of subject of analysis that constitutes your case study.

If your subject of analysis is an incident or event . In the social and behavioral sciences, the event or incident that represents the case to be studied is usually bounded by time and place, with a clear beginning and end and with an identifiable location or position relative to its surroundings. The subject of analysis can be a rare or critical event or it can focus on a typical or regular event. The purpose of studying a rare event is to illuminate new ways of thinking about the broader research problem or to test a hypothesis. Critical incident case studies must describe the method by which you identified the event and explain the process by which you determined the validity of this case to inform broader perspectives about the research problem or to reveal new findings. However, the event does not have to be a rare or uniquely significant to support new thinking about the research problem or to challenge an existing hypothesis. For example, Walo, Bull, and Breen conducted a case study to identify and evaluate the direct and indirect economic benefits and costs of a local sports event in the City of Lismore, New South Wales, Australia. The purpose of their study was to provide new insights from measuring the impact of a typical local sports event that prior studies could not measure well because they focused on large "mega-events." Whether the event is rare or not, the methods section should include an explanation of the following characteristics of the event: a) when did it take place; b) what were the underlying circumstances leading to the event; and, c) what were the consequences of the event in relation to the research problem.

If your subject of analysis is a person. Explain why you selected this particular individual to be studied and describe what experiences they have had that provide an opportunity to advance new understandings about the research problem. Mention any background about this person which might help the reader understand the significance of their experiences that make them worthy of study. This includes describing the relationships this person has had with other people, institutions, and/or events that support using them as the subject for a case study research paper. It is particularly important to differentiate the person as the subject of analysis from others and to succinctly explain how the person relates to examining the research problem [e.g., why is one politician in a particular local election used to show an increase in voter turnout from any other candidate running in the election]. Note that these issues apply to a specific group of people used as a case study unit of analysis [e.g., a classroom of students].

If your subject of analysis is a place. In general, a case study that investigates a place suggests a subject of analysis that is unique or special in some way and that this uniqueness can be used to build new understanding or knowledge about the research problem. A case study of a place must not only describe its various attributes relevant to the research problem [e.g., physical, social, historical, cultural, economic, political], but you must state the method by which you determined that this place will illuminate new understandings about the research problem. It is also important to articulate why a particular place as the case for study is being used if similar places also exist [i.e., if you are studying patterns of homeless encampments of veterans in open spaces, explain why you are studying Echo Park in Los Angeles rather than Griffith Park?]. If applicable, describe what type of human activity involving this place makes it a good choice to study [e.g., prior research suggests Echo Park has more homeless veterans].

If your subject of analysis is a phenomenon. A phenomenon refers to a fact, occurrence, or circumstance that can be studied or observed but with the cause or explanation to be in question. In this sense, a phenomenon that forms your subject of analysis can encompass anything that can be observed or presumed to exist but is not fully understood. In the social and behavioral sciences, the case usually focuses on human interaction within a complex physical, social, economic, cultural, or political system. For example, the phenomenon could be the observation that many vehicles used by ISIS fighters are small trucks with English language advertisements on them. The research problem could be that ISIS fighters are difficult to combat because they are highly mobile. The research questions could be how and by what means are these vehicles used by ISIS being supplied to the militants and how might supply lines to these vehicles be cut off? How might knowing the suppliers of these trucks reveal larger networks of collaborators and financial support? A case study of a phenomenon most often encompasses an in-depth analysis of a cause and effect that is grounded in an interactive relationship between people and their environment in some way.

NOTE:   The choice of the case or set of cases to study cannot appear random. Evidence that supports the method by which you identified and chose your subject of analysis should clearly support investigation of the research problem and linked to key findings from your literature review. Be sure to cite any studies that helped you determine that the case you chose was appropriate for examining the problem.

IV.  Discussion

The main elements of your discussion section are generally the same as any research paper, but centered around interpreting and drawing conclusions about the key findings from your analysis of the case study. Note that a general social sciences research paper may contain a separate section to report findings. However, in a paper designed around a case study, it is common to combine a description of the results with the discussion about their implications. The objectives of your discussion section should include the following:

Reiterate the Research Problem/State the Major Findings Briefly reiterate the research problem you are investigating and explain why the subject of analysis around which you designed the case study were used. You should then describe the findings revealed from your study of the case using direct, declarative, and succinct proclamation of the study results. Highlight any findings that were unexpected or especially profound.

Explain the Meaning of the Findings and Why They are Important Systematically explain the meaning of your case study findings and why you believe they are important. Begin this part of the section by repeating what you consider to be your most important or surprising finding first, then systematically review each finding. Be sure to thoroughly extrapolate what your analysis of the case can tell the reader about situations or conditions beyond the actual case that was studied while, at the same time, being careful not to misconstrue or conflate a finding that undermines the external validity of your conclusions.

Relate the Findings to Similar Studies No study in the social sciences is so novel or possesses such a restricted focus that it has absolutely no relation to previously published research. The discussion section should relate your case study results to those found in other studies, particularly if questions raised from prior studies served as the motivation for choosing your subject of analysis. This is important because comparing and contrasting the findings of other studies helps support the overall importance of your results and it highlights how and in what ways your case study design and the subject of analysis differs from prior research about the topic.

Consider Alternative Explanations of the Findings Remember that the purpose of social science research is to discover and not to prove. When writing the discussion section, you should carefully consider all possible explanations revealed by the case study results, rather than just those that fit your hypothesis or prior assumptions and biases. Be alert to what the in-depth analysis of the case may reveal about the research problem, including offering a contrarian perspective to what scholars have stated in prior research if that is how the findings can be interpreted from your case.

Acknowledge the Study's Limitations You can state the study's limitations in the conclusion section of your paper but describing the limitations of your subject of analysis in the discussion section provides an opportunity to identify the limitations and explain why they are not significant. This part of the discussion section should also note any unanswered questions or issues your case study could not address. More detailed information about how to document any limitations to your research can be found here .

Suggest Areas for Further Research Although your case study may offer important insights about the research problem, there are likely additional questions related to the problem that remain unanswered or findings that unexpectedly revealed themselves as a result of your in-depth analysis of the case. Be sure that the recommendations for further research are linked to the research problem and that you explain why your recommendations are valid in other contexts and based on the original assumptions of your study.

V.  Conclusion

As with any research paper, you should summarize your conclusion in clear, simple language; emphasize how the findings from your case study differs from or supports prior research and why. Do not simply reiterate the discussion section. Provide a synthesis of key findings presented in the paper to show how these converge to address the research problem. If you haven't already done so in the discussion section, be sure to document the limitations of your case study and any need for further research.

The function of your paper's conclusion is to: 1) reiterate the main argument supported by the findings from your case study; 2) state clearly the context, background, and necessity of pursuing the research problem using a case study design in relation to an issue, controversy, or a gap found from reviewing the literature; and, 3) provide a place to persuasively and succinctly restate the significance of your research problem, given that the reader has now been presented with in-depth information about the topic.

Consider the following points to help ensure your conclusion is appropriate:

• If the argument or purpose of your paper is complex, you may need to summarize these points for your reader.
• If prior to your conclusion, you have not yet explained the significance of your findings or if you are proceeding inductively, use the conclusion of your paper to describe your main points and explain their significance.
• Move from a detailed to a general level of consideration of the case study's findings that returns the topic to the context provided by the introduction or within a new context that emerges from your case study findings.

Note that, depending on the discipline you are writing in or the preferences of your professor, the concluding paragraph may contain your final reflections on the evidence presented as it applies to practice or on the essay's central research problem. However, the nature of being introspective about the subject of analysis you have investigated will depend on whether you are explicitly asked to express your observations in this way.

Problems to Avoid

Overgeneralization One of the goals of a case study is to lay a foundation for understanding broader trends and issues applied to similar circumstances. However, be careful when drawing conclusions from your case study. They must be evidence-based and grounded in the results of the study; otherwise, it is merely speculation. Looking at a prior example, it would be incorrect to state that a factor in improving girls access to education in Azerbaijan and the policy implications this may have for improving access in other Muslim nations is due to girls access to social media if there is no documentary evidence from your case study to indicate this. There may be anecdotal evidence that retention rates were better for girls who were engaged with social media, but this observation would only point to the need for further research and would not be a definitive finding if this was not a part of your original research agenda.

Failure to Document Limitations No case is going to reveal all that needs to be understood about a research problem. Therefore, just as you have to clearly state the limitations of a general research study , you must describe the specific limitations inherent in the subject of analysis. For example, the case of studying how women conceptualize the need for water conservation in a village in Uganda could have limited application in other cultural contexts or in areas where fresh water from rivers or lakes is plentiful and, therefore, conservation is understood more in terms of managing access rather than preserving access to a scarce resource.

Failure to Extrapolate All Possible Implications Just as you don't want to over-generalize from your case study findings, you also have to be thorough in the consideration of all possible outcomes or recommendations derived from your findings. If you do not, your reader may question the validity of your analysis, particularly if you failed to document an obvious outcome from your case study research. For example, in the case of studying the accident at the railroad crossing to evaluate where and what types of warning signals should be located, you failed to take into consideration speed limit signage as well as warning signals. When designing your case study, be sure you have thoroughly addressed all aspects of the problem and do not leave gaps in your analysis that leave the reader questioning the results.

Case Studies. Writing@CSU. Colorado State University; Gerring, John. Case Study Research: Principles and Practices . New York: Cambridge University Press, 2007; Merriam, Sharan B. Qualitative Research and Case Study Applications in Education . Rev. ed. San Francisco, CA: Jossey-Bass, 1998; Miller, Lisa L. “The Use of Case Studies in Law and Social Science Research.” Annual Review of Law and Social Science 14 (2018): TBD; Mills, Albert J., Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Putney, LeAnn Grogan. "Case Study." In Encyclopedia of Research Design , Neil J. Salkind, editor. (Thousand Oaks, CA: SAGE Publications, 2010), pp. 116-120; Simons, Helen. Case Study Research in Practice . London: SAGE Publications, 2009;  Kratochwill,  Thomas R. and Joel R. Levin, editors. Single-Case Research Design and Analysis: New Development for Psychology and Education .  Hilldsale, NJ: Lawrence Erlbaum Associates, 1992; Swanborn, Peter G. Case Study Research: What, Why and How? London : SAGE, 2010; Yin, Robert K. Case Study Research: Design and Methods . 6th edition. Los Angeles, CA, SAGE Publications, 2014; Walo, Maree, Adrian Bull, and Helen Breen. “Achieving Economic Benefits at Local Events: A Case Study of a Local Sports Event.” Festival Management and Event Tourism 4 (1996): 95-106.

Writing Tip

At Least Five Misconceptions about Case Study Research

Social science case studies are often perceived as limited in their ability to create new knowledge because they are not randomly selected and findings cannot be generalized to larger populations. Flyvbjerg examines five misunderstandings about case study research and systematically "corrects" each one. To quote, these are:

Misunderstanding 1 :  General, theoretical [context-independent] knowledge is more valuable than concrete, practical [context-dependent] knowledge. Misunderstanding 2 :  One cannot generalize on the basis of an individual case; therefore, the case study cannot contribute to scientific development. Misunderstanding 3 :  The case study is most useful for generating hypotheses; that is, in the first stage of a total research process, whereas other methods are more suitable for hypotheses testing and theory building. Misunderstanding 4 :  The case study contains a bias toward verification, that is, a tendency to confirm the researcher’s preconceived notions. Misunderstanding 5 :  It is often difficult to summarize and develop general propositions and theories on the basis of specific case studies [p. 221].

While writing your paper, think introspectively about how you addressed these misconceptions because to do so can help you strengthen the validity and reliability of your research by clarifying issues of case selection, the testing and challenging of existing assumptions, the interpretation of key findings, and the summation of case outcomes. Think of a case study research paper as a complete, in-depth narrative about the specific properties and key characteristics of your subject of analysis applied to the research problem.

Flyvbjerg, Bent. “Five Misunderstandings About Case-Study Research.” Qualitative Inquiry 12 (April 2006): 219-245.

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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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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 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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What is Case Study Analysis? (Explained With Examples)

Oct 11, 2023

Case Study Analysis is a widely used research method that examines in-depth information about a particular individual, group, organization, or event. It is a comprehensive investigative approach that aims to understand the intricacies and complexities of the subject under study. Through the analysis of real-life scenarios and inquiry into various data sources, Case Study Analysis provides valuable insights and knowledge that can be used to inform decision-making and problem-solving strategies.

1°) What is Case Study Analysis?

Case Study Analysis is a research methodology that involves the systematic investigation of a specific case or cases to gain a deep understanding of the subject matter. This analysis encompasses collecting and analyzing various types of data, including qualitative and quantitative information. By examining multiple aspects of the case, such as its context, background, influences, and outcomes, researchers can draw meaningful conclusions and provide valuable insights for various fields of study.

When conducting a Case Study Analysis, researchers typically begin by selecting a case or multiple cases that are relevant to their research question or area of interest. This can involve choosing a specific organization, individual, event, or phenomenon to study. Once the case is selected, researchers gather relevant data through various methods, such as interviews, observations, document analysis, and artifact examination.

The data collected during a Case Study Analysis is then carefully analyzed and interpreted. Researchers use different analytical frameworks and techniques to make sense of the information and identify patterns, themes, and relationships within the data. This process involves coding and categorizing the data, conducting comparative analysis, and drawing conclusions based on the findings.

One of the key strengths of Case Study Analysis is its ability to provide a rich and detailed understanding of a specific case. This method allows researchers to delve deep into the complexities and nuances of the subject matter, uncovering insights that may not be captured through other research methods. By examining the case in its natural context, researchers can gain a holistic perspective and explore the various factors and variables that contribute to the case.

1.1 - Definition of Case Study Analysis

Case Study Analysis can be defined as an in-depth examination and exploration of a particular case or cases to unravel relevant details and complexities associated with the subject being studied. It involves a comprehensive and detailed analysis of various factors and variables that contribute to the case, aiming to answer research questions and uncover insights that can be applied in real-world scenarios.

When conducting a Case Study Analysis, researchers employ a range of research methods and techniques to collect and analyze data. These methods can include interviews, surveys, observations, document analysis, and experiments, among others. By using multiple sources of data, researchers can triangulate their findings and ensure the validity and reliability of their analysis.

Furthermore, Case Study Analysis often involves the use of theoretical frameworks and models to guide the research process. These frameworks provide a structured approach to analyzing the case and help researchers make sense of the data collected. By applying relevant theories and concepts, researchers can gain a deeper understanding of the underlying factors and dynamics at play in the case.

1.2 - Advantages of Case Study Analysis

Case Study Analysis offers numerous advantages that make it a popular research method across different disciplines. One significant advantage is its ability to provide rich and detailed information about a specific case, allowing researchers to gain a holistic understanding of the subject matter. Additionally, Case Study Analysis enables researchers to explore complex issues and phenomena in their natural context, capturing the intricacies and nuances that may not be captured through other research methods.

Moreover, Case Study Analysis allows researchers to investigate rare or unique cases that may not be easily replicated or studied through experimental methods. This method is particularly useful when studying phenomena that are complex, multifaceted, or involve multiple variables. By examining real-world cases, researchers can gain insights that can be applied to similar situations or inform future research and practice.

Furthermore, this research method allows for the analysis of multiple sources of data, such as interviews, observations, documents, and artifacts, which can contribute to a comprehensive and well-rounded examination of the case. Case Study Analysis also facilitates the exploration and identification of patterns, trends, and relationships within the data, generating valuable insights and knowledge for future reference and application.

1.3 - Disadvantages of Case Study Analysis

While Case Study Analysis offers various advantages, it also comes with certain limitations and challenges. One major limitation is the potential for researcher bias, as the interpretation of data and findings can be influenced by preconceived notions and personal perspectives. Researchers must be aware of their own biases and take steps to minimize their impact on the analysis.

Additionally, Case Study Analysis may suffer from limited generalizability, as it focuses on specific cases and contexts, which might not be applicable or representative of broader populations or situations. The findings of a case study may not be easily generalized to other settings or individuals, and caution should be exercised when applying the results to different contexts.

Moreover, Case Study Analysis can require significant time and resources due to its in-depth nature and the need for meticulous data collection and analysis. This can pose challenges for researchers working with limited budgets or tight deadlines. However, the thoroughness and depth of the analysis often outweigh the resource constraints, as the insights gained from a well-conducted case study can be highly valuable.

Finally, ethical considerations also play a crucial role in Case Study Analysis, as researchers must ensure the protection of participant confidentiality and privacy. Researchers must obtain informed consent from participants and take measures to safeguard their identities and personal information. Ethical guidelines and protocols should be followed to ensure the rights and well-being of the individuals involved in the case study.

2°) Examples of Case Study Analysis

Real-world examples of Case Study Analysis demonstrate the method's practical application and showcase its usefulness across various fields. The following examples provide insights into different scenarios where Case Study Analysis has been employed successfully.

2.1 - Example in a Startup Context

In a startup context, a Case Study Analysis might explore the factors that contributed to the success of a particular startup company. It would involve examining the organization's background, strategies, market conditions, and key decision-making processes. This analysis could reveal valuable lessons and insights for aspiring entrepreneurs and those interested in understanding the intricacies of startup success.

2.2 - Example in a Consulting Context

In the consulting industry, Case Study Analysis is often utilized to understand and develop solutions for complex business problems. For instance, a consulting firm might conduct a Case Study Analysis on a company facing challenges in its supply chain management. This analysis would involve identifying the underlying issues, evaluating different options, and proposing recommendations based on the findings. This approach enables consultants to apply their expertise and provide practical solutions to their clients.

2.3 - Example in a Digital Marketing Agency Context

Within a digital marketing agency, Case Study Analysis can be used to examine successful marketing campaigns. By analyzing various factors such as target audience, message effectiveness, channel selection, and campaign metrics, this analysis can provide valuable insights into the strategies and tactics that contribute to successful marketing initiatives. Digital marketers can then apply these insights to optimize future campaigns and drive better results for their clients.

2.4 - Example with Analogies

Case Study Analysis can also be utilized with analogies to investigate specific scenarios and draw parallels to similar situations. For instance, a Case Study Analysis could explore the response of different countries to natural disasters and draw analogies to inform disaster management strategies in other regions. These analogies can help policymakers and researchers develop more effective approaches to mitigate the impact of disasters and protect vulnerable populations.

In conclusion, Case Study Analysis is a powerful research method that provides a comprehensive understanding of a particular individual, group, organization, or event. By analyzing real-life cases and exploring various data sources, researchers can unravel complexities, generate valuable insights, and inform decision-making processes. With its advantages and limitations, Case Study Analysis offers a unique approach to gaining in-depth knowledge and practical application across numerous fields.

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Arnaud Belinga

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• Roberta Heale 1 ,
• Alison Twycross 2
• 1 School of Nursing , Laurentian University , Sudbury , Ontario , Canada
• 2 School of Health and Social Care , London South Bank University , London , UK
• Correspondence to Dr Roberta Heale, School of Nursing, Laurentian University, Sudbury, ON P3E2C6, Canada; rheale{at}laurentian.ca

https://doi.org/10.1136/eb-2017-102845

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What is it?

Case study is a research methodology, typically seen in social and life sciences. There is no one definition of case study research. 1 However, very simply… ‘a case study can be defined as an intensive study about a person, a group of people or a unit, which is aimed to generalize over several units’. 1 A case study has also been described as an intensive, systematic investigation of a single individual, group, community or some other unit in which the researcher examines in-depth data relating to several variables. 2

Often there are several similar cases to consider such as educational or social service programmes that are delivered from a number of locations. Although similar, they are complex and have unique features. In these circumstances, the evaluation of several, similar cases will provide a better answer to a research question than if only one case is examined, hence the multiple-case study. Stake asserts that the cases are grouped and viewed as one entity, called the quintain . 6  ‘We study what is similar and different about the cases to understand the quintain better’. 6

The steps when using case study methodology are the same as for other types of research. 6 The first step is defining the single case or identifying a group of similar cases that can then be incorporated into a multiple-case study. A search to determine what is known about the case(s) is typically conducted. This may include a review of the literature, grey literature, media, reports and more, which serves to establish a basic understanding of the cases and informs the development of research questions. Data in case studies are often, but not exclusively, qualitative in nature. In multiple-case studies, analysis within cases and across cases is conducted. Themes arise from the analyses and assertions about the cases as a whole, or the quintain, emerge. 6

Benefits and limitations of case studies

If a researcher wants to study a specific phenomenon arising from a particular entity, then a single-case study is warranted and will allow for a in-depth understanding of the single phenomenon and, as discussed above, would involve collecting several different types of data. This is illustrated in example 1 below.

Using a multiple-case research study allows for a more in-depth understanding of the cases as a unit, through comparison of similarities and differences of the individual cases embedded within the quintain. Evidence arising from multiple-case studies is often stronger and more reliable than from single-case research. Multiple-case studies allow for more comprehensive exploration of research questions and theory development. 6

Despite the advantages of case studies, there are limitations. The sheer volume of data is difficult to organise and data analysis and integration strategies need to be carefully thought through. There is also sometimes a temptation to veer away from the research focus. 2 Reporting of findings from multiple-case research studies is also challenging at times, 1 particularly in relation to the word limits for some journal papers.

Examples of case studies

Example 1: nurses’ paediatric pain management practices.

One of the authors of this paper (AT) has used a case study approach to explore nurses’ paediatric pain management practices. This involved collecting several datasets:

Observational data to gain a picture about actual pain management practices.

Questionnaire data about nurses’ knowledge about paediatric pain management practices and how well they felt they managed pain in children.

Questionnaire data about how critical nurses perceived pain management tasks to be.

These datasets were analysed separately and then compared 7–9 and demonstrated that nurses’ level of theoretical did not impact on the quality of their pain management practices. 7 Nor did individual nurse’s perceptions of how critical a task was effect the likelihood of them carrying out this task in practice. 8 There was also a difference in self-reported and observed practices 9 ; actual (observed) practices did not confirm to best practice guidelines, whereas self-reported practices tended to.

Example 2: quality of care for complex patients at Nurse Practitioner-Led Clinics (NPLCs)

The other author of this paper (RH) has conducted a multiple-case study to determine the quality of care for patients with complex clinical presentations in NPLCs in Ontario, Canada. 10 Five NPLCs served as individual cases that, together, represented the quatrain. Three types of data were collected including:

Review of documentation related to the NPLC model (media, annual reports, research articles, grey literature and regulatory legislation).

Interviews with nurse practitioners (NPs) practising at the five NPLCs to determine their perceptions of the impact of the NPLC model on the quality of care provided to patients with multimorbidity.

Chart audits conducted at the five NPLCs to determine the extent to which evidence-based guidelines were followed for patients with diabetes and at least one other chronic condition.

The three sources of data collected from the five NPLCs were analysed and themes arose related to the quality of care for complex patients at NPLCs. The multiple-case study confirmed that nurse practitioners are the primary care providers at the NPLCs, and this positively impacts the quality of care for patients with multimorbidity. Healthcare policy, such as lack of an increase in salary for NPs for 10 years, has resulted in issues in recruitment and retention of NPs at NPLCs. This, along with insufficient resources in the communities where NPLCs are located and high patient vulnerability at NPLCs, have a negative impact on the quality of care. 10

These examples illustrate how collecting data about a single case or multiple cases helps us to better understand the phenomenon in question. Case study methodology serves to provide a framework for evaluation and analysis of complex issues. It shines a light on the holistic nature of nursing practice and offers a perspective that informs improved patient care.

• Gustafsson J
• Calanzaro M
• Sandelowski M

Competing interests None declared.

Provenance and peer review Commissioned; internally peer reviewed.

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What Is a Case Study? How to Write, Examples, and Template

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How to write a case study

Case study template, case study examples, types of case studies, what are the benefits of case studies , what are the limitations of case studies , case study vs. testimonial.

In today's marketplace, conveying your product's value through a compelling narrative is crucial to genuinely connecting with your customers.

Your business can use marketing analytics tools to understand what customers want to know about your product. Once you have this information, the next step is to showcase your product and its benefits to your target audience. This strategy involves a mix of data, analysis, and storytelling. Combining these elements allows you to create a narrative that engages your audience. So, how can you do this effectively?

What is a case study? 

A case study is a powerful tool for showcasing a business's success in helping clients achieve their goals. It's a form of storytelling that details real-world scenarios where a business implemented its solutions to deliver positive results for a client.

In this article, we explore the concept of a case study , including its writing process, benefits, various types, challenges, and more.

Understanding how to write a case study is an invaluable skill. You'll need to embrace decision-making – from deciding which customers to feature to designing the best format to make them as engaging as possible.  This can feel overwhelming in a hurry, so let's break it down.

Step 1: Reach out to the target persona

If you've been in business for a while, you have no shortage of happy customers. But w ith limited time and resources, you can't choose everyone.  So, take some time beforehand to flesh out your target buyer personas. 

Once you know precisely who you're targeting, go through your stable of happy customers to find a buyer representative of the audience you're trying to reach. The closer their problems, goals, and industries align, the more your case study will resonate.

What if you have more than one buyer persona? No problem. This is a common situation for companies because buyers comprise an entire committee. You might be marketing to procurement experts, executives, engineers, etc. Try to develop a case study tailored to each key persona. This might be a long-term goal, and that's fine. The better you can personalize the experience for each stakeholder, the easier it is to keep their attention.  

Here are a few considerations to think about before research:

• Products/services of yours the customer uses (and how familiar they are with them)
• The customer's brand recognition in the industry
• Whether the results they've achieved are specific and remarkable
• Whether they've switched from a competitor's product/service
• How closely aligned they are with your target audience

These items are just a jumping-off point as you develop your criteria.  Once you have a list, run each customer through it to determine your top targets. Approach the ones on the top (your "dream" case study subjects) and work your way down as needed.

Who to interview

You should consider interviewing top-level managers or executives because those are high-profile positions. But consider how close they are to your product and its results.

Focusing on an office manager or engineer who uses your product daily would be better. Look for someone with a courtside view of the effects.

The ways to request customer participation in case studies can vary, but certain principles can improve your chances:

• Make it easy for customers to work with you, respecting their valuable time. Be well-prepared and minimize their involvement.
• Emphasize how customers will benefit through increased publicity, revenue opportunities, or recognition for their success. 
• Acknowledge their contributions and showcase their achievements.
• Standardizing the request process with a script incorporating these principles can help your team consistently secure case study approvals and track performance.

Step 2: Prepare for the interview

Case study interviews are like school exams. The more prepared you are for them, the better they turn out. Preparing thoroughly also shows participants that you value their time. You don't waste precious minutes rehashing things you should have already known. You focus on getting the information you need as efficiently as possible.

You can conduct your case study interview in multiple formats, from exchanging emails to in-person interviews. This isn't a trivial decision.  As you'll see in the chart below, each format has its unique advantages and disadvantages. 

You'll also have to consider who will ask and answer the questions during your case study interview. It's wise to consider this while considering the case study format.  The number of participants factors into which format will work best. Pulling off an in-person interview becomes much harder if you're trying to juggle four or five people's busy schedules. Try a video conference instead.

Before interviewing your case study participant, it is crucial to identify the specific questions that need to be asked.  It's essential to thoroughly evaluate your collaboration with the client and understand how your product's contributions impact the company. 

Remember that structuring your case study is akin to crafting a compelling narrative. To achieve this, follow a structured approach:

• Beginning of your story. Delve into the customer's challenge that ultimately led them to do business with you. What were their problems like? What drove them to make a decision finally? Why did they choose you?
• The middle of the case study.  Your audience also wants to know about the experience of working with you. Your customer has taken action to address their problems. What happened once you got on board?
• An ending that makes you the hero.  Describe the specific results your company produced for the customer. How has the customer's business (and life) changed once they implemented your solution?

Sample questions for the case study interview

If you're preparing for a case study interview, here are some sample case study research questions to help you get started:

• What challenges led you to seek a solution?
• When did you realize the need for immediate action? Was there a tipping point?
• How did you decide on the criteria for choosing a B2B solution, and who was involved?
• What set our product or service apart from others you considered?
• How was your experience working with us post-purchase?
• Were there any pleasant surprises or exceeded expectations during our collaboration?
• How smoothly did your team integrate our solution into their workflows?
• How long before you started seeing positive results?
• How have you benefited from our products or services?
• How do you measure the value our product or service provides?

Step 3: Conduct the interview

Preparing for case study interviews can be different from everyday conversations. Here are some tips to keep in mind:

• Create a comfortable atmosphere.  Before diving into the discussion, talk about their business and personal interests. Ensure everyone is at ease, and address any questions or concerns.
• Prioritize key questions.  Lead with your most crucial questions to respect your customer's time. Interview lengths can vary, so starting with the essentials ensures you get the vital information.
• Be flexible.  Case study interviews don't have to be rigid. If your interviewee goes "off script," embrace it. Their spontaneous responses often provide valuable insights.
• Record the interview.  If not conducted via email, ask for permission to record the interview. This lets you focus on the conversation and capture valuable quotes without distractions.

Step 4: Figure out who will create the case study

When creating written case studies for your business, deciding who should handle the writing depends on cost, perspective, and revisions.

Outsourcing might be pricier, but it ensures a professionally crafted outcome. On the other hand, in-house writing has its considerations, including understanding your customers and products. 

Technical expertise and equipment are needed for video case studies, which often leads companies to consider outsourcing due to production and editing costs. 

Tip: When outsourcing work, it's essential to clearly understand pricing details to avoid surprises and unexpected charges during payment.

Step 5: Utilize storytelling

Understanding and applying storytelling elements can make your case studies unforgettable, offering a competitive edge. 

Source: The Framework Bank

Every great study follows a narrative arc (also called a "story arc"). This arc represents how a character faces challenges, struggles against raising stakes, and encounters a formidable obstacle before the tension resolves.

In a case study narrative, consider:

• Exposition. Provide background information about the company, revealing their "old life" before becoming your customer.
• Inciting incident. Highlight the problem that drove the customer to seek a solution, creating a sense of urgency.
• Obstacles (rising action). Describe the customer's journey in researching and evaluating solutions, building tension as they explore options.
• Midpoint. Explain what made the business choose your product or service and what set you apart.
• Climax. Showcase the success achieved with your product.
• Denouement. Describe the customer's transformed business and end with a call-to-action for the reader to take the next step.

Step 6: Design the case study

The adage "Don't judge a book by its cover" is familiar, but people tend to do just that quite often!

A poor layout can deter readers even if you have an outstanding case study. To create an engaging case study, follow these steps:

• Craft a compelling title. Just like you wouldn't read a newspaper article without an eye-catching headline, the same goes for case studies. Start with a title that grabs attention.
• Organize your content. Break down your content into different sections, such as challenges, results, etc. Each section can also include subsections. This case study approach divides the content into manageable portions, preventing readers from feeling overwhelmed by lengthy blocks of text.
• Conciseness is key. Keep your case study as concise as possible. The most compelling case studies are precisely long enough to introduce the customer's challenge, experience with your solution, and outstanding results. Prioritize clarity and omit any sections that may detract from the main storyline.
• Utilize visual elements. To break up text and maintain reader interest, incorporate visual elements like callout boxes, bulleted lists, and sidebars.
• Include charts and images. Summarize results and simplify complex topics by including pictures and charts. Visual aids enhance the overall appeal of your case study.
• Embrace white space. Avoid overwhelming walls of text to prevent reader fatigue. Opt for plenty of white space, use shorter paragraphs, and employ subsections to ensure easy readability and navigation.
• Enhance video case studies. In video case studies, elements like music, fonts, and color grading are pivotal in setting the right tone. Choose music that complements your message and use it strategically throughout your story. Carefully select fonts to convey the desired style, and consider how lighting and color grading can influence the mood. These elements collectively help create the desired tone for your video case study.

Step 7: Edits and revisions

Once you've finished the interview and created your case study, the hardest part is over. Now's the time for editing and revision. This might feel frustrating for impatient B2B marketers, but it can turn good stories into great ones.

Ideally, you'll want to submit your case study through two different rounds of editing and revisions:

• Internal review. Seek feedback from various team members to ensure your case study is captivating and error-free. Gather perspectives from marketing, sales, and those in close contact with customers for well-rounded insights. Use patterns from this feedback to guide revisions and apply lessons to future case studies.
• Customer feedback. Share the case study with customers to make them feel valued and ensure accuracy. Let them review quotes and data points, as they are the "heroes" of the story, and their logos will be prominently featured. This step maintains positive customer relationships.

Case study mistakes to avoid

• Ensure easy access to case studies on your website.
• Spotlight the customer, not just your business.
• Tailor each case study to a specific audience.
• Avoid excessive industry jargon in your content.

Step 8: Publishing

Take a moment to proofread your case study one more time carefully. Even if you're reasonably confident you've caught all the errors, it's always a good idea to check. Your case study will be a valuable marketing tool for years, so it's worth the investment to ensure it's flawless. Once done, your case study is all set to go!

Consider sharing a copy of the completed case study with your customer as a thoughtful gesture. They'll likely appreciate it; some may want to keep it for their records. After all, your case study wouldn't have been possible without their help, and they deserve to see the final product.

Where you publish your case study depends on its role in your overall marketing strategy. If you want to reach as many people as possible with your case study, consider publishing it on your website and social media platforms. 

Tip: Some companies prefer to keep their case studies exclusive, making them available only to those who request them. This approach is often taken to control access to valuable information and to engage more deeply with potential customers who express specific interests. It can create a sense of exclusivity and encourage interested parties to engage directly with the company.

Step 9: Case study distribution

When sharing individual case studies, concentrate on reaching the audience with the most influence on purchasing decisions

Here are some common distribution channels to consider:

• Sales teams. Share case studies to enhance customer interactions, retention , and upselling among your sales and customer success teams. Keep them updated on new studies and offer easily accessible formats like PDFs or landing page links.
• Company website. Feature case studies on your website to establish authority and provide valuable information to potential buyers. Organize them by categories such as location, size, industry, challenges, and products or services used for effective presentation.
• Events. Use live events like conferences and webinars to distribute printed case study copies, showcase video case studies at trade show booths, and conclude webinars with links to your case study library. This creative approach blends personal interactions with compelling content.
• Industry journalists. Engage relevant industry journalists to gain media coverage by identifying suitable publications and journalists covering related topics. Building relationships is vital, and platforms like HARO (Help A Reporter Out) can facilitate connections, especially if your competitors have received coverage before.

Want to learn more about Marketing Analytics Software? Explore Marketing Analytics products.

It can seem daunting to transform the information you've gathered into a cohesive narrative.  We’ve created a versatile case study template that can serve as a solid starting point for your case study.

With this template, your business can explore any solutions offered to satisfied customers, covering their background, the factors that led them to choose your services, and their outcomes.

The template boasts a straightforward design, featuring distinct sections that guide you in effectively narrating your and your customer's story. However, remember that limitless ways to showcase your business's accomplishments exist.

To assist you in this process, here's a breakdown of the recommended sections to include in a case study:

• Title.  Keep it concise. Create a brief yet engaging project title summarizing your work with your subject. Consider your title like a newspaper headline; do it well, and readers will want to learn more. 
• Subtitle . Use this section to elaborate on the achievement briefly. Make it creative and catchy to engage your audience.
• Executive summary.  Use this as an overview of the story, followed by 2-3 bullet points highlighting key success metrics.
• Challenges and objectives. This section describes the customer's challenges before adopting your product or service, along with the goals or objectives they sought to achieve.
• How product/service helped.  A paragraph explaining how your product or service addressed their problem.
• Testimonials.  Incorporate short quotes or statements from the individuals involved in the case study, sharing their perspectives and experiences.
• Supporting visuals.  Include one or two impactful visuals, such as graphs, infographics, or highlighted metrics, that reinforce the narrative.
• Call to action (CTA).  If you do your job well, your audience will read (or watch) your case studies from beginning to end. They are interested in everything you've said. Now, what's the next step they should take to continue their relationship with you? Give people a simple action they can complete. 

Case studies are proven marketing strategies in a wide variety of B2B industries. Here are just a few examples of a case study:

• Amazon Web Services, Inc.  provides companies with cloud computing platforms and APIs on a metered, pay-as-you-go basis. This case study example illustrates the benefits Thomson Reuters experienced using AWS.
• LinkedIn Marketing Solutions combines captivating visuals with measurable results in the case study created for BlackRock. This case study illustrates how LinkedIn has contributed to the growth of BlackRock's brand awareness over the years. 
• Salesforce , a sales and marketing automation SaaS solutions provider, seamlessly integrates written and visual elements to convey its success stories with Pepe Jeans. This case study effectively demonstrates how Pepe Jeans is captivating online shoppers with immersive and context-driven e-commerce experiences through Salesforce.
• HubSpot offers a combination of sales and marketing tools. Their case study demonstrates the effectiveness of its all-in-one solutions. These typically focus on a particular client's journey and how HubSpot helped them achieve significant results.

There are two different types of case studies that businesses might utilize:

Written case studies 

Written case studies offer readers a clear visual representation of data, which helps them quickly identify and focus on the information that matters most. 

Printed versions of case studies find their place at events like trade shows, where they serve as valuable sales collateral to engage prospective clients.  Even in the digital age, many businesses provide case studies in PDF format or as web-based landing pages, improving accessibility for their audience. 

Note: Landing pages , in particular, offer the flexibility to incorporate rich multimedia content, including images, charts, and videos. This flexibility in design makes landing pages an attractive choice for presenting detailed content to the audience.

Written case study advantages

Here are several significant advantages to leveraging case studies for your company:

• Hyperlink accessibility.  Whether in PDF or landing page format, written case studies allow for embedded hyperlinks, offering prospects easy access to additional information and contact forms.
• Flexible engagement.  Unlike video case studies, which may demand in-person arrangements, written case studies can be conducted via phone or video streaming, reducing customer commitment and simplifying scheduling.
• Efficient scanning . Well-structured written case studies with a scannable format cater to time-strapped professionals. Charts and callout boxes with key statistics enhance the ease of information retrieval.
• Printable for offline use.  Written case studies can be effortlessly printed and distributed at trade shows, sales meetings, and live events. This tangible format accommodates those who prefer physical materials and provides versatility in outreach, unlike video content, which is less portable.

Written case study disadvantages

Here are some drawbacks associated with the use of case studies:

• Reduced emotional impact.  Written content lacks the emotional punch of live video testimonials, which engage more senses and emotions, making a stronger connection.
• Consider time investment.  Creating a compelling case study involves editing, proofreading, and design collaboration, with multiple revisions commonly required before publication.
• Challenges in maintaining attention.  Attention spans are short in today's ad-saturated world. Using graphics, infographics, and videos more often is more powerful to incite the right emotions in customers.

Video case studies

Video case studies are the latest marketing trend. Unlike in the past, when video production was costly, today's tools make it more accessible for users to create and edit their videos. However, specific technical requirements still apply.

Like written case studies, video case studies delve into a specific customer's challenges and how your business provides solutions. Yet, the video offers a more profound connection by showcasing the person who faced and conquered the problem.

Video case studies can boost brand exposure when shared on platforms like YouTube. For example, Slack's engaging case study video with Sandwich Video illustrates how Slack transformed its workflow and adds humor, which can be challenging in written case studies focused on factual evidence.

Source : YouTube

This video case study has garnered nearly a million views on YouTube.

Video case study advantages

Here are some of the top advantages of video case studies. While video testimonials take more time, the payoff can be worth it. 

• Humanization and authenticity.  Video case studies connect viewers with real people, adding authenticity and fostering a stronger emotional connection.
• Engaging multiple senses.  They engage both auditory and visual senses, enhancing credibility and emotional impact. Charts, statistics, and images can also be incorporated.
• Broad distribution.  Videos can be shared on websites, YouTube, social media, and more, reaching diverse audiences and boosting engagement, especially on social platforms.

Video case study disadvantages

Before fully committing to video testimonials, consider the following:

• Technical expertise and equipment.  Video production requires technical know-how and equipment, which can be costly. Skilled video editing is essential to maintain a professional image. While technology advances, producing amateurish videos may harm your brand's perception.
• Viewer convenience.  Some prospects prefer written formats due to faster reading and ease of navigation. Video typically requires sound, which can be inconvenient for viewers in specific settings. Many people may not have headphones readily available to watch your content.
• Demand on case study participants.  On-camera interviews can be time-consuming and location-dependent, making scheduling challenging for case study participants. Additionally, being on screen for a global audience may create insecurities and performance pressure.
• Comfort on camera.  Not everyone feels at ease on camera. Nervousness or a different on-screen persona can impact the effectiveness of the testimonial, and discovering this late in the process can be problematic.

Written or video case studies: Which is right for you?

Now that you know the pros and cons of each, how do you choose which is right for you?

One of the most significant factors in doing video case studies can be the technical expertise and equipment required for a high level of production quality. Whether you have the budget to do this in-house or hire a production company can be one of the major deciding factors.

Still, written or video doesn't have to be an either-or decision. Some B2B companies are using both formats. They can complement each other nicely, minimizing the downsides mentioned above and reaching your potential customers where they prefer.

Let's say you're selling IT network security. What you offer is invaluable but complicated. You could create a short (three- or four-minute) video case study to get attention and touch on the significant benefits of your services. This whets the viewer's appetite for more information, which they could find in a written case study that supplements the video.

Should you decide to test the water in video case studies, test their effectiveness among your target audience. See how well they work for your company and sales team. And, just like a written case study, you can always find ways to improve your process as you continue exploring video case studies.

Case studies offer several distinctive advantages, making them an ideal tool for businesses to market their products to customers. However, their benefits extend beyond these qualities. 

Here's an overview of all the advantages of case studies:

Valuable sales support

Case studies serve as a valuable resource for your sales endeavors. Buyers frequently require additional information before finalizing a purchase decision. These studies provide concrete evidence of your product or service's effectiveness, assisting your sales representatives in closing deals more efficiently, especially with customers with lingering uncertainties.

Validating your value

Case studies serve as evidence of your product or service's worth or value proposition , playing a role in building trust with potential customers. By showcasing successful partnerships, you make it easier for prospects to place trust in your offerings. This effect is particularly notable when the featured customer holds a reputable status.

Unique and engaging content

By working closely with your customer success teams, you can uncover various customer stories that resonate with different prospects. Case studies allow marketers to shape product features and benefits into compelling narratives. 

Each case study's distinctiveness, mirroring the uniqueness of every customer's journey, makes them a valuable source of relatable and engaging content. Storytelling possesses the unique ability to connect with audiences on an emotional level, a dimension that statistics alone often cannot achieve. 

Spotlighting valuable customers

Case studies provide a valuable platform for showcasing your esteemed customers. Featuring them in these studies offers a chance to give them visibility and express your gratitude for the partnership, which can enhance customer loyalty . Depending on the company you are writing about, it can also demonstrate the caliber of your business.

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It's important to consider limitations when designing and interpreting the results of case studies. Here's an overview of the limitations of case studies:

Challenges in replication

Case studies often focus on specific individuals, organizations, or situations, making generalizing their findings to broader populations or contexts challenging. 

Time-intensive process

Case studies require a significant time investment. The extensive data collection process and the need for comprehensive analysis can be demanding, especially for researchers who are new to this method.

Potential for errors

Case studies can be influenced by memory and judgment, potentially leading to inaccuracies. Depending on human memory to reconstruct a case's history may result in variations and potential inconsistencies in how individuals recall past events. Additionally, bias may emerge, as individuals tend to prioritize what they consider most significant, which could limit their consideration of alternative perspectives.

Challenges in verification

Confirming results through additional research can present difficulties. This complexity arises from the need for detailed and extensive data in the initial creation of a case study. Consequently, this process requires significant effort and a substantial amount of time.

While looking at case studies, you may have noticed a quote. This type of quote is considered a testimonial, a key element of case studies.

If a customer's quote proves that your brand does what it says it will or performs as expected, you may wonder: 'Aren't customer testimonials and case studies the same thing?' Not exactly.

Testimonials are brief endorsements designed to establish trust on a broad scale. In contrast, case studies are detailed narratives that offer a comprehensive understanding of how a product or service addresses a specific problem, targeting a more focused audience. 

Crafting case studies requires more resources and a structured approach than testimonials. Your selection between the two depends on your marketing objectives and the complexity of your product or service.

Case in point!

Case studies are among a company's most effective tools. You're  well on your way to mastering them.

Today's buyers are tackling much of the case study research methodology independently. Many are understandably skeptical before making a buying decision. By connecting them with multiple case studies, you can prove you've gotten the results you say you can. There's hardly a better way to boost your credibility and persuade them to consider your solution.

Case study formats and distribution methods might change as technology evolves. However, the fundamentals that make them effective—knowing how to choose subjects, conduct interviews, and structure everything to get attention—will serve you for as long as you're in business. 

We covered a ton of concepts and resources, so go ahead and bookmark this page. You can refer to it whenever you have questions or need a refresher.

Dive into market research to uncover customer preferences and spending habits.

Kristen McCabe

Kristen’s is a former senior content marketing specialist at G2. Her global marketing experience extends from Australia to Chicago, with expertise in B2B and B2C industries. Specializing in content, conversions, and events, Kristen spends her time outside of work time acting, learning nature photography, and joining in the #instadog fun with her Pug/Jack Russell, Bella. (she/her/hers)

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• Case Study | Definition, Examples & Methods

Case Study | Definition, Examples & Methods

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

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

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

Table of contents

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

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

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

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

Prevent plagiarism, run a free check.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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The case study approach

Sarah crowe.

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

Kathrin Cresswell

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

Ann Robertson

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

Anthony Avery

Aziz sheikh.

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

Introduction

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

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

This paper is structured around the following main questions: What is a case study? What are case studies used for? How are case studies conducted? What are the potential pitfalls and how can these be avoided? We draw in particular on four of our own recently published examples of case studies (see Tables ​ Tables1, 1 , ​ ,2, 2 , ​ ,3 3 and ​ and4) 4 ) and those of others to illustrate our discussion[ 3 - 7 ].

Example of a case study investigating the reasons for differences in recruitment rates of minority ethnic people in asthma research[ 3 ]

Example of a case study investigating the process of planning and implementing a service in Primary Care Organisations[ 4 ]

Example of a case study investigating the introduction of the electronic health records[ 5 ]

Example of a case study investigating the formal and informal ways students learn about patient safety[ 6 ]

What is a case study?

A case study is a research approach that is used to generate an in-depth, multi-faceted understanding of a complex issue in its real-life context. It is an established research design that is used extensively in a wide variety of disciplines, particularly in the social sciences. A case study can be defined in a variety of ways (Table ​ (Table5), 5 ), the central tenet being the need to explore an event or phenomenon in depth and in its natural context. It is for this reason sometimes referred to as a "naturalistic" design; this is in contrast to an "experimental" design (such as a randomised controlled trial) in which the investigator seeks to exert control over and manipulate the variable(s) of interest.

Definitions of a case study

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

These are however not necessarily mutually exclusive categories. In the first of our examples (Table ​ (Table1), 1 ), we undertook an intrinsic case study to investigate the issue of recruitment of minority ethnic people into the specific context of asthma research studies, but it developed into a instrumental case study through seeking to understand the issue of recruitment of these marginalised populations more generally, generating a number of the findings that are potentially transferable to other disease contexts[ 3 ]. In contrast, the other three examples (see Tables ​ Tables2, 2 , ​ ,3 3 and ​ and4) 4 ) employed collective case study designs to study the introduction of workforce reconfiguration in primary care, the implementation of electronic health records into hospitals, and to understand the ways in which healthcare students learn about patient safety considerations[ 4 - 6 ]. Although our study focusing on the introduction of General Practitioners with Specialist Interests (Table ​ (Table2) 2 ) was explicitly collective in design (four contrasting primary care organisations were studied), is was also instrumental in that this particular professional group was studied as an exemplar of the more general phenomenon of workforce redesign[ 4 ].

What are case studies used for?

According to Yin, case studies can be used to explain, describe or explore events or phenomena in the everyday contexts in which they occur[ 1 ]. These can, for example, help to understand and explain causal links and pathways resulting from a new policy initiative or service development (see Tables ​ Tables2 2 and ​ and3, 3 , for example)[ 1 ]. In contrast to experimental designs, which seek to test a specific hypothesis through deliberately manipulating the environment (like, for example, in a randomised controlled trial giving a new drug to randomly selected individuals and then comparing outcomes with controls),[ 9 ] the case study approach lends itself well to capturing information on more explanatory ' how ', 'what' and ' why ' questions, such as ' how is the intervention being implemented and received on the ground?'. The case study approach can offer additional insights into what gaps exist in its delivery or why one implementation strategy might be chosen over another. This in turn can help develop or refine theory, as shown in our study of the teaching of patient safety in undergraduate curricula (Table ​ (Table4 4 )[ 6 , 10 ]. Key questions to consider when selecting the most appropriate study design are whether it is desirable or indeed possible to undertake a formal experimental investigation in which individuals and/or organisations are allocated to an intervention or control arm? Or whether the wish is to obtain a more naturalistic understanding of an issue? The former is ideally studied using a controlled experimental design, whereas the latter is more appropriately studied using a case study design.

Case studies may be approached in different ways depending on the epistemological standpoint of the researcher, that is, whether they take a critical (questioning one's own and others' assumptions), interpretivist (trying to understand individual and shared social meanings) or positivist approach (orientating towards the criteria of natural sciences, such as focusing on generalisability considerations) (Table ​ (Table6). 6 ). Whilst such a schema can be conceptually helpful, it may be appropriate to draw on more than one approach in any case study, particularly in the context of conducting health services research. Doolin has, for example, noted that in the context of undertaking interpretative case studies, researchers can usefully draw on a critical, reflective perspective which seeks to take into account the wider social and political environment that has shaped the case[ 11 ].

Example of epistemological approaches that may be used in case study research

How are case studies conducted?

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

Defining the case

Carefully formulated research question(s), informed by the existing literature and a prior appreciation of the theoretical issues and setting(s), are all important in appropriately and succinctly defining the case[ 8 , 12 ]. Crucially, each case should have a pre-defined boundary which clarifies the nature and time period covered by the case study (i.e. its scope, beginning and end), the relevant social group, organisation or geographical area of interest to the investigator, the types of evidence to be collected, and the priorities for data collection and analysis (see Table ​ Table7 7 )[ 1 ]. A theory driven approach to defining the case may help generate knowledge that is potentially transferable to a range of clinical contexts and behaviours; using theory is also likely to result in a more informed appreciation of, for example, how and why interventions have succeeded or failed[ 13 ].

Example of a checklist for rating a case study proposal[ 8 ]

For example, in our evaluation of the introduction of electronic health records in English hospitals (Table ​ (Table3), 3 ), we defined our cases as the NHS Trusts that were receiving the new technology[ 5 ]. Our focus was on how the technology was being implemented. However, if the primary research interest had been on the social and organisational dimensions of implementation, we might have defined our case differently as a grouping of healthcare professionals (e.g. doctors and/or nurses). The precise beginning and end of the case may however prove difficult to define. Pursuing this same example, when does the process of implementation and adoption of an electronic health record system really begin or end? Such judgements will inevitably be influenced by a range of factors, including the research question, theory of interest, the scope and richness of the gathered data and the resources available to the research team.

Selecting the case(s)

The decision on how to select the case(s) to study is a very important one that merits some reflection. In an intrinsic case study, the case is selected on its own merits[ 8 ]. The case is selected not because it is representative of other cases, but because of its uniqueness, which is of genuine interest to the researchers. This was, for example, the case in our study of the recruitment of minority ethnic participants into asthma research (Table ​ (Table1) 1 ) as our earlier work had demonstrated the marginalisation of minority ethnic people with asthma, despite evidence of disproportionate asthma morbidity[ 14 , 15 ]. In another example of an intrinsic case study, Hellstrom et al.[ 16 ] studied an elderly married couple living with dementia to explore how dementia had impacted on their understanding of home, their everyday life and their relationships.

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

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

The selected case study site(s) should allow the research team access to the group of individuals, the organisation, the processes or whatever else constitutes the chosen unit of analysis for the study. Access is therefore a central consideration; the researcher needs to come to know the case study site(s) well and to work cooperatively with them. Selected cases need to be not only interesting but also hospitable to the inquiry [ 8 ] if they are to be informative and answer the research question(s). Case study sites may also be pre-selected for the researcher, with decisions being influenced by key stakeholders. For example, our selection of case study sites in the evaluation of the implementation and adoption of electronic health record systems (see Table ​ Table3) 3 ) was heavily influenced by NHS Connecting for Health, the government agency that was responsible for overseeing the National Programme for Information Technology (NPfIT)[ 5 ]. This prominent stakeholder had already selected the NHS sites (through a competitive bidding process) to be early adopters of the electronic health record systems and had negotiated contracts that detailed the deployment timelines.

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

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

Collecting the data

In order to develop a thorough understanding of the case, the case study approach usually involves the collection of multiple sources of evidence, using a range of quantitative (e.g. questionnaires, audits and analysis of routinely collected healthcare data) and more commonly qualitative techniques (e.g. interviews, focus groups and observations). The use of multiple sources of data (data triangulation) has been advocated as a way of increasing the internal validity of a study (i.e. the extent to which the method is appropriate to answer the research question)[ 8 , 18 - 21 ]. An underlying assumption is that data collected in different ways should lead to similar conclusions, and approaching the same issue from different angles can help develop a holistic picture of the phenomenon (Table ​ (Table2 2 )[ 4 ].

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

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

Analysing, interpreting and reporting case studies

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

The Framework approach is a practical approach, comprising of five stages (familiarisation; identifying a thematic framework; indexing; charting; mapping and interpretation) , to managing and analysing large datasets particularly if time is limited, as was the case in our study of recruitment of South Asians into asthma research (Table ​ (Table1 1 )[ 3 , 24 ]. Theoretical frameworks may also play an important role in integrating different sources of data and examining emerging themes. For example, we drew on a socio-technical framework to help explain the connections between different elements - technology; people; and the organisational settings within which they worked - in our study of the introduction of electronic health record systems (Table ​ (Table3 3 )[ 5 ]. Our study of patient safety in undergraduate curricula drew on an evaluation-based approach to design and analysis, which emphasised the importance of the academic, organisational and practice contexts through which students learn (Table ​ (Table4 4 )[ 6 ].

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

When reporting findings, it is important to provide the reader with enough contextual information to understand the processes that were followed and how the conclusions were reached. In a collective case study, researchers may choose to present the findings from individual cases separately before amalgamating across cases. Care must be taken to ensure the anonymity of both case sites and individual participants (if agreed in advance) by allocating appropriate codes or withholding descriptors. In the example given in Table ​ Table3, 3 , we decided against providing detailed information on the NHS sites and individual participants in order to avoid the risk of inadvertent disclosure of identities[ 5 , 25 ].

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

The case study approach is, as with all research, not without its limitations. When investigating the formal and informal ways undergraduate students learn about patient safety (Table ​ (Table4), 4 ), for example, we rapidly accumulated a large quantity of data. The volume of data, together with the time restrictions in place, impacted on the depth of analysis that was possible within the available resources. This highlights a more general point of the importance of avoiding the temptation to collect as much data as possible; adequate time also needs to be set aside for data analysis and interpretation of what are often highly complex datasets.

Case study research has sometimes been criticised for lacking scientific rigour and providing little basis for generalisation (i.e. producing findings that may be transferable to other settings)[ 1 ]. There are several ways to address these concerns, including: the use of theoretical sampling (i.e. drawing on a particular conceptual framework); respondent validation (i.e. participants checking emerging findings and the researcher's interpretation, and providing an opinion as to whether they feel these are accurate); and transparency throughout the research process (see Table ​ Table8 8 )[ 8 , 18 - 21 , 23 , 26 ]. Transparency can be achieved by describing in detail the steps involved in case selection, data collection, the reasons for the particular methods chosen, and the researcher's background and level of involvement (i.e. being explicit about how the researcher has influenced data collection and interpretation). Seeking potential, alternative explanations, and being explicit about how interpretations and conclusions were reached, help readers to judge the trustworthiness of the case study report. Stake provides a critique checklist for a case study report (Table ​ (Table9 9 )[ 8 ].

Potential pitfalls and mitigating actions when undertaking case study research

Stake's checklist for assessing the quality of a case study report[ 8 ]

Conclusions

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

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

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

Pre-publication history

The pre-publication history for this paper can be accessed here:

http://www.biomedcentral.com/1471-2288/11/100/prepub

Acknowledgements

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

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• Introduction
• Conclusions
• Article Information

Relative risks are calculated compared with mean annual PM 2.5 exposure of 10.6 μg/m 3 . Tick marks indicate distribution of exposure in the total sample; shading, 95% CI.

eTable. Frequency of Tremor-Predominant and Akinetic Rigid PD Subtypes by Average PM 2.5 Exposure Prior to PD Symptom Onset

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Krzyzanowski B , Mullan AF , Turcano P , Camerucci E , Bower JH , Savica R. Air Pollution and Parkinson Disease in a Population-Based Study. JAMA Netw Open. 2024;7(9):e2433602. doi:10.1001/jamanetworkopen.2024.33602

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Air Pollution and Parkinson Disease in a Population-Based Study

• 1 Barrow Neurological Institute, Phoenix, Arizona
• 2 Department of Neurology, Mayo Clinic, Rochester, Minnesota
• 3 Department of Neurology, University of Kansas Medical Center, Kansas City
• 4 Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota

Question   Is air pollution in the form of particulate matter with a diameter of 2.5 µm or less (PM 2.5 ) and nitrogen dioxide (NO 2 ) associated with the risk and clinical characteristics of Parkinson disease (PD)?

Findings   This case-control study including 346 patients with PD matched with 4813 controls found that PM 2.5 and NO 2 exposure was associated with statistically significant increases in PD risk and risk of developing dyskinesia. Higher exposure to PM 2.5 was associated with a statistically significant increase in risk of the akinetic rigid PD subtype in subcohort analysis among patients with PD.

Meaning   These findings suggest that a reduction in air pollution may help reduce PD risk, modifying the PD phenotype and the risk of dyskinesia in patients with PD.

Importance   The role of air pollution in risk and progression of Parkinson disease (PD) is unclear.

Objective   To assess whether air pollution is associated with increased risk of PD and clinical characteristics of PD.

Design, Setting, and Participants   This population-based case-control study included patients with PD and matched controls from the Rochester Epidemiology Project from 1998 to 2015. Data were analyzed from January to June 2024.

Exposures   Mean annual exposure to particulate matter with a diameter of 2.5 µm or less (PM 2.5 ) from 1998 to 2015 and mean annual exposure to nitrogen dioxide (NO 2 ) from 2000 to 2014.

Main Outcomes and Measures   Outcomes of interest were PD risk, all-cause mortality, presence of tremor-predominant vs akinetic rigid PD, and development of dyskinesia. Models were adjusted for age, sex, race and ethnicity, year of index, and urban vs rural residence.

Results   A total of 346 patients with PD (median [IQR] age 72 [65-80] years; 216 [62.4%] male) were identified and matched on age and sex with 4813 controls (median [IQR] age, 72 [65-79] years, 2946 [61.2%] male). Greater PM 2.5 exposure was associated with increased PD risk, and this risk was greatest after restricting to populations within metropolitan cores (odds ratio [OR], 1.23; 95% CI, 1.11-1.35) for the top quintile of PM 2.5 exposure compared with the bottom quintile. Greater NO 2 exposure was also associated with increased PD risk when comparing the top quintile with the bottom quintile (OR, 1.13; 95% CI, 1.07-1.19). Air pollution was associated with a 36% increased risk of akinetic rigid presentation (OR per each 1-μg/m 3 increase in PM 2.5 , 1.36; 95% CI, 1.02-1.80). In analyses among patients with PD only, higher PM 2.5 exposure was associated with greater risk for developing dyskinesia (HR per 1-μg/m 3 increase in PM 2.5 , 1.42; 95% CI, 1.17-1.73), as was increased NO 2 exposure (HR per 1 μg/m 3 increase in NO 2 , 1.13; 95% CI, 1.06-1.19). There was no association between PM 2.5 and all-cause mortality among patients with PD.

Conclusions and Relevance   In this case-control study of air pollution and PD, higher levels of PM 2.5 and NO 2 exposure were associated with increased risk of PD; also, higher levels of PM 2.5 exposure were associated with increased risk of developing akinetic rigid PD and dyskinesia compared with patients with PD exposed to lower levels. These findings suggest that reducing air pollution may reduce risk of PD, modify the PD phenotype, and reduce risk of dyskinesia.

Parkinson disease (PD) is a degenerative disease that affects 2% of the population aged 70 years and older. 1 The number of individuals with PD within the population is estimated to triple in the next 20 years. 2 Several theories have been formulated to explain the progressive increase in the incidence of PD. Complex interactions among environmental factors, genetic predisposition, and known risk factors have been reported through the years as possible causes. 3 , 4 Among environmental exposures, studies have suggested air pollution, in the form of aerosolized particulate matter with a diameter 2.5 µm or less (PM 2.5 ), is associated with increased risk of PD. 5 - 14 The ultrafine particles (≤0.1 µm) contained within PM 2.5 may cross the blood brain barrier in humans, 15 leading to inflammation, oxidative stress, and microglia activation, which are potential pathogenic mechanisms for the development of PD. 15 - 19 At this time, there are no available national datasets on ultrafine particles contained in traffic pollution; however, ultrafine particles are traffic-related pollutants, 20 along with nitrogen dioxide (NO 2 ), for which nationwide data exist. 21 Additionally, previous studies have implicated NO 2 exposure as a PD risk factor. 22 Thus, assessing the association of PM 2.5 and NO 2 with PD may help provide insight into the roles of different sources of air pollution in PD risk. In addition to potentially increasing the risk of developing PD, we hypothesize that air pollution exposure may also be associated with phenotypical manifestations and treatment outcomes. To our knowledge, no studies have explored the association between PM 2.5 exposure and clinical phenotypes of PD. For this reason, we conducted a population-based study using data from the Rochester Epidemiology Project (REP) medical records linkage system to explore the association between PD and air pollution exposure. We also studied the association of air pollution exposure with patient mortality, different clinical characteristics, and presence of dyskinesia.

This case-control study was granted an exemption from review and informed consent by the Mayo Clinic institutional reviewer board. All patients and controls had Minnesota research authorization for use of medical records. This study is reported following the Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) reporting guideline.

We identified patients with PD in Olmstead County, Minnesota, from 1991 to 2015 using International Classification of Diseases, Ninth Revision ( ICD-9 ) (332.0, 333.0, 331.82) and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision ( ICD-10 ) (G20, G21, G23.1, G23.2, G31.83) codes within the Rochester Epidemiology Project (REP) medical records linkage system. 23 The records of all patients identified by ICD-9 and ICD-10 codes were reviewed by a movement disorder specialist (R.S.) to confirm the diagnosis of PD and determine the date of motor symptom onset. Cognitive symptoms were also reviewed for the diagnosis of PD. Details regarding the methods have been reported elsewhere. 23 Although patients with PD were required to be living in Olmsted County at diagnosis date, they were not required to have lived in Olmsted County before that date. Therefore, our analysis includes patients with PD who lived outside of Olmsted County during the exposure window of interest (10 years prior to the date of PD symptom onset), and exposures were linked based on their prior addresses.

Controls were identified from the 27-county REP region in Minnesota, Iowa, and Wisconsin. 24 Controls were screened for the same ICD-9 and ICD-10 codes for PD as were used to identify patients with PD in the case cohort. Controls were matched (using a randomly sorted greedy algorithm) to patients with PD 20:1 on sex and age within an index date that was 3 years prior to motor symptom onset for the matched patient with PD. All controls were required to not have any ICD-9 or ICD-10 codes for PD prior to the index date or up to 5 years after to ensure that no control developed PD motor symptoms. Patients with PD were divided into 2 subgroups (akinetic rigid and tremor-predominant PD subtypes) according to their most prominent feature on examination. 23 Due to a low number of patients with tremor-predominant PD in the cohort, patients presenting with rest tremor and either bradykinesia or rigidity were considered tremor predominant in the analysis.

Mean annual PM 2.5 exposure data were collected from 1998 to 2019 from the Washington University in St Louis Atmospheric Composition Analysis Group. 25 In addition, mean annual nitrogen dioxide (NO 2 ) exposure data were collected from 2000 to 2014 from the Socioeconomic Data and Application Center. 26 The PM 2.5 and NO 2 values for each patient and control were identified each year up to 10 years prior to the index date based on the 1-km 2 area containing their home address of residency each year. Patients with PD with missing data for all 10 years before the index date were excluded, along with their corresponding matched controls.

As a sensitivity analysis, we restricted our patient population to metropolitan cores. In doing so, we ensure that our cases and controls were more comparable in terms of the spectrum of pollution they might have been exposed to. Metropolitan populations were defined as those living in a Rural Urban Commuting Area (RUCA) classification of metropolitan area core (RUCA = 1).

Our primary outcome was risk of incident PD. Secondary outcomes were assessed only among patients with PD and included all-cause mortality following PD symptom onset, presence of tremor-predominant vs akinetic rigid PD, and development of dyskinesia.

We included 2 study designs: a case-control study design to assess the association of PM 2.5 exposure with incidence of PD and a cohort study design focusing on PD subtypes and outcomes (dyskinesia and mortality) within our case group. All statistical analyses were performed during the January to June 2024. P values were 2-sided, and statistical significance was set at P  ≤ .05. All analyses were conducted using R software version 4.2.2 (R Project for Statistical Computing).

In our case-control study, we modeled exposure in quintiles and using 2 linear splines, similar to prior studies of PM 2.5 . 5 The placement of the knot was determined using bootstrap sampling to maximize the area under the receiver operating characteristics curve. Logistic regression was used with PD as the outcome and PM 2.5 (or NO 2 ) as the risk factor, adjusting for age, sex, race, ethnicity, year of index, and residency RUCA. All race and ethnicity information was taken directly from categories used in medical records. The other race category was reported directly in the medical record and not otherwise defined. We adjust for demographics that are well-established risk factors of PD. We adjust for year of index to diminish the potential impact of historical cohort effects. We adjust for RUCA to diminish the impact of differences that exist between urban and rural air pollution composition profiles. We further expect that our RUCA adjustment also diminishes the impact of differences that exist between urban and rural populations regarding other toxic exposures, including prior occupational exposures. RUCA designation was categorized as metropolitan area cores (RUCA = 1) and not metropolitan area cores (RUCA = 2-10). Results were reported as odds ratios (ORs) with 95% CIs.

For our PD-specific cohort study of secondary outcomes, the risk of akinetic rigid subtype was assessed using logistic regression and the risk of all-cause mortality, and risk of dyskinesia was assessed using Cox proportional hazards regression. All models were adjusted for age, sex, race, ethnicity, and residency RUCA. Patient follow-up was censored at last available medical encounter or death, and PM 2.5 was considered as a linear risk factor per 1 μg/m 3 . Model results were reported with ORs or hazard ratios (HRs) with 95% CIs. Differences in outcome based on PM 2.5 exposure were highlighted using Kaplan-Meier cumulative incidence curves with PM 2.5 divided into tertiles for patients with PD.

Of the 450 incident cases of PD identified from Olmsted County, 9 patients (2.0%) were excluded for missing address information and 95 patients (21.1%) were excluded for missing PM 2.5 exposure data, resulting in 346 PD cases (76.9%; median [IQR] age 72 [65-80] years; 216 [62.4%] male) included for analysis, with 1 American Indian or Alaskan Native patient (0.3%), 6 Asian patients (1.7%), 5 Black or African American patients (1.4%), 1 Hawaiian or Pacific Islander patient (0.3%), 330 White patients (95.4%), and 3 patients identifying as other race (0.9%); 7 patients identified as Hispanic or Latino (2.0%) and 339 patients identified as not Hispanic or Latino (98.0%). Among 6920 controls matched to these included PD cases, 1875 (27.1%) were excluded for missing address information and 232 (3.4%) were excluded for missing PM 2.5 exposure data, for a total of 4183 controls (69.6%; median [IQR] age, 72 [65-79] years, 2946 [61.2%] male), including 9 American Indian or Alaskan Native individuals (0.2%), 49 Asian individuals (1.0%), 33 Black or African American individuals (0.7%), 1 Hawaiian or Pacific Islander individual (<0.1%), 4164 White individuals (86.5%), 69 individuals identifying as other race (1.4%), and 488 individuals with unknown or undisclosed race (10.1%); 50 individuals identified as Hispanic or Latino (1.0%) and 4278 individuals identified as not Hispanic or Latino (88.9%). The median (IQR) time lived at these the current address was 15.9 (5.0-39.8) years. Most patients with PD lived inside metropolitan area cores (79.5%) compared with approximately one-third of controls (32.7%), which is why we include our metropolitan-restricted sensitivity analysis ( Table 1 ; eTable in Supplement 1 ).

Median (IQR) PM 2.5 exposure prior to the index date was 10.07 (9.35-10.69) μg/m 3 among patients with PD and 9.44 (8.69-10.22) μg/m 3 among controls (Wilcoxon rank-sum P  < .001). There was a positive association between PM 2.5 and risk of PD: compared with the lowest quintile of PM 2.5 exposure, the increased risk of PD associated with PM 2.5 exposure ranged from 4% in the second quintile (OR, 1.04; 95% CI, 1.02-1.06) to 14% in the top quintile (OR, 1.14; 95% CI, 1.11-1.18) ( Table 2 ). The median (IQR) NO 2 exposure prior to the index date was 17.47 (15.46-19.99) μg/m 3 for patients with PD and 17.17 (14.31-19.46) μg/m 3 for controls (Wilcoxon rank-sum P  = .27). There was a positive association between NO 2 and risk of PD, but only for the top 2 quintiles of NO 2 exposure. Compared with the lowest quintile of NO 2 exposure, the odds of PD were increased by 5% in the fourth quintile (OR, 1.05; 95% CI, 1.01-1.10) and by 13% in the top quintile (OR, 1.13; 95% CI, 1.07-1.19) ( Table 2 ).

The trend in odds ratios across PM 2.5 exposure was positive and linear with some tapering at the higher levels ( Figure 1 ). This was observed in linear splines with a regression knot optimized at 10.6 μg/m 3 , with a 4.9% increase per 1-μg/m 3 increase in PM 2.5 exposure (OR per 1-μg/m 3 increase, 1.05; 95% CI, 1.04-1.06) up to the knot at 10.6 μg/m 3 and then a 1.7% increase per 1 μg/m 3 above the knot (OR, 1.02; 95% CI, 1.00-1.03). A likelihood ratio test comparing the spline model to a linear model favored the nonlinear spline for modeling risk of PD ( P  < .001).

Overall, there was a significant association between PM 2.5 exposure and the development of akinetic rigid PD ( Table 3 ). After accounting for patient age, sex, and residency RUCA classification, increased PM 2.5 exposure was associated with a 36% increased risk of akinetic rigid presentation (OR per 1-μg/m 3 increase, 1.36; 95% CI, 1.02-1.80, P  = .03). The median (IQR) annual PM 2.5 exposure for patients with tremor-predominant PD was 9.98 (9.31-10.65) μg/m 3 , compared with 10.51 (9.90-10.83) μg/m 3 for patients with akinetic rigid PD.

Among 346 patients with PD included in the study, 259 (74.9%) were deceased at the time of data abstraction, with a median (IQR) of 9.0 (6.0-11.8) years from PD symptom onset to death. After accounting for patient demographics (age, sex, race, and ethnicity) and RUCA, there was no significant association between level of PM 2.5 exposure and mortality risk (HR per 1-μg/m 3 increase, 0.93; 95% CI, 0.82-1.05; P  = .23).

A total of 54 patients with PD (15.6%) developed dyskinesia at any time during the disease course. The median (IQR) time from PD symptom onset to dyskinesia was 5.6 (4.4-7.9) years. The Kaplan-Meier cumulative incidence for dyskinesia is shown in Figure 2 , with PM 2.5 classified by tertiles (high, medium, low). After accounting for patient demographics and RUCA, each 1-μg/m 3 increase in PM 2.5 was associated with 42% greater risk for developing dyskinesia (HR, 1.42; 95% CI, 1.17-1.73; P  < .001).

Our analysis restricted to metropolitan core populations provided larger estimates compared with our primary analysis that included both metropolitan and nonmetropolitan populations ( Table 1 ). In metropolitan populations, there was a positive association between PM 2.5 exposure and PD risk. Compared with the lowest quintile of PM 2.5 exposure, metropolitan populations had 10% to 23% increased odds of PD (second quintile: OR, 1.10; 95% CI, 1.00-1.21; fifth quintile: OR, 1.23; 95% CI, 1.11-1.35) ( Table 2 ). However, our metropolitan-restricted analysis of dyskinesia (274 patients with PD; 37 dyskinesia events) found a lower risk compared with the analysis that included both metropolitan and nonmetropolitan populations. Specifically, we found that each 1-μg/m 3 increase in PM 2.5 was associated with 35% greater risk for dyskinesia (HR, 1.35; 95% CI, 1.06-1.72; P  = .01) after accounting for patient demographics.

In this population-based case-control study, PM 2.5 exposure was associated with an increased risk of developing PD, particularly the akinetic-rigid phenotype, and risk was higher with increasing PM 2.5 levels. Exposure to NO 2 was also associated with an increased risk of developing PD. Additionally, higher levels of PM 2.5 and NO 2 were associated with an increased risk of developing dyskinesia following the onset of PD. Contrary to our hypothesis and prior research, 27 PD mortality was not associated with PM 2.5 exposure. We speculate that patients with PD in our study area may have better access to medical care compared to individuals with PD in the general population.

Several studies have reported an association between PM 2.5 exposure and adverse neurological outcomes. 5 , 28 , 29 The ultrafine particles (≤0.1 µm) contained within PM 2.5 cross the blood brain barrier, 15 and PM 2.5 in particular has been reported to be associated with inflammation, oxidative stress, and microglia activation, which are potential pathogenic mechanisms for the development of PD. 15 - 19 Moreover, studies have demonstrated that higher levels of PM 2.5 result in greater neurotoxic effects. 30 Similar to other studies, 5 , 6 , 11 , 31 , 32 we observed that the association between PM 2.5 and PD risk tapered off at the highest levels of PM 2.5 . The reason for this plateauing remains unclear; however, some researchers have suggested that differences in PM 2.5 composition in high-PM 2.5 and low-PM 2.5 regions may account for these findings . 5 Specifically, PM 2.5 composition may be more heterogeneous in regions with the relatively high PM 2.5 , making PM 2.5 alone a less reliable indicator of exposure to specific neurotoxic subcomponents in those regions. Nevertheless, we also acknowledge the possibility that the observed ceiling effect might be tied to a potential biological limit on the mechanisms of neuronal damage occurring in individuals chronically exposed to higher levels of PM 2.5 .

It is possible that PM 2.5 may have varied effects on the development and progression of neurodegenerative disease based on its composition. A multicountry study in Europe confirmed the importance of considering the subcomponents of PM 2.5 . 7 In our study, we were unable to explore broader ranges of PM 2.5 , since the range of PM 2.5 in our study area (parts of Minnesota, Wisconsin, and Iowa) was relatively small compared with the range of PM 2.5 observed nationwide. However, a 2022 study 33 identified notable geographical variation of PM 2.5 subcomponents in the Midwest, finding a north-south gradient in PM 2.5 , nitrite, and organic carbon composition, as well as an inverse gradient of sulfate composition. Additionally, the detected association with NO 2 and the larger effect size observed in metropolitan core populations suggest the possibility that the PM 2.5 association may be driven by traffic-related particulates. Unfortunately, without complete information of prior toxic exposures, we are limited in our ability to draw causal conclusions.

Importantly, in 2024, the US Environmental Protection Agency reduced the annual PM 2.5 standard from 12 μg/m 3 to 9 μg/m 3 due to growing evidence of negative health effects at levels below the previously set standard. 34 Our study not only supports the findings that led to this change, but suggests that the upper limit should be lowered to 8 μg/m 3 —a level previously advocated for by the American Lung Association and other health organizations. Notably, the World Health Organization recommends a more stringent limit than this, setting their standard to 5 μg/m 3 . 35

Individuals with PD who were exposed to higher levels of PM 2.5 were more likely to develop the akinetic rigid subtype of PD. Bradykinesia and rigidity are the predominant findings in these individuals, and this subtype has been linked to faster disease progression. Studies suggest that akinesia and resting tremor may result from different neurobiological processes, with the former resulting from both tonic (sustained) and phasic (intermittent) dopamine levels, and the latter from tonic release of dopamine and dopamine receptor responsiveness. 36 We speculate that these differences may result from differences in PM 2.5 subcomponents and subfractions. Interestingly, similar findings have been reported when using the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) as a model for PD. 37 Indeed, MPTP has been shown to produce both phasic and tonic dopamine dysregulation in the basal ganglia. 38 - 40 In humans, MPTP can produce all major Parkinsonian symptoms, including akinesia and rest tremor; however, in many primate models, MPTP produces akinesia and rigidity without low-frequency tremor. 41 Although MPTP is not found naturally in the environment, it is often referenced when exploring the role of environmental toxins that might cause neurodegeneration by a mechanism similar to MPTP. 42 Thus our finding that PM 2.5 exposure was associated with greater risk of the akinetic rigid PD subtype aligns with the possible evidence of a different clinical manifestations of the disease secondary to an external neurotoxin exposures (MPTP). 41 This work provides insight into the role of PM 2.5 exposure in the development of the different PD phenotypes. Furthermore, our study may offer a new explanation for the onset of dyskinesias that is not solely based on patient demographics, genetics, clinical characteristics, or drug response. 43 - 46 In fact, it possible that environmental factors may lead to an increased risk of developing dyskinesia.

Our study has several strengths. First, we used population-based incidence data, which allows us to better answer questions of PD etiology. Second, rather than relying on ICD-9 and ICD-10 codes alone, all identified cases were screened by a movement disorder specialist to confirm diagnosis of PD. Third, we used address-level data to assign exposure, which is a stronger proxy for patient-level PM 2.5 exposure compared with less precise geographies (eg, zip codes or census tracts). Fourth, our REP data also allowed us to assign PM 2.5 and NO 2 exposure based on multiple years of address information for each patient, meaning that we were able to follow our patients forward through time.

This study also has some limitations. Our population-based dataset had a limited geographical extent. However, the REP captures data from patients for all health systems within our study area, making it a comprehensive population-based dataset. 24 Our study was limited in that the REP population is predominantly White, given the demographics of the study region; however, our results reflect what other studies have found using diverse cohorts, including the nationwide Medicare population. 5 We acknowledge that in our subtype analysis of PD cases, the distribution of PM 2.5 among our PD cases was relatively small. Additionally, we were unable to adjust for all additional clinical characteristics associated with dyskinesia (eg, body weight, disease severity, and levodopa treatment). We did not have information on occupational history, work address, or activity space information; therefore, our results may be vulnerable to exposure misclassification errors (eg, for patients who spend more time at locations other than their home address). Long-term neurotoxic exposures are likely key in PD development. Due to the long prodromal period of PD, 47 we used PM 2.5 estimates for up to 10 years prior to symptom onset date. The relevant exposure window may extend back further, but PM 2.5 estimates prior to 1998 are unavailable. Additionally, a limitation of many epidemiological studies is the use of clinical criteria that do not necessarily correlate with pathology findings and, usually, do not consider the presence of copathology. Importantly, it is possible that the toxicant role of PM 2.5 may interfere with a change in the pathology cascade. On the other hand, we previously reported an clinicopathology concordance of 86.7% synucleoinopathies, supporting our case identification and classiffication. 48

This population-based case-control study provides evidence in support of an association of PM 2.5 and NO 2 exposure with the risk of developing PD. Higher levels of PM 2.5 exposure were associated with increased risk of developing akinetic rigid disease and dyskinesias compared with lower levels of exposure. These findings suggest that a reduction in PM 2.5 may help reduce the risk of PD and affect the clinical profile of PD and disease complications (modifying the PD phenotype and the risk of dyskinesia in patients with PD).

Accepted for Publication: July 19, 2024.

Published: September 16, 2024. doi:10.1001/jamanetworkopen.2024.33602

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2024 Krzyzanowski B et al. JAMA Network Open .

Corresponding Author: Brittany Krzyzanowski, PhD, Barrow Neurological Institute, 240 W Thomas Rd, Phoenix, AZ 85013 ( [email protected] ); Rodolfo Savica MD, PhD, Department of Neurology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 ( [email protected] ).

Author Contributions: Drs Krzyzanowski and Mullan had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Krzyzanowski, Mullan, Savica.

Acquisition, analysis, or interpretation of data: Krzyzanowski, Mullan, Turcano, Camerucci, Bower.

Drafting of the manuscript: Krzyzanowski, Mullan, Savica.

Critical review of the manuscript for important intellectual content: All authors.

Statistical analysis: Krzyzanowski, Mullan, Savica.

Administrative, technical, or material support: Mullan.

Supervision: Turcano, Camerucci, Bower, Savica.

Conflict of Interest Disclosures: Dr Savica reported receiving support from the National Institute on Aging, the National Institute of Neurological Disorders and Stroke, the Parkinson’s Disease Foundation, Acadia Pharmaceuticals, and Michael J. Fox Foundation outside the submitted work.

Data Sharing Statement: See Supplement 2 .

Additional Contributions: We thank the staff of Neuroscience Publications at Barrow Neurological Institute for assistance with manuscript preparation.

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• Published: 18 September 2024

Susceptibility assessment of multi-hazards using random forest—back propagation neural network coupling model: a Hangzhou city case study

• Bofan Yu 1 , 2 ,
• Huaixue Xing 1 &
• Jiaxing Yan 2  

Scientific Reports volume  14 , Article number:  21783 ( 2024 ) Cite this article

Metrics details

• Environmental impact
• Natural hazards

As the demand for regional geological disaster risk assessments in large cities continues to rise, our study selected Hangzhou, one of China’s megacities, as a model to evaluate the susceptibility to two major geological hazards in the region: ground collapse and ground subsidence. Given that susceptibility assessments for such disasters mainly rely on knowledge-driven models, and data-driven models have significant potential for application, we proposed a high-accuracy Random Forest—Back Propagation Neural Network Coupling Model. By using nine evaluation factors selected based on field surveys and expert recommendations, along with disaster data, the model's predictive results indicate a 3–40% improvement in model performance metrics such as AUC, accuracy, precision, recall, and F1-score, compared to single models and traditional SVM and logistic regression models. Ultimately, using the predictive results of this model, we created susceptibility maps for individual disasters and developed a muti-hazards susceptibility map by employing the expert weight discrimination method and the overlay evaluation method. Furthermore, we discussed the feature importance in the prediction process. Our study validated the feasibility of using advanced machine learning models for urban geological disaster assessment, providing a replicable template for other cities.

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Introduction.

With the continuous expansion of urban construction, the conflict between urban geological disasters and urban development has become increasingly prominent 1 , 2 . The prevention and management of geological disasters have thus become critical considerations for every city 3 . Hangzhou, one of China’s megacities, boasts a population exceeding 10 million and achieved a GDP of $259 billion in 2022 4 . However, due to its location in the Hangjiahu Plain and ongoing human-induced modifications to the geological environment 5 , 6 , issues like land subsidence and ground collapse in Hangzhou’s main urban areas have emerged as significant challenges during its development. Specifically, subsidence primarily results from extensive urban development and the prevalent distribution of Quaternary soft soil layers, which are susceptible to compression under structural loads. In contrast, collapses are mainly triggered by the presence of artificial fill and the failure of underground pipelines. Like many cities, Hangzhou has started to undertake regional geological disaster assessments to ensure urban geological safety. The assessment and prediction of these disasters necessitate susceptibility evaluation, as it reflects geological conditions and enables reasonable zoning of the study area 7 , 8 , 9 , 10 . However, assessments based solely on single disaster types might not accurately represent the geological safety of an area, especially as more cities begin to emphasize the overall impact of regional geological issues. Therefore, comprehensive evaluations encompassing multiple types of disasters, or multi-hazards, are commonly employed 11 , 12 , 13 . Current assessments, especially those concerning subsidence and collapse, primarily rely on knowledge-driven models such as the Analytic Hierarchy Process (AHP), which entails subjective scoring of selected indicators to determine their weights for susceptibility analysis 14 , 15 , 16 , Particularly for collapse-related disasters, which occur over small areas, machine learning-based susceptibility assessments of such disasters are, to our knowledge, currently an unexplored area. Meanwhile, in the context of comprehensive disaster evaluations, experts commonly employ AHP to score and determine weights 17 , 18 , 19 , when assessing the relative weights of different types of disasters within a specific area, the lack of learning samples means that reliance on expert judgment is the only viable option.

With advancements in technology and the growing complexity of geological disaster conditions, the limitations of the AHP are becoming increasingly apparent 20 . Its reliance on expert judgment for weighting factors is inherently subjective and can be influenced by factors such as emotions, fatigue, among others, particularly with numerous evaluation criteria. Consequently, researchers are increasingly turning to data-driven models. Unlike traditional models, data-driven models are capable of handling more complex datasets, thereby improving prediction accuracy. They have been extensively applied in evaluating susceptibility to large-scale geological disasters, such as landslides and earthquakes 21 , 22 , 23 , 24 , 25 . Recently, the integration of coupling machine learning models, such as the combination of BP neural networks with SVM models, has demonstrated potential in optimizing predictions by leveraging each model’s strengths and mitigating single-model flaws, thus achieving higher accuracy in case studies 26 , 27 . However, there is still significant potential for development in the field of ensemble models, particularly in urban geological disasters. When facing datasets that include complex geological environments and human activity factors, enhancing the predictive performance of models is crucial for the accuracy of prediction results.

Our study assesses the susceptibility of multi-hazards, including ground subsidence and ground collapse, in commonly filled and silty areas in Hangzhou by employing Random Forest - Back Propagation Neural Network coupling model. We explored the feasibility of utilizing coupled models over single models to enhance evaluation effectiveness, particularly providing a viable template for applying machine learning to small-scale, collapse-type disasters. Our research flowchart is illustrated in Fig. 1 .

Research flowchart.

Materials and methodology

Selection of the study area.

The silty clay soil in Hangzhou City is primarily distributed in the plain areas. Due to the topographic and geomorphological characteristics, the plain areas with accumulative, alluvial, and marine plains are the most typical regions. Considering the comprehensive disaster situation, this paper selects the filled soil-silty clay typical area along the south bank of the Qiantang River in Binjiang District as the study area. Covering an area of 31,970,000m 2 (31.97 km 2 ), it includes urban arterials such as subways, expressways, and elevated roads, marking it as a region in Hangzhou City with significant human activity modifications. The study area is located along the western edge of the Xiaoshao Plain, north to the Hangzhou duplex hill, and south to the Puyang River Plain. The terrain is dominated by plains with a few low hills, featuring monotonous geomorphological types with clear boundaries, flat terrain, a dense river network, and mainly consists of sandy silty soil and silt, with the sand and gravel layer buried at a depth of about 35–50 m. Human activities have profoundly affected the area, with high-rise buildings typically using sand-gravel layers or bedrock as the bearing stratum. The sediments mainly consist of gray to dark gray silty mud clay and silty fine clay, characterized by distinct horizontal stratification and high-water content. The Quaternary strata mainly belong to the lower part of the Holocene, formed during the early Fuyang marine transgression, primarily through flood alluviation, often appearing as river valley plains, river terraces, and other landforms. The strata are composed of sand and gravel, with good sorting and rounding, relatively loose structure, and a thickness of 2–12 m. The geographical location of the study area is shown in Fig. 2 .

Copyright © 2020 Esri and its licensors. All rights reserved. Esri, NASA, NGA, USGS, Sources: Esri, USGS, Esri, © OpenStreetMap contributors, TomTom, Garmin, FAO, NOAA, USGS.)

Location of the study area (This figure was created using ArcGIS Pro software. Desktop GIS Software | Mapping Analytics | ArcGIS Pro (esri.com)) (Map image is the intellectual property of Esri and is used herein under license.

Selection of evaluation factors

Considering the complexity of the urban geological environment and the unique characteristics of the study area, it is imperative to select evaluation factors that comprehensively consider the intensity of human activities in the area and conduct in-depth analyses in conjunction with geological conditions and cultural characteristics. To determine which influencing factors are most closely associated with ground collapse and subsidence in Hangzhou, we collaborated with experts from the Hangzhou urban geological safety assessment at the Zhejiang Geological Survey.

Based on field inspections and expert analyses, ground collapses in the study area are primarily attributed to the following factors: geological conditions such as artificial fill, sandy loam, and concealed ditches; deficiencies in underground drainage pipe structures; hydrogeological influences; and disruptions caused by human engineering activities. Meanwhile, ground subsidence is mainly due to the study area being in a plain, with the distribution of soft soil layers, human activities, and hydrological factors being the primary reasons for ground subsidence occurrences. Given these factors, we identified 9 key factors as preliminary evaluation indicators and conducted a correlation analysis to prevent issues such as overfitting or frequent misjudgments in the machine learning process, as depicted in the correlation heatmap (Fig. 3 ). The evaluation factors used for the disaster, data sources, and data attributes are detailed in Table 1 and Fig. 4 .

Correlation heatmap of evaluation factors.

Assessment factors used in our research.

Random forest—back propagation neural network coupling model

To further enhance model accuracy and ensure that when predicting ground collapse disasters, the small scope of disaster areas leading to fewer data points does not impact the prediction results, we propose the Random Forest - Back Propagation Neural Network coupling model. Random Forest represents a collaborative approach in machine learning, comprising numerous decision trees working in unison 28 , 29 . Each tree receives a randomized subset of data and features, enhancing the model’s overall accuracy and versatility. This approach excels at managing a diverse array of inputs and discerning obscure patterns. The operation of Random Forest can be concisely expressed using the following equations to enhance the understanding of its ensemble methodology:

where \(Var(S)\) represents the variance of the target variable in the entire dataset \(S\) , \(|{S}_{left}|\) and \(|{S}_{right}|\) denote the number of samples in the left and right subsets post-split, respectively. Equation ( 1 ) highlights how Random Forest effectively reduces overfitting by incorporating diverse data samples.

where \({p}_{i}^{2}\) indicates the proportion of the samples in set \(S\) that belong to class \(i\) , and \(n\) is the total number of classes. This measure is critical in determining the best split at each node within the trees. The Eq. ( 2 ) not only allows Random Forest to handle a variety of input types effectively but also enhances its capability to detect subtle patterns in complex datasets.

Conversely, the Backpropagation Neural Network is a pivotal component in machine learning, particularly adept at complex tasks that defy linear analysis 30 , 31 . It comprises multiple layers and enhances its predictive capability through iterative adjustments of its strategy (weights and biases). To further elucidate the learning process within a Backpropagation Neural Network, the following equations can be considered:

where \({W}_{ij}^{\left(old\right)}\) and \({W}_{ij}^{\left(new\right)}\) are the old and new values of the weight between nodes \(i\) and \(j\) , \(\eta\) is the learning rate, and \(\frac{\partial \mathcal{L}}{\partial {W}_{ij}}\) represents the gradient of the loss function \(\mathcal{L}\) with respect to the weight \({W}_{ij}\) Eq. ( 3 ) delineates the core mechanism by which the network learns by iteratively adjusting its weights.

where \(\sigma \left(x\right)\) is the sigmoid activation function, which normalizes the input \(x\) into an output range between 0 and 1, enabling the network to handle non-linear relationships within the data. Equation ( 4 ) illustrates how the sigmoid activation function enables the neural network to transform linear inputs into outputs bounded between 0 and 1, facilitating the handling of probabilistic decisions and non-linear complexities.

To optimize our Random Forest Classifier, we conducted a grid search exploring various hyperparameters 32 , including the number of trees (ranging from 50 to 200 in increments of 50) and max features (options including 'auto', 'sqrt', and 'log2'). The optimal configuration was determined to be 100 trees, ensuring repeatability with a fixed random seed of 42. Similarly, for the Neural Network Classifier, our grid search covered different network architectures, focusing on varying the number of neurons in the hidden layers (options including 50, 100, and 150 for the first layer and 25, 50, and 75 for the second layer) and the maximum number of iterations (500, 1000, and 1500 iterations were tested). The most effective configuration found consists of two hidden layers with 100 and 50 neurons respectively, with a maximum of 1000 iterations, again using the random seed of 42 to maintain consistency. Each set of parameters was evaluated using 5-fold cross-validation 33 , ensuring that our selection process was robust and the results reliable. This comprehensive approach to hyperparameter tuning enhances the individual models' predictive accuracy before integrating them into the Stacking Classifier. The Stacking Classifier utilizes these two models as base models and integrates their predictions using another Random Forest configured with 100 trees as the final meta-model to make the ultimate decision. Subsequently, the Backpropagation Neural Network refines the analysis with its specialized capabilities. Together, they constitute a robust model adept at assimilating extensive information, distilling it, and producing precise predictions. The principle of the ensemble model is depicted in Fig. 5 .

Schematic diagram of RF-BP neural network coupling model structure.

Evaluation and analysis

Model performance analysis.

In this study, we selected 27898 data points using the "Raster to Point" function in ArcGIS, the sample size was determined by dividing the study area and evaluation factors into 32m x 32m pixels. Under these sample conditions, the dataset maintained relative balance, the computation time was reasonable, and subsequent model evaluation metrics also demonstrated the high accuracy of the model predictions. For ground subsidence susceptibility evaluation, susceptible areas were delineated using regional cumulative subsidence data. To ensure model training accuracy, during the ground subsidence susceptibility evaluation, 70% of the total data were randomly extracted for the training set using Python software. For ground collapse susceptibility evaluation, a 1:1 ratio of ground collapse disaster points to non-disaster points was employed to segment the training set (with disaster points labeled as 1 and non-disaster points as 0). Due to the limited scope of collapse areas, we obtained a total of 300 collapse data points, from which we randomly selected 210 collapse points and 210 non-collapse points to serve as the training set. This balanced approach helps to ensure that the model is not biased towards the more prevalent non-collapse conditions. The trained model was subsequently used to predict the remaining points, providing the probability of ground collapse for each pixel (ranging from 0 to 1) and the predicted cumulative subsidence value for each pixel.

To further demonstrate that our Random Forest-Back Propagation Neural Network Coupling Model outperforms individual models and ensures optimal results for susceptibility mapping, we evaluated the model's performance using multiple metrics. Since ground collapse prediction is a binary classification problem in our multi-hazard assessment, we primarily used metrics including ROC curves, AUC values, Accuracy, Precision, Recall, and F1-score.

The AUC (Area Under the ROC Curve) represents the model's overall performance across all classification thresholds, with a higher AUC indicating superior classification capability 34 . Accuracy measures the proportion of correctly predicted instances (true positives and true negatives) out of the total instances, reflecting the model's general effectiveness. Precision evaluates the proportion of true positive predictions among all predicted positives, indicating the model's reliability in predicting positive instances. Recall assesses the proportion of actual positive instances correctly identified by the model, demonstrating its ability to capture positive cases. The F1-score, which is the harmonic mean of precision and recall, provides a balanced measure of both metrics, especially useful for imbalanced datasets. Higher values for these metrics signify better model performance on the given dataset 35 .

Results showed that the stacked model outperformed others in all metrics in ground collapse, as illustrated in Fig. 6 a and b. Following the validation of the stacked model's performance, we employed it to predict susceptibility to non-binary tasks of ground subsidence. The results yielded high AUC values: 0.99 for less than 24mm (low susceptibility), 0.99 for 24mm-64mm (moderate susceptibility), 0.97 for 64mm-96mm (high susceptibility), and 0.99 for 96mm-128mm (very high susceptibility), indicating the model’s high predictive accuracy. The average AUC value of over 0.98 confirms the model's accuracy in predicting ground subsidence in our study and underscores its potential application for non-binary classification tasks. The specific ROC curves and AUC values can be seen in Fig. 6 c.

( a ) The ROC curves and AUC values in the ground collapse prediction task; ( b ) The Accuracy, Precision, Recall, and F1-score in the ground collapse prediction task; ( c ) The ROC curves and AUC values of the stacking model in the ground subsidence prediction task.

Susceptibility analysis

After the model’s prediction was completed, the RF-BP Neural Network Model’s results were used as a benchmark to import all grid points into ArcGIS 10.8 for evaluating the susceptibility zones of ground collapses and ground subsidence. First, regarding single-hazard susceptibility maps, for ground collapse, the probability of occurrence in the study area (ranging from 0 to 1) was reclassified using the equal interval method. This led to its division into four categories: low susceptibility (0–0.25), medium susceptibility (0.25–0.5), high susceptibility (0.5–0.75), and very high susceptibility (0.75–1). Specifically, Fig. 7 a shows the susceptibility map of ground collapses in the study area under this classification, and Table 2 details the specific susceptibility area, its percentage of the total area, and the distribution of disaster cases in the study area. For ground subsidence, the model’s predicted subsidence map was compared with the actual monitored cumulative subsidence map. Susceptibility areas based on cumulative subsidence were categorized as low (0–24 mm), medium (24 mm–64 mm), high (64 mm–96 mm), and very high (96 mm–128 mm) susceptibility areas. Subsequently, the overlap degree was calculated using the grid pixel data. Statistically, the overlap between the actual and the model-simulated cumulative subsidence was 90.31%, with specific overlap degrees for each interval detailed in Table 3 . This also reflects the accuracy of the stacking model. Figure 7 b shows the susceptibility map of ground subsidence in the study area.

( a ) Susceptibility map of ground collapses; ( b ) Susceptibility map of ground subsidence.

For the comprehensive susceptibility map of hazards, we employed two approaches. First, three experts from the Zhejiang Geological Survey were invited to reference the basic data of the two primary hazards affecting the study area, ground collapse and ground subsidence. They combined this information with their understanding of the study area, using the Analytic Hierarchy Process (AHP) to determine the impact magnitude (weights) of these two hazards on the study area. This process entails decomposing decision-making elements into hierarchies, including objectives, criteria, and alternatives, followed by qualitative and quantitative analysis to determine the weights of these disasters in the study area. The objective layer in the judgment process focused on the weight values of ground collapse and subsidence, while the criteria layer comprised ten indicators, including the impacts on the economy and human safety, relationship with geological conditions, current monitoring and management status, susceptibility assessment results, and causes and probabilities of occurrence. Of these, the first five indicators were weight determinants for ground collapse, and the latter five pertained to ground subsidence. Finally, by summing the weights of the disaster indicators for ground collapse and subsidence, the overall weight of the disaster was ascertained, leading to an aggregate judgment on the weights of multi-hazard indicators. The specific AHP judgment table and the results are shown in Table 4 and Fig. 8 .

( a ) The result of AHP assessment; ( b ) Comprehensive susceptibility map based on the AHP assessment. (This figure was created using ArcGIS Pro software. Desktop GIS Software|Mapping Analytics|ArcGIS Pro (esri.com)).

Second, we adopted a common overlay evaluation method used in multi-hazard susceptibility assessments 36 , 37 . This method involves overlaying susceptibility maps of individual hazards to determine the risk of different areas experiencing various hazards. For example, it helps to identify regions at high risk for a single hazard, areas at high risk for multiple hazards simultaneously, or areas where multiple hazards are unlikely to occur. Although this overlay method is relatively simple, it greatly reduces subjective judgments and, assuming the individual hazard susceptibility maps are accurate, provides highly valuable reference data. We selected areas with high and very high susceptibility levels from the four susceptibility categories. In Fig. 9 , the three colors represent areas in the study region with high risks of ground subsidence, ground collapse, and both disasters simultaneously. The remaining areas represent regions with low risk for both types of disasters.

Comprehensive susceptibility map using overlay evaluation method. (This figure was created using ArcGIS Pro software. Desktop GIS Software | Mapping Analytics | ArcGIS Pro (esri.com)) (Map image is the intellectual property of Esri and is used herein under license.

Prediction optimization

In the process of assessing regional disaster susceptibility using machine learning models, optimization is essential to achieve more accurate predictions. In our study, we focused on two main aspects of optimization: first, we employed grid search to obtain the optimal hyperparameters for individual models, ensuring the best performance of the stacked model; second, we optimized the dataset by using multi-source data and selecting an appropriate pixel size (32 m*32 m) to ensure that the dataset, particularly for the binary classification task of ground subsidence prediction, was not extremely imbalanced between disaster and non-disaster points.

Although we adopted reasonable methods to achieve good predictive accuracy, we acknowledge there is still room for improvement. For instance, we could explore different data partition ratios. In our case, we used a 70%:30% ratio for the training and test sets. While this ratio is widely used in many established cases of geological hazard susceptibility mapping, other ratios, such as 80%:20% 38 , might be more optimal for different scenarios. Also, Sameen 39 proposed a systematic subdivision method that captures training samples well-representative of the entire dataset. By subdividing the training/testing set based on Hellinger distance and applying a minimization method to reduce feature interdependence, they successfully enhanced the predictive capability of landslide susceptibility models.

Additionally, considering more multi-source data and evaluation metrics can improve the assessment results and increase the credibility of model predictions. In our predictions of ground subsidence and ground settlement susceptibility, we selected 7 and 6 evaluation metrics, respectively, based on field investigations and expert discussions. While these were reasonable choices, future work could include more metrics to enhance model robustness. Finally, for model hyperparameter optimization, we chose the commonly used grid search method due to the relatively simple nature of our dataset, leading to satisfactory optimization results. However, when considering more evaluation metrics and additional sample points, evaluating and quantifying model uncertainty 40 or opting for more efficient search methods, such as ant colony clustering algorithm in random search 41 or Bayesian optimization 42 , can yield better optimization results.

Prediction interpretability

The "black box" effect of machine learning models often leads to their predictive results not being directly trusted by urban decision-makers. Understanding the influence of data on model decisions and the model judgment process has become increasingly important among scholars. In our model, we used a Random Forest (RF) model, which acts as the final meta-model, to assess feature importance, specifically, feature importance is derived by calculating each feature's cumulative contribution to impurity reduction across multiple decision trees, then averaging and standardizing these contributions. As shown in Fig. 10 , in predicting ground subsidence, the thickness of the surface fill layer and rainfall (weekly) (2022) contribute significantly. In predicting ground settlement, aside from the density of the drainage pipe network and burial depth of the underground confined water level, other factors also have notable contributions.

Feature importance in predicting ground subsidence and collapse.

While our method provides the contribution of each evaluation factor to the model output, this explanation might not be comprehensive. Recently, SHAP (SHapley Additive exPlanations), which uses Shapley values from game theory to analyze and illustrate the impact of each input feature on model decisions, has become a popular choice among scholars 43 , 44 . However, its application in ensemble models, especially those combining different types of models, has not yet been reliably verified. This is an area that we may need to consider in future research. Additionally, integrating physical models with machine learning models to evaluate disaster mechanisms, rather than solely focusing on susceptibility assessment, often yields more convincing results 45 , 46 .

This study focused on a typical plain area in Hangzhou affected by urban geological hazards, creating susceptibility maps for the primary geological hazards in the study area: ground subsidence and ground collapse. The specific conclusions are as follows:

To obtain reliable and reasonable susceptibility assessment results, we conducted field investigations and discussions with the Zhejiang Geological Survey, and selected nine evaluation factors with low correlation coefficients, including seven for ground collapse and six for ground subsidence. Then we used a pixel size of 32 m × 32 m, with 27,898 data samples for model prediction. After optimizing the model using the grid search method, we obtained an optimized Random Forest—Back Propagation Neural Network Coupling Model. By introducing single models and comparing with SVM and logistic regression models, the results showed that the ensemble model improved the AUC, Accuracy, Precision, Recall, and F1-score by 3% to 40% in the binary classification task of ground collapse prediction. For the non-binary task of ground subsidence prediction, the average AUC value reached 0.98.

To achieve the highest accuracy in susceptibility mapping results for the study area, we ultimately selected the best-performing stacked model's prediction results to create susceptibility maps for ground collapse and ground subsidence. To further evaluate the overall hazard situation in the study area, we sought assistance from three experts from the Zhejiang Geological Survey. Using the AHP method, the study assessed the impact weights of ground collapse and ground subsidence on the study area and created a comprehensive hazard susceptibility map. Additionally, we used the traditional overlay method to objectively determine the hazard risk in different areas. After completing the mapping, we investigated the feature importance during the prediction process. The results indicated that for ground collapse prediction, the thickness of the surface fill layer and weekly rainfall (2022) were the most significant contributors. For ground subsidence prediction, besides the density of the drainage pipe network and burial depth of the underground confined water level, other factors showed significant contributions.

Data availability

All data generated or analyzed during this study are included in this published article.

Code availability

Name of the code/library: RF-BP Neural Network Coupling Model Contact:[email protected]. Hardware requirements: Processor: A multi-core processor is recommended for efficient running of machine learning models. Memory: At least 8 GB RAM is advised for effective processing of the datasets and machine learning models. Storage Space: Sufficient storage space to accommodate the datasets, model files, and output files. Program language: Python. Software required: Python Interpreter, preferably version 3.8 or higher. Python Libraries: pandas, scikit-learn, joblib, matplotlib. Excel or a compatible software for reading and writing Excel files. Program size: code:4 KB data:818 KB model:5463 KB. The source codes are available for downloading at the link: https://github.com/xygbb/RF-BP-Neural-Network-Coupling - Model2.git.

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Acknowledgements

This research is supported by the China Geological Survey, Nanjing Center, Zhejiang Geological Survey and China University of Geosciences, Wuhan. The work described in this paper was funded by Laboratory of Geological Safety of Underground Space in Coastal Cities, Ministry of Natural Resources (Project No. BHKF2022Z02), and the China Geological Survey, Nanjing Center (Project No.DD20190281).

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Bofan Yu & Huaixue Xing

China University of Geosciences (Wuhan), The Institute of Geological Survey of China University of Geosciences (Wuhan), Wuhan, 430074, People’s Republic of China

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Bofan Yu: Conceptualization, Investigation, Methodology, Software, Writing—original draft, Writing—review & editing Jiaxing Yan: software, validation Huaixue Xing: Resources, Project administration, Funding acquisition.

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Yu, B., Xing, H. & Yan, J. Susceptibility assessment of multi-hazards using random forest—back propagation neural network coupling model: a Hangzhou city case study. Sci Rep 14 , 21783 (2024). https://doi.org/10.1038/s41598-024-71053-7

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Received : 25 June 2024

Accepted : 23 August 2024

Published : 18 September 2024

DOI : https://doi.org/10.1038/s41598-024-71053-7

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