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Types of Case Studies

There are several different types of case studies, as well as several types of subjects of case studies. We will investigate each type in this article.

Different Types of Case Studies

There are several types of case studies, each differing from each other based on the hypothesis and/or thesis to be proved. It is also possible for types of case studies to overlap each other.

Each of the following types of cases can be used in any field or discipline. Whether it is psychology, business or the arts, the type of case study can apply to any field.


The explanatory case study focuses on an explanation for a question or a phenomenon. Basically put, an explanatory case study is 1 + 1 = 2. The results are not up for interpretation.

A case study with a person or group would not be explanatory, as with humans, there will always be variables. There are always small variances that cannot be explained.

However, event case studies can be explanatory. For example, let's say a certain automobile has a series of crashes that are caused by faulty brakes. All of the crashes are a result of brakes not being effective on icy roads.

What kind of case study is explanatory? Think of an example of an explanatory case study that could be done today

When developing the case study, the researcher will explain the crash, and the detailed causes of the brake failure. They will investigate what actions caused the brakes to fail, and what actions could have been taken to prevent the failure.

Other car companies could then use this case study to better understand what makes brakes fail. When designing safer products, looking to past failures is an excellent way to ensure similar mistakes are not made.

The same can be said for other safety issues in cars. There was a time when cars did not have seatbelts. The process to get seatbelts required in all cars started with a case study! The same can be said about airbags and collapsible steering columns. They all began with a case study that lead to larger research, and eventual change.


An exploratory case study is usually the precursor to a formal, large-scale research project. The case study's goal is to prove that further investigation is necessary.

For example, an exploratory case study could be done on veterans coming home from active combat. Researchers are aware that these vets have PTSD, and are aware that the actions of war are what cause PTSD. Beyond that, they do not know if certain wartime activities are more likely to contribute to PTSD than others.

For an exploratory case study, the researcher could develop a study that certain war events are more likely to cause PTSD. Once that is demonstrated, a large-scale research project could be done to determine which events are most likely to cause PTSD.

Exploratory case studies are very popular in psychology and the social sciences. Psychologists are always looking for better ways to treat their patients, and exploratory studies allow them to research new ideas or theories.

Multiple-Case Studies or Collective Studies

Multiple case or collective studies use information from different studies to formulate the case for a new study. The use of past studies allows additional information without needing to spend more time and money on additional studies.

Using the PTSD issue again is an excellent example of a collective study. When studying what contributes most to wartime PTSD, a researcher could use case studies from different war. For instance, studies about PTSD in WW2 vets, Persian Gulf War vets, and Vietnam vets could provide an excellent sampling of which wartime activities are most likely to cause PTSD.

If a multiple case study on vets was done with vets from the Vietnam War, the Persian Gulf War, and the Iraq War, and it was determined the vets from Vietnam had much less PTSD, what could be inferred?

Furthermore, this type of study could uncover differences as well. For example, a researcher might find that veterans who serve in the Middle East are more likely to suffer a certain type of ailment. Or perhaps, that veterans who served with large platoons were more likely to suffer from PTSD than veterans who served in smaller platoons.

An intrinsic case study is the study of a case wherein the subject itself is the primary interest. The "Genie" case is an example of this. The study wasn't so much about psychology, but about Genie herself, and how her experiences shaped who she was.

Genie is the topic. Genie is what the researchers are interested in, and what their readers will be most interested in. When the researchers started the study, they didn't know what they would find.

They asked the question…"If a child is never introduced to language during the crucial first years of life, can they acquire language skills when they are older?" When they met Genie, they didn't know the answer to that question.


An instrumental case study uses a case to gain insights into a phenomenon. For example, a researcher interested in child obesity rates might set up a study with middle school students and an exercise program. In this case, the children and the exercise program are not the focus. The focus is learning the relationship between children and exercise, and why certain children become obese.

What is an example of an instrumental case study?

Focus on the results, not the topic!

Types of Subjects of Case Studies

There are generally five different types of case studies, and the subjects that they address. Every case study, whether explanatory or exploratory, or intrinsic or instrumental, fits into one of these five groups. These are:

Person – This type of study focuses on one particular individual. This case study would use several types of research to determine an outcome.

The best example of a person case is the "Genie" case study. Again, "Genie" was a 13-year-old girl who was discovered by social services in Los Angeles in 1970. Her father believed her to be mentally retarded, and therefore locked her in a room without any kind of stimulation. She was never nourished or cared for in any way. If she made a noise, she was beaten.

When "Genie" was discovered, child development specialists wanted to learn as much as possible about how her experiences contributed to her physical, emotional and mental health. They also wanted to learn about her language skills. She had no form of language when she was found, she only grunted. The study would determine whether or not she could learn language skills at the age of 13.

Since Genie was placed in a children's hospital, many different clinicians could observe her. In addition, researchers were able to interview the few people who did have contact with Genie and would be able to gather whatever background information was available.

This case study is still one of the most valuable in all of child development. Since it would be impossible to conduct this type of research with a healthy child, the information garnered from Genie's case is invaluable.

Group – This type of study focuses on a group of people. This could be a family, a group or friends, or even coworkers.

An example of this type of case study would be the uncontacted tribes of Indians in the Peruvian and Brazilian rainforest. These tribes have never had any modern contact. Therefore, there is a great interest to study them.

Scientists would be interested in just about every facet of their lives. How do they cook, how do they make clothing, how do they make tools and weapons. Also, doing psychological and emotional research would be interesting. However, because so few of these tribes exist, no one is contacting them for research. For now, all research is done observationally.

If a researcher wanted to study uncontacted Indian tribes, and could only observe the subjects, what type of observations should be made?

Location – This type of study focuses on a place, and how and why people use the place.

For example, many case studies have been done about Siberia, and the people who live there. Siberia is a cold and barren place in northern Russia, and it is considered the most difficult place to live in the world. Studying the location, and it's weather and people can help other people learn how to live with extreme weather and isolation.

Location studies can also be done on locations that are facing some kind of change. For example, a case study could be done on Alaska, and whether the state is seeing the effects of climate change.

Another type of study that could be done in Alaska is how the environment changes as population increases. Geographers and those interested in population growth often do these case studies.

Organization/Company – This type of study focuses on a business or an organization. This could include the people who work for the company, or an event that occurred at the organization.

An excellent example of this type of case study is Enron. Enron was one of the largest energy company's in the United States, when it was discovered that executives at the company were fraudulently reporting the company's accounting numbers.

Once the fraud was uncovered, investigators discovered willful and systematic corruption that caused the collapse of Enron, as well as their financial auditors, Arthur Andersen. The fraud was so severe that the top executives of the company were sentenced to prison.

This type of case study is used by accountants, auditors, financiers, as well as business students, in order to learn how such a large company could get away with committing such a serious case of corporate fraud for as long as they did. It can also be looked at from a psychological standpoint, as it is interesting to learn why the executives took the large risks that they took.

Most company or organization case studies are done for business purposes. In fact, in many business schools, such as Harvard Business School, students learn by the case method, which is the study of case studies. They learn how to solve business problems by studying the cases of businesses that either survived the same problem, or one that didn't survive the problem.

Event – This type of study focuses on an event, whether cultural or societal, and how it affects those that are affected by it. An example would be the Tylenol cyanide scandal. This event affected Johnson & Johnson, the parent company, as well as the public at large.

The case study would detail the events of the scandal, and more specifically, what management at Johnson & Johnson did to correct the problem. To this day, when a company experiences a large public relations scandal, they look to the Tylenol case study to learn how they managed to survive the scandal.

A very popular topic for case studies was the events of September 11 th . There were studies in almost all of the different types of research studies.

Obviously the event itself was a very popular topic. It was important to learn what lead up to the event, and how best to proven it from happening in the future. These studies are not only important to the U.S. government, but to other governments hoping to prevent terrorism in their countries.

Planning A Case Study

You have decided that you want to research and write a case study. Now what? In this section you will learn how to plan and organize a research case study.

Selecting a Case

The first step is to choose the subject, topic or case. You will want to choose a topic that is interesting to you, and a topic that would be of interest to your potential audience. Ideally you have a passion for the topic, as then you will better understand the issues surrounding the topic, and which resources would be most successful in the study.

You also must choose a topic that would be of interest to a large number of people. You want your case study to reach as large an audience as possible, and a topic that is of interest to just a few people will not have a very large reach. One of the goals of a case study is to reach as many people as possible.

Who is your audience?

Are you trying to reach the layperson? Or are you trying to reach other professionals in your field? Your audience will help determine the topic you choose.

If you are writing a case study that is looking for ways to lower rates of child obesity, who is your audience?

If you are writing a psychology case study, you must consider whether your audience will have the intellectual skills to understand the information in the case. Does your audience know the vocabulary of psychology? Do they understand the processes and structure of the field?

You want your audience to have as much general knowledge as possible. When it comes time to write the case study, you may have to spend some time defining and explaining terms that might be unfamiliar to the audience.

Lastly, when selecting a topic you do not want to choose a topic that is very old. Current topics are always the most interesting, so if your topic is more than 5-10 years old, you might want to consider a newer topic. If you choose an older topic, you must ask yourself what new and valuable information do you bring to the older topic, and is it relevant and necessary.

Determine Research Goals

What type of case study do you plan to do?

An illustrative case study will examine an unfamiliar case in order to help others understand it. For example, a case study of a veteran with PTSD can be used to help new therapists better understand what veterans experience.

An exploratory case study is a preliminary project that will be the precursor to a larger study in the future. For example, a case study could be done challenging the efficacy of different therapy methods for vets with PTSD. Once the study is complete, a larger study could be done on whichever method was most effective.

A critical instance case focuses on a unique case that doesn't have a predetermined purpose. For example, a vet with an incredibly severe case of PTSD could be studied to find ways to treat his condition.

Ethics are a large part of the case study process, and most case studies require ethical approval. This approval usually comes from the institution or department the researcher works for. Many universities and research institutions have ethics oversight departments. They will require you to prove that you will not harm your study subjects or participants.

This should be done even if the case study is on an older subject. Sometimes publishing new studies can cause harm to the original participants. Regardless of your personal feelings, it is essential the project is brought to the ethics department to ensure your project can proceed safely.

Developing the Case Study

Once you have your topic, it is time to start planning and developing the study. This process will be different depending on what type of case study you are planning to do. For thissection, we will assume a psychological case study, as most case studies are based on the psychological model.

Once you have the topic, it is time to ask yourself some questions. What question do you want to answer with the study?

For example, a researcher is considering a case study about PTSD in veterans. The topic is PTSD in veterans. What questions could be asked?

Do veterans from Middle Eastern wars suffer greater instances of PTSD?

Do younger soldiers have higher instances of PTSD?

Does the length of the tour effect the severity of PTSD?

Each of these questions is a viable question, and finding the answers, or the possible answers, would be helpful for both psychologists and veterans who suffer from PTSD.

Research Notebook

1. What is the background of the case study? Who requested the study to be done and why? What industry is the study in, and where will the study take place?

2. What is the problem that needs a solution? What is the situation, and what are the risks?

3. What questions are required to analyze the problem? What questions might the reader of the study have? What questions might colleagues have?

4. What tools are required to analyze the problem? Is data analysis necessary?

5. What is your current knowledge about the problem or situation? How much background information do you need to procure? How will you obtain this background info?

6. What other information do you need to know to successfully complete the study?

7. How do you plan to present the report? Will it be a simple written report, or will you add PowerPoint presentations or images or videos? When is the report due? Are you giving yourself enough time to complete the project?

The research notebook is the heart of the study. Other organizational methods can be utilized, such as Microsoft Excel, but a physical notebook should always be kept as well.

Planning the Research

The most important parts of the case study are:

1. The case study's questions

2. The study's propositions

3. How information and data will be analyzed

4. The logic behind the propositions

5. How the findings will be interpreted

The study's questions should be either a "how" or "why" question, and their definition is the researchers first job. These questions will help determine the study's goals.

Not every case study has a proposition. If you are doing an exploratory study, you will not have propositions. Instead, you will have a stated purpose, which will determine whether your study is successful, or not.

How the information will be analyzed will depend on what the topic is. This would vary depending on whether it was a person, group, or organization.

When setting up your research, you will want to follow case study protocol. The protocol should have the following sections:

1. An overview of the case study, including the objectives, topic and issues.

2. Procedures for gathering information and conducting interviews.

3. Questions that will be asked during interviews and data collection.

4. A guide for the final case study report.

When deciding upon which research methods to use, these are the most important:

1. Documents and archival records

2. Interviews

3. Direct observations

4. Indirect observations, or observations of subjects

5. Physical artifacts and tools

Documents could include almost anything, including letters, memos, newspaper articles, Internet articles, other case studies, or any other document germane to the study.

Archival records can include military and service records, company or business records, survey data or census information.

Research Strategy

Before beginning the study you want a clear research strategy. Your best chance at success will be if you use an outline that describes how you will gather your data and how you will answer your research questions.

The researcher should create a list with four or five bullet points that need answers. Consider the approaches for these questions, and the different perspectives you could take.

The researcher should then choose at least two data sources (ideally more). These sources could include interviews, Internet research, and fieldwork or report collection. The more data sources used, the better the quality of the final data.

The researcher then must formulate interview questions that will result in detailed and in-depth answers that will help meet the research goals. A list of 15-20 questions is a good start, but these can and will change as the process flows.

Planning Interviews

The interview process is one of the most important parts of the case study process. But before this can begin, it is imperative the researcher gets informed consent from the subjects.

The process of informed consent means the subject understands their role in the study, and that their story will be used in the case study. You will want to have each subject complete a consent form.

The researcher must explain what the study is trying to achieve, and how their contribution will help the study. If necessary, assure the subject that their information will remain private if requested, and they do not need to use their real name if they are not comfortable with that. Pseudonyms are commonly used in case studies.

Informed Consent

The process by which permission is granted before beginning medical or psychological research

A fictitious name used to hide ones identity

It is important the researcher is clear regarding the expectations of the study participation. For example, are they comfortable on camera? Do they mind if their photo is used in the final written study.

Interviews are one of the most important sources of information for case studies. There are several types of interviews. They are:

Open-ended – This type of interview has the interviewer and subject talking to each other about the subject. The interviewer asks questions, and the subject answers them. But the subject can elaborate and add information whenever they see fit.

A researcher might meet with a subject multiple times, and use the open-ended method. This can be a great way to gain insight into events. However, the researcher mustn't rely solely on the information from the one subject, and be sure to have multiple sources.

Focused – This type of interview is used when the subject is interviewed for a short period of time, and answers a set of questions. This type of interview could be used to verify information learned in an open-ended interview with another subject. Focused interviews are normally done to confirm information, not to gain new information.

Structured – Structured interviews are similar to surveys. These are usually used when collecting data for large groups, like neighborhoods. The questions are decided before hand, and the expected answers are usually simple.

When conducting interviews, the answers are obviously important. But just as important are the observations that can be made. This is one of the reasons in-person interviews are preferable over phone interviews, or Internet or mail surveys.

Ideally, when conducing in-person interviews, more than one researcher should be present. This allows one researcher to focus on observing while the other is interviewing. This is particularly important when interviewing large groups of people.

The researcher must understand going into the case study that the information gained from the interviews might not be valuable. It is possible that once the interviews are completed, the information gained is not relevant.

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A Quick Guide to Case Study with Examples

Published by Alvin Nicolas at August 14th, 2021 , Revised On August 29, 2023

A case study is a documented history and detailed analysis of a situation concerning organisations, industries, and markets.

A case study:

  • Focuses on discovering new facts of the situation under observation.
  • Includes data collection from multiple sources over time.
  • Widely used in social sciences to study the underlying information, organisation, community, or event.
  • It does not provide any solution to the problem .

When to Use Case Study? 

You can use a case study in your research when:

  • The focus of your study is to find answers to how and why questions .
  • You don’t have enough time to conduct extensive research; case studies are convenient for completing your project successfully.
  • You want to analyse real-world problems in-depth, then you can use the method of the case study.

You can consider a single case to gain in-depth knowledge about the subject, or you can choose multiple cases to know about various aspects of your  research problem .

What are the Aims of the Case Study?

  • The case study aims at identifying weak areas that can be improved.
  • This method is often used for idiographic research (focuses on individual cases or events).
  • Another aim of the case study is nomothetic research (aims to discover new theories through data analysis of multiple cases).

Types of Case Studies

There are different types of case studies that can be categorised based on the purpose of the investigation.

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How to Conduct a Case Study?

  • Select the Case to Investigate
  • Formulate the Research Question
  • Review of Literature
  • Choose the Precise Case to Use in your Study
  • Select Data Collection and Analysis Techniques
  • Collect the Data
  • Analyse the Data
  • Prepare the Report

Step1: Select the Case to Investigate

The first step is to select a case to conduct your investigation. You should remember the following points.

  • Make sure that you perform the study in the available timeframe.
  • There should not be too much information available about the organisation.
  • You should be able to get access to the organisation.
  • There should be enough information available about the subject to conduct further research.

Step2: Formulate the Research Question

It’s necessary to  formulate a research question  to proceed with your case study. Most of the research questions begin with  how, why, what, or what can . 

You can also use a research statement instead of a research question to conduct your research which can be conditional or non-conditional. 

Step 3: Review of Literature

Once you formulate your research statement or question, you need to extensively  review the documentation about the existing discoveries related to your research question or statement.

Step 4: Choose the Precise Case to Use in your Study

You need to select a specific case or multiple cases related to your research. It would help if you treated each case individually while using multiple cases. The outcomes of each case can be used as contributors to the outcomes of the entire study.  You can select the following cases. 

  • Representing various geographic regions
  • Cases with various size parameters
  • Explaining the existing theories or assumptions
  • Leading to discoveries
  • Providing a base for future research.

Step 5: Select Data Collection and Analysis Techniques

You can choose both  qualitative or quantitative approaches  for  collecting the data . You can use  interviews ,  surveys , artifacts, documentation, newspapers, and photographs, etc. To avoid biased observation, you can triangulate  your research to provide different views of your case. Even if you are focusing on a single case, you need to observe various case angles. It would help if you constructed validity, internal and external validity, as well as reliability.

Example: Identifying the impacts of contaminated water on people’s health and the factors responsible for it. You need to gather the data using qualitative and quantitative approaches to understand the case in such cases.

Construct validity:  You should select the most suitable measurement tool for your research. 

Internal validity:   You should use various methodological tools to  triangulate  the data. Try different methods to study the same hypothesis.

External validity:  You need to effectively apply the data beyond the case’s circumstances to more general issues.

Reliability:   You need to be confident enough to formulate the new direction for future studies based on your findings.

Also Read:  Reliability and Validity

Step 6: Collect the Data

Beware of the following when collecting data:

  • Information should be gathered systematically, and the collected evidence from various sources should contribute to your research objectives.
  • Don’t collect your data randomly.
  • Recheck your research questions to avoid mistakes.
  • You should save the collected data in any popular format for clear understanding.
  • While making any changes to collecting information, make sure to record the changes in a document.
  • You should maintain a case diary and note your opinions and thoughts evolved throughout the study.

Step 7: Analyse the Data

The research data identifies the relationship between the objects of study and the research questions or statements. You need to reconfirm the collected information and tabulate it correctly for better understanding. 

Step 8: Prepare the Report

It’s essential to prepare a report for your case study. You can write your case study in the form of a scientific paper or thesis discussing its detail with supporting evidence. 

A case study can be represented by incorporating  quotations,  stories, anecdotes,  interview transcripts , etc., with empirical data in the result section. 

You can also write it in narrative styles using  textual analysis  or   discourse analysis . Your report should also include evidence from published literature, and you can put it in the discussion section.

Advantages and Disadvantages of Case Study

Frequently asked questions, what is the case study.

A case study is a research method where a specific instance, event, or situation is deeply examined to gain insights into real-world complexities. It involves detailed analysis of context, data, and variables to understand patterns, causes, and effects, often used in various disciplines for in-depth exploration.

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Action research for my dissertation?, A brief overview of action research as a responsive, action-oriented, participative and reflective research technique.

A hypothesis is a research question that has to be proved correct or incorrect through hypothesis testing – a scientific approach to test a hypothesis.

In correlational research, a researcher measures the relationship between two or more variables or sets of scores without having control over the variables.





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What Is a Case Study?

Weighing the pros and cons of this method of research

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

intrinsic multiple case study

Cara Lustik is a fact-checker and copywriter.

intrinsic multiple case study

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."

Research Design Review

A discussion of qualitative & quantitative research design, case study research: an internal-external classification.

The following is a modified excerpt from Applied Qualitative Research Design: A Total Quality Framework Approach (Roller & Lavrakas, 2015, pp. 295-298).

intrinsic multiple case study

Salmons mentions the work of Robert Yin and Robert Stake. The typologies of Yin (2014) and Stake (1995) are “two key approaches” in case study research that “ensure that the topic of interest is well explored, and that the essence of the phenomenon is revealed” (Baxter & Jack, 2008, p. 545). Yin (2014) outlines four fundamental types of case studies on the basis of the number of cases and units of analysis in the study design. Specifically, Yin’s typology consists of two types of single-case designs – a type with one unit of analysis (Type 1) and a type with multiple units of analysis (Type 2) – and two types of multiple-case designs – those with one unit of analysis (Type 3) and those with more than one (Type 4). Yin believes that theory development is “highly desired” in case study design and therefore selecting cases for a multiple-case design, for example, involves choosing cases that are expected to return results that support or challenge a theoretical proposition or construct.

Where Yin (2014) emphasizes theoretical development and the ability to say something beyond the specific cases studied, Stake (2006) asserts that “the power of case study is its attention to the local situation, not in how it represents other cases in general” (p. 8). Stake (1995) divides case studies into three types: intrinsic – a single case (an individual, group, organization, event, or other entity) that is important in its own right, not necessarily because of its potential predictive theoretical powers; instrumental – a single case where the focus is on going beyond the case to understand a broader phenomenon of interest; and collective – a multiple case version of instrumental where the focus is on learning about a phenomenon. Unlike Yin, Stake is not linking his case studies to the idea of testing preconceived theories but rather to the idea of using the peculiarities of any particular case to illuminate the phenomenon and magnify the understanding of the research topic.

An overarching differentiator in the Yin and Stake typologies is the extent to which case study outcomes are intended to tell the researcher something that is solely about the case itself – that is, the outcomes are “internalized” to the particular case – or the outcomes are intended to tell the researcher something beyond the case, either by facilitating theory development and/or enlightening the researcher’s understanding of a broader phenomenon – that is, the outcomes are “externalized” to situations outside the case.

This internal-external classification, and its relationship to the Yin and Stake typologies, is shown below.

Case Study Internal-External Classification

In this internal-external classification, an intrinsic case study as defined by Stake, with its emphasis on what can be learned about the specific case itself, is classified as an internal type of design because the research findings will only be used to inform that specific case. An example of an internal case study is research that a healthcare organization might conduct to investigate its new patient-referral program to inform their need for new social media solutions.

Stake’s instrumental and collective case study types as well as Yin’s case study designs (i.e., types 1-4), with their emphasis on projecting case study results to something outside the case (i.e., a theory or phenomenon), are classified as external case study designs because the researcher’s primary focus is on extending the outcomes beyond the specific cases(s). For example, an external case study might be conducted with one or two state government department(s) to understand the impact of a newly-implemented, more restrictive sick-leave policy on all state employees.

The internal-external classification is one way to think broadly about case study design. Regardless of the design model, however, case study researchers would do well to clearly articulate, as Salmons states, the “methodological foundations” of their designs.

Baxter, P., & Jack, S. (2008). Qualitative case study methodology: Study design and implementation for novice researchers. The Qualitative Report , 13 (4), 544–559.

Roller, M. R., & Lavrakas, P. J. (2015). Applied qualitative research design: A total quality framework approach . New York: Guilford Press.

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

Yin, R. K. (2014). Case study research: Design and methods (5th ed.). Thousand Oaks, CA: Sage Publications.

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Evaluating complex interventions in context: systematic, meta-narrative review of case study approaches

Sara paparini.

1 Nuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter, Oxford, OX2 6GG UK

Chrysanthi Papoutsi

Jamie murdoch.

2 School of Population Health & Environmental Sciences, King’s College London, London, UK

Judith Green

3 Wellcome Centre for Cultures & Environments of Health, University of Exeter, Exeter, UK

Mark Petticrew

4 Public Health, Environments & Society, London School of Hygiene & Tropical Medicine, London, UK

Trisha Greenhalgh

Sara e. shaw, associated data.

Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.

There is a growing need for methods that acknowledge and successfully capture the dynamic interaction between context and implementation of complex interventions. Case study research has the potential to provide such understanding, enabling in-depth investigation of the particularities of phenomena. However, there is limited guidance on how and when to best use different case study research approaches when evaluating complex interventions. This study aimed to review and synthesise the literature on case study research across relevant disciplines, and determine relevance to the study of contextual influences on complex interventions in health systems and public health research.

Systematic meta-narrative review of the literature comprising (i) a scoping review of seminal texts ( n  = 60) on case study methodology and on context, complexity and interventions, (ii) detailed review of empirical literature on case study, context and complex interventions ( n  = 71), and (iii) identifying and reviewing ‘hybrid papers’ ( n  = 8) focused on the merits and challenges of case study in the evaluation of complex interventions.

We identified four broad (and to some extent overlapping) research traditions, all using case study in a slightly different way and with different goals: 1) developing and testing complex interventions in healthcare; 2) analysing change in organisations; 3) undertaking realist evaluations; 4) studying complex change naturalistically. Each tradition conceptualised context differently—respectively as the backdrop to, or factors impacting on, the intervention; sets of interacting conditions and relationships; circumstances triggering intervention mechanisms; and socially structured practices. Overall, these traditions drew on a small number of case study methodologists and disciplines. Few studies problematised the nature and boundaries of ‘the case’ and ‘context’ or considered the implications of such conceptualisations for methods and knowledge production.


Case study research on complex interventions in healthcare draws on a number of different research traditions, each with different epistemological and methodological preferences. The approach used and consequences for knowledge produced often remains implicit. This has implications for how researchers, practitioners and decision makers understand, implement and evaluate complex interventions in different settings. Deeper engagement with case study research as a methodology is strongly recommended.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-021-01418-3.

There is growing interest in methodological approaches that support meaningful evaluation of complex interventions in health care [ 1 – 3 ], offer to address issues of causality in complex systems [ 4 , 5 ] and grapple with the thorny issue of what counts as ‘context’ and what as ‘intervention’. Case study research focuses on in-depth explorations of complex phenomena in their natural, or real-life, settings [ 6 ], enabling dynamic understanding of complexity, and surfacing the different logics underpinning causal inferences. While there is wide variation in case study research and its implementation, this approach can provide vital evidence for those concerned with internal and external validity and the likely effects of complex interventions across different settings. However, there is currently limited information about how the diversity of available case study research approaches can support implementation and evaluation of complex interventions in health care [ 7 ].

To address a recognised lack of clarity on how researchers should conduct and report empirical case studies [ 7 ], and especially to address the knotty problem of how context should be understood and operationalised in such studies [ 6 ], we undertook a systematic meta-narrative literature review. This was part of the Triple C (Case study, Context and Complex interventions) study that aims to develop guidance and standards for reporting case study research into the influence of context in complex health interventions. We begin by summarising approaches used in evaluating complex interventions, and setting out the principles and methods of meta-narrative review. We then present four research traditions, each comprising a meta-narrative (that is, an unfolding story of empirical research and the underpinning assumptions and theory), relating to case study research on context and complex interventions, arguing that those involved in intervention evaluation need to make explicit and transparent choices about the type/s of case study on which their research draws. Doing so will increase understanding of the knowledge produced and potential for transferability of findings.

Approaches to understanding and evaluating complex interventions

The current interest in case study research represents a shift away from studies of complex interventions that involve a standardised sequence of developing a structured, multi-component intervention, testing it in a RCT [ 8 ] and following a somewhat prescriptive approach to implementation. This well-established approach conceptualised complexity as residing in interventions that consisted of multiple components acting independently and inter-dependently, making it difficult to identify the ‘active ingredient’ [ 9 ] leading to intervention effects. In the UK, this approach formed the basis of the Medical Research Council’s (MRC) 2000 framework for the development and testing of complex interventions [ 9 ] and, later, guidance on conducting process evaluations [ 10 ].

Ways of conceptualising, developing, implementing and evaluating complex interventions have since shifted significantly, in terms of where the complexity is assumed to lie (from the intervention to the system to the interaction between the two [ 11 , 12 ]), and how best to study it (from the RCT to a more pluralistic approach that gives appropriate methodological weight to real-world case studies [ 4 , 6 , 13 ]). In public health and health services research, it is now widely accepted that evaluating complex interventions requires a wide range of evaluative evidence, particularly where RCTs and quasi-experimental studies are either not feasible or inappropriate. Many of the critiques of established research designs are linked to the challenge of ‘context’, which is crucial to understanding intervention effects in particular settings [ 14 ] but often brings ‘noise’ and uncertainty and so is often controlled for and excluded a priori.

Evaluation frameworks and guidance have adapted to account for the necessary behavioural change and organisational involvement required to implement the intervention, the level of variability of outcomes and the degree of intervention adaptability needed, the importance of non-linearity and iterative local tailoring, and the need to pay attention to the social, political or geographical context within which interventions take place [ 10 , 15 , 16 ]. Recently, the MRC and National Institute for Health Research (NIHR) commissioned an update of guidance on complex interventions [ 17 ]. Much uncertainty remains about the best methods for evaluating and implementing complex interventions. For instance, there is a need for better designs that can address questions of causation in natural experiments and questions of complex causation [ 18 ]. This includes more consideration of the potential of non-experimental, mixed methods and process-based approaches, appreciation of the different logics of causality, and use of case study research to understand context [ 13 , 19 – 21 ].

Case study research is sometimes regarded as providing ‘poor evidence’ for causality [ 7 , 22 ]. But empirical case studies can enable dynamic understanding of complex challenges, help strengthen causal inferences (particularly when pathways between intervention and effects are non-linear) and provide evidence about the necessary conditions for intervention implementation and effects [ 23 , 24 ]. This is because they ‘ generally address multiple variables in numerous real-life contexts, often where there is no clear, single set of outcomes ’ ([ 25 ] p775), making case study an important methodology for studying complexity and an invaluable resource for understanding the influence of context on complex system-level interventions.

There are many ways to conceive and operationalise context [ 26 ]. An influential definition from the MRC guidance refers to context as ‘ anything external to the intervention which impedes or strengthens its effects ’ ([ 10 ] p2). This intervention-centred approach reflects concerns (e.g. of researchers, funders) to prepare the grounds for an intervention, plan implementation and assess transferability across settings. Another approach sees context as relational and dynamic, and as emerging over time in multiple different levels of the wider system [ 27 ]. Rather than an external environment into which an intervention is introduced, context is seen as the numerous opportunities, constraints, issues and happenings that become salient as the intervention unfolds. In the latter view, context cannot be conceptualised and ‘measured’ separately from the intervention.

Most health-related interventions happen in complex systems made up of multiple evolving interactions [ 4 ]. As complex interventions typically depend on elements of context for their effectiveness and there is limited control over such context (it cannot be measured or isolated), challenges arise for a priori hypotheses, evaluation and translation beyond a specific study setting [ 28 , 29 ]. Case study research offers a much-needed resource for understanding the evolving influence of context and for enabling users to know what the likely effects of complex programmes or interventions will be in those settings [ 30 – 34 ].

Objectives and focus of the review

The Triple C study was funded via a commissioned call from the UK MRC Better Methods, Better Research panel, focused on improving the quality of case study research into the influences of context on complex system-level interventions. Research questions were as follows:

  • Which research (or epistemic) traditions have considered case study research, and how does each conceptualise and operationalise case study and context?
  • What theoretical and methodological assumptions underpin these research traditions?
  • What insights can be drawn about the use of case study research to understand context by combining and comparing findings from studies coming from different traditions?
  • What are the main methodological insights and/or empirical findings, particularly in relation to context, and the relationship between context and intervention in health research?
  • How do these findings relate to how case study research has been used in studies of complex health interventions? What, if anything, is missing?

The work reported here aimed to: (i) review and synthesise the literature on case study research methods across relevant disciplines, and (ii) determine relevance to the study of contextual influences on complex interventions in health systems and public health research. A subsequent phase involves development and testing of guidance and publication standards using a Delphi panel, workshop, and pilot testing on real-world case studies.

Methodological approach

We conducted a meta-narrative review [ 35 , 36 ]. Originally developed by Greenhalgh and colleagues to explain the disparate data encountered in their review of diffusion of innovation in health care organisations [ 32 ], the meta-narrative review process is guided by six principles (Table  1 ) and involves looking beyond the content of literature to the way it is framed.

Six principles guiding meta-narrative review a

a Adapted from Wong et al. [ 37 ]

Search strategy and selection of documents

Our review was carried out in three linked cycles (Fig.  1 ). Cycle 1 comprised a scoping review of seminal texts on case study methodology and on context, complexity and interventions. In addition to sources known to the research team, we located papers through database searches, expert recommendations (e.g. via social media), citation tracking and snowballing. This informed our detailed search strategy in Cycle 2, developed with an information specialist and using multiple search terms to capture the empirical literature in which case study, context and complex interventions overlapped (see Additional file 1 : Appendix 1). We searched 11 databases: Medline, Embase, PsycINFO, CAB Abstracts, Science Citation Index, Social Sciences Citation Index and Arts & Humanities Citation Index, ERIC, CINAHL, ASSIA, Sociological Abstracts and PAIS Index. We searched the databases from November 2019 back to when their respective records began (the earliest record returned was from 1971). After removal of duplicates, results were imported into Endnote for screening and classification. A sample of 50 papers were screened by SP, CP and SS and discussed in team meetings to progressively refine screening criteria and develop consensus within the team. SP captured the reasoning behind inclusion and exclusion decisions. SP independently screened and sorted all records from 2009 to 2019, initially by reviewing titles and abstracts and then by reviewing full papers in line with the criteria in Table  2 . Results from between 1971 and 2008 were screened by SP via title/abstract looking for high relevance papers only. Included papers were then sorted into groups (dates published; relevance category) and labelled for further analysis. A sample of 10 papers in each category was discussed with other reviewers (SS, CP, JM) until consensus was achieved.

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Overview of search results across cycles

Inclusion and exclusion criteria used in selecting studies for review

Guided by the principles of meta-narrative review (Table ​ (Table1) 1 ) we classified papers as high, partial and low relevance based on the criteria in Table  3 . High relevance papers explicitly focussed on all the 3Cs, i.e. case study, context and complexity.

Criteria for classifying papers according to relevance

Cycle 3 involved identifying and reviewing: (a) additional seminal, methodological texts that were cited in high relevance empirical papers; and (b) ‘hybrid papers’ focused on the merits and challenges of case study in the evaluation of complex interventions that were identified during Cycle 1 and/or were cited in high relevance empirical studies (signalling common logics) and made reference to context and complexity. Hybrid papers provided methodological touchpoints enabling researchers to connect with key issues in case study methodology. Written by scholars from a particular discipline who advocate for the use of case study for evaluating interventions in their own field, hybrid papers frequently condensed original methodological texts (e.g. Stake, Yin), using (mostly their own) empirical examples to illustrate case study research. They sometimes (but not always) included a set of quality and/or reporting criteria.

Data extraction and analysis

Our primary focus was on empirical studies (Cycle 2), with methodological texts (Cycles 1 and 3) enabling us to question how researchers had operationalised case study approaches.

Giving more weight to high relevance papers, we analysed papers in reverse chronological order: starting with 2015–2019, working backwards to 1971 and monitoring how case study research for complex interventions was reported within traditions over time. We sampled 8–10 papers from each time period (71 empirical papers and 8 hybrid papers = 79 in total). The review team (SP, SS, CP, JM) discussed these in detail (e.g. focusing on epistemological underpinnings, how case study methodology was invoked, relevance of context and complexity). We summarised key aspects of each study in a data extraction spreadsheet (e.g. disciplines; key and additional methodologists cited; definition of context; definition of case; discussion on complexity; data collection methods; findings on context). The spreadsheet was modified as we read more papers, with the process then repeated for earlier papers. Adopting a hermeneutic approach, enabling ‘dialogue between the reader and the text, between readers and between texts […and…] translation in a concrete socio-historical and cultural context’ ([ 38 ] p262), we explored key concepts, epistemologies and methods within and across papers, both within particular traditions over time and across traditions.

Guided by a further set of analytical questions inspired by methodological texts (e.g. what does the case study do in this instance? what is this case a case of? how is context operationalised? how is context discussed in relation to the intervention? where does complexity lie according to the author?) we then deliberately placed papers in dialogue with one another. We did this by reading sets of papers each (with SP also reading all papers), sharing analytical notes and meeting regularly to discuss and refine, paying attention to the periods the sets were coming from and other connections (e.g. cross-citations) amongst them. We focussed on narrative threads (i.e. the ways in which authors tell stories about case study, context and complexity to the reader and to each other) to sensitise us to authors’ discussions that ran across groups of studies, allowing us to summarise the assumptions and values driving the empirical research. These narrative threads (e.g. about generalisability of findings; or what made an intervention complex) showed both commonalities and contradictions across research traditions. Indeed, in some cases contradictory narrative threads were evident in the same paper. For example, some studies did not fit neatly into a recognisable methodological paradigm, others recognised context in a specific way (e.g. as emergent) but then failed to operationalise it that way. This process led us to build a set of descriptive statements about the use of case study research and understandings about context and complexity that, in turn, helped us to obtain a picture of the different meta-narratives present in the literature.

We presented emerging narrative threads and meta-narratives to the wider team (JG, MP, and TG), and colleagues (e.g. seminars), with their feedback informing further analytic work (e.g. returning to methodological texts to appreciate threads).

Summary of search results and overview of the literature

Search results are presented in Fig. ​ Fig.1. 1 . The total number of texts informing the review was 139 (71 empirical, 8 hybrid and 60 focusing on case study methodology). Most research teams reporting empirical studies were based in the United Kingdom, followed by the United States, conducting research in the same countries. Fewer study teams were based in Canada, Australia, and in sub-Saharan African and European countries. Authors typically worked in health services, health systems, population health, public health and primary care research teams.

Case study research spans several fields and encompasses multiple perspectives that are grounded in different assumptions about the nature of reality and lead to different combinations of methods applied in different ways [ 22 , 39 ]. This epistemological and methodological diversity was reflected in the empirical case studies reviewed, which covered a wide range of case study designs, from naturalistic approaches (typically employing qualitative methods and focused on one or a small number of cases) to more quasi-experimental studies (typically employing mixed methods across a larger number of cases and with some attempt to standardise aspects of the design across cases). In almost all papers in our dataset, authors placed more emphasis on procedural aspects of the methods and tools used (e.g. data collection, sampling) than on discussions of epistemology or methodology or on the nature, selection, definition or boundaries (if any) of ‘the case’.

Four meta-narratives reflecting four distinct research traditions

We identified four broad meta-narratives on case study research, context and complexity (Table  4 ). We summarise each below before examining commonalities, debates and tensions across these traditions. It should be noted that whereas two of the meta-narratives (1 and 3) were fairly distinct, meta-narratives 2 and 4 showed some overlap which reflected cross-fertilisation of ideas between them. Of note, as well as the four meta-narratives, we identified an additional set of papers that were classified as ‘case study’ (e.g. in the title or abstract), but on closer reading appeared to be qualitative or mixed-methods studies addressing context and complex interventions that were not designed to be case study research and did not engage with case study methodology. We highlight this set of papers in our Discussion as they reveal an important issue of classification and reporting of study research.

Meta-narratives on case study, context and complex intervention identified in the empirical literature

Meta-narrative #1: Case studies develop and test complex interventions

This first research tradition presents the case study as a way of testing complex interventions, comprising a set of specific instructions on how to design, conduct and report on a case study (Table ​ (Table4). 4 ). Building on the Medical Research Council’s widely cited Framework for Developing and Testing Complex Interventions [ 9 ], this tradition favours a qualitative development phase followed by a comparative case study testing phase, as illustrated by the early SHIP study, which formed a model which others followed and refined [ 47 ]. Case study research in this tradition is based on broadly positivist assumptions and the ‘theoretical replication’ methodology of Robert Yin. The focus is on technical research approaches and methods designed to test hypotheses about the impact of an intervention (and what mediates or moderates it) in real-life contexts. Researchers identify a pre-existing case or series of cases (e.g. one or more hospitals) and a specific intervention (e.g. an improvement effort to reduce waiting times), then set out to identify relevant contextual factors that are pre-existing and independent of the intervention (e.g. case mix, technological innovativeness) that can explain variations observed between the stated intervention objectives and outcomes in different settings. Complexity is viewed as an inherent property of the intervention or the context in which it is implemented.

In this tradition, case study research is regarded as an appropriate research design because it offers a robust and transparent research procedure for answering questions about ‘how’ and ‘why’ the intervention works in a specific setting, community or population. Take the example of a case study of an equity-enhancement intervention in primary care in Canada – researchers deliberately used case study as ‘ a comprehensive research strategy useful in exploring, describing, explaining, and evaluating causal links in real world interventions that are too complex to be assessed by survey or experimental strategies alone ’ ([ 44 ] p7).

Case study research that focuses on testing complex interventions often claims to use mixed (qualitative and quantitative) methods. However, data collection methods are predominantly qualitative (e.g. interviews, focus groups, documentary review), and quantitative data tend to be used as an illustration (e.g. describing a reduction in waiting time as part of a wider narrative of improved efficiency) [ 41 ]. The use of multiple data sources is frequently given as evidence of a case study approach, and such “data triangulation” is greatly valued as a way to increase the reliability of case study findings. The analytic process (e.g. framework analysis) is usually deductive, based on aggregation and commonly synthesised in a ‘case description’. For instance, a study of improvement efforts to ameliorate hip-fracture care at a Swedish acute care hospital used a stepwise approach in which data were ‘ organized and coded to characterize a) process problems (before and during the redesign), b) the actual changes carried out, and c) the effects of changes as reported by staff members ’ ([ 41 ] p3). Other studies used structured analytic techniques e.g. framework (see, e.g. [ 40 ]). Guided by Yin [ 30 ], multiple case studies typically present within-case followed by cross-case analysis, seeking generalisation of findings through a process of aggregation.

In this research tradition, the term ‘context’ is not defined but usually features in the commonly cited definition of what a case study is: ‘an empirical inquiry that investigates a contemporary phenomenon within its real-life context’ ([ 66 ] p13). The focus is on defined and tangible contextual features external to the intervention. For example, in a study of the implementation of public health policy in two Swedish municipalities, researchers examined ‘ the contextual steering mechanisms that are practiced in local government ’ ([ 43 ] p220) and local government implementation of national policies – both were held as conceptually separate, with opportunities to act and implement national targets ‘restricted by surrounding structures ’ (p221).

Context is often referred to in terms of specific ‘contextual factors ’, which are typically framed as background to the implementation of an intervention and articulated in terms of a (heterogeneous) list of pre-existing features. For example a case study of an equity-enhancement intervention in primary care listed 5 ‘ contextual factors ’ that shape the intervention: ‘( a) the characteristics of the population; (b) the characteristics of the staff; (c) the organizational milieu, including formal and informal power structures, policies, and funding; (d) the political, policy and economic context (…); and (e) the historical and geographic context, specifically, the physical location of organizations in varied rural and urban locations, and the social conditions linked to those locations’ ([ 44 ] p7).

In this tradition, study descriptions of context are often narrower than the contextual factors considered, and provided as rationales for case selection or sampling. For example, in the above mentioned Swedish study, two different municipalities were selected as cases to illustrate different local contexts, with specific characteristics of each municipal organisation then described as ‘contextual conditions’ [ 43 ].

Complexity (e.g. of the system, setting or intervention) is sometimes invoked in studies in this tradition as a rationale for selecting a case study design (e.g. [ 44 ]) or is presented as a characteristic of the case. But whilst complexity is often mentioned by name, the narrative thread on complexity is typically thin and scarce, often appearing as fleeting statements that reveal little as to how complexity is understood. Complexity, it seems, is just there but does not have to be theorised. The linear nature of the case study methodology in this tradition constrains opportunities to engage with complexity. Hence, while an interest in underlying intervention mechanisms is evident in the decision to adopt case study methodology, this typically plays out with researchers then deconstructing the phenomena under study into factors, components or levels in order to describe associations between context and impact on interventions.

The knowledge produced from designs in this tradition is mostly descriptive, presented in technical accounts detailing contextual factors affecting the intervention. Where theory is drawn on, this is for the specific purpose of disentangling the mechanisms through which the intervention operates in the case study. For example, in the study of hip-fracture care, authors do not cite a particular theoretical approach. They simply state that intervention complexity and the heterogeneity of intervention ‘ application ’ in different contexts ‘ constrain generalizations about which method works, when, and how. To gain a deeper understanding of what works, research needs to better disentangle what is actually being implemented and how the multiple components of improvement interventions contribute, or do not, to improved operational performance ’ ([ 41 ] p2).

The relationship between context and intervention (where addressed) tends to be fixed, with intervention success or failure explained as a matter of ‘fit’ between the relevant theory or hypothesis behind the intervention and the context of implementation. Variation between the local contexts of cases accounts for differences in implementation processes and outcomes. For example, a study of the introduction of an electronic audit and feedback system to improve maternal-newborn care practices and outcomes found that a ‘ one size fits all approach ’ was not feasible because ‘ the diversity in context within our case hospitals and in the facilitators and barriers they experienced demonstrates the challenges of implementing one audit and feedback system across an entire sector (all maternal-newborn hospitals) ’ ([ 45 ] p641).

Meta-narrative #2: Case studies analyse change in organisations

Theory-informed case studies of organisational and institutional change, including quality improvement efforts, seek to understand and evaluate the practices, processes and relationships relevant to the development, implementation and adoption of an intervention within specific organisations (Table ​ (Table4). 4 ). This tradition is more heterogeneous than the one described in meta-narrative 1, having more dispersed origins and wider influence from outside health services research. Researchers in this tradition share a commitment to bringing theoretically-informed rigour to the empirical study of organisational change and quality improvement. Whilst the case study methodologists cited vary, many studies in this tradition are inspired by the work of Yin [ 30 ] and adopt a positivist or critical realist perspective in which the ‘real world’ is external to the intervention. Evaluation involves testing relevant theory (sometimes referred to as a programme theory – that is, overarching theory of how an intervention is expected to work and its anticipated impacts). The unit of analysis is almost always the organisation (or department), and researchers use multiple data collection strategies to study, for instance, how staff variably perceive and carry out change-related activities (e.g. use a new computer system [ 52 ] or create partnerships to sustain organisational innovation [ 50 ]). Theoretical constructs such as agency (which varies amongst actors) are explored in evaluating planned changes, enabling researchers to account for power and resistance in organisations.

Within this broad tradition, there are some differences with regards to what research is valued by scientists in the tradition and how it should be done. One is a system approach to patient safety, in which medical error is theorised as emerging not primarily from individual failings but from features of the system (which is seen as complex and dynamic) [ 52 , 54 ]. Another approach, in which patient safety is also a prominent theme, considers how technologies (used and creatively adapted by humans) subtly alter both front-line work practices and the behaviour of the wider system (e.g. creating panopticon-like surveillance of staff) [ 51 ]. In each of these ‘sub-traditions’, successive studies seek to test and refine theoretical explanations of organisational change generated by previous authors.

Narrative threads about case study research in this tradition, portrayed the case study as an opportunity to study in-depth organisational practices and relationships and develop theories about how these change over time. The case - and what it is a case of - is rarely defined and can sometimes be conflated with setting or organisation of interest (e.g. a hospital). The selection, rather than definition, of case or setting is sometimes explained. For example, in a study of automation in drug-dispensation, the authors illustrate an ‘ archetypal case (…of…) failure ’ of such an innovation carried out in an ‘ ongoing field of activity’ , i.e. a busy emergency department in a US hospital ([ 52 ] p1494).

Qualitative data is usually collected via interviews, observation and documents analysed using the constant comparative method, with authors sometimes reporting using a priori themes from pilot/exploratory phase or literature review. The analysis reveals differentiated intervention effects through the interpretations of different actors involved and inherent consensus and tension.

Context is not defined, but is operationalised through detailed description of the organisation and macro-level changes that frame the intervention. For example, in a study of transformational change of multiple healthcare services into a single regional service in Australia, the context for evaluating ‘ the micro detail of healthcare reform processes ’ was made up of the ‘ forces that influence [the] nature of change efforts in the healthcare sector ’ ([ 53 ] p33).

The focus on specific organisations has led in this tradition to a heterogeneous approach to context. Researchers frequently equate case study setting (e.g. hospital) not only with ‘case’ but also with context, and/or focus on local and national policy contexts (commonly funding issues) as ‘external’ conditions shaping ‘internal’ change efforts. For example, returning to the above-cited study, authors continue: ‘ the change in policy direction (...) was an event that occurred outside the control of the project and an example of the way in which public sector agencies are subject to change caused by the political context within which they operate’ ([ 43 ] p39).

In addition to description of external conditions, context was also operationalised through detailed description of the characteristics of actors (e.g. level of buy-in; power differences), organisations (e.g. management structure, organisational culture), and relationships amongst staff in organisations, as well as of the intervention and its origins (e.g. a study of the use of secondary data analysis from an electronic patient record system to improve safety and quality of care in a UK hospital offered information on a decade-long timeline of the introduction of the e-database itself [ 51 ]). Case study thereby enabled in-depth analysis of one or more units and description of ‘internal’ contextual differences, tensions and contradictions. In contrast with meta-narrative 1, some aspects of context that were internal to the case study organisation were shown as dynamic. This was due to relationships between staff or stakeholders being altered by the intervention.

In this research tradition, there is a noticeable interest in complexity, particularly relating to issues of diffusion, adaptation, implementation stages or cycles of the intervention, as well as sustainability, change and contextual shifts over time. Complexity is captured in iterative methodological approaches to case study evaluation. In a paper reflecting on a case study of healthcare reform in Australia, the authors adopt multiple methods across multiple levels of the system, citing the need ‘to ensure that the evaluation has the flexibility and breadth to accommodate a changing and complex context’ ([ 67 ] p492). The form of data, the sample and the overall structure of the research designs within specific organisations still tends to be pre-determined a priori, but there is room for adaptation over time.

The knowledge produced draws out positive and negative effects of interventions, often through the lens of the different actors involved. Intervention and context remain separate. The intervention is framed as a set of prespecified activities and processes that are re-interpreted by staff at different levels in the organisation.

Accounts provide the detail of intervention effects through actors’ eyes and intrinsic aspects of change in study sites. Empirical generalisation is not a primary objective, hence there is often limited exploration of how findings might be relevant to other settings. For example, in one study of safety improvement programs in US hospitals, the authors set out how their methods were intended ‘to capture a snapshot of the key accomplishments of leading organizations and to synthesize the self-perceived learning of their internal change leaders ’, rather than being ‘ meant to be representative of all health care organizations ’ ([ 54 ] p166). However, theoretical generalisation through development of middle-range theory is often an explicit objective, allowing transferability of theoretical findings (see, e.g. [ 51 ]).

Meta-narrative #3: Case studies are appropriate for undertaking realist evaluation

Case studies in this research tradition apply the theories and methods of realist evaluation [ 68 ], which interrogates how intervention outcomes are achieved by mechanisms triggered in specific contexts by systematically formulating CMO (context-mechanism-outcome) configurations (Table ​ (Table4). 4 ). The realist evaluation tradition drew explicitly on social realist philosophy and the foundational work of Pawson and Tilley who originally developed the approach within social policy research [ 68 ]. A seminal paper in 2005 made this work accessible and appealing to health services researchers [ 69 ]. A leading research funder, the UK National Institute of Health Research, was attracted to its systematic approach to exploring why interventions work well in some contexts but less well in others, and supported the development of guidance and standards (‘RAMESES’) for both empirical studies and theory-driven systematic reviews of such studies [ 36 , 70 ]. Many though not all studies in our sample followed the RAMESES methods and reporting structure and were ‘realist’ in the sense meant by Pawson and Tilley: surfacing policymakers’ theories about why a programme was thought to work, then testing these theories by collecting and analysing (mostly qualitative) data. The main empirical phase maps context-mechanism-outcome configurations as emerging from data analysis, and identifies (generative) causal relationships in order to develop middle-range or programme theory that can account for how and why an intervention works (or not) and under what conditions. Some studies that cited Pawson’s work appeared to be realist in name only or to be based on a different conception of realism known as critical realism (developed and popularised by Bhaskar). Within this meta-narrative, therefore, not all studies followed the methods that have been endorsed by scholars in the tradition.

Realist case study evaluation is seen as a theory-testing approach because the case study can ‘ illuminate mechanism in relation to outcome ’ ([ 60 ] p5). Case study methodology is advocated due to the focus on phenomena (e.g. interventions) in context, linking closely with the emphasis in realist evaluations on ‘ how causal mechanisms are shaped and constrained by social, political, economic (and so on) contexts ’ ([ 70 ] p9). The choice to use case study is often because it allows multiple and emergent data collection methods (e.g. [ 58 , 60 ]). For example, one paper reporting trial of a breastfeeding support group in Scotland describes how realist evaluation ‘ examines baseline contexts, how organisations, structures and interrelationships shape both implementation and outcomes over time’ ([ 58 ] p771). Authors reflect that it is ‘ detailed case studies, employing quantitative and qualitative data’, that are useful in order ‘to test our propositions about the importance of context, organisation and professional relationships for outcome’ (p. 771) .

Case studies in the realist evaluation tradition commonly employed qualitative data collection methods (e.g. interviews, focus groups, observation) supplemented by targeted quantitative methods (e.g. structured surveys, retrospective cohort data). Different data were generally analysed separately first, using deductive and inductive approaches. Findings were then synthesised to map context-mechanism-outcome formations, using retroductive logic (i.e. asking “what could explain this?” and building and testing hypotheses about mechanisms that produce what are known as ‘demi-regularities—things that tend to happen, though they do not always happen, under particular circumstances). Counterfactual thinking (“what if this were not the case?” or “what if this happened instead of that?”) is used to test alternative explanations that can confirm or disprove the context-mechanism-outcome hypotheses obtained.

The notion of context features strongly in the realist evaluation tradition. It is central to the theoretical core of realism and viewed as a set of circumstances where mechanisms are triggered to produce specific outcomes. However, as noted above, broad definitions of context included in theoretical and methodological papers did not always match how context was understood or operationalised in the studies reported. The meaning of context was wide-ranging, capturing the characteristics of organisations or local area, relationships between staff or broader regional or national policies. Context was also linked to ‘space and place’ with, for instance ‘ the public–private interface and tensions between a mother’s choice and societal pressures’ ([ 58 ] p769) used as a starting point for theoretical development.

Some authors discussed the challenge of differentiating context from phenomena when seeking to distinguish mechanisms. This is illustrated in a case study of a mental health intervention to improve links between primary care and specialist services in England [ 55 ]. Here prevalence of mental health conditions, GPs’ professional background, or the relationships between staff could all count as context, with authors reflecting that: ‘ the same phenomenon could be coded as an outcome or context, or as an outcome or a mechanism. For example a disease register was an outcome of service development and could then act as a mechanism for improving care ’ (p.78).

Realist case study evaluations tended to include two key narrative threads about complexity, both shaped by an understanding of the interaction between context and mechanisms in the production of intervention outcomes. First, that realist evaluation is an appropriate approach to understanding complex interventions (i.e., the intervention is complex in and of itself and realist evaluation can unpack its differential outcomes). Second, that the complexity of the intervention is surfaced in the implementation context or system (i.e. complexity can be observed through the evaluation as it emerges from the interaction between intervention and context). For example, in a case study of academic/practice collaborations in England, authors suggest that: ‘ Realist evaluation is particularly appropriate for developing explanations about how programmes, which by their nature are complex, work contingently within the context of implementation ’ ([ 59 ] p3). The realist case study approach is presented by authors as ideal for exploring this complexity, allowing researchers to study ‘ [collaborations] that are complex, in the sense that their behaviour can be explained with reference to the properties of a whole (adaptive) system rather than its individual components’ (p. 13). The authors conclude that such an approach ‘enables a complexity theory lens that views outcomes as emerging from interactions amongst individuals within a system’ (p.13).

In terms of the knowledge produced, outputs of realist evaluations tend to be presented as technical reports focused on how and why the intervention did (or perhaps didn’t) work. In-depth, thick description and rich information on context are required in order to obtain ‘ insights into the attributes necessary within complex health systems for a policy to work ’ ([ 58 ] p777). As Byng et al. [ 55 ] report: ‘ in some cases potential contingent mechanisms or contexts could not be identified to explain why a mechanism was associated with an outcome in some situations but not others. This could be due to the paucity of data regarding potential contingent contexts or due to inconsistency of the data and lack of clear associations’ (p.79). There is a sense, however, that in such cases the researchers felt that they had looked exhaustively for CMO configurations and identified all the demi-regularities there were to find.

Meta-narrative #4: Case studies enable naturalistic study of complex change

This research tradition, inspired by the work of Robert Stake [ 71 , 72 ], is oriented to achieving hermeneutic understanding and is characterised by a deliberately open-ended approach to the case, complexity and context (Table ​ (Table4). 4 ). Grounded in interpretivism (an orientation to inquiry that sees social reality as shaped by human experiences and social contexts), this kind of case study research involves granular, naturalistic and often longitudinal observation of events and relationships. The detail of the case is built iteratively, with context understood as an emergent property of ongoing interactions between the complex system and intervention. The researchers’ task is to interpret these interactions though a process of sense-making. Some researchers in this tradition (but not all) seek to engage with, and extend, social science theory.

Whilst ‘thick description’ (that is, a very detailed presentation of real-world events and settings using the narrative form, illustrated with extensive extracts from field notes and on-the-job interviews) is valued to some extent by all case study researchers, in this meta-narrative such description is a goal in its own right. In this sense the naturalistic case study can trace its origins to seminal work in anthropology, where thick description was advocated to provide a picture of what human behaviour and symbols meant in different cultures so they could be understood [ 73 ].

Unlike the traditions described in meta-narratives 1–3, the design of naturalistic case study research is not prescribed. The effects of interventions are seen as nonlinear, explained by narrative causality, as in the events in an unfolding story. Instead of seeking predictable and generalisable relationships between variables (as in meta-narrative 1), transferable theoretical models about change (as in meta-narrative 2) or demi-regularities (as in meta-narrative 3), this tradition is oriented to describing ‘ interacting processes [and the] extent of reciprocal adaptation and embedding ’ ([ 61 ] p539). The focus is on an emic (i.e. from the participants’ perspective) analysis of the case (as opposed to an external, “etic” analysis from the researchers’ perspective), with selection of data sources guided by the principle of ‘the opportunity to learn’ [ 74 ]. Researchers are interested in reflexivity, granularity and preserving ‘multiple realities’—that is, the perspectival view of different individuals and interest groups, which may conflict but which, taken together, contribute to a rich picture of what is going on ([ 72 ] p12). In sum, naturalistic case study research is understood as building a rich, detailed picture in context. In this tradition, the understanding of a case is not specified up front and emerges through the process of conducting the case study.

Data tend to be gathered via qualitative, especially ethnographic, methods (e.g. observation), sometimes with additional quantitative data such as clinic audits relating to patient outcomes and demographics, and patient surveys (e.g. [ 58 ]). Longitudinal approaches are favoured. Another important data source is the reflexive experiences of the researcher, which may include accounts of events ‘from the field’ and an analysis of the researcher’s reactions to these (what John Van Maanen calls ‘confessional tales’ [ 75 ]). In contrast with the research tradition described in meta-narrative 1, where the researcher is seen, more or less, as a dispassionate observer in the case, in this tradition he or she may, in some cases, be a character in the story of the case study. Analysis of the dataset in naturalistic case study involves iteration, comparison and integration of multiple data sources using narrative as the key synthesising device, an emphasis on stakeholders’ perspectives, input from those involved in the research and (in most cases) an ongoing dialogue with relevant theory. Reflexivity is seen by some authors as aiding transparency about subject position and relational dynamics between researcher and researched.

Context is rarely defined in this research tradition, but represented as emerging from a set of relationships and in interaction with wider social forces (e.g. the economy). Such interaction is situated as ‘sense-making’. To put it another way, the essential goal of naturalistic case study is to tell a story, and the story form presents actions and their contexts as interwoven. Operationalisation of context emerges through a narrative iteration between micro and macro contexts and through reflexivity (which brings in the context of the researcher as well as the research). Whilst naturalistic case study has traditionally placed little emphasis on theory (emphasising what Stake has called “the intrinsic study of the valued particular” ([ 76 ], p448), those who have applied this approach in a healthcare setting have often brought in theoretical models to move back and forth from the particular of the case to the general lessons that might be drawn from it (e.g. [ 62 , 65 ]).

Naturalistic cases are usually singular, with the knowledge produced revealing complexity through thick description of complex processes and systems. Meta-level accounts of problems and solutions read as accounts of the particular, with close analysis of the specificities of each case instrumental in generating in-depth understandings about wider structural relations and the unfolding of complex change that are potentially illuminating for (though not predictive of) other situations and settings. Cases do not need to be representative to learn from and generate knowledge [ 73 , 77 ]. The basis for transferability is primarily naturalistic generalisation (in which the researcher and those who immerse themselves in the detail of the case acquire a richer vocabulary and imaginative capabilities which they can then apply to other cases), and—to a lesser extent— theoretical generalisation , where the rich description of the case enables the application of theory, potentially increasing the explanatory power of the case [ 76 ]. Most of the naturalistic case studies in our dataset favoured rich description without extensive theorising. For example a community HIV project in South Africa [ 63 ] was presented without use of the word ‘theory’; a study of hospital mergers in the UK [ 62 ] states that a ‘preliminary theoretical framework’ was selected to guide data collection but is not mentioned further in the paper. In a study of the sustainability of whole-system change in healthcare in London, a theoretical framework based on system dynamics ‘ was developed after completion of the data collection’ and used to inform analysis ([ 61 ] p542). In all three cases, however, the primary focus of the paper is on presenting an authentic descriptive account.

Commonalities, debates and tensions across meta-narratives

Engagement with methodological literature.

Two key methodologists – Yin and Stake (Table ​ (Table5) 5 ) – were repeatedly cited across empirical papers. Those adopting a ‘Stakian’ approach differed, often significantly, from those drawing mainly on Yin, though it should be noted that many studies cited these methodologists without following the actual methods they advocated (some studies in meta-narrative 1, for example, cited Stake but approached case study research from a technical and largely positivist stance). Both Yin and Stake (and also Pawson, who draws broadly on Yin) emphasise detail, depth and contextualisation; however, while Stake’s method aims to build a naturalistic and evolving picture in context through immersion and interpretation, Yin’s pays more attention to design choices at the outset (e.g. case selection, sampling), a priori theoretical frameworks, and the description of step-wise processes (e.g. to develop chains of evidence). This distinction was reflected in our review. Yin-influenced studies (meta-narratives 1 and 3 along with most studies in 2) tended to describe and justify certain elements of case study design (e.g. the type of case study; data collection methods) more than others (e.g. definition of the case). Studies inspired by Stake (meta-narrative 4) tended to emphasise knowledge as emergent.

Overview of Robert Yin’s and Robert Stake’s work on case study research

As we synthesized findings across the literature in Cycles 1–3, we were struck by many authors’ limited reflexivity as to how case study methodology was taken up and modified in empirical application, leading to multiple, contradictory and confusing narrative threads about the philosophical foundations and methodological requirements of case study research. For example, empirical case studies in meta-narratives 1 and 2 tended to approach case study research as a set of procedures or tools. Few of the studies citing Yin (especially those in meta-narrative 1) included an explicit theoretical and methodological aim, despite Yin’s emphasis on setting out theoretical propositions a priori. There was an inconsistent use of Yin’s original methodology.

Some studies used ‘hybrid papers’ (Table  6 ) as a source of methodological input. Table ​ Table6 6 shows key observations of relevance in these papers with regards to the study of context in complex interventions, and the meta-narratives they relate to.

Overview of hybrid papers (Cycle 3)

a from Google Scholar; b 1 = Case studies develop and test complex interventions; 2 = Case studies analyse change in organisations

This body of hybrid literature was important in providing a ‘bridge’ from the empirical work to methodological sources. However, they frequently provided selected methodological detail (likely due to space constraints as journal articles) and tended to draw predominantly on Yin and Stake. There was limited reference, in empirical and hybrid papers, to how other disciplines have engaged with context and with the case, and how this has informed the researchers’ understanding of complexity in their study. This carries the potential to narrow the scope and potential of the methodology.

Overall, leading case study methodology experts from outside the healthcare field (e.g. Mitchell [ 83 ], Gerring [ 84 , 85 ], Flyvberg [ 22 ], Burawoy [ 85 ]) were conspicuously absent in the review of empirical case studies. Even where Yin and Stake were cited, empirical papers were not always faithful to the methodological principles of the original or provided a rationale for divergence.

Defining the case

Case definition is central to case study research and consequential for the knowledge produced. Moreover, case selection and its intended relationship to a broader class of phenomena forms the basis for causal inference. According to Gerring, ‘ what differentiates the case study from cross-unit study is its way of defining cases, not its analysis of those cases or its method of modelling causal relations’ ([ 84 ] p353).

Many papers offered a description of how a case was selected but not of how the case under study (regardless of whether it was ‘arrived at’ a priori or with an open-ended approach) was defined. This is important as, for example, defining a case by mentioning ‘the organisation’ (as several papers in our dataset did) at the exclusion of – for instance - how policy, discourse and wider structural relations shape organisational practices inevitably limits the choice of methods, analytical approach and findings to the boundaries of that organisation. Take the example of a study of mergers between different healthcare institutions in England, based on ‘ four in-depth case studies’ [ 62 ]. Each case study focused on integration of two institutions and they purposively selected four community trusts, in which such integration was taking place (to ensure ‘range of trust types and geographical spread in London ’). Case selection thus appears difficult to distinguish from the sampling of units of analysis. The authors then discuss how a ‘cross-case comparison’ produces a set of themes for the paper. Their detailed account is rich and offers a sense of the different processes of integration. However it remained unclear whether there was a specific case (of the process of integration) or whether the four ‘case studies’ were rather examples of what might happen during mergers. We reflected that examples such as these raised questions about the extent to which research teams had to make discipline-related choices regarding giving much detail about case selection whilst presenting the cases themselves as having unproblematic boundaries. It may be that in the empirical reality, as the research unfolded, what was ‘in frame’ and what was ‘out of frame’ changed, but these key decisions did not make it into the paper.

Connecting with context

Across papers it was for the most part unclear how authors understood, approached or defined context as a concept. There were varied meanings and uses of the term in empirical case studies, with implications for how evaluations of complex interventions are designed and conducted, the knowledge produced and potential transferability.

That said, case studies in all four research traditions clearly included an intention to contextualise. This was evident in: (i) the choice of a case study approach (e.g. citing Yin’s definition of a case as a phenomenon in ‘real life context’, e.g. [ 40 ]), (ii) use of context-mechanism-outcomes frameworks, (iii) details provided about organisations or settings ‘for’ an intervention, and iv) discussion about the importance of context more broadly. Papers attempted to operationalise context in different ways, e.g. describing study settings, offering contextualised justifications for case selection, reviewing national and local policies linked to the intervention, or recounting the history of an intervention or improvement activity.

In meta-narratives 1 and 2 (where case study is often procedure-driven and context external to the intervention), papers typically engaged with context in the ‘findings’ sections by offering lists of ‘contextual factors’ to be taken into consideration when assessing the intervention (e.g. [ 45 ]). In meta-narrative 3, realist case study evaluations included ‘context’ in the construction of context-mechanism-outcome hypotheses. In meta-narrative 4, naturalistic case studies situated context as emergent, relational and in dialogue with the intervention, offering rich or ‘thick’ descriptions for the reader to gain a ‘vicarious experience’ ([ 72 ] p86) of the case and relevant context (e.g. [ 63 ]).

Strikingly, even where authors discussed the importance of context and pointed at the contexts of relevance to their study, what is meant by ‘context’ and how this applied in the empirical studies reviewed remained unspecified. This lack of clarity made it difficult to appreciate how different kinds of contexts were conceptualised, how they compare (e.g. the ‘context’ of a specific hospital versus the policy ‘context’) or the relationship between context and intervention. A handful of papers (e.g. [ 63 ] explicitly engaged with context in ways that were ontologically coherent with the methods they adopted and had a clear level of analysis to focus on (e.g. language, social action). In absence of a conceptual definition, this was helpful to make sense of contextual dimensions of the case.

Some empirical papers cited (e.g. [ 50 , 59 ]) or made use of (e.g. [ 86 ]) the Consolidated Framework for Implementation Research (CFIR) [ 87 ], a meta-theoretical framework combining previous implementation research theories and models, to aid the assessment of different ‘dimensions of context’ (e.g. outer setting; inner setting) and linked sub-dimensional constructs (e.g. cost; implementation climate; planning). The papers using the CFIR largely (though not exclusively) aligned with meta-narrative 1, as the framework’s emphasis on contextual factors as ‘ surrounding the implementation efforts ’ ([ 87 ], p4) maintains a clear division between intervention, implementation and context.

Finally, a common characteristic across papers in meta-narratives 1–3 was a view of ‘changing contexts’ as an unexpected source of complexity, rather than change and dynamism being inherent qualities of context. Researchers frequently invoked the use of case study as a way to address complexity in and of context, but then revealed change as a finding. In some cases, attempts to integrate in results sections through the use of abstract phrases about ‘dynamic relationships’ were supported by limited empirical evidence of how this happens.

Transferability of findings from case study research

The question of transferability is central to much health services and public health research, whose goal might be said to be generating lessons from one setting that can be applied in other settings. Whilst case study research outside the healthcare field includes much discussion of this topic, we found limited engagement with the question of transferability (what some researchers call ‘external validity’) of case study evidence.

In the empirical studies we analysed, researchers rarely stated how findings could be generalised theoretically or applied to other settings. In meta-narrative 1, narratives focused on the need to aggregate and standardise datasets resulting from multiple data collection activities and provide lists of ‘contextual factors’ (typically high level and with limited contextual nuance) to explain variation in intervention outcomes. In meta-narrative 2, the focus was on how being ‘ rooted in specific context ’ means that generalisability of findings to other contexts was ‘limited by the extent to which contexts are similar ’ ([ 88 ] p9). Meta-narrative 3 used the concept of demi-regularities to convey the idea of partial transferability, and meta-narrative 4, as noted above, construed transferability mostly in terms of understanding and capacity to imagine, produced by immersion in the narrative detail of a single case. Overall, case studies provided insights into the organisation or other unit of analysis under study, while the choice of data collection methods, analytical approach and form of reporting meant they could easily be represented as too context specific to have wider relevance.

In meta-narratives 1–3, study findings were sometimes seen as informing middle-range theories—that is, theories that are sufficiently detailed to help explain some regularities in empirical findings but which do not account for every eventuality. For instance, studies in meta-narrative 3 sought to explain how an intervention works, why, for whom and under what conditions. This gave researchers a structured theoretical framework of reference and a way to express generalisability through middle-range theory development.

In meta-narratives 1 and 2 especially, authors frequently placed limitations on the explanatory power of single case studies (presented as offering useful points of transferability rather than stronger claims to theoretical generalisability) and appeared somewhat defensive vis-à-vis potential critiques rooted in statistical generalisation. In contrast, in meta-narrative 4 generalisation and transferability were based partly in the confidence researchers had in the naturalistic generalisability of a richly-described ‘n of 1’ case and partly on the development and refinement of substantive theory, noticing patterns, differences, commonalities or exceptions in instances or events in context and keeping these in dialogue with the theoretical approach adopted coming into the research study.

To our knowledge, this review is the first to focus on empirical and methodological literature relating to the intersection between case study research, context and complex interventions. Findings demonstrate the array of applications and the potential of case study research for evaluations of complex interventions in health care and public health research in key areas, including the use and refinement of theory, design flexibility and adaptability to emerging issues, breadth and depth of data sources and use of multiple methods, appreciating different kinds of causal mechanisms and complex causation, pragmatic advantages when experimenting is not feasible, and potential for transferability and generalisability from single and multiple case studies.

Summary of key findings and links to wider literature

The review has identified four broad research traditions in which case study was used to study complex interventions and the role of context: developing and testing complex interventions; developing theoretical models of change in organisations; undertaking realist evaluations; and producing thick descriptions of the change process. In these different traditions, case study, context and complex intervention, along with the interaction between them, were operationalised differently.

In the wider methodological literature, case study research is widely recognised as an overall approach or strategy encompassing a range of methods, and places much emphasis on the understanding and definition of the case, especially whether it has boundaries and the question of what it is a case of [ 22 , 71 , 84 , 85 , 89 , 90 ]. This was rarely reflected in the empirical literature we reviewed, with many papers emphasising case study methods but taking the case itself as given. The selection of the case (e.g. a particular intervention, a theory behind an intervention) and of the relevant units of analysis (e.g. an organisation through which the intervention is implemented) needs to be integrated with how a case study is understood and intended [ 81 ]. The lack of detail across meta-narratives about case definition and case selection (rather than simply a sampling strategy) makes it difficult to assess the value of case study evaluations. This, in turn, raised challenges for appreciating the context in which the case is situated and the evolving relationship between case, intervention and context.

Findings show that case study research offers useful avenues for analysing the nature of the relationship between context and intervention (e.g. whether distinct, interdependent, or indistinguishable). However, most empirical papers were limited in the extent to which the relationship between context and intervention was expressed and explored, the ways in which context can be understood and evaluated and the potential of case study research to aid this.

The current definition of context in MRC guidance as ‘anything external to the intervention which impedes or strengthens its effects’ ([ 10 ] p10) has been broadened to ‘any feature of the circumstances in which an intervention is implemented that may interact with the intervention to produce variation in outcomes’ in more recent Canadian Institute of Health Research/ National Institute of Health Research guidance for population health interventions studies ([ 13 ] p6). Taken together, these definitions reflect a predominant approach to thinking about context (e.g. meta-narratives 1–3), focusing on specific features that can aid understanding of any changes brought about by interaction with an intervention. Such research rarely sets out to study context, but is faced with challenges in intervention variation and understanding outcomes that lead researchers to then develop taxonomies and lists of contextual factors. This approach may risk de-contextualising context as high level ‘factors’, potentially losing the contextual nuance offered to the reader that is one of the strengths of case study research [ 6 ].

The dominance of this approach is tied up with the historical roots of health research (e.g. the biomedical institutionalisation of research and the RCT, need to generate probabilistic evidence of causality and generalisation), which has led to context being a distinct object of inquiry. By attempting to compartmentalise context/s, studies (e.g. meta-narrative 1) often move away from the stated aim of addressing complexity through case study, and return to a notion of discrete components (of the system, of the context) of a fixed reality, rather than engaging with the relational and processual nature of context and intervention.

Alongside the previously mentioned Consolidated Framework for Implementation Research [ 87 ], a number of other models of context, detailing different domains, constructs and attributes of context have become available in recent years [ 91 ]. For example, the 2017 Context and Implementation of Complex Interventions (CICI) framework is aimed at ‘simplifying and structuring complexity’ ([ 92 ] p1) in order to provide a lens for understanding interacting dimensions of context, implementation and setting. It presents a multi-level understanding of both context and implementation and sees context as ‘an overarching concept, comprising not only a physical location but also roles, interactions and relationships at multiple levels’ ([ 92 ] p6). Although not taken up by empirical papers reviewed in this paper, our scoping review showed that it is becoming popular in the field more recently.

Broader ways of thinking about and operationalising context are emerging in the healthcare field [ 13 , 17 , 27 , 93 ] emphasising, for instance, interventions in complex social systems and even interventions as system changes in themselves [ 94 , 95 ]. Methodological literature in the wider social sciences goes further, describing an array of ways in which context can be conceptualised with implications for the design, conduct and impact of case study research. There are connections across diverse disciplines between the idea of context as an event, as relational and/or socially structured action, or context as a process. For instance, Hawe’s idea of interventions as ‘events in systems’ [ 11 ], links with Rhodes and Lancaster’s idea of entanglements [ 96 ], and Meir and Dopson’s relational view as social action/process [ 97 ]. From this perspective, context is something that happens dynamically or is performed (usually to make sense of what is taking place) – this view of context was visible in meta-narratives 3 and 4, though not always articulated or operationalised explicitly in this way. We plan to examine cross-disciplinary contributions to understanding context in further detail in a future paper.

There are clearly opportunities for case study research to offer explanation and transfer of findings to other contexts. Empirical papers often held back from stating potential transferability and generalisability. This may be due to a historical tendency to understate and critique the potential (i) of case study to offer explanation and to test or build theory (compounded by the historical relegation of case study at the bottom of a methodological hierarchy of effectiveness) [ 6 ], and (ii) for abstraction from ‘the particular’ (e.g. specific case or context) to the general [ 22 ]. In-depth case studies, particularly in meta-narratives 3 and 4, tended to include lack of ‘representativeness’ as one of the limitations. This might be due to peer review in publication and a misunderstanding of the nature of inferences and how they are made (e.g. with authors starting with strong claims about theoretical generalisation from a single case, reviewers requesting acknowledgement of the case as limited in generalising to other cases characterised by different contextual factors, and authors accepting this point and downplaying explanatory power in order to get the paper accepted). Further work is needed to appreciate how and why transferability and inference are downplayed, how this manifests across meta-narratives and case study approaches, and to correct this.

Strengths and limitations of this study

Reviewing a vast and disciplinarily diverse literature focused on methodology and its operationalisation was challenging. The use of meta-narrative review was critical, enabling breadth to identify meta-narratives and depth to unpick pertinent methodological, ontological and epistemological concerns. Using three hermeneutic cycles allowed us to engage with the different layers of the literature – complexity, context and case study research – in iterative ways that a standard systematic review would not have enabled.

The aim of a meta-narrative review is to connect with seminal papers and key threads running through the literature. This allowed us to foreground different disciplines and paradigmatic approaches to case study and the ways in which these shape conceptual and empirical use. As the four meta-narratives demonstrate, case study research is a broad and contested terrain, with a lack of consensus on design and implementation and variation across disciplines. Given this breadth, we were aware that there may be sections of the literature that may have used case study methodology but different terminology (i.e. would likely meet our definitions for relevance but not use the 3C terms, perhaps ones describing their work as ‘ethnographies’, ‘mixed-methods’ or ‘qualitative studies’). These articles were unlikely to have been identified through our literature search; identifying them would need a much-expanded review.

One limitation was that our search strategy was neither sensitive nor specific. On the one hand, the final dataset was relatively small, making it difficult, for example, to demonstrate historicity in the different meta-narratives. It is likely that many relevant studies were missed. On the other hand, in an attempt to avoid an over-specific search (allowing ‘2Cs’ rather than insisting on ‘3Cs’), we turned up a significant body of work that used the term ‘case study’ but did not appear to adopt the methodology and were perhaps of marginal relevance to our research question. Nevertheless, these studies comprised a significant part of the dataset and allowed us to explore the reasoning behind the reporting of evaluative research as ‘case study’.

Our review focussed on ‘intervention-dependent context’, guiding us to literature in which the primary drive to study context came from the need to understand the effects of interventions. As set out above, other ways of conceiving context are possible.

This review also focused on reports of single case studies. A key contribution of case study designs to the literature on causal inference in complex systems is through comparative analysis of series of cases, such as through formal Qualitative Comparative Analysis (QCA) methods [ 98 ]. These use set-theory to systematically compare ‘configurations of conditions’ (such as elements of context, intervention features) to identify patterns associated with presence and absence of an outcome. As the findings of a QCA study are unlikely to be reported as ‘case studies’, they would not have been in scope for our search: the ‘cases’ here are the data for analysis, rather than describing the design of the study. QCA approaches can be applied to primary or secondary data. A recent review of these methods in evaluative health research [ 99 ] identified lack of empirical diversity as a challenge: in short, better reporting of primary case studies would also bring benefits for researchers using QCA and similar methods to improve causal inferences from reviews of those studies.

The need for better methods for evaluation of complex interventions is now widely recognised [ 13 , 21 , 28 , 29 ]. The ‘complexity turn’ has drawn attention to the limitations of relying on causal inference alone for understanding whether, and under which conditions, interventions in complex systems improve health services or the public health, and what mechanisms might link interventions and outcomes [ 4 ]. The four meta-narratives identified in our review are rooted in different ways of seeing the world, leading to different case study designs and methods and the production of different types of knowledge. Clearly, there are choices to be made about the exact approach to be taken in light of the focus of any evaluation, and the research questions that users of evaluation evidence need answered, the nature of the complex intervention and the extent of complexity within the intervention and system. If evaluative health research is to move beyond the current impasse on methods for understanding interventions as interruptions in complex systems then there is a need to more fully exploit the potential learning from this breadth of case study research in evaluation of complex interventions. To do so researchers, funders and users need to address five challenges.

First health research draws on multiple, and arguably incommensurable, conceptualisations of case study research: what a case study is, and the diversity in how empirical case studies are conducted and reported. Whilst we do not believe that consistency is needed across different approaches (indeed, each has important strengths), work is needed to appreciate the range of relevant meta-narratives shaping case study research, the scope and use of different methodologies and type of knowledge produced.

Second, misconceptions remain that case study research can only provide exploratory or descriptive evidence. Yet evidence from one case can be all that is needed for causal claims (e.g. claims that X CAN lead to Y; claims that X doesn’t necessarily lead to Y). This point relates to the value given to case study research generally. However, it has a particular salience in health sciences, where the evidence based medicine movement has instilled a hierarchy of evidence in which case study is firmly relegated to the bottom of the hierarchy. While there has been challenge to this hierarchy, and some movement, resituating and internalising case study research within health sciences requires significant change in the way in which researchers, funders and publishers within the field, not only conceive and rank different kinds of evidence and different kinds of causal inference [ 5 ] and their integration (where possible), but also the ways in which the community puts that into practice (e.g. via peer review, in scaling interventions).

Third, case study researchers, especially in some traditions, typically focus on ‘thick description’ of findings as a means of contextualising detail. This can make it challenging for those more familiar with RCT and quasi-experimental approaches to evaluation to identify the key messages related to intervention evaluation. It likely requires both a readiness on the part of users (e.g. policymakers, journal editors) to engage with the detail of case study research and better skills on the part of case study authors in distilling what are likely to be key issues for decision makers.

Fourth, the relationship between context and intervention needs to be conceptualised along a spectrum, from being separate through to being in interaction. This is not simply a matter of definition, but also relates to evaluation perspective and intended utility. For instance, from a realist perspective (meta-narrative 3) one might not differentiate between context and intervention (and indeed, outcome and mechanisms), but from an intervention-centred perspective (e.g. meta-narrative 1) it might be different. This approach represents a significant challenge to current approaches that tend to construct context as a set of factors/characteristics.

Finally, papers are variably framed as case study research. This is fostered by institutionalised conventions and checklists in which case study methodology either does not feature (and so almost inevitably becomes lost) or in which it is misinterpreted and misunderstood. There is scope for developing guidance and publication standards to help those reporting, publishing and using evidence from case studies.


Thanks go to Nia Roberts, librarian at the Bodleian Health Care Library of the University of Oxford, for her help and support in developing search strategies and carrying out searches.


Authors’ contributions.

JM had the initial idea for the research and, with SS, developed the initial study design. SS led the funding application and was principal investigator for this study and (as such) its guarantor. She was involved in all aspects of study design, review, analysis and writing; she drafted the first version of the paper. CP, JM and TG are senior academics with expertise in evidence review and synthesis and were involved in refining study design. CP led on oversight of the meta-narrative review, was part of the review team (with JM, SP and SS) and contributed to all other aspects of the study. SP is a senior academic and was involved in all aspects of the research. She led on searching and meta-narrative review of papers. JG and MP are senior academics with expertise in public health. Along with TG they formed the wider study steering group, reviewing study progress, inputting to the meta-narrative review and identifying wider literature on case study, context and complex interventions. All three contributed theoretical and methodological perspectives on case study research relating to complex interventions in health systems and public health. All authors have reviewed and approved the final manuscript.

The research was funded by the Medical Research Council (MR/S014632/1).

Additional funding for SP, TG, CP and SS salaries over the course of the study was provided by the UK National Institute for Health Research Oxford Biomedical Research Centre (BRC-1215-20008), Wellcome Trust (WT104830MA; 221457/Z/20/Z) and the University of Oxford’s Higher Education Innovation Fund. JG was additionally supported by a Wellcome Trust Centre Grant (203109/Z/16/Z).

Funding bodies had no input to the design of the study and collection, analysis, and interpretation of data or preparation of this paper.

Availability of data and materials


Not applicable.

The authors declare that they have no competing interests.

Publisher’s Note

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

Writing A Case Study

Types Of Case Study

Barbara P

Understand the Types of Case Study Here

Published on: Jun 22, 2019

Last updated on: Nov 29, 2023

Types of Case Study

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Case studies are effective research methods that focus on one specific case over time. This gives a detailed view that's great for learning.

Writing a case study is a very useful form of study in the educational process. With real-life examples, students can learn more effectively. 

A case study also has different types and forms. As a rule of thumb, all of them require a detailed and convincing answer based on a thorough analysis.

In this blog, we are going to discuss the different types of case study research methods in detail.

So, let’s dive right in!

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Understanding Case Studies

Case studies are a type of research methodology. Case study research designs examine subjects, projects, or organizations to provide an analysis based on the evidence.

It allows you to get insight into what causes any subject’s decisions and actions. This makes case studies a great way for students to develop their research skills.

A case study focuses on a single project for an extended period, which allows students to explore the topic in depth.

What are the Types of Case Study?

Multiple case studies are used for different purposes. The main purpose of case studies is to analyze problems within the boundaries of a specific organization, environment, or situation. 

Many aspects of a case study such as data collection and analysis, qualitative research questions, etc. are dependent on the researcher and what the study is looking to address. 

Case studies can be divided into the following categories:

Illustrative Case Study

Exploratory case study, cumulative case study, critical instance case study, descriptive case study, intrinsic case study, instrumental case study.

Let’s take a look at the detailed description of each type of case study with examples. 

An illustrative case study is used to examine a familiar case to help others understand it. It is one of the main types of case studies in research methodology and is primarily descriptive. 

In this type of case study, usually, one or two instances are used to explain what a situation is like. 

Here is an example to help you understand it better:

Illustrative Case Study Example

An exploratory case study is usually done before a larger-scale research. These types of case studies are very popular in the social sciences like political science and primarily focus on real-life contexts and situations.

This method is useful in identifying research questions and methods for a large and complex study. 

Let’s take a look at this example to help you have a better understanding:

Exploratory Case Study Example

A cumulative case study is one of the main types of case studies in qualitative research. It is used to collect information from different sources at different times.

This case study aims to summarize the past studies without spending additional cost and time on new investigations. 

Let’s take a look at the example below:

Cumulative Case Study Example

Critical instances case studies are used to determine the cause and consequence of an event. 

The main reason for this type of case study is to investigate one or more sources with unique interests and sometimes with no interest in general. 

Take a look at this example below:

Critical Instance Case Study Example

When you have a hypothesis, you can design a descriptive study. It aims to find connections between the subject being studied and a theory.

After making these connections, the study can be concluded. The results of the descriptive case study will usually suggest how to develop a theory further.

This example can help you understand the concept better:

Descriptive Case Study Example

Intrinsic studies are more commonly used in psychology, healthcare, or social work. So, if you were looking for types of case studies in sociology, or types of case studies in social research, this is it.

The focus of intrinsic studies is on the individual. The aim of such studies is not only to understand the subject better but also their history and how they interact with their environment.

Here is an example to help you understand;

Intrinsic Case Study Example

This type of case study is mostly used in qualitative research. In an instrumental case study, the specific case is selected to provide information about the research question.

It offers a lens through which researchers can explore complex concepts, theories, or generalizations.

Take a look at the example below to have a better understanding of the concepts:

Instrumental Case Study Example

Review some case study examples to help you understand how a specific case study is conducted.

Types of Subjects of Case Study 

In general, there are 5 types of subjects that case studies address. Every case study fits into the following subject categories. 

  • Person: This type of study focuses on one subject or individual and can use several research methods to determine the outcome. 
  • Group: This type of study takes into account a group of individuals. This could be a group of friends, coworkers, or family. 
  • Location: The main focus of this type of study is the place. It also takes into account how and why people use the place. 
  • Organization: This study focuses on an organization or company. This could also include the company employees or people who work in an event at the organization. 
  • Event: This type of study focuses on a specific event. It could be societal or cultural and examines how it affects the surroundings. 

Benefits of Case Study for Students

Here's a closer look at the multitude of benefits students can have with case studies:

Real-world Application

Case studies serve as a crucial link between theory and practice. By immersing themselves in real-world scenarios, students can apply theoretical knowledge to practical situations.

Critical Thinking Skills

Analyzing case studies demands critical thinking and informed decision-making. Students cultivate the ability to evaluate information, identify key factors, and develop well-reasoned solutions – essential skills in both academic and professional contexts.

Enhanced Problem-solving Abilities

Case studies often present complex problems that require creative and strategic solutions. Engaging with these challenges refines students' problem-solving skills, encouraging them to think innovatively and develop effective approaches.

Holistic Understanding

Going beyond theoretical concepts, case studies provide a holistic view of a subject. Students gain insights into the multifaceted aspects of a situation, helping them connect the dots and understand the broader context.

Exposure to Diverse Perspectives

Case studies often encompass a variety of industries, cultures, and situations. This exposure broadens students' perspectives, fostering a more comprehensive understanding of the world and the challenges faced by different entities.

So there you have it!

We have explored different types of case studies and their examples. Case studies act as the tools to understand and deal with the many challenges and opportunities around us.

Case studies are being used more and more in colleges and universities to help students understand how a hypothetical event can influence a person, group, or organization in real life. 

Not everyone can handle the case study writing assignment easily. It is even scary to think that your time and work could be wasted if you don't do the case study paper right. 

Our professional paper writing service is here to make your academic journey easier. 

Let us worry about your essay and buy case study today to ease your stress and achieve academic success.

Barbara P (Literature, Marketing)

Dr. Barbara is a highly experienced writer and author who holds a Ph.D. degree in public health from an Ivy League school. She has worked in the medical field for many years, conducting extensive research on various health topics. Her writing has been featured in several top-tier publications.

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  • Open access
  • Published: 27 June 2011

The case study approach

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

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

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

Peer Review reports


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

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

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

What is a case study?

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

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

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

What are case studies used for?

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

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

How are case studies conducted?

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

Defining the case

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

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

Selecting the case(s)

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

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

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

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

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

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

Collecting the data

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

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

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

Analysing, interpreting and reporting case studies

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

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

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

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

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

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

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


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.

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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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Writing a Case Study

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What is a case study?

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A Case study is: 

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

What are the different types of case studies?

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

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

Who are your case study participants?

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What is triangulation ? 

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

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How to write a Case Study?

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

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

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

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A Case in Case Study Methodology

Christine Benedichte Meyer

Norwegian School of Economics and Business Administration

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

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

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

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

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

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


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

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

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


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

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

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

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


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

Selection of Cases

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

Single or Multiple Cases

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

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

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

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

Sampling Cases

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

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

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

Unit of Analysis

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

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

Sampling Time

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

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

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

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

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

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

Sampling Business Areas, Divisions, and Sites

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


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

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

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

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

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

Sampling Interviewees

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

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

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

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

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

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

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

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

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

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


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

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

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

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

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

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


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

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

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

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

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

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

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

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

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

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

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

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

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

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


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

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

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


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

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

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

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

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

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

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

Construct Validity

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

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

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

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

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

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

Internal Validity

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

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

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


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

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

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


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

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

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

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

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

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

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

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

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

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

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  • Published: 19 February 2024

Sustaining the collaborative chronic care model in outpatient mental health: a matrixed multiple case study

  • Bo Kim 1 , 2 ,
  • Jennifer L. Sullivan 3 , 4 ,
  • Madisen E. Brown 1 ,
  • Samantha L. Connolly 1 , 2 ,
  • Elizabeth G. Spitzer 1 , 5 ,
  • Hannah M. Bailey 1 ,
  • Lauren M. Sippel 6 , 7 ,
  • Kendra Weaver 8 &
  • Christopher J. Miller 1 , 2  

Implementation Science volume  19 , Article number:  16 ( 2024 ) Cite this article

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Sustaining evidence-based practices (EBPs) is crucial to ensuring care quality and addressing health disparities. Approaches to identifying factors related to sustainability are critically needed. One such approach is Matrixed Multiple Case Study (MMCS), which identifies factors and their combinations that influence implementation. We applied MMCS to identify factors related to the sustainability of the evidence-based Collaborative Chronic Care Model (CCM) at nine Department of Veterans Affairs (VA) outpatient mental health clinics, 3–4 years after implementation support had concluded.

We conducted a directed content analysis of 30 provider interviews, using 6 CCM elements and 4 Integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) domains as codes. Based on CCM code summaries, we designated each site as high/medium/low sustainability. We used i-PARIHS code summaries to identify relevant factors for each site, the extent of their presence, and the type of influence they had on sustainability (enabling/neutral/hindering/unclear). We organized these data into a sortable matrix and assessed sustainability-related cross-site trends.

CCM sustainability status was distributed among the sites, with three sites each being high, medium, and low. Twenty-five factors were identified from the i-PARIHS code summaries, of which 3 exhibited strong trends by sustainability status (relevant i-PARIHS domain in square brackets): “Collaborativeness/Teamwork [Recipients],” “Staff/Leadership turnover [Recipients],” and “Having a consistent/strong internal facilitator [Facilitation]” during and after active implementation. At most high-sustainability sites only, (i) “Having a knowledgeable/helpful external facilitator [Facilitation]” was variably present and enabled sustainability when present, while (ii) “Clarity about what CCM comprises [Innovation],” “Interdisciplinary coordination [Recipients],” and “Adequate clinic space for CCM team members [Context]” were somewhat or less present with mixed influences on sustainability.


MMCS revealed that CCM sustainability in VA outpatient mental health clinics may be related most strongly to provider collaboration, knowledge retention during staff/leadership transitions, and availability of skilled internal facilitators. These findings have informed a subsequent CCM implementation trial that prospectively examines whether enhancing the above-mentioned factors within implementation facilitation improves sustainability. MMCS is a systematic approach to multi-site examination that can be used to investigate sustainability-related factors applicable to other EBPs and across multiple contexts.

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Contributions to the literature

We examined the ways in which the sustainability of the evidence-based Collaborative Chronic Care Model differed across nine outpatient mental health clinics where it was implemented.

This work demonstrates a unique application of the Matrixed Multiple Case Study (MMCS) method, originally developed to identify factors and their combinations that influence implementation, to investigate the long-term sustainability of a previously implemented evidence-based practice.

Contextual influences on sustainability identified through this work, as well as the systematic approach to multi-site examination offered by MMCS, can inform future efforts to sustainably implement and methodically evaluate an evidence-based practice’s uptake and continued use in routine care.

The sustainability of evidence-based practices (EBPs) over time is crucial to maximize the public health impact of EBPs implemented into routine care. Implementation evaluators focus on sustainability as a central implementation outcome, and funders of implementation efforts seek sustained long-term returns on their investment. Furthermore, practitioners and leadership at implementation sites face the task of sustaining an EBP’s usage even after implementation funding, support, and associated evaluation efforts conclude. The circumstances and influences contributing to EBP sustainability are therefore of high interest to the field of implementation science.

Sustainability depends on the specific EBP being implemented, the individuals undergoing the implementation, the contexts in which the implementation takes place, and the facilitation of (i.e., support for) the implementation. Hence, universal conditions that invariably lead to sustainability are challenging to establish. Even if a set of conditions could be identified as being associated with high sustainability “on average,” its usefulness is questionable when most real-world implementation contexts may deviate from “average” on key implementation-relevant metrics.

Thus, when seeking a better understanding of EBP sustainability, there is a critical need for methods that examine the ways in which sustainability varies in diverse contexts. One such method is Matrixed Multiple Case Study (MMCS) [ 1 ], which is beginning to be applied in implementation research to identify factors related to implementation [ 2 , 3 , 4 , 5 ]. MMCS capitalizes on the many contextual variations and heterogeneous outcomes that are expected when an EBP is implemented across multiple sites. Specifically, MMCS provides a formalized sequence of steps for cross-site analysis by arranging data into an array of matrices, which are sorted and filtered to test for expected factors and identify less expected factors influencing an implementation outcome of interest.

Although the MMCS represents a promising method for systematically exploring the “black box” of the ways in which implementation is more or less successful, it has not yet been applied to investigate the long-term sustainability of implemented EBPs. Therefore, we applied MMCS to identify factors related to the sustainability of the evidence-based Collaborative Chronic Care Model (CCM), previously implemented using implementation facilitation [ 6 , 7 , 8 ], at nine VA medical centers’ outpatient general mental health clinics. An earlier interview-based investigation of CCM provider perspectives had identified key determinants of CCM sustainability at the sites, yet characteristics related to the ways in which CCM sustainability differed at the sites are still not well understood. For this reason, our objective was to apply MMCS to examine the interview data to determine factors associated with CCM sustainability at each site.

Clinical and implementation contexts

CCM-based care aims to ensure that patients are treated in a coordinated, patient-centered, and anticipatory manner. This project’s nine outpatient general mental health clinics had participated in a hybrid CCM effectiveness-implementation trial 3 to 4 years prior, which had resulted in improved clinical outcomes that were not universally maintained post-implementation (i.e., after implementation funding and associated evaluation efforts concluded) [ 7 , 9 ]. This lack of aggregate sustainability across the nine clinics is what prompted the earlier interview-based investigation of CCM provider perspectives that identified key determinants of CCM sustainability at the trial sites [ 10 ].

These prior works were conducted in VA outpatient mental health teams, known as Behavioral Health Interdisciplinary Program (BHIP) teams. While there was variability in the exact composition of each BHIP team, all teams consisted of a multidisciplinary set of frontline clinicians (e.g., psychiatrists, psychologists, social workers, nurses) and support staff, serving a panel of about 1000 patients each.

This current project applied MMCS to examine the data from the earlier interviews [ 10 ] for the ways in which CCM sustainability differed at the sites and the factors related to sustainability. The project was determined to be non-research by the VA Boston Research and Development Service, and therefore did not require oversight by the Institutional Review Board (IRB). Details regarding the procedures undertaken for the completed hybrid CCM effectiveness-implementation trial, which serves as the context for this project, have been previously published [ 6 , 7 ]. Similarly, details regarding data collection for the follow-up provider interviews have also been previously published [ 10 ]. We provide a brief overview of the steps that we took for data collection and describe the steps that we took for applying MMCS to analyze the interview data. Additional file  1 outlines our use of the Consolidated Criteria for Reporting Qualitative Research (COREQ) Checklist [ 11 ].

Data collection

We recruited 30 outpatient mental health providers across the nine sites that had participated in the CCM implementation trial, including a multidisciplinary mix of mental health leaders and frontline staff. We recruited participants via email, and we obtained verbal informed consent from all participants. Each interview lasted between 30 and 60 min and focused on the degree to which the participant perceived care processes to have remained aligned to the CCM’s six core elements: work role redesign, patient self-management support, provider decision support, clinical information systems, linkages to community resources, and organizational/leadership support [ 12 , 13 , 14 ]. Interview questions also inquired about the participant’s perceived barriers and enablers influencing CCM sustainability, as well as about the latest status of CCM-based care practices. Interviews were digitally recorded and professionally transcribed. Additional details regarding data collection have been previously published [ 10 ].

Data analysis

We applied MMCS’ nine analytical steps [ 1 ] to the interview data. Each step described below was led by one designated member of the project team, with subsequent review by all project team members to reach a consensus on the examination conducted for each step.

We established the evaluation goal (step 1) to identify the ways in which sustainability differed across the sites and the factors related to sustainability, defining sustainability (step 2) as the continued existence of CCM-aligned care practices—namely, that care processes remained aligned with the six core CCM elements. Table  1 shows examples of care processes that align with each CCM element. As our prior works directly leading up to this project (i.e., design and evaluation of the CCM implementation trial that involved the very sites included in this project [ 6 , 15 , 16 ]) were guided by the Integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) framework [ 17 ] and i-PARIHS positions facilitation (the implementation strategy that our trial was testing) as the core ingredient that drives implementation [ 17 ], we selected i-PARIHS’ four domains—innovation, recipients, context, and facilitation—as relevant domains under which to examine factors influencing sustainability (step 3). i-PARIHS posits that the successful implementation of an innovation and its sustained use by recipients in a context is enabled by facilitation (both the individuals doing the facilitation and the process used for facilitation). We examined the data on both sustainability and potentially relevant i-PARIHS domains (step 4) by conducting directed content analysis [ 18 ] of the recorded and professionally transcribed interview data. We used the six CCM elements and the four i-PARIHS domains as a priori codes.

Additional file  2 provides an overview of data input, tasks performed, and analysis output for MMCS steps 5 through 9 described below. We assessed sustainability per site (step 5) by generating CCM code summaries per site, and reached a consensus on whether each site exhibited high, medium, or low sustainability relative to other sites based on the summary data. We assigned a higher sustainability level for sites that exhibited more CCM-aligned care processes, had more participants consistently mention those processes, and considered those processes more as “just the way things are done” at the site. Namely, (i) high sustainability sites had concrete examples of CCM-aligned care processes (such as the ones shown in Table  1 ) for many of the six CCM elements, which multiple participants mentioned as central to how they deliver care, (ii) low sustainability sites had only a few concrete examples of CCM-aligned care processes, mentioned by only a small subset of participants and/or inconsistently practiced, and (iii) medium sustainability sites matched neither of the high nor low sustainability cases, having several concrete examples of CCM-aligned care process for some of the CCM elements, varying in whether they are mentioned by multiple participants or how consistently they are a part of delivering care. For the CCM code summaries per site, one project team member initially reviewed the coded data to draft the summaries including exemplar quotes. Each summary and relevant exemplar quotes were then reviewed by and refined with input from all six project team members during recurring team meetings to finalize the high, medium, or low sustainability designation to use in the subsequent MMCS steps. Reviewing and refining the summaries for the nine sites took approximately four 60-min meetings of the six project team members, with each site’s CCM code summary taking approximately 20–35 min to discuss and reach consensus on. We referred to lists of specific examples of how the six core CCM elements were operationalized in our CCM implementation trial [ 19 , 20 ]. Refinements occurred mostly around familiarizing the newer members of the project team (i.e., those who had not participated in our prior CCM-related work) with the examples and definitions. We aligned to established qualitative analysis methods for consensus-reaching discussions [ 18 , 21 ]. Recognizing the common challenge faced by such discussions in adequately accounting for everyone’s interpretations of the data [ 22 ], we drew on Bens’ meeting facilitation techniques [ 23 ] that include setting ground rules, ensuring balanced participation from all project team members, and accurately recording decisions and action items.

We then identified influencing factors per site (step 6), by generating i-PARIHS code summaries per site and identifying distinct factors under each domain of i-PARIHS (e.g., Collaborativeness and teamwork as a factor under the Recipients domain). For the i-PARIHS code summaries per site, one project team member initially reviewed the coded data to draft the summaries including exemplar quotes. They elaborated on each i-PARIHS domain-specific summary by noting distinct factors that they deemed relevant to the summary, proposing descriptive wording to refer to each factor (e.g., “team members share a commitment to their patients” under the Recipients domain). Each summary, associated factor descriptions, and relevant exemplar quotes were then reviewed and refined with input from all six project team members during recurring team meetings to finalize the relevant factors to use in the subsequent MMCS steps. Finalizing the factors included deciding which similar proposed factor descriptions from different sites to consolidate into one factor and which wording to use to refer to the consolidated factor (e.g., “team members share a commitment to their patients,” “team members collaborate well,” and “team members know each other’s styles and what to expect” were consolidated into the Collaborativeness and teamwork factor under the Recipients domain). It took approximately four 60-min meetings of the six project team members to review and refine the summaries and factors for the nine sites, with each site’s i-PARIHS code summary and factors taking approximately 20–35 min to discuss and reach consensus on. We referred to lists of explicit definitions of i-PARIHS constructs that our team members had previously developed and published [ 16 , 24 ]. We once again aligned to established qualitative analysis methods for consensus-reaching discussions [ 18 , 21 ], drawing on Bens’ meeting facilitation techniques [ 23 ] to adequately account for everyone’s interpretations of the data [ 22 ].

We organized the examined data (i.e., the assessed sustainability and identified factors per site) into a sortable matrix (step 7) using Microsoft Excel [ 25 ], laid out by influencing factor (row), sustainability (column), and site (sheet). We conducted within-site analysis of the matrixed data (step 8), examining the data on each influencing factor and designating whether the factor (i) was present, somewhat present, or minimally present [based on aggregate reports from the site’s participants; used “minimally present” when, considering all available data from a site regarding a factor, the factor was predominantly weak (e.g., predominantly weak Ability to continue patient care during COVID at a medium sustainability site); used “somewhat present” when, considering all available data from a site regarding a factor, the factor was neither predominantly strong nor predominantly weak (e.g., neither predominantly strong nor predominantly weak Collaborativeness and teamwork at a low sustainability site)], and (ii) had an enabling, hindering, or neutral/unclear influence on sustainability (designated as “neutral” when, considering all available data from a site regarding a factor, the factor had neither a predominantly enabling nor a predominantly hindering influence on sustainability). These designations of factors’ presence and influence are conceptually representative of what is commonly referred to as magnitude and valence, respectively, by other efforts that construct scoring for qualitative data (e.g., [ 26 , 27 ]). Like the team-based consensus approach of earlier MMCS steps, factors’ presence and type of influence per site were initially proposed by one project team member after reviewing the matrix’s site-specific data, then refined with input from all project team members during recurring team meetings that reviewed the matrix. Accordingly, similar to the earlier MMCS steps, we aligned to established qualitative methods [ 18 , 21 ] and meeting facilitation techniques [ 23 ] for these consensus-reaching discussions.

We then conducted a cross-site analysis of the matrixed data (step 9), assessing whether factors and their combinations were (i) present across multiple sites, (ii) consistently associated with higher or lower sustainability, and (iii) emphasized at some sites more than others. We noted that any factor may have not come up during interviews with a site because either it is not pertinent or it is pertinent but still did not come up, although we asked an open-ended question at the end of each interview about whether there was anything else that the participant wanted to share regarding sustainability. To adequately account for these possibilities, we decided as a team to regard a factor or a combination of factors as being associated with high/medium/low sustainability if it was identified at a majority (i.e., even if not all) of the sites designated as high/medium/low sustainability (e.g., if the Collaborativeness and teamwork factor is identified at a majority, even if not all, of the high sustainability sites, we would find it to be associated with high sustainability). Like the team-based consensus approach of earlier MMCS steps, cross-site patterns were initially proposed by one project team member after reviewing the matrix’s cross-site data, then refined with input from all project team members during recurring team meetings that reviewed the matrix. Accordingly, similar to the earlier MMCS steps, we aligned to established qualitative methods [ 18 , 21 ] and meeting facilitation techniques [ 23 ] for these consensus-reaching discussions. We acknowledged the potential existence of additional factors influencing sustainability that may not have emerged during our interviews and also may vary substantially between sites. For example, adaptation of the CCM, characteristics of the patient population, and availability of continued funding, which are factors that extant literature reports as being relevant to sustainability [ 28 , 29 ], were not seen in our interview data. To maintain our analytic focus on the factors seen in our data, we did not add these factors to our analysis.

For the nine sites included in this project, we found the degree of CCM sustainability to be split evenly across the sites—three high-, three medium-, and three low-sustainability. Twenty-five total influencing factors were identified under the i-PARIHS domains of Innovation (6), Recipients (6), Context (8), and Facilitation (5). Table  2 shows these identified influencing factors by domain. Figure  1 shows 11 influencing factors that were identified for at least two sites within a group of high/medium/low sustainability sites—e.g., the factor “consistent and strong internal facilitator” is shown as being present at high sustainability sites with an enabling influence on sustainability, because it was identified as such at two or more of the high sustainability sites. Of these 11 influencing factors, four were identified only for sites with high CCM sustainability and two were identified only for sites with medium or low CCM sustainability.

figure 1

Influencing factors that were identified for at least two sites within a group of high/medium/low sustainability sites

Key trends in influencing factors associated with high, medium, and/or low CCM sustainability

Three factors across two i-PARIHS domains exhibited strong trends by sustainability status. They were the Collaborativeness and teamwork and Turnover of clinic staff and leadership factors under the Recipients domain, and the Having a consistent and strong internal facilitator factor under the Facilitation domain.

Recipients-related factors

Collaborativeness and teamwork was present with an enabling influence on CCM sustainability at most high and medium sustainability sites, while it was only somewhat present with a neutral influence on CCM sustainability at most low sustainability sites. When asked what had made their BHIP team work well, a participant from a high sustainability site said,

“Just a collaborative spirit.” (Participant 604)

A participant from a medium sustainability site said,

“We joke that [the BHIP teams] are even family, that the teams really do function pretty tightly and they each have their own personality.” (Participant 201)

At the low sustainability sites, willingness to work as a team varied across team members; a participant from a low sustainability site said,

“… I think it has to be the commitment of the people who are on the team. So those that are regularly attending, we get a lot more out of it than those that probably don't ever come [to team meetings].” (Participant 904)

Collaborativeness and teamwork of BHIP team members were often perceived as the highlight of pursuing interdisciplinary care.

Turnover of clinic staff and leadership was present with a hindering influence on CCM sustainability at most high, medium, and low sustainability sites.

“We’ve lost a lot of really, really good providers here in the time I’ve been here …,” (Participant 102)

said a participant from a low-sustainability site that had to reconfigure its BHIP teams due to clinic staff shortages. Turnover of mental health clinic leadership made it difficult to maintain CCM practices, especially beyond the teams that participated in the original CCM implementation trial. A participant from a medium sustainability site said,

“Probably about 90 percent of the things that we came up with have fallen by the wayside. Within our team, many of those remain but again, that hand off towards the other teams that I think partly is due to the turnover rate with program managers, supervisors, didn’t get fully implemented.” (Participant 703)

Although turnover was an issue for high sustainability sites as well, there was also indication of the situation improving in recent years; a participant from a high sustainability site said,

“… our attrition rollover rate has dropped quite a bit and I would really attribute that to [the CCM being] more functional and more sustainable and tolerable for the providers.” (Participant 502)

As such, staff and leadership turnover was deemed a major challenge for CCM sustainability for all sites regardless of the overall level of sustainability.

Facilitation-related factor

Having a consistent and strong internal facilitator was present with an enabling influence on CCM sustainability at high sustainability sites, not identified as an influencing factor at most of the medium sustainability sites, and variably present with a hindering, neutral, or unclear influence on CCM sustainability at low sustainability sites. Participants from a high sustainability site perceived that it was important for the internal facilitator to understand different BHIP team members’ personalities and know the clinic’s history. A participant from another high sustainability site shared that, as an internal facilitator themselves, they focused on recognizing and reinforcing the progress of team members:

“… I'm often the person who kind of [starts] off with, ‘Hey, look at what we've done in this location,’ ‘Hey look at what the team's done this month.’” (Participant 402)

A participant from a low sustainability site had also served as an internal facilitator and recounted the difficulty and importance of readying the BHIP team to function in the long run without their assistance:

“I should have been able to get out sooner, I think, to get it to have them running this themselves. And that was just a really difficult process.” (Participant 301)

Participants, especially from the high and low sustainability sites, attributed their BHIP teams’ successes and challenges to the skills of the internal facilitator.

Influencing factors identified only for sites with high CCM sustainability

Four factors across four i-PARIHS domains were identified for high sustainability sites and not for medium or low sustainability sites. They were the factors Details about the CCM being well understood (Innovation domain), Interdisciplinary coordination (Recipients domain), Having adequate clinic space for CCM team members (Context domain), and Having a knowledgeable and helpful external facilitator (Facilitation domain).

Innovation-related factor

Details about the CCM being well understood was minimal to somewhat present with an unclear influence on CCM sustainability.

“We’ve … been trying to help our providers see the benefit of team-based care and the episodes-of-care idea, and I would say that is something our folks really have continued to struggle with as well,” (Participant 401)

said a participant from a high sustainability site. “What is considered CCM-based care?” continued to be a question on providers’ minds. A participant from a high sustainability site asked during the interview,

“Is there kind of a clearing house of some of the best practices for [CCM] that you guys have … or some other collection of resources that we could draw from?” (Participant 601)

Although such references are indeed accessible online organization-wide, participants were not always aware of those resources or what exactly CCM entails.

Recipients-related factor

Interdisciplinary coordination was somewhat present with a hindering, neutral, or unclear influence on CCM sustainability. Coordination between psychotherapy and psychiatry providers was deemed difficult by participants from high-sustainability sites. A participant said,

“We were initially kind of top heavy on the psychiatry so just making sure we have … therapy staff balancing that out [has been important].” (Participant 501)

Another participant perceived that BHIP teams were helpful in managing.

… ‘sibling rivalry’ between different disciplines … because [CCM] puts us all in one team and we communicate.” (Participant 505)

Interdisciplinary coordination was understood by the participants as being necessary for effective CCM-based care yet difficult to achieve.

Context-related factor

Having adequate clinic space for CCM team members was minimal to somewhat present with a hindering, neutral, or unclear influence on CCM sustainability. COVID-19 led to changes in how clinic space was used/assigned. A participant from a high sustainability site remarked,

“Pre-COVID everything was in a room instead of online. And now all our meetings are online and so it's actually really easy for the supervisors to be able to rotate through them and then, you know, they can answer programmatic questions ….” (Participant 402)

Participants from another high sustainability site found that issues regarding limited clinic space were both exacerbated and alleviated by COVID, with the mental health service losing space to vaccine clinics but more mental health clinicians teleworking and in less need of clinic space. Virtual connections were seen to alleviate some physical workspace-related concerns.

Having a knowledgeable and helpful external facilitator was variably present; when present, it had an enabling influence on CCM sustainability. Participants from a high sustainability site noted how many of the external facilitator’s efforts to change the BHIP team’s work processes very much remained over time. An example of a change was to have team meetings be structured to meet evolving patient needs. Team members came to meetings with the shared knowledge and expectation that,

“… we need to touch on folks who are coming out of the hospital, we need to touch on folks with higher acuity needs.” (Participant 402)

Implementation support that sites received from their external facilitator mostly occurred during the time period of the original CCM implementation trial; correspondence with the external facilitator after that trial time period was not common for sites. Participants still largely found the external facilitator to provide helpful guidance and advice on delivering CCM-based care.

Influencing factors identified only for sites with medium or low CCM sustainability

Two factors were identified for medium or low sustainability sites and not for high sustainability sites. They were the factors Ability to continue patient care during COVID and Adequate resources/capacity for care delivery . These factors were both under i-PARIHS’ Context domain, unlike the influencing factors above that were identified only for high sustainability sites, which spanned all four i-PARIHS domains.

Context-related factors

Ability to continue patient care during COVID had a hindering influence on CCM sustainability when minimally present. Participants felt that their CCM work was challenged when delivering care through telehealth was made difficult—e.g., at a medium sustainability site, site policies during the pandemic required a higher number of in-person services than the BHIP team providers expected or desired to deliver. On the other hand, this factor had an enabling influence on CCM sustainability when present. A participant at a low sustainability site mentioned the effect of telehealth on being able to follow up more easily with patients who did not show up for their appointments:

“… my no-show rate has dropped dramatically because if people don’t log on after a couple minutes, I call them. They're like ‘oh, I forgot, let me pop right on,’ whereas, you know, in the face-to-face space, you know, you wait 15 minutes, you call them, it’s too late for them to come in so then they're no shows.” (Participant 102)

The advantages of virtual care delivery, as well as the challenges of getting approvals to pursue it to varying extents, were well recognized by the participants.

Adequate resources/capacity for care delivery was minimally present at medium sustainability sites with a hindering influence on CCM sustainability. At a medium sustainability site, although leadership was supportive of CCM, resources were being used to keep clinics operational (especially during COVID) rather than investing in building new CCM-based care delivery processes.

“I think that if my boss came to me, [and asked] what could I do for [the clinics] … I would say even more staff,” (Participant 202)

said a participant from a medium sustainability site. At the same time, the participant, as many others we interviewed, understood and emphasized the need for BHIP teams to proceed with care delivery even when resources were limited:

“… when you’re already dealing with a very busy clinic, short staff and then you’re hit with a pandemic you handle it the best that you can.” (Participant 202)

Participants felt the need for basic resource requirements to be met in order for CCM-based care to be feasible.

In this project, we examined factors influencing the sustainability of CCM-aligned care practices at general mental health clinics within nine VA medical centers that previously participated in a CCM implementation trial. Guided by the core CCM elements and i-PARIHS domains, we conducted and analyzed CCM provider interviews. Using MMCS, we found CCM sustainability to be split evenly across the nine sites (three high, three medium, and three low), and that sustainability may be related most strongly to provider collaboration, knowledge retention during staff/leadership transitions, and availability of skilled internal facilitators.

In comparison to most high sustainability sites, participants from most medium or low sustainability sites did not mention a knowledgeable and helpful external facilitator who enabled sustainability. Participants at the high sustainability sites also emphasized the need for clarity about what CCM-based care comprises, interdisciplinary coordination in delivering CCM-aligned care, and adequate clinic space for BHIP team members to connect and collaborate. In contrast, in comparison to participants at most high sustainability sites, participants at most medium or low sustainability sites emphasized the need for better continuity of patient-facing activities during the COVID-19 pandemic and more resources/capacity for care delivery. A notable difference between these two groups of influencing factors is that the ones emphasized at most high sustainability sites are more CCM-specific (e.g., external facilitator with CCM expertise, knowledge, and structures to support delivery of CCM-aligned care), while the ones emphasized at most medium or low sustainability sites are factors that certainly relate to CCM sustainability but are focused on care delivery operations beyond CCM-aligned care (e.g., COVID’s widespread impacts, limited staff availability). In short, an emphasis on immediate, short-term clinical needs in the face of the COVID-19 pandemic and staffing challenges appeared to sap sites’ enthusiasm for sustaining more collaborative, CCM-consistent care processes.

Our previous qualitative analysis of these interview data suggested that in order to achieve sustainability, it is important to establish appropriate infrastructure, organizational readiness, and mental health service- or department-wide coordination for CCM implementation [ 10 ]. The findings from the current project augment these previous findings by highlighting the specific factors associated with higher and lower CCM sustainability across the project sites. This additional knowledge provides two important insights into what CCM implementation efforts should prioritize with regard to the previously recommended appropriate infrastructure, readiness, and coordination. First, for knowledge retention and coordination during personnel changes (including any changes in internal facilitators through and following implementation), care processes and their specific procedures should be established and documented in order to bring new personnel up to speed on those care processes. Management sciences, as applied to health care and other fields, suggest that such organizational knowledge retention can be maximized when there are (i) structures set up to formally recognize/praise staff when they share key knowledge, (ii) succession plans to be applied in the event of staff turnover, (iii) opportunities for mentoring and shadowing, and (iv) after action reviews of conducted care processes, which allow staff to learn about and shape the processes themselves [ 30 , 31 , 32 , 33 ]. Future CCM implementation efforts may thus benefit from enacting these suggestions alongside establishing and documenting CCM-based care processes and associated procedures.

Second, efforts to implement CCM-aligned practices into routine care should account for the extent to which sites’ more fundamental operational needs are met or being addressed. That information can be used to appropriately scope the plan, expectations, and timeline for implementation. For instance, ongoing critical staffing shortages or high turnover [ 34 ] at a site are unlikely to be resolved through a few months of CCM implementation. In fact, in that situation, it is possible that CCM implementation efforts could lead to reduced team effectiveness in the short term, given the effort required to establish more collaborative and coordinated care processes [ 35 ]. Should CCM implementation move forward at a given site, implementation goals ought to be set on making progress in realms that are within the implementation effort’s control (e.g., designing CCM-aligned practices that take staffing challenges into consideration) [ 36 , 37 ] rather than on factors outside of the effort’s control (e.g., staffing shortages). As healthcare systems determine how to deploy support (e.g., facilitators) to sites for CCM implementation, they would benefit from considering whether it is primarily CCM expertise that the site needs at the moment, or more foundational organizational resources (e.g., mental health staffing, clinical space, leadership enhancement) [ 38 ] to first reach an operational state that can most benefit from CCM implementation efforts at a later point in time. There is growing consensus across the field that the readiness of a healthcare organization to innovate is a prerequisite to successful innovation (e.g., CCM implementation) regardless of the specific innovation [ 39 , 40 ]. Several promising strategies specifically target these organizational considerations for implementing evidence-based practices (e.g., [ 41 , 42 ]). Further, recent works have begun to more clearly delineate leadership-related, climate-related, and other contextual factors that contribute to organizations’ innovation readiness [ 43 ], which can inform healthcare systems’ future decisions regarding preparatory work leading to, and timing of, CCM implementation at their sites.

These considerations informed by MMCS may have useful implications for implementation strategy selection and tailoring for future CCM implementation efforts, especially in delineating the target level (e.g., system, organizational, clinic, individual) and timeline of implementation strategies to be deployed. For instance, of the three factors found to most notably trend with CCM sustainability, Collaborativeness and teamwork may be strengthened through shorter-term team-building interventions at the organizational and/or clinic levels [ 38 ], Turnover of clinic staff and leadership may be mitigated by aiming for longer-term culture/climate change at the system and/or organizational levels [ 44 , 45 , 46 ], and Having a consistent and strong internal facilitator may be ensured more immediately by selecting an individual with fitting expertise/characteristics to serve in the role [ 15 ] and imparting innovation/facilitation knowledge to them [ 47 ]. Which of these factors to focus on, and through what specific strategies, can be decided in partnership with an implementation site—for instance, candidate strategies can be identified based on ones that literature points to for addressing these factors [ 48 ], systematic selection of the strategies to move forward can happen with close input from site personnel [ 49 ], and explicit further specification of those strategies [ 50 ] can also happen in collaboration with site personnel to amply account for site-specific contexts [ 51 ].

As is common for implementation projects, the findings of this project are highly context-dependent. It involves the implementation of a specific evidence-based practice (the CCM) using a specific implementation strategy (implementation facilitation) at specific sites (BHIP teams within general mental health clinics at nine VA medical centers). For such context-dependent findings to be transferable [ 52 , 53 ] to meaningfully inform future implementation efforts, sources of variation in the findings and how the findings were reached must be documented and traceable. This means being explicit about each step and decision that led up to cross-site analysis, as MMCS encourages, so that future implementation efforts can accurately view and consider why and how findings might be transferable to their own work. For instance, beyond the finding that Turnover of clinic staff and leadership was a factor present at most of the examined sites, MMCS’ traceable documentation of qualitative data associated with this factor at high sustainability sites also allowed highlighting the perception that CCM implementation is contributing to mitigating turnover of providers in the clinic over time, which may be a crucial piece of information that fuels future CCM implementation efforts.

Furthermore, to compare findings and interpretations across projects, consistent procedures for setting up and conducting these multi-site investigations are indispensable [ 54 , 55 , 56 ]. Although many projects involve multiple sites and assess variations across the sites, it is less common to have clearly delineated protocols for conducting such assessments. MMCS is meant to target this very gap, by offering a formalized sequence of steps that prompt specification of analytical procedures and decisions that are often interpretive and left less specified. MMCS uses a concrete data structure (the matrix) to traceably organize information and knowledge gained from a project, and the matrix can accommodate various data sources and conceptual groundings (e.g., guiding theories, models, and frameworks) that may differ from project to project – for instance, although our application of MMCS aligned to i-PARIHS, other projects applying MMCS [ 2 , 5 ] use different conceptual guides (e.g., Consolidated Framework for Implementation Research [ 57 ], Theoretical Domains Framework [ 58 ]). Therefore, as more projects align to the MMCS steps [ 1 ] to identify factors related to implementation and sustainability, better comparisons, consolidations, and transfers of knowledge between projects may become possible.

This project has several limitations. First, the high, medium, and low sustainability assigned to the sites were based on the sites’ CCM sustainability relative to one another, rather than based on an external metric of sustainability. As measures of sustainability such as the Program Sustainability Assessment Tool [ 59 , 60 ] and the Sustainment Measurement System Scale [ 61 ] become increasingly developed and tested, future projects may consider the feasibility of incorporating such measures to assess each site’s sustainability. In our case, we worked on addressing this limitation by using a consensus approach within our project team to assign sustainability levels to sites, as well as by confirming that the sites that we designated as high sustainability exhibited CCM elements that we had previously observed at the end of their participation in the original CCM implementation trial [ 19 ]. Second, we did not assign strict thresholds above/below which the counts or proportions of data regarding a factor would automatically indicate whether the factor (i) was present, somewhat present, or minimally present and (ii) had an enabling, hindering, or neutral/unclear influence on sustainability. This follows widely accepted qualitative analytical guidance that discourages characterizing findings solely based on the frequency with which a notion is mentioned by participants [ 62 , 63 , 64 ], in order to prevent unsubstantiated inferences or conclusions. We sought to address this limitation in two ways: We carefully documented the project team’s rationale for each consensus reached, and we reviewed all consensuses reached in their entirety to ensure that any two factors with the same designation (e.g., “minimally present”) do not have associated rationale that conflict across those factors. These endeavors we undertook closely adhere to established case study research methods [ 65 ], which MMCS builds on, that emphasize strengthening the validity and reliability of findings through documenting a detailed analytic protocol, as well as reviewing data to ensure that patterns match across analytic units (e.g., factors, interviewees, sites). Third, our findings are based on three sites each for high/medium/low sustainability, and although we identified single factors associated with sustainability, we found no specific combinations of factors’ presence and influence that were repeatedly existent at a majority of the sites designated as high/medium/low sustainability. Examining additional sites on the factors identified through this work (as we will for our subsequent CCM implementation trial described below) will allow more opportunities for repeated combinations and other factors to emerge, making possible firmer conclusions regarding the extent to which the currently identified factors and absence of identified combinations are applicable beyond the sites included in this study. Fourth, the identified influencing factor “leadership support for CCM” (under the Context domain of the i-PARIHS framework) substantially overlaps in concept with the core “organizational/leadership support” element of the CCM. To avoid circular reasoning, we used leadership support-related data to inform our assignment of sites’ high, medium, or low CCM sustainability, rather than as a reason for the sites’ CCM sustainability. In reality, strong leadership support may both result from and contribute to implementation and sustainability [ 16 , 66 ], and thus causal relationships between the i-PARIHS-aligned influencing factors and the CCM elements (possibly with feedback loops) warrant further examination to most appropriately use leadership support-related data in future analyses of CCM sustainability. Fifth, findings may be subject to both social desirability bias in participants providing more positive than negative evidence of sustainability (especially participants who are responsible for implementing and sustaining CCM-aligned care at their site) and the project team members’ bias in interpreting the findings to align to their expectations of further effort being necessary to sustainably implement the CCM. To help mitigate this challenge, the project interviewers strove to elicit from participants both positive and negative perceptions and experiences related to CCM-based care delivery, both of which were present in the examined interview data.

Future work stemming from this project is twofold. Regarding CCM implementation, we will conduct a subsequent CCM implementation trial involving eight new sites to prospectively examine how implementation facilitation with an enhanced focus on these findings affects CCM sustainability. We started planning for sustainability prior to implementation, looking to this work for indicators of specific modifications needed to the previous way in which we used implementation facilitation to promote the uptake of CCM-based care [ 67 ]. Findings from this work suggest that sustainability may be related most strongly to (i) provider collaboration, (ii) knowledge retention during staff/leadership transitions, and (iii) availability of skilled internal facilitators. Hence, we will accordingly prioritize developing procedures for (i) regular CCM-related information exchange amongst BHIP team members, as well as between the BHIP team and clinic leadership, (ii) both translating knowledge to and keeping knowledge documented at the site, and (iii) supporting the sites’ own personnel to take the lead in driving CCM implementation.

Regarding MMCS, we will continuously refine and improve the method by learning from other projects applying, testing, and critiquing MMCS. Outside of our CCM-related projects, examinations of implementation data using MMCS are actively underway for various implementation efforts including that of a data dashboard for decision support on transitioning psychiatrically stable patients from specialty mental health to primary care [ 2 ], a peer-led healthy lifestyle intervention for individuals with serious mental illness [ 3 ], screening programs for intimate partner violence [ 4 ], and a policy- and organization-based health system strengthening intervention to improve health systems in sub-Saharan Africa [ 5 ]. As MMCS is used by more projects that differ from one another in their specific outcome of interest, and especially in light of our MMCS application that examines factors related to sustainability, we are curious whether certain proximal to distal outcomes are more subject to heterogeneity in influencing factors than other outcomes. For instance, sustainability outcomes, which are tracked following a longer passage of time than some other outcomes, may be subject to more contextual variations that occur over time and thus could particularly benefit from being examined using MMCS. We will also explore MMCS’ complementarity with coincidence analysis and other configurational analytical approaches [ 68 ] for examining implementation phenomena. We are excited about both the step-by-step traceability that MMCS can bring to such methods and those methods’ computational algorithms that can be beneficial to incorporate into MMCS for projects with larger numbers of sites. For example, Salvati and colleagues [ 69 ] described both the inspiration that MMCS provided in structuring their data as well as how they addressed MMCS’ visualization shortcomings through their innovative data matrix heat mapping, which led to their selection of specific factors to include in their subsequent coincidence analysis. Coincidence analysis is an enhancement to qualitative comparative analysis and other configurational analytical methods, in that it is formulated specifically for causal inference [ 70 ]. Thus, in considering improved reformulations of MMCS’ steps to better characterize examined factors as explicit causes to the outcomes of interest, we are inspired by and can draw on coincidence analysis’ approach to building and evaluating causal chains that link factors to outcomes. Relatedly, we have begun to actively consider the potential contribution that MMCS can make to hypothesis generation and theory development for implementation science. As efforts to understand the mechanisms through which implementation strategies work are gaining momentum [ 71 , 72 , 73 ], there is an increased need for methods that help decompose our understanding of factors that influence the mechanistic pathways from strategies to outcomes [ 74 ]. Implementation science is facing the need to develop theories, beyond frameworks, which delineate hypotheses for observed implementation phenomena that can be subsequently tested [ 75 ]. The methodical approach that MMCS offers can aid this important endeavor, by enabling data curation and examination of pertinent factors in a consistent way that allows meaningful synthesis of findings across sites and studies. We see these future directions as concrete steps toward elucidating the factors related to sustainable implementation of EBPs, especially leveraging data from projects where the number of sites is much smaller than the number of factors that may matter—which is indeed the case for most implementation projects.

Using MMCS, we found that provider collaboration, knowledge retention during staff/leadership transitions, and availability of skilled internal facilitators may be most strongly related to CCM sustainability in VA outpatient mental health clinics. Informed by these findings, we have a subsequent CCM implementation trial underway to prospectively test whether increasing the aforementioned factors within implementation facilitation enhances sustainability. The MMCS steps used here for systematic multi-site examination can also be applied to determining sustainability-related factors relevant to various other EBPs and implementation contexts.

Availability of data and materials

The data analyzed during the current project are not publicly available because participant privacy could be compromised.


Behavioral Health Interdisciplinary Program

Collaborative Chronic Care Model

Consolidated Criteria for Reporting Qualitative Research

coronavirus disease

evidence-based practice

Institutional Review Board

Integrated Promoting Action on Research Implementation in Health Services

Matrixed Multiple Case Study

United States Department of Veterans Affairs

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The authors sincerely thank the project participants for their time, as well as the project team members for their guidance and support. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the United States government.

This project was funded by VA grant QUE 20–026 and was designed and conducted in partnership with the VA Office of Mental Health and Suicide Prevention.

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Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System, 150 South Huntington Avenue, Boston, MA, 02130, USA

Bo Kim, Madisen E. Brown, Samantha L. Connolly, Elizabeth G. Spitzer, Hannah M. Bailey & Christopher J. Miller

Harvard Medical School, 25 Shattuck Street, Boston, MA, 02115, USA

Bo Kim, Samantha L. Connolly & Christopher J. Miller

Center of Innovation in Long Term Services and Supports (LTSS COIN), VA Providence Healthcare System, 385 Niagara Street, Providence, RI, 02907, USA

Jennifer L. Sullivan

Brown University School of Public Health, 121 South Main Street, Providence, RI, 02903, USA

VA Rocky Mountain Mental Illness Research, Education and Clinical Center (MIRECC), 1700 N Wheeling Street, Aurora, CO, 80045, USA

Elizabeth G. Spitzer

VA Northeast Program Evaluation Center, 950 Campbell Avenue, West Haven, CT, 06516, USA

Lauren M. Sippel

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Kendra Weaver

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Concept and design: BK, JS, and CM. Acquisition, analysis, and/or interpretation of data: BK, JS, MB, SC, ES, and CM. Initial drafting of the manuscript: BK. Critical revisions of the manuscript for important intellectual content: JS, MB, SC, ES, HB, LS, KW, and CM. All the authors read and approved the final manuscript.

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Supplementary Information

Additional file 1..

COREQ (COnsolidated criteria for REporting Qualitative research) Checklist.

Additional file 2.

Data input, tasks performed, and analysis output for MMCS Steps 5 through 9.

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Kim, B., Sullivan, J.L., Brown, M.E. et al. Sustaining the collaborative chronic care model in outpatient mental health: a matrixed multiple case study. Implementation Sci 19 , 16 (2024).

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