limitations of case study method in research

10 Case Study Advantages and Disadvantages

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

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A case study in academic research is a detailed and in-depth examination of a specific instance or event, generally conducted through a qualitative approach to data.

The most common case study definition that I come across is is Robert K. Yin’s (2003, p. 13) quote provided below:

“An empirical inquiry that investigates a contemporary phenomenon within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident.”

Researchers conduct case studies for a number of reasons, such as to explore complex phenomena within their real-life context, to look at a particularly interesting instance of a situation, or to dig deeper into something of interest identified in a wider-scale project.

While case studies render extremely interesting data, they have many limitations and are not suitable for all studies. One key limitation is that a case study’s findings are not usually generalizable to broader populations because one instance cannot be used to infer trends across populations.

Case Study Advantages and Disadvantages

1. in-depth analysis of complex phenomena.

Case study design allows researchers to delve deeply into intricate issues and situations.

By focusing on a specific instance or event, researchers can uncover nuanced details and layers of understanding that might be missed with other research methods, especially large-scale survey studies.

As Lee and Saunders (2017) argue,

“It allows that particular event to be studies in detail so that its unique qualities may be identified.”

This depth of analysis can provide rich insights into the underlying factors and dynamics of the studied phenomenon.

2. Holistic Understanding

Building on the above point, case studies can help us to understand a topic holistically and from multiple angles.

This means the researcher isn’t restricted to just examining a topic by using a pre-determined set of questions, as with questionnaires. Instead, researchers can use qualitative methods to delve into the many different angles, perspectives, and contextual factors related to the case study.

We can turn to Lee and Saunders (2017) again, who notes that case study researchers “develop a deep, holistic understanding of a particular phenomenon” with the intent of deeply understanding the phenomenon.

3. Examination of rare and Unusual Phenomena

We need to use case study methods when we stumble upon “rare and unusual” (Lee & Saunders, 2017) phenomena that would tend to be seen as mere outliers in population studies.

Take, for example, a child genius. A population study of all children of that child’s age would merely see this child as an outlier in the dataset, and this child may even be removed in order to predict overall trends.

So, to truly come to an understanding of this child and get insights into the environmental conditions that led to this child’s remarkable cognitive development, we need to do an in-depth study of this child specifically – so, we’d use a case study.

4. Helps Reveal the Experiences of Marginalzied Groups

Just as rare and unsual cases can be overlooked in population studies, so too can the experiences, beliefs, and perspectives of marginalized groups.

As Lee and Saunders (2017) argue, “case studies are also extremely useful in helping the expression of the voices of people whose interests are often ignored.”

Take, for example, the experiences of minority populations as they navigate healthcare systems. This was for many years a “hidden” phenomenon, not examined by researchers. It took case study designs to truly reveal this phenomenon, which helped to raise practitioners’ awareness of the importance of cultural sensitivity in medicine.

5. Ideal in Situations where Researchers cannot Control the Variables

Experimental designs – where a study takes place in a lab or controlled environment – are excellent for determining cause and effect . But not all studies can take place in controlled environments (Tetnowski, 2015).

When we’re out in the field doing observational studies or similar fieldwork, we don’t have the freedom to isolate dependent and independent variables. We need to use alternate methods.

Case studies are ideal in such situations.

A case study design will allow researchers to deeply immerse themselves in a setting (potentially combining it with methods such as ethnography or researcher observation) in order to see how phenomena take place in real-life settings.

6. Supports the generation of new theories or hypotheses

While large-scale quantitative studies such as cross-sectional designs and population surveys are excellent at testing theories and hypotheses on a large scale, they need a hypothesis to start off with!

This is where case studies – in the form of grounded research – come in. Often, a case study doesn’t start with a hypothesis. Instead, it ends with a hypothesis based upon the findings within a singular setting.

The deep analysis allows for hypotheses to emerge, which can then be taken to larger-scale studies in order to conduct further, more generalizable, testing of the hypothesis or theory.

7. Reveals the Unexpected

When a largescale quantitative research project has a clear hypothesis that it will test, it often becomes very rigid and has tunnel-vision on just exploring the hypothesis.

Of course, a structured scientific examination of the effects of specific interventions targeted at specific variables is extermely valuable.

But narrowly-focused studies often fail to shine a spotlight on unexpected and emergent data. Here, case studies come in very useful. Oftentimes, researchers set their eyes on a phenomenon and, when examining it closely with case studies, identify data and come to conclusions that are unprecedented, unforeseen, and outright surprising.

As Lars Meier (2009, p. 975) marvels, “where else can we become a part of foreign social worlds and have the chance to become aware of the unexpected?”

Disadvantages

1. not usually generalizable.

Case studies are not generalizable because they tend not to look at a broad enough corpus of data to be able to infer that there is a trend across a population.

As Yang (2022) argues, “by definition, case studies can make no claims to be typical.”

Case studies focus on one specific instance of a phenomenon. They explore the context, nuances, and situational factors that have come to bear on the case study. This is really useful for bringing to light important, new, and surprising information, as I’ve already covered.

But , it’s not often useful for generating data that has validity beyond the specific case study being examined.

2. Subjectivity in interpretation

Case studies usually (but not always) use qualitative data which helps to get deep into a topic and explain it in human terms, finding insights unattainable by quantitative data.

But qualitative data in case studies relies heavily on researcher interpretation. While researchers can be trained and work hard to focus on minimizing subjectivity (through methods like triangulation), it often emerges – some might argue it’s innevitable in qualitative studies.

So, a criticism of case studies could be that they’re more prone to subjectivity – and researchers need to take strides to address this in their studies.

3. Difficulty in replicating results

Case study research is often non-replicable because the study takes place in complex real-world settings where variables are not controlled.

So, when returning to a setting to re-do or attempt to replicate a study, we often find that the variables have changed to such an extent that replication is difficult. Furthermore, new researchers (with new subjective eyes) may catch things that the other readers overlooked.

Replication is even harder when researchers attempt to replicate a case study design in a new setting or with different participants.

Comprehension Quiz for Students

Question 1: What benefit do case studies offer when exploring the experiences of marginalized groups?

a) They provide generalizable data. b) They help express the voices of often-ignored individuals. c) They control all variables for the study. d) They always start with a clear hypothesis.

Question 2: Why might case studies be considered ideal for situations where researchers cannot control all variables?

a) They provide a structured scientific examination. b) They allow for generalizability across populations. c) They focus on one specific instance of a phenomenon. d) They allow for deep immersion in real-life settings.

Question 3: What is a primary disadvantage of case studies in terms of data applicability?

a) They always focus on the unexpected. b) They are not usually generalizable. c) They support the generation of new theories. d) They provide a holistic understanding.

Question 4: Why might case studies be considered more prone to subjectivity?

a) They always use quantitative data. b) They heavily rely on researcher interpretation, especially with qualitative data. c) They are always replicable. d) They look at a broad corpus of data.

Question 5: In what situations are experimental designs, such as those conducted in labs, most valuable?

a) When there’s a need to study rare and unusual phenomena. b) When a holistic understanding is required. c) When determining cause-and-effect relationships. d) When the study focuses on marginalized groups.

Question 6: Why is replication challenging in case study research?

a) Because they always use qualitative data. b) Because they tend to focus on a broad corpus of data. c) Due to the changing variables in complex real-world settings. d) Because they always start with a hypothesis.

Lee, B., & Saunders, M. N. K. (2017). Conducting Case Study Research for Business and Management Students. SAGE Publications.

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Tetnowski, J. (2015). Qualitative case study research design.  Perspectives on fluency and fluency disorders ,  25 (1), 39-45. ( Source )

Yang, S. L. (2022). The War on Corruption in China: Local Reform and Innovation . Taylor & Francis.

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Case study as a research method

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This chapter reviews the strengths and limitations of case study as a research method in social sciences. It provides an account of an evidence base to justify why a case study is best suitable for some research questions and why not for some other research questions. Case study designing around the research context, defining the structure and modality, conducting the study, collecting the data through triangulation mode, analysing the data, and interpreting the data and theory building at the end give a holistic view of it. In addition, the chapter also focuses on the types of case study and when and where to use case study as a research method in social science research.

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Methodology

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

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

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

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

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

Table of contents

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Research bias

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

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Case Study Research Method in Psychology

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

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

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

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

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

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

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

 Famous Case Studies

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

Clinical Case Studies

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

Child Psychology Case Studies

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

Types of Case Studies

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

Where Do You Find Data for a Case Study?

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

1. Primary sources

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

2. Secondary sources

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

3. Archival records

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

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

4. Organizational records

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

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

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

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

How do I Write a Case Study in Psychology?

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

1. Introduction

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

2. Case Presentation

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

3. Management and Outcome

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

4. Discussion

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

5. Additional Items

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

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

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

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

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

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

Limitations

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Further Information

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

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

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

Research question

• Conceptual framework
• Conceptual vs. theoretical framework

Data collection

• Qualitative research methods
• Focus groups
• Observational research

What is a case study?

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

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

Case studies

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

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

Definition of a case study

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

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

Characteristics of case studies

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

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

The role of case studies in research

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

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

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

What is the purpose of a case study?

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

Why use case studies in qualitative research?

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

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

The explanatory, exploratory, and descriptive roles of case studies

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

The impact of case studies on knowledge development

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

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

Types of case studies

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

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

Exploratory case studies

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

Descriptive case studies

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

Explanatory case studies

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

Intrinsic, instrumental, and collective case studies

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

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

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

Critical information systems research

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

Health research

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

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

Asthma research studies

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

Other fields

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

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

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

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

Propositions

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

Units of analysis

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

Argumentation

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

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

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

Defining the research question

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

Selecting and defining the case

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

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

Developing a detailed case study protocol

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

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

Collecting data

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

Analyzing and interpreting data

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

Writing the case study report

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

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

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

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

Observations

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

Documents and artifacts

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

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

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

Ensuring the quality of data collection

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

Data analysis

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

Organizing the data

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

Categorizing and coding the data

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

Identifying patterns and themes

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

Interpreting the data

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

Verification of the data

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

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

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

Benefits include the following:

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

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

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

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

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

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

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

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

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

Definitions of qualitative case study research

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

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

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

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

Current methodological issues in qualitative case study research

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

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

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

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

Assessment of rigour

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

Framework for assessing quality in qualitative case study research.

Adapted from Stake ( 1995 , p. 131).

Study design

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

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

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

Search strategy

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

Outcomes of search of qualitative methods journals.

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

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

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

Case study methodology or method

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

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

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

Case study of something particular and case selection

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

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

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

Contextually bound case study

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

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

Article synopsis of case study research using Stake's tradition

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

Article synopsis of case study research using Yin's tradition

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

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

Researcher and case interactions and triangulation

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

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

Study design inconsistent with methodology

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

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

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

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

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

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

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

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

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

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

Limitations of the review

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

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

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

Conflict of interest and funding

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

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Case Study: Types, Advantages And Disadvantages

  Case Study: Types, Advantages And Disadvantages 

Case study is both method and tool for research. Case study is the intensive study of a phenomenon, but it gives subjective information rather than objective. It gives detailed knowledge about the phenomena and is not able to generalize beyond the knowledge.

Case studies aim to analyze specific issues within the boundaries of a specific environment, situation or organization. According to its design, case study research method can be divided into three categories: explanatory, descriptive and exploratory.

Explanatory case studies aim to answer ‘how’ or ‘why’ questions with little control on behalf of the researcher over occurrence of events. This type of case study focuses on phenomena within the contexts of real-life situations.

Descriptive case studies aim to analyze the sequence of interpersonal events after a certain amount of time has passed. Case studies belonging to this category usually describe culture or sub-culture, and they attempt to discover the key phenomena.

Exploratory case studies aim to find answers to the questions of ‘what’ or ‘who’. Exploratory case study data collection method is often accompanied by additional data collection method(s) such as interviews, questionnaires, experiments etc.

DEFINITION OF CASE STUDY

The case study or case history method is not a newer thing, but it is a linear descendent of very ancient methods of sociological description and generalization namely, the ‘parable’, the ‘allegory’, the ‘story’ and the ‘novel’.

According to P.V. Young . “A fairly exhaustive study of a person or group is called a life of case history.”

Thus, the case study is more intensive in nature; the field of study is comparatively limited but has more depth in it.

TYPES OF CASE STUDY

Six types of case studies are conducted which are as follows:

Community Studies: The community study is a careful description and analysis of a group of people living together in a particular geographic location in a corporative way. The community study deals with such elements of the community as location, appearance, prevailing economic activity, climate and natural sources, historical development, how the people live, the social structure, goals and life values, an evaluation of the social institutions within the community that meet the human needs etc. Such studies are case studies, with the community serving as the case under investigation.

Casual Comparative Studies: Another type of study seeks to find the answers to the problems through the analysis of casual relationships. What factors seem to be associated with certain occurrences, conditions or types of behaviour? By the methodology of descriptive research, the relative importance of these factors may be investigated.

Activity Analysis: The analysis of the activities or processes that an individual is called upon to perform is important, both in industry and in various types of social agencies. This process of analysis is appropriate in any field of work and at all levels of responsibility. In social system, the roles of superintendent, the principal, the teacher and the custodian have been carefully analyzed to discover what these individuals do and need to be able to do.

Content or Document Analysis: Content analysis, sometimes known as document analysis. Deals with the systematic examination of current records or documents as sources of data. In documentary analysis, the following may be used as sources of data: official records and reports, printed forms, text-books, reference books, letters, autobiographies diaries, pictures, films and cartoons etc . But in using documentary sources, one must bear in mind the fact that data appearing in print is not necessarily trustworthy. This content or document analysis should serve a useful purpose in research, adding important knowledge to a field to study or yielding information that is helpful in evaluating and improving social or educational practices.

A Follow-up Study: A follow-up study investigates individuals who have left an institution after having completed programme, a treatment or a course of study, to know what has been the impact of the institutions and its programme upon them. By examining their status or seeking their opinions, one may get some idea of the adequacy or inadequacy of the institutes programme. Studies of this type enable an institution to evaluate various aspects of its programme in the light of actual results.

Trend Studies: The trend or predictive study is an interesting application of the descriptive method. In essence, it is based upon a longitudinal consideration of recorded data, indicating what has been happening in the past, what does the present situation reveal and on the basis of these data, what will be likely to happen in the future.

Whatever type of case study is to conduct, it’s important to first identify the purpose, goals, and approach for conducting methodologically sound research.

ADVANTAGES OF CASE STUDY

The main points of advantages of case study are given below:

Formation of valid hypothesis: Case study helps in formulating valid hypothesis. Once the various cases are extensively studied and analyze, the researcher can deduce various generalizations, which may be developed into useful hypotheses. It is admitted by all that the study of relevant literature and case study form the only potent sources of hypothesis.

  Useful in framing questionnaires and schedules: Case study is of great help in framing questionnaires, schedules or other forms. When a questionnaire is prepared after thorough case study the peculiarities of the group as well as individual units, become known also the type of response likely to be available, liking and aversions of the people. This helps in getting prompt response.

Sampling: Case study is of help in the stratification of the sample. By studying the individual units the researcher can put them in definite classes or types and thereby facilitate the perfect stratification of the sample.

Location of deviant cases: The case study makes it possible to locate deviant cases. There exists a general tendency to ignore them, but for scientific analysis, they are very important. The analysis of such cases is of valuable help in clarifying the theory itself.

Study of process: In cases where the problem under study constitutes a process and not one incident e.g. courtship process, clique formation etc., case study is the appropriate method as the case data is essential for valid study of such problems.

Enlarges experience: The range of personal experience of the researcher is enlarged by the case study on the other hand in statistical methods a narrow range of topics is selected, and the researcher’s knowledge is restricted to the particular aspect only.

Qualitative analysis in actual situation: Case study enables the establishment of the significance of the recorded data when the individual is alive and later on within the life of the classes of individuals. The researcher has the opportunity to come into contact with different classes of people and he is in a position to watch their life and hear their experiences. This provides him with an opportunity to acquire experiences of such life situations which he is never expected to lead.

This discussion highlights the advantages of the case data in social research. Social scientists developed the techniques to make it more perfect and remove the chances of bias.

LIMITATIONS/DISADVANTAGES OF CASE STUDY METHOD

Subjective bias: Research subjectivity in collecting data for supporting or refuting a particular explanation, personal view of investigation influences the findings and conclusion of the study.

Problem of objectivity: Due to excessive association with the social unit under investigation the researcher may develop self-justificatory data which are far from being factual.

Difficulty in comparison: Because of wide variations among human beings in terms of their response and behaviour, attitudes and values, social setting and circumstances, etc., the researcher actually finds it difficult to trace out two social units which are identical in all respects. This hinders proper comparison of cases.

A time, energy and money consuming method: The preparation of a case history involves a lot of time and expenditure of human energy, therefore, there is every possibility that most of the cases may get stray. Due to such difficulties, only a few researchers can afford to case study method.

Time span: Long time span may be another factor that is likely to distort the information provided by the social unit to the researcher.

Unreliable source material: The two major sources of case study are: Personal documents and life history. But in both these cases, the records or the own experience of the social units may not present a true picture. On the contrary, the social unit may try to suppress his unpleasant facts or add colour to them. As a result, the conclusions drawn do not give a true picture and dependable findings.

Scope for wrong conclusions: The case study is laden with inaccurate observation, wrong inferences, faulty reporting, memory failure, repression or omission of unpleasant facts in an unconscious manner, dramatization of facts, more imaginary description, and difficulty in choosing a case typical of the group. All these problems provide the researcher with every possibility of drawing wrong conclusions and errors.

Case studies are complex because they generally involve multiple sources of data, may include multiple cases within a study and produce large amounts of data for analysis. Researchers from many disciplines use the case study method to build upon theory, to produce new theory, to dispute or challenge theory, to explain a situation, to provide a basis to apply solutions to situations, to explore, or to describe an object or phenomenon. The advantages of the case study method are its applicability to real-life, contemporary, human situations and its public accessibility through written reports. Case study results relate directly to the common readers everyday experience and facilitate an understanding of complex real-life situations.

__________________________________________________________________________

Research Methodology Methods and Techniques~C. R. Kothari (p.113) - Link

Fundamental of Research Methodology and Statistics~Yogesh Kumar Singh (Chapter–10: Case Study Method p. 147) - Link

Social Research Methods: Qualitative and Quantitative Approaches~W. Lawrence Neuman (p.42) - Link

The Basics of Social Research~Earl Babbie (p.280) - Link

Social Science Research Principles, Methods, and Practices~Anol Bhattacherjee (93) - Link

PREPARING A CASE STUDY: A Guide for Designing and Conducting a Case Study for Evaluation Input - Link

A Case in Case Study Methodology - Link

Case Study Method - Link1 & Link 2

Unit-4 Case Study - Link

Case study as a research method - Link

Case_Study~Tanya Sammut-Bonnici and John McGee - Link

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What is a Case Study in Research? Definition, Methods, and Examples

Case study methodology offers researchers an exciting opportunity to explore intricate phenomena within specific contexts using a wide range of data sources and collection methods. It is highly pertinent in health and social sciences, environmental studies, social work, education, and business studies. Its diverse applications, such as advancing theory, program evaluation, and intervention development, make it an invaluable tool for driving meaningful research and fostering positive change.[ 1]  

Table of Contents

What is a Case Study?  

A case study method involves a detailed examination of a single subject, such as an individual, group, organization, event, or community, to explore and understand complex issues in real-life contexts. By focusing on one specific case, researchers can gain a deep understanding of the factors and dynamics at play, understanding their complex relationships, which might be missed in broader, more quantitative studies.  

When to do a Case Study?  

A case study design is useful when you want to explore a phenomenon in-depth and in its natural context. Here are some examples of when to use a case study :[ 2]  

• Exploratory Research: When you want to explore a new topic or phenomenon, a case study can help you understand the subject deeply. For example , a researcher studying a newly discovered plant species might use a case study to document its characteristics and behavior.  
• Descriptive Research: If you want to describe a complex phenomenon or process, a case study can provide a detailed and comprehensive description. For instance, a case study design   could describe the experiences of a group of individuals living with a rare disease.  
• Explanatory Research: When you want to understand why a particular phenomenon occurs, a case study can help you identify causal relationships. A case study design could investigate the reasons behind the success or failure of a particular business strategy.  
• Theory Building: Case studies can also be used to develop or refine theories. By systematically analyzing a series of cases, researchers can identify patterns and relationships that can contribute to developing new theories or refining existing ones.  
• Critical Instance: Sometimes, a single case can be used to study a rare or unusual phenomenon, but it is important for theoretical or practical reasons. For example , the case of Phineas Gage, a man who survived a severe brain injury, has been widely studied to understand the relationship between the brain and behavior.  
• Comparative Analysis: Case studies can also compare different cases or contexts. A case study example involves comparing the implementation of a particular policy in different countries to understand its effectiveness and identifying best practices.  

How to Create a Case Study – Step by Step  

Step 1: select a case  .

Careful case selection ensures relevance, insight, and meaningful contribution to existing knowledge in your field. Here’s how you can choose a case study design :[ 3]  

• Define Your Objectives: Clarify the purpose of your case study and what you hope to achieve. Do you want to provide new insights, challenge existing theories, propose solutions to a problem, or explore new research directions?  
• Consider Unusual or Outlying Cases: Focus on unusual, neglected, or outlying cases that can provide unique insights.  
• Choose a Representative Case: Alternatively, select a common or representative case to exemplify a particular category, experience, or phenomenon.   
• Avoid Bias: Ensure your selection process is unbiased using random or criteria-based selection.  
• Be Clear and Specific: Clearly define the boundaries of your study design , including the scope, timeframe, and key stakeholders.   
• Ethical Considerations: Consider ethical issues, such as confidentiality and informed consent.  

Step 2: Build a Theoretical Framework  

To ensure your case study has a solid academic foundation, it’s important to build a theoretical framework:   

• Conduct a Literature Review: Identify key concepts and theories relevant to your case study .  
• Establish Connections with Theory: Connect your case study with existing theories in the field.  
• Guide Your Analysis and Interpretation: Use your theoretical framework to guide your analysis, ensuring your findings are grounded in established theories and concepts.   

Step 3: Collect Your Data  

To conduct a comprehensive case study , you can use various research methods. These include interviews, observations, primary and secondary sources analysis, surveys, and a mixed methods approach. The aim is to gather rich and diverse data to enable a detailed analysis of your case study .  

Step 4: Describe and Analyze the Case  

How you report your findings will depend on the type of research you’re conducting. Here are two approaches:   

• Structured Approach: Follows a scientific paper format, making it easier for readers to follow your argument.  
• Narrative Approach: A more exploratory style aiming to analyze meanings and implications.  

Regardless of the approach you choose, it’s important to include the following elements in your case study :   

• Contextual Details: Provide background information about the case, including relevant historical, cultural, and social factors that may have influenced the outcome.  
• Literature and Theory: Connect your case study to existing literature and theory in the field. Discuss how your findings contribute to or challenge existing knowledge.  
• Wider Patterns or Debates: Consider how your case study fits into wider patterns or debates within the field. Discuss any implications your findings may have for future research or practice.  

What Are the Benefits of a Case Study   

Case studies offer a range of benefits , making them a powerful tool in research.  

1. In-Depth Analysis  

• Comprehensive Understanding: Case studies allow researchers to thoroughly explore a subject, understanding the complexities and nuances involved.  
• Rich Data: They offer rich qualitative and sometimes quantitative data, capturing the intricacies of real-life contexts.  

2. Contextual Insight  

• Real-World Application: Case studies provide insights into real-world applications, making the findings highly relevant and practical.  
• Context-Specific: They highlight how various factors interact within a specific context, offering a detailed picture of the situation.  

3. Flexibility  

• Methodological Diversity: Case studies can use various data collection methods, including interviews, observations, document analysis, and surveys.  
• Adaptability: Researchers can adapt the case study approach to fit the specific needs and circumstances of the research.  

4. Practical Solutions  

• Actionable Insights: The detailed findings from case studies can inform practical solutions and recommendations for practitioners and policymakers.  
• Problem-Solving: They help understand the root causes of problems and devise effective strategies to address them.  

5. Unique Cases  

• Rare Phenomena: Case studies are particularly valuable for studying rare or unique cases that other research methods may not capture.  
• Detailed Documentation: They document and preserve detailed information about specific instances that might otherwise be overlooked.  

What Are the Limitations of a Case Study   

While case studies offer valuable insights and a detailed understanding of complex issues, they have several limitations .  

1. Limited Generalizability  

• Specific Context: Case studies often focus on a single case or a small number of cases, which may limit the generalization of findings to broader populations or different contexts.  
• Unique Situations: The unique characteristics of the case may not be representative of other situations, reducing the applicability of the results.  

2. Subjectivity  

• Researcher Bias: The researcher’s perspectives and interpretations can influence the analysis and conclusions, potentially introducing bias.  
• Participant Bias: Participants’ responses and behaviors may be influenced by their awareness of being studied, known as the Hawthorne effect.  

3. Time-Consuming  

• Data Collection and Analysis: Gathering detailed, in-depth data requires significant time and effort, making case studies more time-consuming than other research methods.  
• Longitudinal Studies: If the case study observes changes over time, it can become even more prolonged.  

4. Resource Intensive  

• Financial and Human Resources: Conducting comprehensive case studies may require significant financial investment and human resources, including trained researchers and participant access.  
• Access to Data: Accessing relevant and reliable data sources can be challenging, particularly in sensitive or proprietary contexts.  

5. Replication Difficulties  

• Unique Contexts: A case study’s specific and detailed context makes it difficult to replicate the study exactly, limiting the ability to validate findings through repetition.  
• Variability: Differences in contexts, researchers, and methodologies can lead to variations in findings, complicating efforts to achieve consistent results.  

By acknowledging and addressing these limitations , researchers can enhance the rigor and reliability of their case study findings.  

Key Takeaways  

Case studies are valuable in research because they provide an in-depth, contextual analysis of a single subject, event, or organization. They allow researchers to explore complex issues in real-world settings, capturing detailed qualitative and quantitative data. This method is useful for generating insights, developing theories, and offering practical solutions to problems. They are versatile, applicable in diverse fields such as business, education, and health, and can complement other research methods by providing rich, contextual evidence. However, their findings may have limited generalizability due to the focus on a specific case.  

Frequently Asked Questions  

Q: What is a case study in research?  

A case study in research is an impactful tool for gaining a deep understanding of complex issues within their real-life context. It combines various data collection methods and provides rich, detailed insights that can inform theory development and practical applications.  

Q: What are the advantages of using case studies in research?  

Case studies are a powerful research method, offering advantages such as in-depth analysis, contextual insights, flexibility, rich data, and the ability to handle complex issues. They are particularly valuable for exploring new areas, generating hypotheses, and providing detailed, illustrative examples that can inform theory and practice.  

Q: Can case studies be used in quantitative research?  

While case studies are predominantly associated with qualitative research, they can effectively incorporate quantitative methods to provide a more comprehensive analysis. A mixed-methods approach leverages qualitative and quantitative research strengths, offering a powerful tool for exploring complex issues in a real-world context. For example , a new medical treatment case study can incorporate quantitative clinical outcomes (e.g., patient recovery rates and dosage levels) along with qualitative patient interviews.  

Q: What are the key components of a case study?  

A case study typically includes several key components:   

• Introductio n, which provides an overview and sets the context by presenting the problem statement and research objectives;  
• Literature review , which connects the study to existing theories and prior research;  
• Methodology , which details the case study design , data collection methods, and analysis techniques;   
• Findings , which present the data and results, including descriptions, patterns, and themes;   
• Discussion and conclusion , which interpret the findings, discuss their implications, and offer conclusions, practical applications, limitations, and suggestions for future research.  

Together, these components ensure a comprehensive, systematic, and insightful exploration of the case.  

References  

• de Vries, K. (2020). Case study methodology. In  Critical qualitative health research  (pp. 41-52). Routledge.  
• Fidel, R. (1984). The case study method: A case study.  Library and Information Science Research ,  6 (3), 273-288.  
• Thomas, G. (2021). How to do your case study.  How to do your case study , 1-320.  

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Home » Pros and Cons » 12 Case Study Method Advantages and Disadvantages

12 Case Study Method Advantages and Disadvantages

A case study is an investigation into an individual circumstance. The investigation may be of a single person, business, event, or group. The investigation involves collecting in-depth data about the individual entity through the use of several collection methods. Interviews and observation are two of the most common forms of data collection used.

The case study method was originally developed in the field of clinical medicine. It has expanded since to other industries to examine key results, either positive or negative, that were received through a specific set of decisions. This allows for the topic to be researched with great detail, allowing others to glean knowledge from the information presented.

Here are the advantages and disadvantages of using the case study method.

List of the Advantages of the Case Study Method

1. it turns client observations into useable data..

Case studies offer verifiable data from direct observations of the individual entity involved. These observations provide information about input processes. It can show the path taken which led to specific results being generated. Those observations make it possible for others, in similar circumstances, to potentially replicate the results discovered by the case study method.

2. It turns opinion into fact.

Case studies provide facts to study because you’re looking at data which was generated in real-time. It is a way for researchers to turn their opinions into information that can be verified as fact because there is a proven path of positive or negative development. Singling out a specific incident also provides in-depth details about the path of development, which gives it extra credibility to the outside observer.

3. It is relevant to all parties involved.

Case studies that are chosen well will be relevant to everyone who is participating in the process. Because there is such a high level of relevance involved, researchers are able to stay actively engaged in the data collection process. Participants are able to further their knowledge growth because there is interest in the outcome of the case study. Most importantly, the case study method essentially forces people to make a decision about the question being studied, then defend their position through the use of facts.

4. It uses a number of different research methodologies.

The case study method involves more than just interviews and direct observation. Case histories from a records database can be used with this method. Questionnaires can be distributed to participants in the entity being studies. Individuals who have kept diaries and journals about the entity being studied can be included. Even certain experimental tasks, such as a memory test, can be part of this research process.

5. It can be done remotely.

Researchers do not need to be present at a specific location or facility to utilize the case study method. Research can be obtained over the phone, through email, and other forms of remote communication. Even interviews can be conducted over the phone. That means this method is good for formative research that is exploratory in nature, even if it must be completed from a remote location.

6. It is inexpensive.

Compared to other methods of research, the case study method is rather inexpensive. The costs associated with this method involve accessing data, which can often be done for free. Even when there are in-person interviews or other on-site duties involved, the costs of reviewing the data are minimal.

7. It is very accessible to readers.

The case study method puts data into a usable format for those who read the data and note its outcome. Although there may be perspectives of the researcher included in the outcome, the goal of this method is to help the reader be able to identify specific concepts to which they also relate. That allows them to discover unusual features within the data, examine outliers that may be present, or draw conclusions from their own experiences.

List of the Disadvantages of the Case Study Method

1. it can have influence factors within the data..

Every person has their own unconscious bias. Although the case study method is designed to limit the influence of this bias by collecting fact-based data, it is the collector of the data who gets to define what is a “fact” and what is not. That means the real-time data being collected may be based on the results the researcher wants to see from the entity instead. By controlling how facts are collected, a research can control the results this method generates.

2. It takes longer to analyze the data.

The information collection process through the case study method takes much longer to collect than other research options. That is because there is an enormous amount of data which must be sifted through. It’s not just the researchers who can influence the outcome in this type of research method. Participants can also influence outcomes by given inaccurate or incomplete answers to questions they are asked. Researchers must verify the information presented to ensure its accuracy, and that takes time to complete.

3. It can be an inefficient process.

Case study methods require the participation of the individuals or entities involved for it to be a successful process. That means the skills of the researcher will help to determine the quality of information that is being received. Some participants may be quiet, unwilling to answer even basic questions about what is being studied. Others may be overly talkative, exploring tangents which have nothing to do with the case study at all. If researchers are unsure of how to manage this process, then incomplete data is often collected.

4. It requires a small sample size to be effective.

The case study method requires a small sample size for it to yield an effective amount of data to be analyzed. If there are different demographics involved with the entity, or there are different needs which must be examined, then the case study method becomes very inefficient.

5. It is a labor-intensive method of data collection.

The case study method requires researchers to have a high level of language skills to be successful with data collection. Researchers must be personally involved in every aspect of collecting the data as well. From reviewing files or entries personally to conducting personal interviews, the concepts and themes of this process are heavily reliant on the amount of work each researcher is willing to put into things.

These case study method advantages and disadvantages offer a look at the effectiveness of this research option. With the right skill set, it can be used as an effective tool to gather rich, detailed information about specific entities. Without the right skill set, the case study method becomes inefficient and inaccurate.

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Case Study Method – 18 Advantages and Disadvantages

The case study method uses investigatory research as a way to collect data about specific demographics. This approach can apply to individuals, businesses, groups, or events. Each participant receives an equal amount of participation, offering information for collection that can then find new insights into specific trends, ideas, of hypotheses.

Interviews and research observation are the two standard methods of data collection used when following the case study method.

Researchers initially developed the case study method to develop and support hypotheses in clinical medicine. The benefits found in these efforts led the approach to transition to other industries, allowing for the examination of results through proposed decisions, processes, or outcomes. Its unique approach to information makes it possible for others to glean specific points of wisdom that encourage growth.

Several case study method advantages and disadvantages can appear when researchers take this approach.

List of the Advantages of the Case Study Method

1. It requires an intensive study of a specific unit. Researchers must document verifiable data from direct observations when using the case study method. This work offers information about the input processes that go into the hypothesis under consideration. A casual approach to data-gathering work is not effective if a definitive outcome is desired. Each behavior, choice, or comment is a critical component that can verify or dispute the ideas being considered.

Intensive programs can require a significant amount of work for researchers, but it can also promote an improvement in the data collected. That means a hypothesis can receive immediate verification in some situations.

2. No sampling is required when following the case study method. This research method studies social units in their entire perspective instead of pulling individual data points out to analyze them. That means there is no sampling work required when using the case study method. The hypothesis under consideration receives support because it works to turn opinions into facts, verifying or denying the proposals that outside observers can use in the future.

Although researchers might pay attention to specific incidents or outcomes based on generalized behaviors or ideas, the study itself won’t sample those situations. It takes a look at the “bigger vision” instead.

3. This method offers a continuous analysis of the facts. The case study method will look at the facts continuously for the social group being studied by researchers. That means there aren’t interruptions in the process that could limit the validity of the data being collected through this work. This advantage reduces the need to use assumptions when drawing conclusions from the information, adding validity to the outcome of the study over time. That means the outcome becomes relevant to both sides of the equation as it can prove specific suppositions or invalidate a hypothesis under consideration.

This advantage can lead to inefficiencies because of the amount of data being studied by researchers. It is up to the individuals involved in the process to sort out what is useful and meaningful and what is not.

4. It is a useful approach to take when formulating a hypothesis. Researchers will use the case study method advantages to verify a hypothesis under consideration. It is not unusual for the collected data to lead people toward the formulation of new ideas after completing this work. This process encourages further study because it allows concepts to evolve as people do in social or physical environments. That means a complete data set can be gathered based on the skills of the researcher and the honesty of the individuals involved in the study itself.

Although this approach won’t develop a societal-level evaluation of a hypothesis, it can look at how specific groups will react in various circumstances. That information can lead to a better decision-making process in the future for everyone involved.

5. It provides an increase in knowledge. The case study method provides everyone with analytical power to increase knowledge. This advantage is possible because it uses a variety of methodologies to collect information while evaluating a hypothesis. Researchers prefer to use direct observation and interviews to complete their work, but it can also advantage through the use of questionnaires. Participants might need to fill out a journal or diary about their experiences that can be used to study behaviors or choices.

Some researchers incorporate memory tests and experimental tasks to determine how social groups will interact or respond in specific situations. All of this data then works to verify the possibilities that a hypothesis proposes.

6. The case study method allows for comparisons. The human experience is one that is built on individual observations from group situations. Specific demographics might think, act, or respond in particular ways to stimuli, but each person in that group will also contribute a small part to the whole. You could say that people are sponges that collect data from one another every day to create individual outcomes.

The case study method allows researchers to take the information from each demographic for comparison purposes. This information can then lead to proposals that support a hypothesis or lead to its disruption.

7. Data generalization is possible using the case study method. The case study method provides a foundation for data generalization, allowing researches to illustrate their statistical findings in meaningful ways. It puts the information into a usable format that almost anyone can use if they have the need to evaluate the hypothesis under consideration. This process makes it easier to discover unusual features, unique outcomes, or find conclusions that wouldn’t be available without this method. It does an excellent job of identifying specific concepts that relate to the proposed ideas that researchers were verifying through their work.

Generalization does not apply to a larger population group with the case study method. What researchers can do with this information is to suggest a predictable outcome when similar groups are placed in an equal situation.

8. It offers a comprehensive approach to research. Nothing gets ignored when using the case study method to collect information. Every person, place, or thing involved in the research receives the complete attention of those seeking data. The interactions are equal, which means the data is comprehensive and directly reflective of the group being observed.

This advantage means that there are fewer outliers to worry about when researching an idea, leading to a higher level of accuracy in the conclusions drawn by the researchers.

9. The identification of deviant cases is possible with this method. The case study method of research makes it easier to identify deviant cases that occur in each social group. These incidents are units (people) that behave in ways that go against the hypothesis under consideration. Instead of ignoring them like other options do when collecting data, this approach incorporates the “rogue” behavior to understand why it exists in the first place.

This advantage makes the eventual data and conclusions gathered more reliable because it incorporates the “alternative opinion” that exists. One might say that the case study method places as much emphasis on the yin as it does the yang so that the whole picture becomes available to the outside observer.

10. Questionnaire development is possible with the case study method. Interviews and direct observation are the preferred methods of implementing the case study method because it is cheap and done remotely. The information gathered by researchers can also lead to farming questionnaires that can farm additional data from those being studied. When all of the data resources come together, it is easier to formulate a conclusion that accurately reflects the demographics.

Some people in the case study method may try to manipulate the results for personal reasons, but this advantage makes it possible to identify this information readily. Then researchers can look into the thinking that goes into the dishonest behaviors observed.

List of the Disadvantages of the Case Study Method

1. The case study method offers limited representation. The usefulness of the case study method is limited to a specific group of representatives. Researchers are looking at a specific demographic when using this option. That means it is impossible to create any generalization that applies to the rest of society, an organization, or a larger community with this work. The findings can only apply to other groups caught in similar circumstances with the same experiences.

It is useful to use the case study method when attempting to discover the specific reasons why some people behave in a specific way. If researchers need something more generalized, then a different method must be used.

2. No classification is possible with the case study method. This disadvantage is also due to the sample size in the case study method. No classification is possible because researchers are studying such a small unit, group, or demographic. It can be an inefficient process since the skills of the researcher help to determine the quality of the data being collected to verify the validity of a hypothesis. Some participants may be unwilling to answer or participate, while others might try to guess at the outcome to support it.

Researchers can get trapped in a place where they explore more tangents than the actual hypothesis with this option. Classification can occur within the units being studied, but this data cannot extrapolate to other demographics.

3. The case study method still offers the possibility of errors. Each person has an unconscious bias that influences their behaviors and choices. The case study method can find outliers that oppose a hypothesis fairly easily thanks to its emphasis on finding facts, but it is up to the researchers to determine what information qualifies for this designation. If the results from the case study method are surprising or go against the opinion of participating individuals, then there is still the possibility that the information will not be 100% accurate.

Researchers must have controls in place that dictate how data gathering work occurs. Without this limitation in place, the results of the study cannot be guaranteed because of the presence of bias.

4. It is a subjective method to use for research. Although the purpose of the case study method of research is to gather facts, the foundation of what gets gathered is still based on opinion. It uses the subjective method instead of the objective one when evaluating data, which means there can be another layer of errors in the information to consider.

Imagine that a researcher interprets someone’s response as “angry” when performing direct observation, but the individual was feeling “shame” because of a decision they made. The difference between those two emotions is profound, and it could lead to information disruptions that could be problematic to the eventual work of hypothesis verification.

5. The processes required by the case study method are not useful for everyone. The case study method uses a person’s memories, explanations, and records from photographs and diaries to identify interactions on influences on psychological processes. People are given the chance to describe what happens in the world around them as a way for researchers to gather data. This process can be an advantage in some industries, but it can also be a worthless approach to some groups.

If the social group under study doesn’t have the information, knowledge, or wisdom to provide meaningful data, then the processes are no longer useful. Researchers must weigh the advantages and disadvantages of the case study method before starting their work to determine if the possibility of value exists. If it does not, then a different method may be necessary.

6. It is possible for bias to form in the data. It’s not just an unconscious bias that can form in the data when using the case study method. The narrow study approach can lead to outright discrimination in the data. Researchers can decide to ignore outliers or any other information that doesn’t support their hypothesis when using this method. The subjective nature of this approach makes it difficult to challenge the conclusions that get drawn from this work, and the limited pool of units (people) means that duplication is almost impossible.

That means unethical people can manipulate the results gathered by the case study method to their own advantage without much accountability in the process.

7. This method has no fixed limits to it. This method of research is highly dependent on situational circumstances rather than overarching societal or corporate truths. That means the researcher has no fixed limits of investigation. Even when controls are in place to limit bias or recommend specific activities, the case study method has enough flexibility built into its structures to allow for additional exploration. That means it is possible for this work to continue indefinitely, gathering data that never becomes useful.

Scientists began to track the health of 268 sophomores at Harvard in 1938. The Great Depression was in its final years at that point, so the study hoped to reveal clues that lead to happy and healthy lives. It continues still today, now incorporating the children of the original participants, providing over 80 years of information to sort through for conclusions.

8. The case study method is time-consuming and expensive. The case study method can be affordable in some situations, but the lack of fixed limits and the ability to pursue tangents can make it a costly process in most situations. It takes time to gather the data in the first place, and then researchers must interpret the information received so that they can use it for hypothesis evaluation. There are other methods of data collection that can be less expensive and provide results faster.

That doesn’t mean the case study method is useless. The individualization of results can help the decision-making process advance in a variety of industries successfully. It just takes more time to reach the appropriate conclusion, and that might be a resource that isn’t available.

The advantages and disadvantages of the case study method suggest that the helpfulness of this research option depends on the specific hypothesis under consideration. When researchers have the correct skills and mindset to gather data accurately, then it can lead to supportive data that can verify ideas with tremendous accuracy.

This research method can also be used unethically to produce specific results that can be difficult to challenge.

When bias enters into the structure of the case study method, the processes become inefficient, inaccurate, and harmful to the hypothesis. That’s why great care must be taken when designing a study with this approach. It might be a labor-intensive way to develop conclusions, but the outcomes are often worth the investments needed.

• 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

Introduction

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

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

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

What is a case study?

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

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

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

What are case studies used for?

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

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

How are case studies conducted?

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

Defining the case

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

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

Selecting the case(s)

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

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

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

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

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

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

Collecting the data

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

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

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

Analysing, interpreting and reporting case studies

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

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

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

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

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

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

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

Conclusions

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

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Acknowledgements

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

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

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

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What are the limitations of case studies?

Case studies are in-depth analyses of a particular person, group, circumstance, or civilization. Data is frequently obtained from several sources and in various methods (e.g. observations & interviews). The patient’s medical history or personal case study is where the case study research methodology started, and case studies frequently look into one person in their investigations.

The content is mostly biographical and pertains to noteworthy events in the person’s past (i.e., retrospective) and current events in their day-to-day lives. The case study is not a research method in and of itself; rather, researchers select methods for data collection and analysis that will result in case study-worthy data.

Limitations of Case Studies

• There is insufficient scientific rigour and no basis for extending findings to a broader population.
• The researchers could inject their personal opinions into the case study (researcher bias).
• It is challenging to repeat.
• It’s expensive and time-consuming.
• The amount of analysis done with the instruments was constrained by the data and the time limits imposed.

It is hard to determine whether a case study represents a larger body of “similar” events because it only examines one individual, event, or group. As a result, the findings drawn in one instance might not apply in another. Since case studies are based on qualitative (descriptive) data, the psychologist’s interpretation is essential.

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A Patient-Driven Mobile Health Innovation in Cystic Fibrosis Care: Comparative Cross-Case Study

Authors of this article:

Original Paper

• Pamela Mazzocato 1, 2 , PhD   ; 
• Jamie Linnea Luckhaus 1, 3 , MPH   ; 
• Moa Malmqvist Castillo 1 , MPhil   ; 
• Johan Burnett 4 , RN   ; 
• Andreas Hager 4 , LLM   ; 
• Gabriela Oates 5 , PhD   ; 
• Carolina Wannheden 1 , PhD   ; 
• Carl Savage 1 , PhD  

1 Department of Learning, Informatics, Management and Ethics, Medical Management Centre, Karolinska Institutet, Stockholm, Sweden

2 Södertälje Hospital, Södertälje, Sweden

3 Participatory e-Health and Health Data, Department of Women’s and Child’s Health, Uppsala University, Uppsala, Sweden

4 Upstream Dream, Bromma, Sweden

5 Pulmonary, Allergy and Critical Care Medicine, The University of Alabama at Birmingham, Birmingham, AL, United States

Corresponding Author:

Pamela Mazzocato, PhD

Department of Learning, Informatics, Management and Ethics

Medical Management Centre

Karolinska Institutet

Tomtebodavägen 18 A

Phone: 46 8 524 83 696

Email: [email protected]

Background: Patient-driven innovation in health care is an emerging phenomenon with benefits for patients with chronic conditions, such as cystic fibrosis (CF). However, previous research has not examined what may facilitate or hinder the implementation of such innovations from the provider perspective.

Objective: The aim of this study was to explain variations in the adoption of a patient-driven innovation among CF clinics.

Methods: A comparative multiple-case study was conducted on the adoption of a patient-controlled app to support self-management and collaboration with health care professionals (HCPs). Data collection and analysis were guided by the nonadoption, abandonment, spread, scale-up, and sustainability and complexity assessment tool (NASSS-CAT) framework. Data included user activity levels of patients and qualitative interviews with staff at 9 clinics (n=8, 88.9%, in Sweden; n=1, 11.1%, in the United States). We calculated the maximum and mean percentage of active users at each clinic and performed statistical process control (SPC) analysis to explore how the user activity level changed over time. Qualitative data were subjected to content analysis and complexity analysis and used to generate process maps. All data were then triangulated in a cross-case analysis.

Results: We found no evidence of nonadoption or clear abandonment of the app. Distinct patterns of innovation adoption were discernable based on the maximum end-user activity for each clinic, which we labeled as low (16%-23%), middle (25%-47%), or high (58%-95%) adoption. SPC charts illustrated that the introduction of new app features and research-related activity had a positive influence on user activity levels. Variation in adoption was associated with providers’ perceptions of care process complexity. A higher perceived complexity of the value proposition, adopter system, and organization was associated with lower adoption. In clinics that adopted the innovation early or those that relied on champions, user activity tended to plateau or decline, suggesting a negative impact on sustainability.

Conclusions: For patient-driven innovations to be adopted and sustained in health care, understanding patient-provider interdependency and providers’ perspectives on what generates value is essential.

Introduction

Patient-driven innovation in health care is an emerging phenomenon. An example of coproduction and prosumerism (where consumers produce what they consume), patient-driven innovations can be seen as the next logical step in health care evolution [ 1 , 2 ] and could fundamentally challenge the essence of what it means to be a professional health care provider. The number of publications about patient-driven or informal caregiver-driven innovations (ie, innovations that are both initiated and driven by patients or informal caregivers or both) mostly concern chronic conditions and have increased substantially in recent years [ 3 ]. However, the current literature does not examine the factors that influence the adoption, spread, and scale-up of patient-driven innovations in health care organizations [ 3 ]. The paucity of research studies evaluating and reporting the outcomes of patient-driven innovations has been suggested as a potential obstacle to their adoption in health care [ 4 ].

Cystic fibrosis (CF) is a complex chronic and genetic condition that affects respiratory and other organ systems [ 5 ]. Disease activity varies over time, and treatment requires a high degree of discipline and self-care outside of the clinical microsystem [ 6 , 7 ]. Patient-driven innovations in CF care have resulted in the development and dissemination of mobile health (mHealth) apps that support patients with CF and their caregivers in self-care and information sharing with health care providers [ 8 - 11 ]. Sharing of patient-generated health data has been associated with improved symptom control and quality of life and reduced health care use [ 12 ]. The COVID-19 pandemic has further demonstrated the value of and opportunity for patient-generated health data [ 13 ], as well as the importance of actively involving patients with CF and caregivers in critical conversations about care and self-care management [ 14 ].

However, implementing innovations in health care can be challenging [ 9 , 15 - 18 ]. The issue is even more pronounced if innovations are created or driven by patients [ 19 ], as that can challenge traditional hierarchical values and structures and professional identities. When implementation is not appropriately managed, mHealth apps fail to be adopted, are abandoned, or falter when they are scaled up or spread [ 20 , 21 ]. To increase the ability of hospitals, staff, and patients to adopt technological innovations, implementation approaches need to be anchored in the needs of patients and adapted to the organizational context and the wider system in which the new technology is implemented [ 21 , 22 ]. The level of organization and system complexity will influence the level of adoption by patients and providers [ 20 , 21 , 23 - 25 ].

Building on the field of complexity, we see complexity as a characteristic and property that emerges from 3 variables: the number of elements or components, often referred to as nodes (eg, actors and stakeholders); the number of interactions and interdependences between these nodes; and the variation within these nodes and interactions [ 26 - 28 ]. Successful implementation often requires a higher level of alignment between the purpose of the organization and its users [ 20 , 21 , 24 ]. The risk for failure increases with the level of complexity as health care systems respond to changes in unpredictable and nonlinear ways due to fuzzy organizational boundaries and interconnected actions with other actors that are often difficult to predict or even be aware of [ 21 , 29 ].

With patients and informal caregivers playing an increased role in health care, we need to know more about how their potential contributions can be realized through the adoption of patient-driven innovations in health care. Therefore, the aim of this study was to explain variations in the adoption of a patient-driven innovation among CF clinics. We posed the following research questions:

• How does the adoption of a patient-driven innovation, based on patterns of patient use, vary among clinics?
• What factors influence the level of adoption of the patient-driven innovation over time?

Study Design

This comparative multiple-case study used mixed (quantitative and qualitative) methods to explain differences in the adoption of a patient-driven innovation among patients with CF at 9 clinics. The Consolidated Criteria for Reporting Qualitative Research (COREQ) guideline [ 30 ] was followed in reporting this study ( Multimedia Appendix 1 ). The study is part of the Patient in the Driver’s Seat research program conducted at the Medical Management Centre, Karolinska Institutet, Sweden. It is a 6-year program that studies how 5 patient-driven innovations are implemented in clinical practice and the daily lives of patients and their networks, 1 of which is the subject of this study.

Theoretical Framework

This study was guided by the framework for theorizing and evaluating nonadoption, abandonment, and challenges in the scale-up (ie, building infrastructure to support full-scale implementation across an organization, locality, or health systems), spread (ie, replicating an intervention somewhere else), and sustainability of health and care technologies (nonadoption, abandonment, spread, scale-up, and sustainability [NASSS]) and the NASSS complexity assessment tool (NASSS-CAT) [ 29 ]. We chose the NASSS framework because it was designed to both analyze and prepare for the implementation of technology in health care. Its development process has been well described, lending surface validity to the framework, and it has garnered attention among researchers [ 20 , 31 , 32 ]. According to the framework, the dynamic interactions that influence the nonadoption, abandonment, scale-up, spread, and sustainability of technological innovations are inherent to the complexity within and between 7 domains:

• Condition: nature of the condition or illness, comorbidities, sociocultural factors
• Technology: material features, type of data generated, knowledge needed to use, supply model
• Value proposition: supply-side value for the developer and for the patient
• Adopters: staff, patients, caregivers
• Organization: capacity to innovate, readiness for technology, nature of adoption/funding decision, extent of change in team routines, work needed
• Wider context: political/policy, regulatory/legal, professional and sociocultural
• Embedding and adaptation over time: scope, organizational resilience [ 29 ]

Simple systems consist of a few components that interact in straightforward and predicable ways. Complicated systems have multiple components that interact in a predictable fashion. Complex systems have multiple and intricately related interactions that are constantly changing, unpredictable, nonlinear, and difficult to deconstruct [ 29 ]. NASSS and, practically, CAT can be used to distinguish between simple, complicated, and complex elements in the 7 domains [ 29 ]. The intention is to identify the multiple influences that are at play; to determine how complexity once identified can be reduced, addressed, or navigated; and to provide information and guidance to the involved actors on how to do so.

The Patient-Driven Innovation

The technology (innovation) studied was a patient-controlled app (named Genia ) that was originally designed as a patient-facing app to foster self-management. With the addition of a function to generate reports for providers, the app expanded its scope to become a patient-controlled information app for the coproduction of care that places the patient at the center of the decision-making process [ 10 , 11 ]. Founded in 2012 by a father of children with CF, Upstream Dream, which developed the patient-driven innovation, employs individuals with lived experience as patients or informal caregivers of a family member with a rare disease. The innovation was developed in collaboration with the Swedish CF community and upon research conducted at Karolinska Institutet and Dartmouth University. Launched in Sweden in 2015, it was introduced to all CF clinics in the country within a period of a few months. Subsequently, the innovation was piloted (2020-2021) and adopted (2021) as part of routine care in 1 pediatric CF program in the United States and is now the focus of a multicenter study. At launch, the patient-driven innovation was only compatible with the iOS platform. Android support was added later.

Upstream Dream is working to spread the innovation to other clinics in the United States and South America. The innovation has also been tested for use with other chronic medical conditions and has demonstrated improved patient engagement, patient-centered care, and practice-based learning, with the conclusion that the innovation can be recommended for other chronic conditions [ 31 ].

The main features of the patient-driven innovation are related to the tracking of symptoms and medications. What differentiates it from a regular personal health record for patients to record disease progression is that information can be shared with care providers, which is why the app was introduced through the clinics to reach patients with CF. Information that patients wish to share with their multidisciplinary clinical care team is submitted via previsit reports in the form of portable document format (PDF) files. Data are integrated into the Swedish National Cystic Fibrosis Quality Registry. In the United States, data are incorporated into the local electronic health record (EHR) [ 9 ]. Over time, additional features were added based on input from the clinics. These included an antibiotic use–reporting tool, “Antibiotic Check-in,” to support care and research on the use of new antibiotics and therapies; a medication-monitoring tool for the Orkambi medical treatment; and a “Health Check-in” feature to simplify communication of the information used by clinics for planning meetings and patient visits.

In Sweden, clinics were not charged to use the innovation, whereas in the United States, clinics paid an annual fee. The innovation was free for patients to use in both countries. Patients’ user activity can be seen as an outcome that reflects how well clinics integrate the app in their own care processes.

When the study was conducted, 2 generic health information and communication apps were provided by the regions and in use in the Swedish clinics, “1177” and “Always Open.” Neither app provides a comparable service (patient-controlled communication of disease activity) to the innovation; instead, all 3 apps provide complementary functions that did not interfere with one another and could therefore be used simultaneously. The 1177 app is a patient portal that provides information about illnesses and clinics, booking, and electronic medical records. The Always Open app (Swedish Alltid Öppet ) was designed as a secure platform for providing remote care services, such as appointment reminders, prescription renewals, and video visits. Its availability was limited to 1 region, so only 2 clinics had access to it.

Study Setting

The study was conducted at 1 CF center in the United States (referred to as clinic A) and all 8 pediatric and adult CF centers in Sweden (referred to as clinics B-I). All but 1 clinic had used the innovation for 7 years (2 years for the most recent clinic). The clinics were small, with 7-10 staff members (typically including pulmonologists, registered nurses (RNs), physiotherapists or respiratory therapists, psychologists or social workers, and dietitians), and focused specifically on CF. All were located at academic medical centers. One clinic in Sweden provided both pediatric and adult care, and the same staff served both patient populations. However, because adoption levels were different between these 2 patient groups, the data were presented separately.

Based on the inclusion of many different implementation settings, we expected different patterns of adoption. This would allow us to develop an empirical basis for both literal replication (cases that predict similar results) and theoretical replication (cases that predict different results for predictable reasons) [ 32 ]. The US site was selected because it was the first use case outside Sweden. We expected its inclusion to provide further insights into relevant contextual aspects.

Data Collection

Quantitative data were collected to assess the level of adoption based on the number of active users (ie, patient activity). Since the innovation was designed to improve patient-provider communication, patient activity levels can be seen as an indicator of adoption. Anonymous user activity data for each clinic were extracted from Upstream Dream’s monthly reports on user activity for the period from March 2015 (when the innovation was implemented at the first clinic) to March 2022. At clinic A, where the innovation was implemented last, the user activity period was from February 2020 to March 2022.

Qualitative data were collected to understand how the innovation was perceived and used based on the NASSS domains and to identify specific interventions or factors that may have influenced user activity. A semistructured interview guide was developed in both Swedish and English ( Multimedia Appendix 2 ). Questions were designed to elicit information about NASSS domains and their degrees of complexity [ 21 ], as well as to capture information about app integration into care processes. A precursor to the interview guide was first tested in a separate study [ 33 ] and revised based on that experience. Further input was sought from Upstream Dream to ensure that we would capture a holistic understanding of how the innovation was used in daily practice with respect to the different organizational contexts and potential differences in complexity. The interview guide was then piloted twice, with minor changes made to enhance the clarity of the questions in only the Swedish version.

Purposive and snowball sampling strategies were used to identify participants with knowledge of and personal experience with the innovation and who represented the professions involved in CF care. Upstream Dream’s clinical coordinators contacted the staff coordinators at each CF center on our behalf, who then connected us with the staff who expressed an interest to participate in the study. We contacted these individuals via email and followed up by telephone. In total, 21 participants were interviewed, including 2 key members of Upstream Dream, one of whom was interviewed twice (first, to develop a contextual understanding of the innovation and the supplier perspective and then to provide additional information and clarity after the adopter interviews), RNs, physicians, respiratory therapists or physiotherapists, a psychologist, a dietician, and a researcher involved in the development, implementation, and evaluation of the innovation in 1 of the clinics, without being a health care provider. This role distribution reflected typical staff distribution at the clinics. The CF centers involved had a small number of employees, which limited the number of potential participants. The number of participants was also limited by the high workloads brought on by the COVID-19 pandemic. Thus, the participants involved represented between 28% and 40% of working staff. Participants’ experiences with the innovation ranged from 3 months to 7 years.

Interviews were conducted online via the Zoom videoconferencing system due to the ongoing COVID-19 pandemic, in Swedish or English, and lasted 30-60 minutes. Interviews were conducted by 2 authors with training in qualitative research, with support from a senior researcher. The interviewers had no prior relationship with the participants. Audio was digitally recorded and transcribed verbatim.

Data Analysis

Quantitative data on user activity were analyzed using descriptive statistics. We calculated the percentage of active end users per month among the total number of patients and the percentage of active users on average over the entire period. Active users were defined as end users who logged on and used some of the basic app features within a 6-month period. As clinic A first introduced the patient-driven innovation as a pilot study, the percentage of active users for that period was calculated based on the pilot sample size and after the end of the pilot was calculated based on the clinic size. The descriptive statistics (ie, maximum end-user activity and average over the entire period) provided insights into the level of adoption. We defined low (<25%), middle (25-50%), and high (>50%) activity levels based on the maximum percentage of end-user level achieved.

To put user activity data into an organizational context, we complemented the descriptive data with statistical process control (SPC) charts. SPC charts were created for each clinic to identify whether and when statistically significant changes in app adoption levels occurred and whether these were sustained. SPC makes it possible to determine whether a change is a matter of chance (ie, common-cause variation) or due to a specific happening or intervention (ie, special-cause variation) [ 34 - 36 ]. We used P charts with the following rules to identify special-cause variation: rule 1/3 sigma violation (1 point +/– the upper control limit/lower control limit [UCL/LCL], with the control limits set to +/–3 sigma), rule 2/shift (8 successive consecutive points above or below the centerline), rule 3/trend (6 or more consecutive points steadily increasing or decreasing), and rule 5/hugging the centerline (15 or more consecutive points within +/–1 sigma on either side of the centerline) [ 37 ].

Qualitative data were analyzed using content analysis (directed and inductive) [ 38 ], process mapping, and complexity analysis. Interview transcripts were read through repeatedly to develop familiarity and then subjected to directed qualitative content analysis [ 39 ]. Two authors together identified meaning units, which they abstracted to condensed meaning units and added as “sticky notes” to the MIRO online whiteboard for visual collaboration, where they were directed to 1 of the NASSS domains (ie, categories). The condensed meaning units were labeled with descriptive codes. Where the codes did not fit the framework, additional subcategories were created through traditional inductive content analysis [ 39 ]. All codes and the categorization were reviewed and corroborated by 2 other authors. During the analysis, interview data from suppliers and HCPs were kept separate, and the former were used solely to provide contextual information about specific interventions and factors that were integrated in the SPC charts (eg, timeline of interventions that could have influenced user activity).

To support the cross-case comparison, the traditional approach to reporting qualitative analyses was then transformed into tabulated form based on the original NASSS framework and expanded to include the additional subcategories.

Process maps were created for each clinic based on interview data to illustrate how the innovation was integrated into clinical work processes. The process maps and the qualitative analysis were shared with participants in an informant validation process. Five clinics made small adjustments. The suppliers provided additional corroborating feedback, where needed, for the clinics that did not respond.

We diagnosed complexity levels (see the definitions of simple, complicated, complex in the theoretical framework) of the NASSS domains for each clinic by analyzing interview data using the NASSS complexity table ( Multimedia Appendix 3 ) and the NASSS-CAT Short survey, which was specifically designed to assess and differentiate between complexity levels [ 29 ]. Both analyses were combined to generate the complexity assessment. Although the survey was originally intended to spark a reflective discussion, we used the reflective discussion created in the interview setting to diagnose the level of complexity. For the qualitative analyses and the complexity assessment, conflicting interpretations were discussed until consensus was reached.

Qualitative data were first analyzed case by case but then triangulated with quantitative data to develop initial explanations of variation in adoption. These were then tested against the data and the analyses to identify those domains or interacting domains that could explain the observed patterns. In a process akin to modified analytic induction [ 38 ], when falsifying evidence was found, the explanatory model was dropped. This process involved vigorous discussion and iterative cycles to narrow and refine the explanatory models that are presented in the cross-case comparison.

Ethical Considerations

Ethical approval was obtained from the Swedish Ethical Review Authority (approval number 2019-03849). The study followed the Swedish Research Council’s ethical principles for humanities and social science research. Participants were informed orally and in writing about their rights and what study participation would entail. Written and verbal consent was obtained from all participants prior to commencement of interviews. Quantitative data were completely anonymous. Qualitative data were pseudonymized and deidentified prior to coding and analysis. In presenting the findings, we made efforts to maintain participants’ privacy and confidentiality, referencing HCPs only with their pseudonym identifiers and clinic letters (eg, “HCP01, clinic A”). No participant received any compensation for participating in the study.

In this section, we present the triangulation of the qualitative and quantitative data first with user activity levels, and then a cross-case comparison based on the complexity assessment.

Participant Details

In total, 21 participants (n=16, 76.2%, women and n=5, 23.8%, men) were interviewed. Of the 21 participants, 9 (42.9%) were RNs, 5 (23.8%) physicians, 4 (19%) respiratory therapists or physiotherapists, 1 (4.8%) psychologist, 1 (4.8%) dietician, and 1 (4.8%) researcher.

In 2 of the clinics (D and H), we were able to interview only 1 (4.8%) participant each; the remaining 7 clinics were represented by 2 (9.5%) or more participants: clinic A, n=3 (14.3%); clinic B, n=4 (19%); clinic C, n=4 (19%); clinic E, n=2 (9.5%); clinic F, n=2 (9.5%); clinic G, n=2 (9.5%); and clinic I, n=2 (9.5%).

User Activity Level

The end-user activity levels showed that the innovation was adopted by patients at all clinics; there was no evidence of nonadoption. Based on the maximum end-user level achieved, we found 3 clusters: high-adoption clinics A (maximum n=40, 65%), B (maximum n=60, 58%), and C (maximum n=66, 96%); medium-adoption clinics D (maximum n=125, 35%), E (maximum n=30, 47%), and F (maximum n=60, 25%); and low-adoption clinics G (maximum n=120, 19%), H (maximum n=116, 23%), and I (maximum n=155, 16%).

To further explore user activity levels over time, SPC charts were created ( Figure 1 ) for each clinic to plot the user activity level over 81 months. In the SPC charts, specific interventions or events retrieved through the interviews, which may have influenced user activity levels over time, are indicated as vertical dotted lines and labeled as a-g. These included the introduction of new features, research-related activity, and the COVID-19 pandemic.

New features included the launch of Orkambi medication monitoring (intervention a) in month 42, which likely explains the increased use among 5 clinics (B-F), particularly among pediatric clinics. Antibiotic Check-in was launched in Swedish clinics in month 62 (intervention b), which was followed by a campaign (intervention d), which could explain the increased activity in 7 (87.5%) of the 8 Swedish clinics (C-I). The introduction of an Android-compatible version in month 68 (intervention e) opened the innovation up to all patients and caregivers with a smartphone or tablet. Health Check-in (intervention f) may have contributed to the observable increase around month 70 (clinics C, D, F, and H).

The influence of research-related activities was mainly identified in clinic A, in which there was a rapid increase in activity starting month 60, which plateaued. This corresponded to when the innovation was first introduced in clinic A as a year-long single-group pilot study (n=40 participants, pre-post design) [ 40 ]. When the patient quota for the pilot was met (first vertical dotted line, Figure 1 ), 40% of the invited patients were active users. Activity declined after the pilot ended but began to rise again (month 81) when the decision was made to launch the innovation clinic-wide. The consistency of this increase continued after the last point recorded in Figure 1 until activity was halted again in preparation for a new study (data not included in the SPC). Clinic C launched a digitization research project (intervention c), which required participants to use the innovation, and later launched a second digitization project (intervention g) in month 79.

The COVID-19 pandemic also appeared to influence user activity levels. Clinic A partially transitioned to telehealth visits during the pandemic, which made the Health Check-in feature desirable as patients could upload photos and other information. This may have contributed to increased user activity. In contrast, for clinics E, F, H, and I, a deterioration (months 70-78) was concomitant with an active choice not to focus on the innovation due to strained resources.

Cross-Case Comparison: Complexity Assessment Linked to Adoption Level

Specific characteristics of the clinics related to each NASSS domain gleaned from the interviews and the process maps are presented in Multimedia Appendix 4 . In terms of complexity, all clinics viewed the nature of the condition , technology , and wider context domains as complicated ( Figure 2 ). Differences were found in the value proposition , adopter system , organization , and embedding domains. The cross-case comparison presented next was organized around levels of adoption, integrating data from the SPC analysis and exploring differences and similarities in the NASSS domains.

High-Adoption Cluster (Clinics A-C)

The first group perceived the value proposition as simple, the adopter system and organization as complicated, and embedding as either simple or complicated. The staff had a shared perception that there is a clear benefit to using the innovation (ie, the innovation-facilitated meeting of patient and provider creates value in health care for this chronic condition). This was aligned with their view that value in health care for this chronic condition is created in the patient-provider meeting. Although going through reports lengthened the previsit planning process, the innovation was perceived to save time through more concise patient visits.

Just doing that, [opening reports in weekly team meetings] will change it a little bit, it is going to lengthen our [team] meeting a bit (…) So it helps everybody to be prepared ahead of time and hopefully make the visit more concise. [HCP14, clinic A]

For clinics B and C, where Antibiotic Check-in was used, these data were highly valued for research purposes and research was seen as an integral component of high quality care. For clinic C, this was corroborated by SPC analysis (intervention c).

The adopter system was viewed by clinics A-C as complicated. Patient-controlled data were viewed as integral to previsit planning, suggesting a view of patients as active contributors to the cocreation of care and of the staff as having a responsibility to ensure that patients contributed with these data.

Way more attention is being paid now to this patient-generated data rather than the core clinical data. I mean, we still look at lung function and microbiology and what not, but patient-reported symptoms and outcomes are a bigger part of the discussion now, as well as patient preferences and…and goals and what people want to focus on. So that is 1 change that has happened. [HCP15, clinic A]

This person-centered culture was reflected in the organization domain, which the staff perceived as complicated, as organizational routines and care pathways needed to be flexible to reinforce the importance of patient input and the use of the innovation as an integral source of information for previsit planning. For example, if a patient had either not downloaded the innovation or submitted a report, clinics A and C had routines to complete those tasks together with the patient ( Multimedia Appendix 4 ). Even though these clinics saw a clear value in the innovation, they still expressed the difficulties of cultural change and that it requires key drivers.

We often do not have the personnel for this. It needs to be carried out, in addition to the usual work. And there has to be someone driven to be able to push these questions forward. [HCP01, clinic C]

Embedding was seen as simple or complicated based on how mature the routines for incorporating user information (the reports) into the patient pathway were. In clinic B, the continual increase in adoption observed in Figure 1 could be explained by the clinic’s routines of using the innovation with the whole clinical team, as well as its regular communication with the developer. For example, clinic A had clear plans and used collective reflection among the staff for embedding the technology in the short and the long term.

The good thing is that the way we have set up this pragmatic trial is that they are [clinicians] not required to do anything extra than they normally do, so they are not required to log in on a separate platform or a dashboard or anything extra. Everything is embedded and integrated, which makes it an easier sell. [HCP15, clinic A]

Clinics A-C saw a match between what they valued (the patient-provider interaction) and the value proposition of the innovation because it improved the quality and efficiency of the patient-provider encounter. These clinics had existing and further developed their routines to ensure and reinforce patient use of the innovation. Moreover, they behaved as if they “co-owned” the innovation either by conducting research studies or by taking responsibility for patient training. In the adopter system, most of the staff had clearly defined roles in relation to the use of the innovation, as well as established routines for group reflection. Participants valued patients’ role in the cocreation of care.

Middle-Adoption Cluster (Clinics D-F)

The second group perceived the value proposition and adopter system as complicated and organization and embedding as complex. The value proposition was seen as complicated because the technology’s desirability was contested, and the business case for adoption was deemed unclear. The participants experienced a mismatch between the condition and technology that reflected itself in their view of the value proposition: clinics D and F (adult clinics) believed that the technology better serves pediatric patients, who typically receive outpatient care and need to report symptoms, whereas adult patients with CF in Sweden are often hospitalized and their symptomatology easier to track. The staff felt that the graphical user interface is less appropriate for adults.

Regarding the adopter system, clinics E and F questioned the appropriateness of care providers in a public institution to convince their patients to use a product from a private company.

If a patient is completely on top of it with their treatment and medications and everything, then it feels a little like a car salesman if I am to try and sell something that is not a directive of the hospital. And that role we all feel is a bit annoying. But if you can show a direct benefit to using [the innovation], then it feels good. [HCP12, clinic F]

Organization was seen as complex because of difficulties integrating the innovation in the workflow. For example, patient-generated reports were scheduled on the weekly agenda at clinics E and F but seldom discussed. Work routines also included contact with the supplier, who felt that clinic D demonstrated heightened commitment. This was mirrored in the SPC data, which showed a clear increase in adoption toward the end of the data collection period. However, patient workflow processes were not established. Adoption for all 3 clinics was largely the responsibility of individual clinicians and, due to individual levels of enthusiasm or work practices, gave rise to variation ( Figure 1 ). This impacted patients.

We are a center where not everyone is on the team in the same way. I think that is a factor for whether, depending on which doctor one meets, there will be a question about [the innovation] or not (…) It becomes person dependent in a crazy way. [HCP19, clinic E]

It impacted staff as well.

If everyone did it, there would not be any extra work, but since we cannot manage to get everyone here doing it, I end up trying to take the main responsibility (…) Sometimes I sit and go through [the reports] (…) So, I have a bit of extra work, but it is too difficult to create a routine for such a thing if not all patients use it, then it can become forgotten. [HCP18, clinic H]

In clinics E and F, adoption relied heavily on champions, which could explain the decrease observed in months 26-43 ( Figure 1 ), which was also compounded by a severe staff shortage. Embedding was deemed complex at clinics E and F as they were forced to prioritize resources due to the COVID-19 pandemic, which shifted focus away from the innovation and was reflected in the user activity decrease. Moreover, they felt the questions prior to the introduction of Antibiotic Check-in and Health Check-in were too generic.

Low-Adoption Cluster (Clinics G-I)

The third group perceived the value proposition, adopter system, organization, and embedding as complex. Like clinics D-E, these providers had a negative experience of advocating for a privately owned app. They were among the first to adopt the innovation, at a point where app features were minimal and the app was limited to 1 platform. They felt that this effort to get patients to use an underdeveloped app negatively impacted the patient-provider relationship. The SPC analysis for clinics H and I ( Figure 1 ) confirmed that early adopters struggled to maintain adoption as the user activity level either remained stable (clinic H) or decreased (clinic I). The addition of new features, although potentially increasing the value of the innovation, was offset by previous experiences, which had worn them out.

It is now actually that you should start trying to get patients to use [the innovation]. But in [this region], we have sort of worn ourselves out because we already did it 4-5 years ago. [HCP18, clinic H]

The innovation was seen as undesirable by most of the staff at these clinics, and they perceived their patients were equally uninterested. Several providers mentioned that patients do not want to “have their illness in an app,” as symptom tracking can become a reminder of how sick one has been and add yet another task, when patients with CF are already “drowning in health care” (HCP06). Some also felt adults have a hard time changing their ways. These opinions demonstrated a mismatch between the value of the technology and the needs and challenges related to the condition.

Adopter systems were deemed complex because, although at all clinics the staff had to learn new skills, the staff at clinics G-I felt the innovation poses a threat to their professional identity and scope of practice and felt patients find the innovation challenging. Clinicians preferred digital technologies available from the regions, rather than from a private company. Here, they referred to 1177 and Always Open as examples of such tools, which they also perceived served a clearer purpose. Clinicians were skeptical of how the app was introduced and that it did not come from within the clinic.

It was not we as providers who went to an app developer and said, “We want a tool.” Rather, it was they who came from the outside and said, “You need a tool, and here it is.” [HCP03, clinic G]

Clinicians at pediatric clinics believed there is a particular need for medication tracking among adult patients, whereas the staff at adult clinics expressed the opposite. Past experiences with other technological interventions and how well they were received also influenced how hesitant or open clinics were to innovation.

Organizations also demonstrated complexity; none of clinics G-I had integrated the innovation into their clinical workflow, and the innovation was used on an individual rather than on a team basis, which put pressure on the single user ( Multimedia Appendix 3 ). This was reinforced by the special cause variation observable in clinic G (consecutive points below/above the center line, months 69-83), where the activity dipped down before shooting up and could be linked to a champion staff member who led the adoption but left temporarily before returning. The clinics saw funding as a barrier to implementing new technologies, including the innovation. Clinic I mentioned a severe resource pressure, including hiring stops (frozen posts), which halted the use of the innovation, especially under the stress of the pandemic. The embedding system was complex due to the clinic’s inability to adapt the innovation use to critical and unforeseen events (eg, the COVID-19 pandemic).

Principal Findings

In this study, the adoption of a patient-driven innovation was studied using a complexity-based framework and tools for the introduction of technology in health care, NASSS-CAT. The innovation was developed as a patient-controlled information app to support the self-management of CF and communicate disease related–activity with health care providers. Although we found no evidence of nonadoption or clear abandonment of the app, distinct patterns of innovation adoption were discernable based on user activity data (ie, low, medium, and high adoption). The perceived value proposition of the technology and the experienced complexity were associated with different levels of adoption. Research activity and the introduction of new app features positively impacted adoption. In clinics that adopted the innovation early or those that relied on champions, user activity tended to plateau or decline, suggesting a negative impact on sustainability.

Perceived Complexity Influencing Adoption

There was little variation between clinics regarding perceptions of the condition and technology domains. Differences in complexity were seen within the value proposition, adopter system, organization, and embedding and adaptation domains. The more complex these domains were perceived to be, the lower the level of adoption was.

The perceptions of value identified in this study demonstrate a patient-provider interdependency (ie, both the provider and the patient must value and use the patient-driven innovation, or else it will lead to a downward spiral of abandonment). As Floch et al [ 8 ] found, “Self-management enfolds a collaboration between patients and [health care providers].” This suggests that studying providers’ experiences of using patient-driven innovations can be an important perspective as patients’ and providers’ behaviors are 2 sides of the proverbial same coin. One could expect that a patient-driven innovation, as an example of prosumerism, would entail a higher level of acceptance or be more highly valued than an innovation external to the clinical context.

All clinics seemed to agree that there is a clear need to focus clinic visits on what patients value. Where the value proposition was perceived as simple, HCPs saw the innovation as a solution, or at least worth testing as a solution. Although going through reports lengthened weekly previsit planning, the staff saw that the innovation enables shorter and more concise patient visits [ 9 ]. This mirrors the findings for another patient-centered care app for patients with CF [ 8 ]. Clinics with lower adoption described the innovation as interfering with the patient-provider interaction, since they believed they already knew their patients well due to the chronic nature of CF and perceived the app as an affront to their professionalism. The time providers spent with their patients to elicit this information was seen as a demonstration of how they valued their patients. The difference between the 2 interpretations of value could be paraphrased, from the perspective of the professional, as “we value our patients’ time” versus “we value our time with patients.” In the former, providers focus on what matters to the patient with the help of the innovation; in the latter, providers try to find out what is the matter with the patient through a person-to-person conversation without the innovation and the information it provides.

In terms of working with the adopter system and organization, our findings suggest a need to work with the context to integrate a new patient-driven innovation in health care. In this respect, despite prosumerism, this patient-driven innovation is not different from other innovations in health care [ 33 ]. Working with a broader group of adopters, not just champions, and integrating the patient-driven innovation with care processes appeared to facilitate adoption. If context is not addressed by suppliers, there is a risk that the perceived value of the innovation will be influenced by the perceived complexity of the setting. This lived experience of complexity could not be explained in terms of differences in the medical condition or technology. Instead, it appeared to be more dependent on how care processes had evolved and the human (in)ability to deal with variation, uncertainty, complexity, and ambiguity in everyday work life: complexity was in the eye of the beholder.

Co-ownership and Trust

When the app was first launched, the company took responsibility for staff and patient education, with the intention of having as little disturbance as possible in the clinics. However, clinics that took shared responsibility for the patient-driven rollout had higher and sustained adoption levels. As studies in behavioral economics have demonstrated [ 41 ], a higher level of perceived co-ownership leads to a higher evaluation of the object in question. Co-ownership invites the staff to learn and understand more about the patient-driven innovation, which could explain why merely relying on champions can be associated with lower adoption and responsibility for patient training and research with higher adoption.

Most clinics raised questions about the financial motives of the company behind the patient-driven innovation. Two clinics questioned whether it is appropriate for them as medical providers to “sell” a product from a private company. Particularly, during the early rollout, the staff felt that pushing a premature version of the innovation on patients is a violation of their professional integrity. The distrust of a private business overshadowed the patient-driven prosumer nature of the innovation that should have engendered trust. This distrust could be related to a commonly held negative view of privatization in Sweden or may indicate that the company’s patient origins had not been communicated clearly.

Utility of NASSS-CAT

This study used NASSS-CAT as a framework and tool to analyze the implementation of a patient-driven innovation. We found it helpful to characterize single domains but less suitable to explore the interaction between domains. The framework is innovation centric, which risks generating a bias that values innovation per se regardless of its suitability for addressing the challenge at hand or the purpose of the hosting clinic or organization.

Another issue relates to the essence of the complexity captured with CAT. Our findings support the basic tenet of NASSS-CAT that adoption is inversely related to the level of complexity. However, a closer look into the data suggests that what was captured may have been individuals’ perceptions of complexity related to lived experiences rather than the actual contextual complexity related to the level of interdependency. This corroborates preliminary observations of the original CAT [ 29 ]. Thus, results may be more indicative of the maturity of the complexity mindset of individuals [ 42 ] rather than the contextual complexity itself. To develop adoption strategies based on such data would be tantamount to developing treatment strategies based on an incorrect diagnosis.

A more accurate assessment of contextual complexity could be achieved by exploring the level of agreement between understanding the challenge and the proposed response [ 25 , 26 , 43 ]. These 2 questions are simpler to ask and evaluate to generate actionable data: less agreement would suggest a higher degree of complexity and therefore a need for strategies that facilitate learning [ 43 , 44 ]. More direct implementation works when things are simple (ie, greater agreement).

Strengths and Limitations

Directed content analysis inherently has some biases due to the use of a preselected theory [ 39 ]. However, several measures were taken to mitigate this limitation. For example, we used open-ended questions in the interview guide, and multiple authors were involved in all the steps of the qualitative analysis.

There was variation in the number of participants per clinic, which could have influenced the analysis. Clinics where the innovation was perceived more positively and used to a greater degree also tended to yield more interviews. This difference may reflect both resource availability and the perceived value of the innovation. Overall, the number of interview participants was limited by the number of employees at each clinic and the COVID-19 pandemic. The literature suggests that theoretical saturation is usually attained at around 12 interviews [ 45 ]. This exceeds the number of staff members working with the innovation in most of the clinics we studied. Despite our small sample size, the participants’ specific knowledge about the innovation and the care processes in each clinic contributed to strengthening information power [ 46 ]. Moreover, the triangulation of qualitative and quantitative data strengthened the trustworthiness of the findings.

Not all clinics provided feedback on the process maps, although all were given the opportunity. To further improve trustworthiness, process maps were checked again against the transcripts and reviewed by the developer’s clinic coordinator, who had insight into the clinics and staff.

The total number of potential users was limited because the innovation was first released in an iOS version only. As we did not have data on the proportion of potential users who had an iOS smartphone, we may have overestimated the number of potential users, in particular prior to the release of the Android version.

This study did not examine patient outcomes related to the innovation or satisfaction with the innovation. Interviewing patients and informal caregivers would add valuable perspectives to that of providers.

Patient-driven innovations could be highly relevant for health care, but their adoption has seldom been explored from the perspective of health care providers. We found that providers play a significant role in the adoption of patient-driven innovations in health care: patients cannot do it alone. Health care providers who make an effort to reduce the perceived complexity in the adoption process, simplify their processes, take co-ownership of the innovation, and work on its adoption and improvement as a team, rather than relying on change champions, improve their capability to support the adoption and sustainability of innovative ideas developed by patients. For patient-driven innovations to be adopted and sustained in health care, understanding patient-provider interdependency and providers’ perspectives on what generates value is essential.

Acknowledgments

The authors acknowledge the contributions of Rafiq Muhammad to the statistical process control analyses and the valuable input of Henna Hasson and other members of the Patient in the Driver’s Seat research program to the manuscript draft. A hallmark of the research program is that the team, which includes patients and patient-innovators, has involved co-creative efforts throughout all aspects of the research process, including meta-level discussions on how our different perspectives influence the research process.

This work was financially supported by the Swedish Research Council for Health, Working Life and Welfare (grant number 2018-01472). The funders had no involvement in the study design; in the collection, analysis, and interpretation of the data; in the writing of the report; and in the decision to submit the paper for publication.

Data Availability

No additional data are available. The data sets generated and analyzed during this study are available from the corresponding author upon reasonable request.

Authors' Contributions

CS, PM, and AH were responsible for conceptualization, with input from JLL, MMC, CW, JB, GO, and members of the Patient in the Driver’s Seat research program. The interview guide was developed by JLL, MMC, JB, CS, and PM. Data collection was conducted by JLL and MMC, with support from CS. Qualitative data analysis was conducted by JLL, MMC, and CS. Statistical process control (SPC) analysis was conducted and interpreted by JLL, MMC, PM, CS, and Rafiq Muhammad. JB and CW provided input on the interpretation of the results. SPC graphs were compiled by JLL. The manuscript was drafted by CS, JLL, MMC, JB, and PM. The manuscript was revised by CS, JLL, MMC, and PM, with input from JB, AH, CW, and GO. AH and JB were involved in the revision of the manuscript and in the decision to submit the paper for publication. CW, CS, PM, and AH were coapplicants of the funding grant, with Professor Henna Hasson as program lead. CS and PM served as principal investigators.

Conflicts of Interest

AH and JB are employees of Upstream Dream, the company that developed the innovation. Upstream Dream was not involved in the study design but did facilitate data collection, and JB helped interpret the data based on knowledge of the participating CF clinics. To mitigate bias, interviews and preliminary analysis were conducted without participation of the supplier. AH and JB were interviewed, and their transcripts were subjected to the same data analysis methods, kept separate from the analyses of the other participants, and then used for clarification purposes for the statistical process control timeline analysis and complexity analysis.

Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist.

Interview guide.

Nonadoption, abandonment, spread, scale-up, and sustainability (NASSS) domain areas and case-specific descriptions.

Process maps.

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Abbreviations

Edited by T de Azevedo Cardoso; submitted 04.07.23; peer-reviewed by D Rose, G Akrong; comments to author 06.03.24; revised version received 08.04.24; accepted 20.06.24; published 31.07.24.

©Pamela Mazzocato, Jamie Linnea Luckhaus, Moa Malmqvist Castillo, Johan Burnett, Andreas Hager, Gabriela Oates, Carolina Wannheden, Carl Savage. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 31.07.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

• Open access
• Published: 25 July 2024

Strategies to strengthen the resilience of primary health care in the COVID-19 pandemic: a scoping review

• Ali Mohammad Mosadeghrad 1 ,
• Mahnaz Afshari 2 ,
• Parvaneh Isfahani 3 ,
• Farahnaz Ezzati 4 ,
• Mahdi Abbasi 4 ,
• Shahrzad Akhavan Farahani 4 ,
• Maryam Zahmatkesh 5 &
• Leila Eslambolchi 4  

BMC Health Services Research volume  24 , Article number:  841 ( 2024 ) Cite this article

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Metrics details

Primary Health Care (PHC) systems are pivotal in delivering essential health services during crises, as demonstrated during the COVID-19 pandemic. With varied global strategies to reinforce PHC systems, this scoping review consolidates these efforts, identifying and categorizing key resilience-building strategies.

Adopting Arksey and O'Malley's scoping review framework, this study synthesized literature across five databases and Google Scholar, encompassing studies up to December 31st, 2022. We focused on English and Persian studies that addressed interventions to strengthen PHC amidst COVID-19. Data were analyzed through thematic framework analysis employing MAXQDA 10 software.

Our review encapsulated 167 studies from 48 countries, revealing 194 interventions to strengthen PHC resilience, categorized into governance and leadership, financing, workforce, infrastructures, information systems, and service delivery. Notable strategies included telemedicine, workforce training, psychological support, and enhanced health information systems. The diversity of the interventions reflects a robust global response, emphasizing the adaptability of strategies across different health systems.

Conclusions

The study underscored the need for well-resourced, managed, and adaptable PHC systems, capable of maintaining continuity in health services during emergencies. The identified interventions suggested a roadmap for integrating resilience into PHC, essential for global health security. This collective knowledge offered a strategic framework to enhance PHC systems' readiness for future health challenges, contributing to the overall sustainability and effectiveness of global health systems.

Peer Review reports

The health system is a complex network that encompasses individuals, groups, and organizations engaged in policymaking, financing, resource generation, and service provision. These efforts collectively aim to safeguard and enhance people health, meet their expectations, and provide financial protection [ 1 ]. The World Health Organization's (WHO) framework outlines six foundational building blocks for a robust health system: governance and leadership, financing, workforce, infrastructure along with technologies and medicine, information systems, and service delivery. Strengthening these elements is essential for health systems to realize their objectives of advancing and preserving public health [ 2 ].

Effective governance in health systems encompasses the organization of structures, processes, and authority, ensuring resource stewardship and aligning stakeholders’ behaviors with health goals [ 3 ]. Financial mechanisms are designed to provide health services without imposing financial hardship, achieved through strategic fund collection, management and allocation [ 4 , 5 ]. An equitable, competent, and well-distributed health workforce is crucial in delivering healthcare services and fulfilling health system objectives [ 2 ]. Access to vital medical supplies, technologies, and medicines is a cornerstone of effective health services, while health information systems play a pivotal role in generating, processing, and utilizing health data, informing policy decisions [ 2 , 5 ]. Collectively, these components interact to offer quality health services that are safe, effective, timely, affordable, and patient-centered [ 2 ]

The WHO, at the 1978 Alma-Ata conference, introduced primary health care (PHC) as the fundamental strategy to attain global health equity [ 6 ]. Subsequent declarations, such as the one in Astana in 2018, have reaffirmed the pivotal role of PHC in delivering high-quality health care for all [ 7 ]. PHC represents the first level of contact within the health system, offering comprehensive, accessible, community-based care that is culturally sensitive and supported by appropriate technology [ 8 ]. Essential care through PHC encompasses health education, proper nutrition, access to clean water and sanitation, maternal and child healthcare, immunizations, treatment of common diseases, and the provision of essential drugs [ 6 ]. PHC aims to provide protective, preventive, curative, and rehabilitative services that are as close to the community as possible [ 9 ].

Global health systems, however, have faced significant disruptions from various shocks and crises [ 10 ], with the COVID-19 pandemic being a recent and profound example. The pandemic has stressed health systems worldwide, infecting over 775 million and claiming more than 7.04 million lives as of April 13th, 2024 [ 11 ]. Despite the pandemic highlighting the critical role of hospitals and intensive care, it also revealed the limitations of specialized medicine when not complemented by a robust PHC system [ 12 ].

The pandemic brought to light the vulnerabilities of PHC systems, noting a significant decrease in the use of primary care for non-emergency conditions. Routine health services, including immunizations, prenatal care, and chronic disease management, were severely impacted [ 13 ]. The challenges—quarantine restrictions, fears of infection, staffing and resource shortages, suspended non-emergency services, and financial barriers—reduced essential service utilization [ 14 ]. This led to an avoidance of healthcare, further exacerbating health inequalities and emphasizing the need for more resilient PHC systems [ 15 , 16 , 17 ].

Resilient PHC systems are designed to predict, prevent, prepare, absorb, adapt, and transform when facing crises, ensuring the continuity of routine health services [ 18 ]. Investing in the development of such systems can not only enhance crisis response but also foster post-crisis transformation and improvement. This study focuses on identifying global interventions and strategies to cultivate resilient PHC systems, aiding policymakers and managers in making informed decisions in times of crisis.

In 2023, we conducted a scoping review to collect and synthesize evidence from a broad spectrum of studies addressing the COVID-19 pandemic. A scoping review allows for the assessment of literature's volume, nature, and comprehensiveness, and is uniquely inclusive of both peer-reviewed articles and gray literature—such as reports, white papers, and policy documents. Unlike systematic reviews, it typically does not require a quality assessment of the included literature, making it well-suited for rapidly gathering a wide scope of evidence [ 19 ]. Our goal was to uncover the breadth of solutions aimed at bolstering the resilience of the PHC system throughout the COVID-19 crisis. The outcomes of this review are intended to inform the development of a model that ensures the PHC system's ability to continue delivering not just emergency services but also essential care during times of crisis.

We employed Arksey and O'Malley's methodological framework, which consists of six steps: formulating the research question, identifying relevant studies, selecting the pertinent studies, extracting data, synthesizing and reporting the findings, and, where applicable, consulting with stakeholders to inform and validate the results [ 20 ]. This comprehensive approach is designed to capture a wide range of interventions and strategies, with the ultimate aim of crafting a robust PHC system that can withstand the pressures of a global health emergency

Stage 1: identifying the research question

Our scoping review was guided by the central question: "Which strategies and interventions have been implemented to enhance the resilience of primary healthcare systems in response to the COVID-19 pandemic?" This question aimed to capture a comprehensive array of responses to understand the full scope of resilience-building activities within PHC systems.

Stage 2: identifying relevant studies

To ensure a thorough review, we conducted systematic searches across multiple databases, specifically targeting literature up to December 31st, 2022. The databases included PubMed, Web of Science, Scopus, Magiran, and SID. We also leveraged the expansive reach of Google Scholar. Our search strategy incorporated a bilingual approach, utilizing both English and Persian keywords that encompassed "PHC," "resilience," "strategies," and "policies," along with the logical operators AND/OR to refine the search. Additionally, we employed Medical Subject Headings (MeSH) terms to enhance the precision of our search. The results were meticulously organized and managed using the Endnote X8 citation manager, facilitating the systematic selection and review of pertinent literature.

Stage 3: selecting studies

In the third stage, we meticulously vetted our search results to exclude duplicate entries by comparing bibliographic details such as titles, authors, publication dates, and journal names. This task was performed independently by two of our authors, LE and MA, who rigorously screened titles and abstracts. Discrepancies encountered during this process were brought to the attention of a third author, AMM, for resolution through consensus.

Subsequently, full-text articles were evaluated by four team members—LE, MA, PI, and SHZ—to ascertain their relevance to our research question. The selection hinged on identifying articles that discussed strategies aimed at bolstering the resilience of PHC systems amidst the COVID-19 pandemic Table 1 .

We have articulated the specific inclusion and exclusion criteria that guided our selection process in Table 2 , ensuring transparency and replicability of our review methodology

Stage 4: charting the data

Data extraction was conducted by a team of six researchers (LE, MA, PI, MA, FE, and SHZ), utilizing a structured data extraction form. For each selected study, we collated details including the article title, the first author’s name, the year of publication, the country where the study was conducted, the employed research methodology, the sample size, the type of document, and the PHC strengthening strategies described.

In pursuit of maintaining rigorous credibility in our study, we adopted a dual-review process. Each article was independently reviewed by pairs of researchers to mitigate bias and ensure a thorough analysis. Discrepancies between reviewers were addressed through discussion to reach consensus. In instances where consensus could not be reached, the matter was escalated to a third, neutral reviewer. Additionally, to guarantee thoroughness, either LE or MA conducted a final review of the complete data extraction for each study.

Stage 5: collating, summarizing and reporting the results

In this stage, authors LE, MZ, and MA worked independently to synthesize the data derived from the selected studies. Differences in interpretation were collaboratively discussed until a consensus was reached, with AMM providing arbitration where required.

We employed a framework thematic analysis, underpinned by the WHO's health system building blocks model, to structure our findings. This model categorizes health system components into six foundational elements: governance and leadership; health financing; health workforce; medical products, vaccines, and technologies; health information systems; and service delivery [ 2 ]. Using MAXQDA 10 software, we coded the identified PHC strengthening strategies within these six thematic areas.

Summary of search results and study selection

In total, 4315 articles were found by initial search. After removing 397 duplicates, 3918 titles and abstracts were screened and 3606 irrelevant ones were deleted. Finally, 167 articles of 312 reviewed full texts were included in data synthesis (Fig.  1 ). Main characteristics of included studies are presented in Appendix 1.

PRISMA Flowchart of search process and results

Characteristics of studies

These studies were published in 2020 (18.6%), 2021 (36.5%) and 2022 (44.9%). They were conducted in 48 countries, mostly in the US (39 studies), the UK (16 studies), Canada (11 studies), Iran (10 studies) and Brazil (7 studies) as shown in Fig.  2 .

Distribution of reviewed studies by country

Although the majority of the reviewed publications were original articles (55.1 %) and review papers (21 %), other types of documents such as reports, policy briefs, analysis, etc., were also included in this review (Fig.  3 ).

An overview of the publication types

Strengthening interventions to build a resilient PHC system

In total, 194 interventions were identified for strengthening the resilience of PHC systems to respond to the COVID-19 pandemic. They were grouped into six themes of PHC governance and leadership (46 interventions), PHC financing (21 interventions), PHC workforce (37 interventions), PHC infrastructures, equipment, medicines and vaccines (30 interventions), PHC information system (21 interventions) and PHC service delivery (39 interventions). These strategies are shown in Table 3 .

This scoping review aimed to identify and categorize the range of interventions employed globally to strengthen the resilience of primary healthcare (PHC) systems in the face of the COVID-19 pandemic. Our comprehensive search yielded 194 distinct interventions across 48 countries, affirming the significant international efforts to sustain healthcare services during this unprecedented crisis. These interventions have been classified according to the WHO’s six building block model of health systems, providing a framework for analyzing their breadth and depth. This review complements and expands upon the findings from Pradhan et al., who identified 28 interventions specifically within low and middle-income countries, signaling the universality of the challenge and the myriad of innovative responses it has provoked globally [ 178 ].

The review highlights the critical role of governance and leadership in PHC resilience. Effective organizational structure changes, legal reforms, and policy development were crucial in creating adaptive healthcare systems capable of meeting the dynamic challenges posed by the pandemic. These findings resonate with the two strategies of effective leadership and coordination emphasized by Pradhan et al. (2023), and underscore the need for clear vision, evidence-based policy, and active community engagement in governance [ 178 ]. The COVID-19 pandemic posed significant challenges for PHC systems globally. A pivotal response to these challenges was the active involvement of key stakeholders in the decision-making process. This inclusivity spanned across the spectrum of general practitioners, health professionals, health managers, and patients. By engaging these vital contributors, it became possible to address their specific needs and to design and implement people-centered services effectively [ 41 , 42 , 43 ].

The development and implementation of collaborative, evidence-informed policies and national healthcare plans were imperative. Such strategies required robust leadership, bolstered by political commitment, to ensure that the necessary changes could be enacted swiftly and efficiently [ 41 , 45 ]. Leaders within the health system were called upon to foster an environment of good governance. This entailed promoting increased participation from all sectors of the healthcare community, enhancing transparency in decision-making processes, and upholding the principles of legitimacy, accountability, and responsibility within the health system [ 10 ]. The collective aim was to create a more resilient, responsive, and equitable healthcare system in the face of the pandemic's demands.

In the wake of the COVID-19 pandemic, governments were compelled to implement new laws and regulations. These were designed to address a range of issues from professional accreditation and ethical concerns to supporting the families of healthcare workers. Additionally, these legal frameworks facilitated the integration of emerging services such as telemedicine into the healthcare system, ensuring that these services were regulated and standardized [ 38 , 40 , 61 ]. A key aspect of managing the pandemic was the establishment of effective and transparent communication systems for patients, public health authorities, and the healthcare system at large [ 60 , 61 ]. To disseminate vital information regarding the pandemic, vaccination programs, and healthcare services, authorities leveraged various channels. Public media, local online platforms, and neighborhood networks were instrumental in keeping the public informed about the ongoing situation and available services [ 53 , 60 , 86 ]. For health professionals, digital communication tools such as emails and WhatsApp groups, as well as regular meetings, were utilized to distribute clinical guidelines, government directives, and to address any queries they might have had. This ensured that healthcare workers were kept up-to-date with the evolving landscape of the pandemic and could adapt their practices accordingly [ 60 , 144 ].

Healthcare facilities function as complex socio-technical entities, combining multiple specialties and adapting to the ever-changing landscape of healthcare needs and environments [ 179 ]. To navigate this dynamic, policy makers must take into account an array of determinants—political, economic, social, and environmental—that influence health outcomes. Effective management of a health crisis necessitates robust collaboration across various sectors, including government bodies, public health organizations, primary healthcare systems, and hospitals. Such collaboration is not only pivotal during crisis management but also during the development of preparedness plans [ 63 ]. Within the health system, horizontal collaboration among departments and vertical collaboration between the Ministry of Health and other governmental departments are vital. These cooperative efforts are key to reinforce the resilience of the primary healthcare system. Moreover, a strong alliance between national pandemic response teams and primary healthcare authorities is essential to identifying and resolving issues within the PHC system [ 29 ]. On an international scale, collaborations and communications are integral to the procurement of essential medical supplies, such as medicines, equipment, and vaccines. These international partnerships are fundamental to ensuring that health systems remain equipped to face health emergencies [ 63 ].

To ensure the PHC system's preparedness and response capacity was at its best, regular and effective monitoring and evaluation programs were put in place. These included rigorous quarterly stress tests at the district level, which scrutinized the infrastructure and technology to pinpoint the system’s strengths and areas for improvement [ 43 ]. Furthermore, clinical audits were conducted to assess the structure, processes, and outcomes of healthcare programs, thereby enhancing the quality and effectiveness of the services provided [ 63 ]. These evaluation measures were crucial for maintaining a high standard of care and for adapting to the ever-evolving challenges faced by the PHC system.

Financial strategies played a critical role in enabling access to essential health services without imposing undue financial hardship. Various revenue-raising, pooling, and purchasing strategies were implemented to expand PHC financing during the pandemic, illustrating the multifaceted approach needed to sustain healthcare operations under strained circumstances [ 9 , 19 ].

In response to the COVID-19 pandemic, the Indian government took decisive action to bolster the country's healthcare infrastructure. By enhancing the financial capacity of states, the government was able to inject more funds into the Primary Health Care (PHC) system. This influx of resources made it possible to introduce schemes providing free medications and diagnostic services [ 50 ]. The benefits of increased financial resources were also felt beyond India's borders, enabling the compensation of health services in various forms. In Greece, it facilitated the monitoring and treatment of COVID-19 through in-person, home-based, and remote health services provided by physicians in private practice. Similarly, in Iran, the financial boost supported the acquisition of basic and para-clinical services from the private sector [ 21 , 65 ]. These measures reflect a broader international effort to adapt and sustain health services during a global health crisis.

The COVID-19 pandemic presented a formidable challenge to the PHC workforce worldwide. Healthcare workers were subjected to overwhelming workloads and faced significant threats to both their physical and mental well-being. To build resilience in the face of this crisis, a suite of interventions was implemented. These included recruitment strategies, training and development programs, enhanced teamwork, improved protective measures, comprehensive performance appraisals, and appropriate compensation mechanisms, as documented in Table 3 . To address staffing needs within PHC centers, a range of professionals including general practitioners, nurses, community health workers, and technical staff were either newly employed or redeployed from other healthcare facilities [ 63 ]. Expert practitioners were positioned on the frontlines, providing both in-person services and telephone consultations, acting as gatekeepers in the health system [ 49 , 63 ]. Support staff with technological expertise played a crucial role as well, assisting patients in navigating patient portals, utilizing new digital services, and conducting video visits [ 102 ]. Furthermore, the acute shortage of healthcare workers was mitigated by recruiting individuals who were retired, not currently practicing, or in training as students, as well as by enlisting volunteers. This strategy was key to bolstering the workforce and ensuring continuity of care during the pandemic [ 109 ].

During the pandemic, new training programs were developed to prepare healthcare staff for the evolving demands of their roles. These comprehensive courses covered a wide array of critical topics, including the correct use of personal protective equipment (PPE), the operation of ventilators, patient safety protocols, infection prevention, teamwork, problem-solving, self-care techniques, mental health support, strategies for managing stress, navigating and applying reliable web-based information, emergency response tactics, telemedicine, and direct care for COVID-19 patients [ 74 , 95 , 100 , 108 , 110 , 112 , 117 ].

Acknowledging the psychological and professional pressures faced by the primary healthcare workforce, health managers took active measures to safeguard both the physical and mental well-being of their employees during this challenging period [ 124 ]. Efforts to protect physical health included monitoring health status, ensuring vaccination against COVID-19, and providing adequate PPE [ 63 , 72 ]. To address mental health, a variety of interventions were deployed to mitigate anxiety and related issues among frontline workers. In Egypt, for instance, healthcare workers benefited from psychotherapy services and adaptable work schedules to alleviate stress [ 126 ]. Singapore employed complementary strategies, such as yoga, meditation, and the encouragement of religious practices, to promote relaxation among staff [ 133 ]. In the United States, the Wellness Hub application was utilized as a tool for employees to enhance their mental health [ 132 ]. In addition to health and wellness initiatives, there were financial incentives aimed at motivating employees. Payment protocols were revised, and new incentives, including scholarship opportunities and career development programs, were introduced to foster job satisfaction and motivation among healthcare workers [ 63 ].

The resilience of PHC systems during the pandemic hinged on several key improvements. Enhancing health facilities, supplying medicines and diagnostic kits, distributing vaccines, providing medical equipment, and building robust digital infrastructure were all fundamental elements that contributed to the strength of PHC systems, as outlined in Table 3 . Safe and accessible primary healthcare was facilitated through various means. Wheelchair routes were created for patients to ensure their mobility within healthcare facilities. , dedicated COVID-19 clinics were established, mass vaccination centers were opened to expedite immunization, and mobile screening stations were launched to extend testing capabilities [ 23 , 33 , 63 , 140 ].

In Iran, the distribution and availability of basic medicines were managed in collaboration with the Food and Drug Organization, ensuring that essential medications reached those in need [ 89 ]. During the outbreak, personal protective equipment (PPE) was among the most critical supplies. Access to PPE was prioritized, particularly for vulnerable groups and healthcare workers, to provide a layer of safety against the virus [ 63 ]. Vaccines were made available at no cost, with governments taking active measures to monitor their safety and side effects, to enhance their quality, and to secure international approvals. Furthermore, effective communication strategies were employed to keep the public informed about vaccine-related developments [ 32 , 83 ].

These comprehensive efforts underscored the commitment to maintaining a resilient PHC system in the face of a global health every individual in the community could access healthcare services. To facilitate this, free high-speed Wi-Fi hotspots were established, enabling patients to engage in video consultations and utilize a range of e-services without the barrier of internet costs crisis. Significant enhancements were made to the digital infrastructure. This expansion was critical in ensuring that [ 30 , 54 ]. Complementing these measures, a variety of digital health tools were deployed to further modernize care delivery. Countries like Nigeria and Germany, for instance, saw the introduction of portable electrocardiograms and telemedical stethoscopes. These innovations allowed for more comprehensive remote assessments and diagnostics, helping to bridge the gap between traditional in-person consultations and the emerging needs for telemedicine [ 141 , 180 ].

Throughout the COVID-19 pandemic, targeted interventions were implemented to bolster information systems and research efforts, as outlined in Table 3 . Key among these was the advancement of a modern, secure public health information system to ensure access to health data was not only reliable and timely but also transparent and accurate [ 33 , 45 , 49 ]. The "Open Notes" initiative in the United States exemplified this effort, guaranteeing patient access to, and editorial control over, their health records [ 141 ]. Management strategies also promoted the "one-health" approach, facilitating the exchange of health data across various departments and sectors to enhance public health outcomes [ 10 ].

In addition to these information system upgrades, active patient surveillance and early warning systems were instituted in collaboration with public health agencies. These systems played a pivotal role in detecting outbreaks, providing precise reports on the incidents, characterizing the epidemiology of pathogens, tracking their spread, and evaluating the efficacy of control strategies. They were instrumental in pinpointing areas of concern, informing smart lockdowns, and improving contact tracing methods [ 33 , 63 , 72 ]. The reinforcement of these surveillance and warning systems had a profound impact on shaping and implementing a responsive strategy to the health crisis [ 10 ].

To further reinforce the response to the pandemic, enhancing primary healthcare (PHC) research capacity became crucial. This enabled healthcare professionals and policymakers to discern both facilitators and barriers within the system and to devise fitting strategies to address emerging challenges. To this end, formal advisory groups and multidisciplinary expert panels, which included specialists from epidemiology, clinical services, social care, sociology, policy-making, and management, were convened. These groups harnessed the best available evidence to inform decision-making processes [ 30 ]. Consequently, research units were established to carry out regular telephone surveys and to collect data on effective practices, as well as new diagnostic and therapeutic approaches [ 31 , 89 ]. The valuable insights gained from these research endeavors were then disseminated through trusted channels to both the public and policymakers, ensuring informed decisions at all levels [ 36 ].

The COVID-19 pandemic acted as a catalyst for the swift integration of telemedicine into healthcare systems globally. This period saw healthcare providers leverage telecommunication technologies to offer an array of remote services, addressing medical needs such as consultations, diagnosis, monitoring, and prescriptions. This transition was instrumental in ensuring care continuity and mitigating infection risks for both patients and healthcare workers, highlighting an innovative evolution in healthcare delivery [ 170 , 181 ].

Countries adapted to this new model of healthcare with varied applications: Armenia established telephone follow-ups and video consultations for remote patient care, while e-pharmacies and mobile health tools provided immediate access to medical information and services [ 29 ]. In France and the United States, tele-mental health services and online group support became a means to support healthy living during the pandemic [ 147 , 158 ] . New Zealand introduced the Aroha chatbot, an initiative to assist with mental health management [ 139 ].

The implementation and effectiveness of these telehealth services were not limited by economic barriers, as underscored by Pradhan et al. (2023), who noted the key role of telemedicine in low and middle-income countries. These countries embraced the technology to maintain health service operations, proving its global applicability and utility [ 178 ]. The widespread adoption of telemedicine, therefore, represents a significant and perhaps lasting shift in healthcare practice, one that has redefined patient care in the face of a global health crisis and may continue to shape the future of healthcare delivery [ 170 , 178 , 181 ].

The study highlighted PHC strengthening strategies in COVID-19 time . Notably, the adaptations and reforms spanned across governance, financing, workforce management, information system, infrastructural readiness, and service delivery enhancements. These interventions collectively contributed to the robustness of health systems against the sudden surge in demand and the multifaceted challenges imposed by the pandemic and resulted.

Significantly, the findings have broader implications for health policy and system design worldwide. The pandemic has highlighted the critical need for resilient health systems that are capable of not only responding to health emergencies but also maintaining continuity in essential services. The strategies documented in this review serve as a template for countries to fortify their health systems by embedding resilience into their PHC frameworks (Fig.  4 ). Future health crises can be better managed by learning from these evidenced responses, which emphasize the necessity of integrated, well-supported, and dynamically adaptable health care structures.

A model for strengthening the resilience of the primary health care system

Looking ahead, realist reviews could play a pivotal role in refining PHC resilience strategies. By understanding the context in which specific interventions succeed or fail, realist reviews can help policymakers and practitioners design more effective health system reforms, as echoed in the need for evidence-based planning in health system governance [ 9 ] ​​. These reviews offer a methodological advantage by focusing on the causality between interventions and outcomes, aligning with the importance of effective health system leadership and management [ 50 , 182 ] ​​. They take into account the underlying mechanisms and contextual factors, thus providing a nuanced understanding that is crucial for tailoring interventions to meet local needs effectively [ 28 , 86 ] ​​, ultimately leading to more sustainable health systems globally. This shift towards a more analytical and context-sensitive approach in evaluating health interventions, as supported by WHO's framework for action [ 2 , 10 ] ​​, will be crucial for developing strategies that are not only effective in theory but also practical and sustainable in diverse real-world settings.

Limitations and future research

In our comprehensive scoping review, we analyzed 167 articles out of a dataset of 4,315, classifying 194 interventions that build resilience in primary healthcare systems across the globe in response to pandemics like COVID-19. While the review's extensive search provides a sweeping overview of various strategies, it may not capture the full diversity of interventions across all regions and economies. Future research should focus on meta-analyses to evaluate the effectiveness of these interventions in greater detail and employ qualitative studies to delve into the specific challenges and successes, thus gaining a more nuanced understanding of the context. As the review includes articles only up to December 31, 2022, it may overlook more recent studies. Regular updates, a broader linguistic range, and the inclusion of a more diverse array of databases are recommended to maintain relevance and expand the breadth of literature, ultimately guiding more focused research that could significantly enhance the resilience of PHC systems worldwide.

Availability of data and materials

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

Abbreviations

Primary Health Care

World Health Organization

Sustainable Development Goals

Universal Health Coverage

Personal Protective Equipment

General Practitioner

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We would like to thank Dr. Arshad Altaf for his invaluable comments on the earlier drafts of this work.

Funding for this project was provided by the World Health Organization Eastern Mediterranean Region.

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Farahnaz Ezzati, Mahdi Abbasi, Shahrzad Akhavan Farahani & Leila Eslambolchi

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Mosadeghrad, A.M., Afshari, M., Isfahani, P. et al. Strategies to strengthen the resilience of primary health care in the COVID-19 pandemic: a scoping review. BMC Health Serv Res 24 , 841 (2024). https://doi.org/10.1186/s12913-024-11278-4

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A spatial case-based reasoning method for healthy city assessment: a case study of middle layer super output areas (msoas) in birmingham, england.

1. Introduction

2. materials and methods, 2.1. research framework, 2.2. establishment of a case database, 2.2.1. data sources, 2.2.2. spatial case representation, 2.3. case pre-organization, 2.4. attribute reduction and weight assignment, 2.5. integrated reasoning of attribute and spatial similarity, 2.5.1. calculation of attribute feature similarity, 2.5.2. calculation of spatial feature similarity.

• Calculation of Similarity for Spatial Point Targets

2.6. Case Reuse

2.7. case revision, 3. case study and results analysis, 3.1. construction of the case base, 3.2. spatial clustering organization of case library, 3.3. feature extraction and weight allocation, 3.4. case retrieval and revision, 3.5. experiment and result analysis, 3.5.1. experiment one: comparison with traditional evaluation methods, 3.5.2. experiment two: comparison with other case-based reasoning methods, 3.5.3. experiment three: real-world application, 3.6. discussion summary, 4. conclusions, author contributions, data availability statement, conflicts of interest.

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Deng, S.; Liu, W.; Peng, Y.; Liu, B. A Spatial Case-Based Reasoning Method for Healthy City Assessment: A Case Study of Middle Layer Super Output Areas (MSOAs) in Birmingham, England. ISPRS Int. J. Geo-Inf. 2024 , 13 , 271. https://doi.org/10.3390/ijgi13080271

Deng S, Liu W, Peng Y, Liu B. A Spatial Case-Based Reasoning Method for Healthy City Assessment: A Case Study of Middle Layer Super Output Areas (MSOAs) in Birmingham, England. ISPRS International Journal of Geo-Information . 2024; 13(8):271. https://doi.org/10.3390/ijgi13080271

Deng, Shuguang, Wei Liu, Ying Peng, and Binglin Liu. 2024. "A Spatial Case-Based Reasoning Method for Healthy City Assessment: A Case Study of Middle Layer Super Output Areas (MSOAs) in Birmingham, England" ISPRS International Journal of Geo-Information 13, no. 8: 271. https://doi.org/10.3390/ijgi13080271

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