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Making Learning Relevant With Case Studies

The open-ended problems presented in case studies give students work that feels connected to their lives.

To prepare students for jobs that haven’t been created yet, we need to teach them how to be great problem solvers so that they’ll be ready for anything. One way to do this is by teaching content and skills using real-world case studies, a learning model that’s focused on reflection during the problem-solving process. It’s similar to project-based learning, but PBL is more focused on students creating a product.

Case studies have been used for years by businesses, law and medical schools, physicians on rounds, and artists critiquing work. Like other forms of problem-based learning, case studies can be accessible for every age group, both in one subject and in interdisciplinary work.

You can get started with case studies by tackling relatable questions like these with your students:

• How can we limit food waste in the cafeteria?
• How can we get our school to recycle and compost waste? (Or, if you want to be more complex, how can our school reduce its carbon footprint?)
• How can we improve school attendance?
• How can we reduce the number of people who get sick at school during cold and flu season?

Addressing questions like these leads students to identify topics they need to learn more about. In researching the first question, for example, students may see that they need to research food chains and nutrition. Students often ask, reasonably, why they need to learn something, or when they’ll use their knowledge in the future. Learning is most successful for students when the content and skills they’re studying are relevant, and case studies offer one way to create that sense of relevance.

Teaching With Case Studies

Ultimately, a case study is simply an interesting problem with many correct answers. What does case study work look like in classrooms? Teachers generally start by having students read the case or watch a video that summarizes the case. Students then work in small groups or individually to solve the case study. Teachers set milestones defining what students should accomplish to help them manage their time.

During the case study learning process, student assessment of learning should be focused on reflection. Arthur L. Costa and Bena Kallick’s Learning and Leading With Habits of Mind gives several examples of what this reflection can look like in a classroom: 

Journaling: At the end of each work period, have students write an entry summarizing what they worked on, what worked well, what didn’t, and why. Sentence starters and clear rubrics or guidelines will help students be successful. At the end of a case study project, as Costa and Kallick write, it’s helpful to have students “select significant learnings, envision how they could apply these learnings to future situations, and commit to an action plan to consciously modify their behaviors.”

Interviews: While working on a case study, students can interview each other about their progress and learning. Teachers can interview students individually or in small groups to assess their learning process and their progress.

Student discussion: Discussions can be unstructured—students can talk about what they worked on that day in a think-pair-share or as a full class—or structured, using Socratic seminars or fishbowl discussions. If your class is tackling a case study in small groups, create a second set of small groups with a representative from each of the case study groups so that the groups can share their learning.

4 Tips for Setting Up a Case Study

1. Identify a problem to investigate: This should be something accessible and relevant to students’ lives. The problem should also be challenging and complex enough to yield multiple solutions with many layers.

2. Give context: Think of this step as a movie preview or book summary. Hook the learners to help them understand just enough about the problem to want to learn more.

3. Have a clear rubric: Giving structure to your definition of quality group work and products will lead to stronger end products. You may be able to have your learners help build these definitions.

4. Provide structures for presenting solutions: The amount of scaffolding you build in depends on your students’ skill level and development. A case study product can be something like several pieces of evidence of students collaborating to solve the case study, and ultimately presenting their solution with a detailed slide deck or an essay—you can scaffold this by providing specified headings for the sections of the essay.

Problem-Based Teaching Resources

There are many high-quality, peer-reviewed resources that are open source and easily accessible online.

• The National Center for Case Study Teaching in Science at the University at Buffalo built an online collection of more than 800 cases that cover topics ranging from biochemistry to economics. There are resources for middle and high school students.
• Models of Excellence , a project maintained by EL Education and the Harvard Graduate School of Education, has examples of great problem- and project-based tasks—and corresponding exemplary student work—for grades pre-K to 12.
• The Interdisciplinary Journal of Problem-Based Learning at Purdue University is an open-source journal that publishes examples of problem-based learning in K–12 and post-secondary classrooms.
• The Tech Edvocate has a list of websites and tools related to problem-based learning.

In their book Problems as Possibilities , Linda Torp and Sara Sage write that at the elementary school level, students particularly appreciate how they feel that they are taken seriously when solving case studies. At the middle school level, “researchers stress the importance of relating middle school curriculum to issues of student concern and interest.” And high schoolers, they write, find the case study method “beneficial in preparing them for their future.”

Organizing Your Social Sciences Research Assignments

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

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

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

How to Approach Writing a Case Study Research Paper

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

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

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

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

Structure and Writing Style

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

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

I.  Introduction

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

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

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

II.  Literature Review

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

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

III.  Method

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

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

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

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

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

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

IV.  Discussion

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

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

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

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

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

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

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

V.  Conclusion

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

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

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

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

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

Problems to Avoid

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

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

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

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

Writing Tip

At Least Five Misconceptions about Case Study Research

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

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

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

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

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

http://dx.doi.org/10.1136/eb-2017-102845

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What is it?

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

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

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

Benefits and limitations of case studies

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

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

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

Examples of case studies

Example 1: nurses’ paediatric pain management practices.

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

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

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

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

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

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

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

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

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

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

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

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

• Gustafsson J
• Calanzaro M
• Sandelowski M

Competing interests None declared.

Provenance and peer review Commissioned; internally peer reviewed.

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

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

Published on May 8, 2019 by Shona McCombes . Revised on June 22, 2023.

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

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

Table of contents

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Research bias

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

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What the Case Study Method Really Teaches

• Nitin Nohria

Seven meta-skills that stick even if the cases fade from memory.

It’s been 100 years since Harvard Business School began using the case study method. Beyond teaching specific subject matter, the case study method excels in instilling meta-skills in students. This article explains the importance of seven such skills: preparation, discernment, bias recognition, judgement, collaboration, curiosity, and self-confidence.

During my decade as dean of Harvard Business School, I spent hundreds of hours talking with our alumni. To enliven these conversations, I relied on a favorite question: “What was the most important thing you learned from your time in our MBA program?”

• Nitin Nohria is a professor and former dean at Harvard Business School and the chairman of Thrive Capital, a venture capital firm based in New York.

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Writing A Case Study

A Complete Case Study Writing Guide With Examples

Published on: Jun 14, 2019

Last updated on: Nov 16, 2023

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Simple Case Study Format for Students to Follow

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Brilliant Case Study Examples and Templates For Your Help

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Many writers find themselves grappling with the challenge of crafting persuasive and engaging case studies. 

The process can be overwhelming, leaving them unsure where to begin or how to structure their study effectively. And, without a clear plan, it's tough to show the value and impact in a convincing way.

But don’t worry!

In this blog, we'll guide you through a systematic process, offering step-by-step instructions on crafting a compelling case study. 

Along the way, we'll share valuable tips and illustrative examples to enhance your understanding. So, let’s get started.

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What is a Case Study? 

A case study is a detailed analysis and examination of a particular subject, situation, or phenomenon. It involves comprehensive research to gain a deep understanding of the context and variables involved. 

Typically used in academic, business, and marketing settings, case studies aim to explore real-life scenarios, providing insights into challenges, solutions, and outcomes. They serve as valuable tools for learning, decision-making, and showcasing success stories.

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Types of Case Studies

Case studies come in various forms, each tailored to address specific objectives and areas of interest. Here are some of the main types of case studies :

• Illustrative Case Studies: These focus on describing a particular situation or event, providing a detailed account to enhance understanding.
• Exploratory Case Studies: Aimed at investigating an issue and generating initial insights, these studies are particularly useful when exploring new or complex topics.
• Explanatory Case Studies: These delve into the cause-and-effect relationships within a given scenario, aiming to explain why certain outcomes occurred.
• Intrinsic Case Studies: Concentrating on a specific case that holds intrinsic value, these studies explore the unique qualities of the subject itself.
• Instrumental Case Studies: These are conducted to understand a broader issue and use the specific case as a means to gain insights into the larger context.
• Collective Case Studies: Involving the study of multiple cases, this type allows for comparisons and contrasts, offering a more comprehensive view of a phenomenon or problem.

How To Write a Case Study - 9 Steps

Crafting an effective case study involves a structured approach to ensure clarity, engagement, and relevance. 

Here's a step-by-step guide on how to write a compelling case study:

Step 1: Define Your Objective

Before diving into the writing process, clearly define the purpose of your case study. Identify the key questions you want to answer and the specific goals you aim to achieve. 

Whether it's to showcase a successful project, analyze a problem, or demonstrate the effectiveness of a solution, a well-defined objective sets the foundation for a focused and impactful case study.

Step 2: Conduct Thorough Research

Gather all relevant information and data related to your chosen case. This may include interviews, surveys, documentation, and statistical data. 

Ensure that your research is comprehensive, covering all aspects of the case to provide a well-rounded and accurate portrayal. 

The more thorough your research, the stronger your case study's foundation will be.

Step 3: Introduction: Set the Stage

Begin your case study with a compelling introduction that grabs the reader's attention. Clearly state the subject and the primary issue or challenge faced. 

Engage your audience by setting the stage for the narrative, creating intrigue, and highlighting the significance of the case.

Step 4: Present the Background Information

Provide context by presenting the background information of the case. Explore relevant history, industry trends, and any other factors that contribute to a deeper understanding of the situation. 

This section sets the stage for readers, allowing them to comprehend the broader context before delving into the specifics of the case.

Step 5: Outline the Challenges Faced

Identify and articulate the challenges or problems encountered in the case. Clearly define the obstacles that needed to be overcome, emphasizing their significance. 

This section sets the stakes for your audience and prepares them for the subsequent exploration of solutions.

Step 6: Detail the Solutions Implemented

Describe the strategies, actions, or solutions applied to address the challenges outlined. Be specific about the decision-making process, the rationale behind the chosen solutions, and any alternatives considered. 

This part of the case study demonstrates problem-solving skills and showcases the effectiveness of the implemented measures.

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Step 7: Showcase Measurable Results

Present tangible outcomes and results achieved as a direct consequence of the implemented solutions. Use data, metrics, and success stories to quantify the impact. 

Whether it's increased revenue, improved efficiency, or positive customer feedback, measurable results add credibility and validation to your case study.

Step 8: Include Engaging Visuals

Enhance the readability and visual appeal of your case study by incorporating relevant visuals such as charts, graphs, images, and infographics. 

Visual elements not only break up the text but also provide a clearer representation of data and key points, making your case study more engaging and accessible.

Step 9: Provide a Compelling Conclusion

Wrap up your case study with a strong and conclusive summary. Revisit the initial objectives, recap key findings, and emphasize the overall success or significance of the case. 

This section should leave a lasting impression on your readers, reinforcing the value of the presented information.

Case Study Methods

The methods employed in case study writing are diverse and flexible, catering to the unique characteristics of each case. Here are common methods used in case study writing:

Conducting one-on-one or group interviews with individuals involved in the case to gather firsthand information, perspectives, and insights.

• Observation

Directly observing the subject or situation to collect data on behaviors, interactions, and contextual details.

• Document Analysis

Examining existing documents, records, reports, and other written materials relevant to the case to gather information and insights.

• Surveys and Questionnaires

Distributing structured surveys or questionnaires to relevant stakeholders to collect quantitative data on specific aspects of the case.

• Participant Observation

Combining direct observation with active participation in the activities or events related to the case to gain an insider's perspective.

• Triangulation

Using multiple methods (e.g., interviews, observation, and document analysis) to cross-verify and validate the findings, enhancing the study's reliability.

• Ethnography

Immersing the researcher in the subject's environment over an extended period, focusing on understanding the cultural context and social dynamics.

Case Study Format

Effectively presenting your case study is as crucial as the content itself. Follow these formatting guidelines to ensure clarity and engagement:

• Opt for fonts that are easy to read, such as Arial, Calibri, or Times New Roman.
• Maintain a consistent font size, typically 12 points for the body text.
• Aim for double-line spacing to maintain clarity and prevent overwhelming the reader with too much text.
• Utilize bullet points to present information in a concise and easily scannable format.
• Use numbered lists when presenting a sequence of steps or a chronological order of events.
• Bold or italicize key phrases or important terms to draw attention to critical points.
• Use underline sparingly, as it can sometimes be distracting in digital formats.
• Choose the left alignment style.
• Use hierarchy to distinguish between different levels of headings, making it easy for readers to navigate.

If you're still having trouble organizing your case study, check out this blog on case study format for helpful insights.

Case Study Examples

If you want to understand how to write a case study, examples are a fantastic way to learn. That's why we've gathered a collection of intriguing case study examples for you to review before you begin writing.

Case Study Research Example

Case Study Template

Case Study Introduction Example

Amazon Case Study Example

Business Case Study Example

APA Format Case Study Example

Psychology Case Study Example

Medical Case Study Example

UX Case Study Example

Looking for more examples? Check out our blog on case study examples for your inspiration!

Benefits and Limitations of Case Studies

Case studies are a versatile and in-depth research method, providing a nuanced understanding of complex phenomena. 

However, like any research approach, case studies come with their set of benefits and limitations. Some of them are given below:

Tips for Writing an Effective Case Study

Here are some important tips for writing a good case study:

• Clearly articulate specific, measurable research questions aligned with your objectives.
• Identify whether your case study is exploratory, explanatory, intrinsic, or instrumental.
• Choose a case that aligns with your research questions, whether it involves an individual case or a group of people through multiple case studies.
• Explore the option of conducting multiple case studies to enhance the breadth and depth of your findings.
• Present a structured format with clear sections, ensuring readability and alignment with the type of research.
• Clearly define the significance of the problem or challenge addressed in your case study, tying it back to your research questions.
• Collect and include quantitative and qualitative data to support your analysis and address the identified research questions.
• Provide sufficient detail without overwhelming your audience, ensuring a comprehensive yet concise presentation.
• Emphasize how your findings can be practically applied to real-world situations, linking back to your research objectives.
• Acknowledge and transparently address any limitations in your study, ensuring a comprehensive and unbiased approach.

To sum it up, creating a good case study involves careful thinking to share valuable insights and keep your audience interested. 

Stick to basics like having clear questions and understanding your research type. Choose the right case and keep things organized and balanced.

Remember, your case study should tackle a problem, use relevant data, and show how it can be applied in real life. Be honest about any limitations, and finish with a clear call-to-action to encourage further exploration.

However, if you are having issues understanding how to write a case study, it is best to hire the professionals.  Hiring a paper writing service online will ensure that you will get best grades on your essay without any stress of a deadline. 

So be sure to check out case study writing service online and stay up to the mark with your grades. 

Frequently Asked Questions

What is the purpose of a case study.

The objective of a case study is to do intensive research on a specific matter, such as individuals or communities. It's often used for academic purposes where you want the reader to know all factors involved in your subject while also understanding the processes at play.

What are the sources of a case study?

Some common sources of a case study include:

• Archival records
• Direct observations and encounters
• Participant observation
• Facts and statistics
• Physical artifacts

What is the sample size of a case study?

A normally acceptable size of a case study is 30-50. However, the final number depends on the scope of your study and the on-ground demographic realities.

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

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What Is a Case Study?

An in-depth study of one person, group, or event

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

Cara Lustik is a fact-checker and copywriter.

Verywell / Colleen Tighe

Benefits and Limitations

Types of case studies, how to write a case study.

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

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

While case studies focus on a single individual or group, they follow a format similar to other types of psychology writing. If you are writing a case study, it is important to follow the rules of APA format .  

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

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

• Allows researchers to collect a great deal of information
• Give researchers the chance to collect information on rare or unusual cases
• Permits researchers to develop hypotheses that can be explored in experimental research

On the negative side, a case study:

• Cannot necessarily be generalized to the larger population
• Cannot demonstrate cause and effect
• May not be scientifically rigorous
• Can lead to bias

Researchers may choose to perform a case study if they are interested in exploring a unique or recently discovered phenomenon. The insights gained from such research can help the researchers develop additional ideas and study questions that might be explored in future studies.

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

Case Study Examples

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

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

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

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

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

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

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

The type of case study that psychology researchers utilize depends on the unique characteristics of the situation as well as the case itself.

There are also different methods that can be used to conduct a case study, including prospective and retrospective case study methods.

Prospective case study methods are those in which an individual or group of people is observed in order to determine outcomes. For example, a group of individuals might be watched over an extended period of time to observe the progression of a particular disease.

Retrospective case study methods involve looking at historical information. For example, researchers might start with an outcome, such as a disease, and then work their way backward to look at information about the individual's life to determine risk factors that may have contributed to the onset of the illness.

Where to Find Data

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

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

Section 1: A Case History

This section will have the following structure and content:

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

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

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

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

Section 2: Treatment Plan

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

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

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

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

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

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

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

A Word From Verywell

Case studies can be a useful research tool, but they need to be used wisely. In many cases, they are best utilized in situations where conducting an experiment would be difficult or impossible. They are helpful for looking at unique situations and allow researchers to gather a great deal of information about a specific individual or group of people.

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

Simply Psychology. Case Study Method .

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

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

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

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

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• Introduction
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• Article Information

The sample construction diagram shows inclusion and exclusion criteria for assembly of the sample of individuals with post–COVID-19 condition (PCC) and matched controls without COVID-19. BMI indicates body mass index (calculated as weight in kilograms divided by height in meters squared); ER, emergency room.

The 12-month mortality for individuals with post–COVID-19 condition was substantially higher than in matched controls without COVID-19.

eTable 1. Baseline characteristics of initial Covid population vs post covid conditions (PCC) cohort

eTable 2. List of symptoms and Covid diagnosis used to identify PCC cases with their ICD 10 codes and description

eTable 3. Index month distributions among the overall cohort

eFigure. Propensity score balance checks for common support

eTable 4. Distribution of PCC symptoms during the weeks 5 to 12 post index among the PCC cohort

eTable 5. Sensitivity analysis among members with 6 months continuous enrollment

Data Sharing Statement

• Cardiovascular Risks in Patients With Post–COVID-19 Condition JAMA Health Forum Editorial March 3, 2023 Mark É. Czeisler, PhD; Said A. Ibrahim, MD, MPH, MBA
• Error in Study Type JAMA Health Forum Correction July 28, 2023

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DeVries A , Shambhu S , Sloop S , Overhage JM. One-Year Adverse Outcomes Among US Adults With Post–COVID-19 Condition vs Those Without COVID-19 in a Large Commercial Insurance Database. JAMA Health Forum. 2023;4(3):e230010. doi:10.1001/jamahealthforum.2023.0010

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One-Year Adverse Outcomes Among US Adults With Post–COVID-19 Condition vs Those Without COVID-19 in a Large Commercial Insurance Database

• 1 Elevance Health, Inc, Indianapolis, Indiana
• Editorial Cardiovascular Risks in Patients With Post–COVID-19 Condition Mark É. Czeisler, PhD; Said A. Ibrahim, MD, MPH, MBA JAMA Health Forum
• Correction Error in Study Type JAMA Health Forum

Question   Do postacute sequelae of SARS-CoV-2 increase risks of 1-year adverse outcomes?

Findings   In this cohort study of 13 435 US adults with post–COVID-19 condition (PCC) and 26 870 matched adults without COVID-19, the adults with PCC experienced increased risks for a number of cardiovascular outcomes, such as ischemic stroke. During the 12-month follow-up period, 2.8% of the individuals with PCC vs 1.2% of the individuals without COVID-19 died, implying an excess death rate of 16.4 per 1000 individuals.

Meaning   Individuals with PCC may be at increased risk for adverse outcomes in the year following initial infection.

Importance   Many individuals experience ongoing symptoms following the onset of COVID-19, characterized as postacute sequelae of SARS-CoV-2 or post–COVID-19 condition (PCC). Less is known about the long-term outcomes for these individuals.

Objective   To quantify 1-year outcomes among individuals meeting a PCC definition compared with a control group of individuals without COVID-19.

Design, Setting, and Participants   This cohort study with a propensity score–matched control group included members of commercial health plans and used national insurance claims data enhanced with laboratory results and mortality data from the Social Security Administration’s Death Master File and Datavant Flatiron data. The study sample consisted of adults meeting a claims-based definition for PCC with a 2:1 matched control cohort of individuals with no evidence of COVID-19 during the time period of April 1, 2020, to July 31, 2021.

Exposures   Individuals experiencing postacute sequelae of SARS-CoV-2 using a Centers for Disease Control and Prevention–based definition.

Main Outcomes and Measures   Adverse outcomes, including cardiovascular and respiratory outcomes and mortality, for individuals with PCC and controls assessed over a 12-month period.

Results   The study population included 13 435 individuals with PCC and 26 870 individuals with no evidence of COVID-19 (mean [SD] age, 51 [15.1] years; 58.4% female). During follow-up, the PCC cohort experienced increased health care utilization for a wide range of adverse outcomes: cardiac arrhythmias (relative risk [RR], 2.35; 95% CI, 2.26-2.45), pulmonary embolism (RR, 3.64; 95% CI, 3.23-3.92), ischemic stroke (RR, 2.17; 95% CI, 1.98-2.52), coronary artery disease (RR, 1.78; 95% CI, 1.70-1.88), heart failure (RR, 1.97; 95% CI, 1.84-2.10), chronic obstructive pulmonary disease (RR, 1.94; 95% CI, 1.88-2.00), and asthma (RR, 1.95; 95% CI, 1.86-2.03). The PCC cohort also experienced increased mortality, as 2.8% of individuals with PCC vs 1.2% of controls died, implying an excess death rate of 16.4 per 1000 individuals.

Conclusions and Relevance   This cohort study leveraged a large commercial insurance database and found increased rates of adverse outcomes over a 1-year period for a PCC cohort surviving the acute phase of illness. The results indicate a need for continued monitoring for at-risk individuals, particularly in the area of cardiovascular and pulmonary management.

Among the many puzzling aspects of COVID-19 has been the variable recovery time and range of complications experienced by many individuals. Median recovery time for mild cases is approximately 2 weeks and for severe cases is 6 weeks. 1 Numerous studies have identified a subset of patients for whom recovery time exceeds 6 weeks and who experience an increased risk of adverse outcomes. 2 - 4 The condition among the subset of patients experiencing post–COVID-19 symptoms has been described in the lay press as “long COVID” and in the medical literature as experiencing postacute sequelae of SARS-CoV-2, or post–COVID-19 condition (PCC). 5 - 8

The Centers for Disease Control and Prevention defines PCC as having new, returning, or ongoing health issues occurring more than 4 weeks after onset of initial infection. 9 Estimates of PCC incidence vary widely, with published reports estimating that between 10% and 25% of symptomatic patients experience symptoms persisting beyond the acute phase of illness. 10 A diagnosis of PCC is based on symptoms including fatigue, cough, pain (joint, throat, chest), loss of taste or smell, shortness of breath, thromboembolic conditions, neurocognitive difficulties, and depression. 9

There are limitations to the initial studies assessing PCC rates and outcomes. Estimates were often based on hospitalized patients who had a higher severity of illness. 11 - 15 Many reports were based on patient surveys that did not include comparison groups of similar individuals. Follow-up on individuals with milder cases has been difficult, given that individuals often self-manage. In addition, early reports were often research letters or field reports not subject to peer review. 16 , 17 Finally, individuals at risk for PCC tend to have higher baseline risks due to preexisting conditions, resulting in selection bias for the exposure cohort. 18 - 20

Subsequent to initial reports, additional work on PCC has been published, providing a more rigorous assessment of patient experiences. For example, a large panel survey study of symptomatic individuals with a matched control group showed that nearly half of respondents experienced lingering symptoms, most commonly fatigue, headache, and muscle weakness, even after 12 months. 21 Other studies of PCC focused on neurological manifestations, depression, and anxiety. 22 , 23

This cohort study provides a 12-month assessment of adverse outcomes for a cohort of individuals with PCC compared with a propensity-matched comparison group with similar baseline risks. The study provides a comprehensive view of individuals with and without initial hospitalizations. By leveraging a large health insurance claims database, we ascertained health status before the initial COVID-19 diagnosis, including assessment of baseline characteristics such as hypertension, obesity, depression, and chronic obstructive pulmonary disease (COPD). By using medical claims and socioeconomic variables, this study is unique in providing a comprehensive follow-up for a nationally representative sample. The findings will be useful in informing care coordination efforts for individuals with PCC, especially with respect to careful monitoring for cardiovascular and pulmonary risks after the period of acute infection.

We analyzed administrative claims and laboratory results from the HealthCore Integrated Research Environment, which contains medical, pharmacy, and laboratory data from 14 commercial health plans with members who reside in all 50 US states and the District of Columbia. This study was conducted in compliance with relevant provisions of the Health Insurance Portability and Accountability Act. Only deidentified data were used, and the study was determined to be exempt from review by the WCG Institutional Review Board. The Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) reporting guidelines were followed. 24

The PCC cohort was drawn from an initial pool of 249 013 individuals 18 years and older who were diagnosed with COVID-19 between April 1, 2020, and July 31, 2020. 22 , 23 Patients were included if they had a medical claim with an International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) diagnosis code for COVID-19 (U071, B342, B9721, B9729, J1281) or a laboratory-confirmed positive COVID-19 test. The first observed diagnosis or positive test date was set as the index date. Individuals were required to have 6 months of continuous enrollment prior to the index date and to have survived at least 30 days following their diagnosis date. An index month was set by adding 30 days to the COVID-19 diagnosis date. Continuous enrollment was not required beyond the initial 30 days, as mortality was included as an outcome measure. Characteristics of the full COVID-19 cohort vs PCC cohort are summarized in eTable 1 in Supplement 1 .

A claims-based definition for PCC was constructed based on symptoms drawn from Centers for Disease Control and Prevention publications and other peer-reviewed publications. 3 - 6 , 9 Individuals in the PCC cohort received 3 or more diagnoses for COVID-19 or COVID-19 symptoms across more than 1 visit during weeks 5 to 12 after their index date, inclusive of telehealth visits (see eTable 2 in Supplement 1 for ICD-10 codes used in the definition). In 2021, several ICD-10 codes were issued to capture PCC (M35.81, U09.9) 25 ; however, they were not available during the time period used for defining the cohort. From the initial pool of individuals confirmed positive for COVID-19, 14 086 (6.8%) were identified as having PCC and meeting cohort inclusion criteria ( Figure 1 ).

The pre–COVID-19 health care utilization for the PCC cohort was used to create a matched cohort of individuals without COVID-19 (non–COVID-19 [NC]), allowing calculation of actual vs expected rates for postindex outcomes. An initial pool of potential control group members consisted of individuals without evidence of COVID-19 in claims or laboratory data between November 2019 and June 2021, a time period that predates widespread availability of home tests. Each potential control group member was assigned an index month in proportion to the distribution of dates for the PCC cohort, ensuring factors such as seasonality would be consistent between cohorts. The distribution by month is summarized in eTable 3 in Supplement 1 . Once eligibility criteria were applied consistent with the PCC cohort, a pool of 1 998 156 individuals with no evidence of COVID-19 were available for matching ( Figure 1 ).

A 1:2 propensity score match was performed using multivariate logistic regression. Matching variables included baseline characteristics of age, sex, region, neighborhood-based social determinants of health (race and ethnicity, education, socioeconomic status), Elixhauser Comorbidity Index score, 26 comorbid conditions, index month, and 6-month baseline health care utilization and costs. Socioeconomic status quartiles were created using a composite score generated from 7 variables from the 2018 American Community Survey available at the census block group level, matching to member address. 27 We used log-transformed cost values in propensity score matching to normalize cost data. The cohorts were selected using a greedy algorithm to ensure baseline comparability after matching. Propensity score balance checks were performed, and these results are included in the eFigure in Supplement 1 . Due to the large comparison group available, 95% of the PCC cohort matched to the NC cohort, resulting in a final sample of 13 485 individuals with PCC and 26 870 individuals without COVID-19. Table 1 summarizes characteristics used for matching.

The outcomes were selected based on internal health plan analysis during the first year of the pandemic, when it became apparent that there was a high rate of cardiovascular-related utilization observed among health plan members diagnosed with COVID-19. This coincided with case reports but predated other published work in the area. Outcomes of interest included claims-based utilization tied to cardiovascular disorders (heart failure, cardiac arrhythmias, peripheral artery disease, pulmonary embolism/deep vein thrombosis, coronary artery disease, and stroke), as well as chronic respiratory disorders (chronic obstructive lung disorders [eg, COPD] and asthma) and mortality. All clinical outcomes were ascertained using ICD-10 codes, with additional utilization information such as hospitalizations identified via claims. The Social Security Administration’s Death Master File and Datavant Flatiron data files were used to capture mortality that may have occurred after any health plan disenrollment. In setting the study measurement period, 12-month outcomes were assessed according to each individual index date (falling between April 1, 2020, and July 31, 2020), with study follow-up ending July 31, 2021.

All variables were summarized using descriptive statistics, with mean, SD, and median for continuous data, and frequencies and proportions for categorical data. All outcome measures were assessed using t tests for continuous data and Pearson χ 2 tests for categorical data. Relative risks (RRs) with 95% CIs were calculated for binary outcomes. Statistical significance was set at a 2-sided P  = .05. The mortality analysis was carried out using Kaplan-Meier survival estimates to get mortality percentages for each month. Variables were created using the Instant Health Data platform (Panalgo). Statistical analyses were performed using SAS Enterprise Guide, version 8.3 (SAS Institute).

Many initial PCC studies reported outcomes for individuals who had an initial hospitalization. To compare results with prior studies, we performed a subset analysis for 3697 individuals with hospitalizations in the first month after COVID-19 diagnosis compared with the matched NC cohort.

The study sample included 13 435 adults with PCC and 26 870 matched adults without COVID-19. The mean (SD) age for the PCC cohort was 50.1 (15.1) years, with 58.7% female. The PCC cohort included individuals from across the US, with representation from the Northeast (31.9%), South (30.5%), Midwest (14.1%), and West (23.5%). In the sample, 33.7% of the individuals were in the least disadvantaged socioeconomic status quartile, and 20.4% were in the most disadvantaged socioeconomic status quartile.

The PCC cohort had a relatively high level of chronic conditions before developing COVID-19, with the following conditions commonly observed: hypertension (39.2%), depression (23.7%), diabetes (20.5%), COPD (19.1%), asthma (13.3%), and severe obesity, defined as body mass index (calculated as weight in kilograms divided by height in meters squared) of 40 or higher (10.3%). The mean (SD) Elixhauser Comorbidity Index score for the cohort was 2.4 (2.7), with 52.0% of the cohort having 2 or more preindex comorbidities. The PCC cohort experienced average health care costs of $2093 per month in the preindex period.

The propensity-matched NC cohort had similar rates and costs for all metrics during the preindex period. The standardized mean difference for all characteristics of the propensity-matched cohorts was below 0.10 ( Table 1 ).

The most common symptoms observed during follow-up for the PCC cohort included shortness of breath (41%), anxiety (31%), muscle aches/weakness (30%), depression (25%), and fatigue (21%). See eTable 4 in Supplement 1 for a full distribution of post–COVID-19 symptoms for the PCC cohort.

There was a consistent elevation in adverse outcomes in the PCC cohort relative to the NC cohort ( Table 2 ). During the follow-up period, the PCC cohort, compared with the NC cohort, experienced increased health care utilization for cardiac arrhythmias (postperiod rate, 29.4% vs 12.5%), with an increase in RR of 2.35 (95% CI, 2.26-2.45); pulmonary embolism (postperiod rate, 8.0% vs 2.2%), with an increase in RR of 3.64 (95% CI, 3.23-3.92); ischemic stroke (postperiod rate, 3.9% vs 1.8%), with an increase in RR of 2.17 (95% CI, 1.98-2.52); coronary artery disease (postperiod rate, 17.1% vs 9.6%), with an increase in RR of 1.78 (95% CI, 1.70-1.88); heart failure (postperiod rate, 11.8% vs 6.0%), with an increase in RR of 1.97 (95% CI, 1.85-2.10); COPD (postperiod rate, 32.0% vs 16.5%), with an increase in RR of 1.94 (95% CI, 1.88-2.00); and asthma (postperiod rate, 24.2% vs 12.4%), with an increase in RR of 1.95 (95% CI, 1.86-2.03). With regard to mortality, 2.8% of the PCC cohort vs 1.2% of the NC cohort died during the follow-up period. This difference implies an excess death rate of 16.4 per 1000 individuals ( Figure 2 ).

Within the PCC cohort, 27.5% of individuals (n = 3697) experienced hospitalizations in the first month. The mean (SD) age for the hospitalized subset of the PCC cohort was 57.4 (13.6) years, 6 years older than the overall PCC cohort, and 55.2% female. This hospitalized subset of patients had higher levels of chronic conditions before developing COVID-19 relative to the overall PCC cohort, including hypertension (54.1%), type 2 diabetes (30.7%), COPD (22.2%), asthma (15.6%), and severe obesity (14.7%). By contrast, this hospitalized subset had lower levels of depression (16.1%). The mean (SD) Elixhauser Comorbidity Index score for the cohort was 3.2 (3.2), with 61.9% of the cohort having 2 or more comorbidities in the preindex period ( Table 1 ). In the preindex period, the hospitalized PCC subset experienced mean health care costs of $2792 per month; 15.5% of the cohort experienced an inpatient stay during the preindex period. The matched NC cohort had similar rates and costs for all metrics during the preindex period compared with the hospitalized PCC cohort ( Table 1 ).

The hospitalized subset experienced higher rates of adverse outcomes relative to the NC cohort ( Table 2 ). During the follow-up period, the hospitalized PCC cohort, compared with the NC cohort, experienced increased health care utilization for cardiac arrhythmias (postperiod rate, 51.7% vs 17.4%), with an increase in RR of 2.97 (95% CI, 2.81-3.16); pulmonary embolism (postperiod rate, 19.3% vs 3.1%), with an increase in RR of 6.23 (95% CI, 5.36-7.15); ischemic stroke (postperiod rate, 8.3% vs 2.7%), with an increase in RR of 3.07 (95% CI, 2.59-3.66); coronary artery disease (postperiod rate, 28.9% vs 14.5%), with an increase in RR of 1.99 (95% CI, 1.85-2.15); heart failure (postperiod rate, 25.6% vs 10.1%), with an increase in RR of 2.53 (95% CI, 2.32-2.76); COPD (postperiod rate, 43.1% vs 19.2%), with an increase in RR of 2.24 (95% CI, 2.11-2.38); and asthma (postperiod rate, 31.6% vs 14.7%), with an increase in RR of 2.15 (95% CI, 2.00-2.31).

There has been considerable attention devoted to issues facing individuals with PCC. This study provides new insights into risks for adverse outcomes in individuals with PCC after accounting for higher levels of pre–COVID-19 disease burden. Based on published literature, the most common symptoms experienced by individuals with PCC include fatigue, headache, and attention disorder. 6 While these symptoms are concerning, results from this study also indicated a statistically significant increased risk for a range of cardiovascular conditions as well as mortality. While these risks were heightened for individuals who experienced a more severe acute episode of COVID-19 (ie, requiring hospitalization), it is essential to note that most individuals (72.5%) in the cohort did not experience hospitalization during the acute phase. Many of these conditions will have lasting effects on quality of life.

Several studies have found increased risks of cardiovascular disease 28 - 30 among people post–COVID-19, looking at cohorts with varying degrees of severity of illness. For example, an American Heart Association study of patients with COVID-19 treated in the emergency department or hospitalized found that 1.3% of patients (103 of 8163) developed acute ischemic stroke during their hospital stay. 31

A European study of 2292 individuals presenting at the emergency department with mild to moderate COVID-19 found increased thrombosis risk in the subsequent 28 days: a rate of 2.3% in the presence of moderate COVID-19 and 0.6% for individuals with mild COVID-19. After adjusting for comorbid conditions, patients in the moderate cohort had an absolute increase in risk for thrombosis of 1.69%. 32

While these studies inform risk in the immediate aftermath of acute illness (eg, within 30 days), fewer studies address long-term event outcomes. A 2022 study of outcomes among 153 760 patients from the US Department of Veterans Affairs national health care database who were followed up for 12 months after COVID-19 infection compared with a control group with no evidence of COVID-19 found substantial cardiovascular burden in the following year, including increased risk of stroke (hazard ratio [HR], 1.52), ischemic heart disease (HR, 1.75), and thromboembolic disorders (HR, 2.93). 33 The Veterans Affairs population included all levels of illness severity as opposed to a focus on individuals with PCC. Consequently, while risk of increased cardiovascular events increased among all COVID-19 survivors, the present study highlights the greater risks for individuals experiencing PCC.

Prior studies have found increases in 1-year mortality among individuals who were initially hospitalized. 34 , 35 A study using electronic health record data showed that 12-month adjusted all-cause mortality was statistically significantly higher for patients who presented with severe COVID-19 compared with individuals who had not had COVID-19 (HR, 2.50). Another study of US Veterans Health Administration data showed that beyond the first 30 days of illness, individuals with COVID-19 had increased risk of mortality (HR of 1.59, and an adjusted excess burden of death estimated at 8.39 cases per 1000 patients at 6 months) compared with a matched cohort of individuals who had not had COVID-19. 36 In contrast, the present study revealed numbers substantially higher than earlier reports for several reasons: a focus on PCC, the ability to evaluate data comprehensively across all care settings, comprehensive mortality information, and a 12-month follow-up period.

This study focused on cardiovascular, pulmonary, and mortality outcomes as the events that could be well captured from administrative data sources. As the number of PCC cases grows, it is essential to learn more about this subset of patients with COVID-19 for several reasons. Gaining additional insight into the risks and trajectory of the disease is essential for clinicians caring for these individuals, especially a need for primary prevention for individuals at higher risk. At a health-systems level, it is also necessary to develop resources and guidance for individuals at risk for serious complications. For example, following the dissemination of early results within Elevance Health, Inc, a care management program was developed and deployed to individuals identified as being at risk for PCC.

From a health policy perspective, these results also indicate a meaningful effect on future health care utilization, and even potential implications for labor force participation. Gaining knowledge on the scope and trajectory of PCC is relevant for policy makers, given the recent guidance by the US Department of Health and Human Services that classifies “long COVID” as a disability if it substantially limits major life activities. 37

There are several limitations in undertaking a claims-based evaluation for a condition where individuals experience a wide range of symptoms, many of which are less likely to be captured in claims data (eg, fatigue, ageusia). Because claims data provide information on people who receive care, the PCC cohort evaluated in this study excluded people who experienced symptoms but were self-managing. Second, the definition of PCC used in this study is more stringent and represents a higher severity population compared with studies using survey data. This would imply a higher incidence of adverse outcomes compared with a broader definition. However, research using broad definitions of PCC may underestimate the consequences for high-risk populations. A third limitation lies in the generalizability of findings, given that the outcomes are for individuals first experiencing COVID-19 in 2020. The time period for identification of members in the study predates the availability of vaccines. Following the availability of vaccines, individuals may have had different health care utilization patterns, due to potential mitigating effects of vaccines on PCC. Given the widespread nature of COVID-19, there may be concerns with the extent to which the control group also had COVID-19 exposures. However, the study period predated the widespread availability of home tests, lending more confidence in the creation of the control group. In the event that individuals in the control group had COVID-19 exposure, this would bias the results toward a null finding. Changes to the virus over time may affect outcomes for individuals. It would be helpful to repeat this evaluation on future cohorts to determine whether patterns remain consistent. We could not capture outcomes for individuals in either the PCC or control cohort who disenrolled from a health plan for reasons other than death. To the extent that individuals disenrolled for health-related reasons (eg, leaving employment), severe outcomes may be underestimated. To account for potential bias, we carried out a sensitivity analysis to assess outcomes for individuals with continuous enrollment and observed consistent risk differences for that cohort as well (eTable 5 in Supplement 1 ). Finally, this study focused on a commercially insured population, and future efforts should focus on individuals with Medicaid or other coverage to account for influence of access to care.

In this cohort study of 13 435 US adults with PCC and 26 870 matched adults without COVID-19, individuals with PCC experienced elevated rates of adverse health events and mortality over the 12-month follow-up period, after accounting for risk factors present pre–COVID-19. To our knowledge, this analysis is the largest national study of commercially insured individuals with PCC including a full year of follow-up. Assessing ongoing needs of this population will be crucial, especially as it relates to the onset of new chronic conditions following the initial illness. These findings will improve understanding of care needed for individuals with PCC, as well as inform health care systems directing resources toward surveillance, follow-up, and case management to this population.

Accepted for Publication: December 22, 2022.

Published: March 3, 2023. doi:10.1001/jamahealthforum.2023.0010

Correction: This article was corrected on July 28, 2023, to change the study type throughout the article from a case-control study to a cohort study.

Open Access: This is an open access article distributed under the terms of the CC-BY-NC-ND License . © 2023 DeVries A et al. JAMA Health Forum .

Corresponding Author: Andrea DeVries, PhD, Elevance Health, Inc, 220 Virginia Ave, Indianapolis, IN 46204 ( [email protected] ).

Author Contributions: Dr DeVries and Ms Shambhu had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: All authors.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: DeVries, Shambhu, Sloop.

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

Statistical analysis: Shambhu, Sloop.

Obtained funding: DeVries.

Administrative, technical, or material support: All authors.

Supervision: DeVries.

Conflict of Interest Disclosures: None reported.

Funding/Support: This work was supported using resources and facilities of Elevance Health, Inc.

Role of the Funder/Sponsor: Elevance, Inc, employees were responsible for the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: This content is solely the responsibility of the authors and does not necessarily represent the official views of Elevance, Inc.

Data Sharing Statement: See Supplement 2 .

Additional Contributions: We thank Eugene Hsu, MD, MBA, of Elevance Health, Inc, for his clinical input in the development of the manuscript. He did not receive additional compensation beyond his salary for these contributions.

Case Study 1.12 Providers/Roles/Documentation (10 points) CAHIIM Standard

1. Classify the providers for each stage of the patient’s care noted above and outline their responsibilities. 2. Explain the documentation that each provider will be creating as part of the patient’s record.

• PCP (Primary Care Physician) – The responsibility of PCP in this case was to give the woman a chest x-ray and refer her to a pathologist for biopsy.
• Pathologist – Analyzes tissue samples removed during a biopsy. The pathologist gives the woman the diagnosis of cancer and then performs a right lower leboctomy.
• Infectious disease specialist-Deals with the control and treatment of infections, evaluating the woman and recommending appropriate course.
• Caregiver-Takes care of elderly who can’t/struggle with doing for themselves and helps take care of them, taking care of the women for two weeks.
• Radiologist-A doctor who specializes in diagnosing and treating disease and injury by use of radiology techniques and in this case, he initiated the radiotherapy.
• Palliative care-Specialized medical care for people living with a serious illness. The woman decided to only receive this type of care.
• Explain the documentation that each provider will be creating as part of the patient’s record. Each provider will be creating and providing the patient’s demographics, vital signs, diagnoses, medications, treatment plans, progress notes, problems, immunization dates, allergies, radiology images, and laboratory and test results. However, there are specific documentation that would be needed for each provider and these are as noted below:
• PCP-Physician’s orders for xray and biopsy: A biopsy is a sample of tissue taken from the body in order to examine it more closely. A doctor should recommend a biopsy when an initial test suggests an area of tissue in the body isn’t normal. In the above case, the PCP has to fill an order form for biopsy and xray indicating where specifically will the procedure be focused on.
• Physician –  Operative report, lab report, discharge summary Infectious disease spet-Care plan: An Operative report is a report written in a patient’s medical record to document the details of a surgery. A discharge summary is a clinical report prepared by a health professional at the conclusion of a hospital stay or series of treatments.  The care plan should should include goals, treatment types and specific measures for outcome.
• Home care provider- progress note: The progress note Progress notes should clearly denote the care rendered and how it relates to the patient’s plan of care

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• Published: 16 November 2023

Interrater agreement of multi-professional case review as reference standard for specialist palliative care need: a mixed-methods study

• Evelyn Müller 1 ,
• Michael Josef Müller 1 ,
• Katharina Seibel 1 ,
• Christopher Boehlke 2 ,
• Henning Schäfer 3 ,
• Carsten Klein 4 ,
• Maria Heckel 4 ,
• Steffen T. Simon 5 &
• Gerhild Becker 1  

BMC Palliative Care volume  22 , Article number:  181 ( 2023 ) Cite this article

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A wide variety of screening tools for the need for specialist palliative care (SPC) have been proposed for the use in oncology. However, as there is no established reference standard for SPC need to compare their results with, their sensitivity and specificity have not yet been determined. The aim of the study was to explore whether SPC need assessment by means of multi-professional case review has sufficient interrater agreement to be employed as a reference standard.

Comprehensive case descriptions were prepared for 20 inpatients with advanced oncologic disease at the University Hospital Freiburg (Germany). All cases were presented to the palliative care teams of three different hospitals in independent, multi-professional case review sessions. The teams assessed whether patients had support needs in nine categories and subsequently concluded SPC need (yes / no). Interrater agreement regarding SPC need was determined by calculating Fleiss’ Kappa.

In 17 out of 20 cases the three teams agreed regarding their appraisal of SPC need (substantial interrater agreement: Fleiss’ Kappa κ = 0.80 (95% CI: 0.55–1.0; p  < 0.001)). The number of support needs was significantly lower for patients who all teams agreed had no SPC need than for those with agreed SPC need.

Conclusions

The proposed expert case review process shows sufficient reliability to be used as a reference standard. Key elements of the case review process (e.g. clear definition of SPC need, standardized review of the patients’ support needs) and possible modifications to simplify the process are discussed.

Trial registration

German Clinical Trials Register, DRKS00021686, registered 17.12.2020.

Peer Review reports

The issue of identifying patients in need of specialist palliative care (SPC) in oncology has occupied experts for more than a decade [ 1 , 2 , 3 ], and the widespread introduction of screening for SPC need is currently being sought [ 4 , 5 ]. Accordingly, a wide variety of screening tools have been proposed: Some are generic [ 6 , 7 ], while others are indication- [ 1 , 3 , 8 , 9 ] or entity-specific [ 10 , 11 , 12 , 13 ]. The majority of the tools require assessment of criteria by staff [ 1 , 3 , 8 , 9 ]; some authors suggest the use of patient-reported outcome measures [ 14 , 15 ]. The proposed screening tools include a wide variety of criteria: disease-, treatment- and care-related aspects, as well as patient and family needs [ 2 , 3 , 8 , 9 , 16 ]. Although all these tools have very similar objectives, the suggested criteria for determining SPC need differ considerably among them.

In practice, the question arises as to which of the proposed screening tools should be employed. Which assessment best identifies patients with SPC need (sensitivity) and at the same time sorts out those who do not need SPC as reliably as possible (specificity)? Determining sensitivity and specificity requires a reference standard against which the results of the screening tool can be compared. A reference standard is defined as the best available method for determining the presence or absence of the target condition; it differs from a gold standard which is error-free [ 17 ]. To our knowledge, no validated reference standard has yet been suggested for determining the need for SPC in oncology patients [ 16 , 18 ]. In its absence, individual screening instruments have been shown to correlate with various parameters, such as SPC referral [ 9 , 19 ], mortality / prognosis [ 2 , 6 , 16 , 19 , 20 ] and patient need questionnaires [ 19 ]. But do these parameters accurately and reliably reflect SPC need?

SPC referral and reception are closely related to SPC need. Unfortunately, in current practice, it cannot be assumed that patients reliably receive SPC when they need it. Oncologists’ views, awareness and knowledge of SPC [ 21 , 22 , 23 ], resources and patient wishes, for example, can all influence SPC referral [ 24 ], making it a very imprecise measure of actual SPC need.

Mortality and prognosis (e.g. surprise question) can be easily measured [ 25 ]. They are employed in validation studies of screening tools for SPC need based on the concept of early integration of palliative care (PC) [ 2 , 15 ]. Early integration is typically defined as referral to palliative care within 2–3 months of diagnosis of advanced disease in cancer patients, as symptom burden increases on average as death approaches [ 26 , 27 , 28 , 29 ]. Due to limited resources in SPC and data suggesting that SPC mainly benefits patients with pre-identified support needs but not those without support needs [ 30 ], the concept of timely integration of SPC was introduced. Timely integration shifts the focus away from disease progression and aims “to identify patients with high support care needs and to refer these individuals to specialist palliative care in a timely manner” [ 4 ]. If the aim is to identify patients for timely integration, prognosis and mortality surely correlate with SPC need but are not a suitable sole reference standard.

Patient reported outcome measures like the Integrated Palliative Outcome Scale (IPOS) [ 31 ] or Edmonton Symptom Assessment System (ESAS) [ 32 ] cover a broad and relevant range of patient needs and thus reflect the idea of needs-based, timely integration well. IPOS has been employed for validation of the screening of criteria proposed by the National Comprehensive Cancer Network (NCCN) [ 19 ]. Conversely, both IPOS and ESAS have been proposed as screening tools for SPC need, including initial suggestions for cut-offs [ 14 , 15 ]. However, to our knowledge, it has never been confirmed that the questionnaires themselves reflect SPC need, and the proposed cut-offs have also not been sufficiently validated.

When there is no gold standard, clinical expertise is frequently used as a reference standard [ 33 ]. We are aware of two recently published studies that employed clinical expertise as the reference standard for SPC need assessment: Teike Lüthi et al. (2021) asked a PC team of physician and nurse to determine SPC need [ 34 ], Effendy et al. (2022) used independent assessments made by the treating oncology physician and nurse [ 35 ]. Neither of the studies report interrater agreement of the reference standard.

The reported study is a pre-study to validate the reference standard in the context of the ScreeningPall study, which aims to develop easy-to-use screening criteria for SPC need (study protocol see [ 36 ]).

The aim of this pre-study was to explore whether SPC need assessment by means of multi-professional case review has sufficient interrater agreement to be employed as a reference standard. Additionally, we assessed the challenges in its use as a reference standard for SPC need.

Study design

The pre-study was designed as a mixed-methods study, data were collected between 08/2021 and 11/2022. It combines a reliability study, in which three PC teams independently assessed the same 20 patients with metastatic or locally advanced incurable cancer in structured multi-professional case reviews regarding SPC need, with a qualitative analysis of case review transcripts to identify challenges.

Definition of SPC need

In our study, we employ a definition of SPC need that is aligned with the requirements of the German health system. The question in case review is (translated from German): ‘Due to the needs of the patient and the relatives, is there currently a challenging situation with complex symptoms (physical, psychological, social or spiritual) that requires specialist palliative care? Specialist palliative care is characterized by practitioners with specific palliative care qualifications and experience, a multi-professional team approach and 24 h availability’ (based on the German S3-Guideline [ 13 ]). The teams were asked to focus on the current presence of SPC need and to assess it independently of the service that would carry out the SPC (e.g. consultation service, outpatient service). There also was a lower-level option of an ‘advisory session to inform the patient about possibilities and accessibility of specialised palliative care’, which could be chosen e.g. in cases of possible future need. It did not count as ‘SPC need’.

The pre-study was conducted at the University Medical Center Freiburg in Germany, a tertiary care centre with a Comprehensive Cancer Center. Patients were recruited in inpatient radiotherapy. The two cooperating PC teams from Erlangen and Cologne are also located at large university hospitals with Comprehensive Cancer Centers in Germany.

Patient sample

Inclusion criteria for patients were metastatic or locally advanced, incurable cancer with low probability of long-term control of the disease (estimated survival < 2 years) as assessed by the treating physician, ≥ 18 years of age and informed consent by patient or proxy. Patients with malignant haematological diseases as their main oncological diagnosis were excluded. We aimed to include 20 case descriptions for case reviews with approximately equal numbers of patients with and without SPC need for determination of interrater agreement. The sample size was based on a pragmatic decision, 20 cases was the maximum number for which the effort was still considered feasible for the external teams. Patient recruitment was to be terminated when 10 patients had been assessed as having SPC need by the Freiburg team. Due to recruitment of a higher number of patients without SPC need than with SPC need, we selected patients without SPC need with the aim of obtaining a heterogeneous sample regarding tumour entity, age and gender.

Case descriptions were based on information from routine documentation and standardized medical history taking by a physician and / or nurse from the PC team during a bedside visit (for details see Additional file 1 ).

Multi-professional case review

Each case was discussed by the three PC teams from Freiburg (internal team), Erlangen and Cologne university hospitals (external teams), without them knowing the results from the other PC teams. PC teams consisted of at least one physician, one nurse, one social worker or case manager, and one psychologist or pastoral worker (four different professional groups). An overview of the structured process of the multi-professional case review is presented in Fig.  1 . The case reviews were digitally recorded and transcribed verbatim; the outcome and observations on the process were documented in writing on site (for further information see Additional file 1 ).

Overview of case review process

Statistical and qualitative analysis

Fleiss' Kappa was calculated to test the interrater agreement on SPC need among the three teams [ 37 ], employing IBM SPSS 28 Software [ 38 ]. Descriptive statistics and the median test (alpha = 5%, two-sided) were used for an exploratory analysis of differences in support needs profiles among the three case groups ‘agreement SPC need’, ‘agreement no SPC need’ and ‘no agreement regarding SPC need’. There were no missing values.

For the cases in which the three teams did not agree regarding SPC need, a qualitative analysis [ 39 ] was conducted to identify possible factors that caused the differing conclusions. A team of four (social worker, social scientist, psychologist, nurse/medical documentarist; two members of the study team, two not involved) first read the transcripts line by line individually and annotated them, taking into account pragmatic, syntactic and semantic aspects. The team then developed a code system for possible influencing factors. This consisted of the nine predefined support needs categories and the SPC needs category (see Additional file 1 ), as well as the possible influencing factors identified in the team discussion: missing/additional information in the presentation of the patient cases, interruptions and interactions in the case presentation, and the roles of case presenter and facilitators (local senior physicians). Subsequently, the transcripts were coded, i.e. the texts were examined sequentially and the text passages were assigned to categories and discussed in the team. The results of the team discussions were recorded in case summaries and these were finally compared in a cross-evaluation with regard to the similarities and differences of the influencing factors.

History taking and case review took place for 32 patients before we reached 10 patients for whom the Freiburg team had concluded SPC need (criterion for recruitment termination). Two cases were excluded due to problems in medical history taking (e.g. focus on emotional support instead of medical history taking). Of the 30 remaining cases 20 were selected (for characteristics see Table 1 ): Of the 30 cases nine were assessed as having SPC need, 21 as having no SPC need by the internal team. All patients with SPC need were included with the aim of a well-balanced ratio of cases with and without SPC need. Of the 21 patients assessed as having no SPC need by the interal team, two were included due to special interest after controversial discussion in the internal team and nine based on the pre-defined criterion of heterogeneity regarding tumour entity, gender and age. There were no missing data on the relevant variables for the selected cases (for characteristics of excluded/non-selected cases, see Additional file  2 ).

Between four and nine professionals took part in case review sessions, with variations among teams. The composition of the Freiburg team changed weekly according to the duty rosters; in the external teams, there were two block appointments for 10 case reviews each and team compositions were consistent. In all case reviews, at least four different professional groups were represented.

Interrater agreement and assessment of SPC need in the three PC teams

In 17 of the 20 cases, there was agreement among the three PC teams on whether the patients currently had a need for SPC. This corresponds to an interrater agreement of Fleiss’ Kappa κ = 0.80 (95% CI: 0.55–1.0; p  < 0.001), which indicates substantial agreement [ 37 ]. The internal team identified SPC need in nine cases, the two external teams in ten and twelve. The agreement for individual cases is shown in Table 2 .

Support needs profiles and SPC need

Table 2 shows the support needs profiles. Explorative comparison of the needs profiles showed that patients for whom SPC need was identified by all three PC teams had a significantly higher number of support needs in their needs profiles than patients for whom SPC need was consistently not identified (see Table 3 ). In the three cases without agreement, the median number of support needs was higher than that of patients without SPC need and lower than that of those with SPC need (due to the small sample size, the median test was not informative).

Qualitative analysis of cases with no agreement on SPC need

Relevant different conclusions of the teams occurred in situations involving (Case A) the ambiguous patient statement “I mainly fight for my sons” by a widow with a currently effective therapy regime (see Fig.  2 ), (Case B) divergent assessment of whether the family and professional support system in place is capable of handling the situation of a man with a learning disability who cannot return home to live by himself and (Case C) anticipation of possible SPC need in the near future in a man currently with no relevant physical needs but a high need for psycho-spiritual and social work support (Cases B and C in Additional file 3 ). In Case A, a procedural aspect—a slip of the tongue during the case presentation—might have led to different levels of attention being paid to specific information. Additional file 4 summarises further observations on the case review procedure.

Qualitative analysis of Case A regarding decision making in case reviews on SPC need

We aimed to explore the use of the clinical expertise of multi-professional teams as a reference standard for SPC need. The substantial agreement among the three teams indicates reliability [ 37 ]; however, the confidence interval is still large due to the rather small sample. Further studies might contribute to a more precise estimation of interrater agreement.

The number of needs in the needs profile reflects the concept of timely integration of palliative care [ 4 ], where an increasing number of support needs in the course of the illness is associated with the timing of SPC integration. While cases with a high or low number of support needs are easy to agree upon regarding SPC need, the PC teams disagreed about three cases. Examples of case characteristics that led to patients being put into this group are unclear coping skills of the patient and/or support system, ambiguous statements of the patient and possible needs in the near future. For the reference standard, these are sources of error which are difficult to avoid.

Regarding the processes of SPC assessment, the following features should be considered for further development and use as a reference standard:

How should “SPC need” be defined in studies ? We assumed that a definition of SPC need that is clear and as close to everyday care as possible will be easier to assess and most useful for the subsequent validation of screening tools in our context. Therefore, our definition reflects what we would like to identify: patients who need the expertise and resources of SPC due to high support needs [ 13 ].

What information should the reference standard for SPC need be based on? Patients’ SPC need is determined by their current support needs, and whether they and their support system can cope [ 40 ]. In their study, Teike Lüthi et al. based their assessment on computer-based patient records alone or on patient records combined with palliative care liaison rounds [ 34 ]. The appropriateness of that approach depends on local completeness and the timelines of information in the records. In our study, medical history taking was necessary, as patient records did not contain sufficient information e.g. on the coping of patients and the support system.

Who should make the assessment of the reference standard for SPC need? Considering studies that show the impact of professionals' knowledge, experience and sensitisation in palliative care on the assessment of SPC need [ 21 , 22 , 23 ], we believe that experienced palliative care professionals should carry out the assessment as opposed to treating professionals. The approach of Teike Lüthi et al. involving assessment by dyads [ 34 ] instead of multi-professional teams is promising, especially combined with a holistic needs profile. As physicians and nurses in palliative care are usually attentive and sensitive to psycho-spiritual needs [ 41 , 42 ], the participation of psychologists and social workers might not be necessary.

Strengths of the study

To our knowledge our study is the first to show sufficient interrater agreement of expert opinion on SPC need and explore the prerequisites of the assessment processes. The suggested approach is not a gold standard but a reference standard, as the assessment cannot be free of error [ 17 ]. However, just like the surprise question for determining prognosis, it might be the best available option for the complex assessment of SPC need. The suggested procedure is transferable to other settings and healthcare systems, applicable and likely reliable.

Limitations of the study

Our results are based on data from only 20 patients. A larger patient sample would allow a more precise measurement of interrater agreement and further exploration of patient case characteristics and process features that might cause difficulties in the assessment of SPC need.

Case reviews were not strictly blinded as the senior physician at Freiburg presented the cases to the external expert teams. The background to that decision was a pre-test with Freiburg staff not involved in the study, in which the written case descriptions were prepared in advance (see Additional file 1 ). It became apparent that the high effort of working through the 20 case descriptions resulted in selective attention to certain information based on personal / professional priorities and in a game of predicting the team's answers in terms of SPC needs (and thus pre-judgment). Consequently, we preferred oral case presentation by a Freiburg team member, allowing for the exact same procedure as in Freiburg and the presence of a person with further in-depth information if needed. Guidelines for the senior physician stipulated that he would only speak during team review and assessment phases if asked for additional information on the case. In reality, however, non-verbal reactions cannot be fully ruled out and transcripts reveal minor deviations from the guideline to not speak, e.g. repeated discussion in one external team about the differences in radiotherapy use between the two hospitals, triggered by questions to the case presenter from the external senior physician.

Case selection was not random and the predefined rule of heterogeneity was not followed as strictly as it could have been. For example, the case C (no current physical but high psychological needs) was deliberately included after controversial discussion in the internal team—and the three teams did not agree on it. The use of real patient cases instead of constructed, controlled cases makes it possible to analyse the challenges of case reviews as reference standard. However, we cannot determine the influence of that selection on the interrater agreement.

The qualitative analysis is based only on the three cases where there was disagreement, as these contribute most to the understanding of pitfalls and the need for adaptation of our processes in future research.

The approach of medical history taking and structured, multi-professional case review shows sufficient interrater agreement to be employed as a reference standard for SPC needs in studies validating screening tools. However, further research is needed to confirm these results. For use in studies in other countries or care services, we recommend a review and possibly adaption to national and local requirements.

Availability of data and materials

The datasets generated and/or analysed during the current study are not publicly available due to ensuring data protection and anonymity for the patients, but are available from the corresponding author on reasonable request.

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Acknowledgements

We would like to thank all members of the PC teams of Freiburg, Erlangen und Cologne University Hospitals. Without their expertise, time and commitment, the study would not have been possible. We would also like to thank the directors, senior physicians and staff of the recruiting Department of Radiation Oncology. Last but not least we thank the patients, who contributed not only their time but were also open to disclosing their medical history and allowing us to report on it.

Open Access funding enabled and organized by Projekt DEAL. This work is supported by German Cancer Aid grant number 70114472.

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Department of Palliative Medicine, Medical Center – University of Freiburg, Faculty of Medicine, University of Freiburg, Robert-Koch-Straße 3, 79106, Freiburg, Germany

Evelyn Müller, Michael Josef Müller, Katharina Seibel & Gerhild Becker

Department of Palliative Care, University Hospital Basel, Petersgraben 4, 4031, Basel, Switzerland

Christopher Boehlke

Department of Radiation Oncology, Medical Center, Faculty of Medicine, University of Freiburg, German Cancer Consortium (DKTK) Partner Site Freiburg, German Cancer Research Center (DKFZ), Heidelberg, Robert-Koch-Straße 3, 79106, Freiburg, Germany

Henning Schäfer

Department of Palliative Medicine, University Hospital Erlangen-EMN, Comprehensive Cancer Center CCC Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg, Krankenhausstraße 12, 91054, Erlangen, Germany

Carsten Klein & Maria Heckel

Department of Palliative Medicine and Center for Integrated Oncology Aachen Bonn Cologne Dusseldorf (CIO ABCD), University Hospital of Cologne, Faculty of Medicine and University Hospital, Kerpener Str. 62, 50937, Cologne, Germany

Steffen T. Simon

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Contributions

MJM, CB and GB initiated the project. EM, MJM and GB are primarily responsible for the conception and design of the study and acquisition of funding. CB, HS, GB, CK, MH and STS provided valuable feedback in the conception process and thereby contributed to the study design. MJM and EM coordinated the study. CK, STS, HS, MH and MJM contributed in data collection. KS was responsible for qualitative analysis, EM for quantitative analysis. EM wrote the first draft of the manuscript. All authors read, revised and approved of the final manuscript.

Corresponding author

Correspondence to Evelyn Müller .

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Ethics approval and consent to participate.

The study was approved by the Ethics Committee of Albert-Ludwigs-University Freiburg, Germany (Approval No. 20–1103; 17/12/2020). All study participants (patients and PC team members) provided written informed consent before participation. All procedures are in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki Declaration and its later amendments.

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Informed consent has been obtained from patient or proxy.

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Supplementary Information

Additional file 1..

Development and Documentation of the Reference Standard. Detailed description of a process and documentation of medical history taking and case review as reference standard, including final versions of the used documents.

Additional file 2.

Characteristics of not selected patients. Characteristics of patients not selected for case reviews ( n =10) and excluded patients ( n =2).

Additional file 3.

Additional results of qualitative analysis. Additional results of qualitative analysis of cases with no agreement regarding SPC need assessment.

Additional file 4.

Observations on the case review procedure. Observations on the case review process, including effort of case reviewers, framework conditions, supportive needs profile, and oral case presentation.

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Comprehensive evaluation of community human settlement resilience and spatial characteristics based on the supply–demand mismatch between health activities and environment: a case study of downtown Shanghai, China

• Qikang Zhong 1 ,
• Yue Chen   ORCID: orcid.org/0000-0002-0132-4993 1 &
• Jiale Yan 2  

Globalization and Health volume  19 , Article number:  87 ( 2023 ) Cite this article

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Introduction

Under globalization, human settlement has become a major risk factor affecting life. The relationship between humans and the environment is crucial for improving community resilience and coping with globalization. This study focuses on the key contradictions of community development under globalization, exploring community resilience by analyzing the mismatch between residents' health activities and the environment.

Using data from Shanghai downtown, including land use, Sports app, geospatial and urban statistics, this paper constructs a comprehensive community resilience index (CRI) model based on the DPSIR model. This model enables quantitative analysis of the spatial and temporal distribution of Community Human Settlement Resilience (CR). Additionally, the paper uses geodetector and Origin software to analyze the coupling relationship between drivers and human settlement resilience.

i) The scores of CR showed a "slide-shaped" fluctuation difference situation; ii) The spatial pattern of CR showed a "pole-core agglomeration and radiation" type and a "ring-like agglomeration and radiation" type. iii) Distance to bus stops, average annual temperature, CO 2 emissions, building density and number of jogging trajectories are the dominant factors affecting the resilience level of community human settlement.

This paper contributes to the compilation of human settlement evaluation systems globally, offering insights into healthy community and city assessments worldwide. The findings can guide the creation of similar evaluation systems and provide valuable references for building healthy communities worldwide.

As a crucial setting for residents' daily activities, the community plays a vital role in promoting the concept of a healthy community in the era of globalization. Community human settlements are an integral part of the community system. It does not exist in isolation [ 1 , 2 ]. Globalization has profoundly influenced community human settlements in various ways. Urbanization has worsened the issue of inefficient land utilization and has led to significant environmental degradation in certain regions. Simultaneously, globalization has facilitated increased international resource flows and exchanges. This can lead to resource consumption, competition and a pronounced imbalance between environmental supply and demand. Additionally, heightened cultural and social interactions may give rise to cultural conflicts and social unrest. This has negative impacts on community human settlements and human health. These factors have tangible effects on human health activities. Challenges such as resource scarcity, environmental pollution, health risks, urbanization, and social development pose significant threats to the well-being of community residents. It has become an urgent challenge to meet the needs of community residents. Particularly in countries like the United States, China, and India, large population sizes, high population densities, and frequent social mobility have led to the hollowing out and impoverishment of certain industrial and manufacturing cities, exacerbating socioeconomic inequalities. Concurrently, rapid urbanization has resulted in the gradual disappearance of urban open spaces, deteriorating urban health, and causing serious physical and mental health issues among urban residents. This has significantly impacted the connection between people and places in communities, reducing the stability and adaptability of community human settlement systems [ 3 , 4 ]. Resilience, as an inherent property of systems, serves as a powerful means of maintaining stable operation and promoting sustainable system evolution. The varying levels of resilience observed in different communities directly reflect their ability to withstand diverse shocks and are closely tied to the well-being of their residents [ 7 , 8 , 9 ]. To address the influence of globalization on community human settlements and human health, various organizations worldwide have undertaken numerous policy initiatives. The United Nations Environment Programme (UNEP) advocates sustainable development and environmental protection to promote the sustainability of community human settlements. UN-Habitat aims to enhance the quality of the human environment in cities and communities while fostering sustainable development in the context of urbanization. Moreover, many countries have formulated policies and programs to promote the resilience and sustainability of community human settlements. Therefore, it is crucial to examine how to adapt to the risks of stress in a globalized environment and to address the tension between the health movement and environmental supply and demand. This will promote a symbiotic harmony between people and the environment and an increase in the level of resilience of community human settlements. At the same time, it will effectively improve the human settlements environment and human health.

In this context, researchers are increasingly focusing on CR [ 10 , 11 , 12 , 13 ]. Resilience refers to the ability of a system to maintain functional stability and adaptability in the face of shocks. Within the context of community human settlements, increased resilience can help communities effectively confront the challenges posed by globalization and safeguard the health and well-being of their residents. However, there are still certain limitations in current CR research. Firstly, the research scope has primarily concentrated on single natural ecosystems [ 14 , 15 , 16 , 17 , 18 ] and partially extended to relatively complex social-ecological systems [ 19 , 20 , 21 , 22 , 23 ]. Although these studies have emphasized optimizing and enhancing natural or social-ecological systems, they often overlook the interactions within their own internal mechanisms. Secondly, existing studies have predominantly focused on resilience concepts and indicators [ 24 , 25 ], comprehensive assessments [ 26 , 27 , 28 , 29 ], influencing factors [ 30 , 31 , 32 ], and application scopes [ 33 , 34 , 35 ], but lack in-depth exploration of the resilience formation mechanism. Furthermore, there is a wide range of resilience assessment methods, which have evolved from qualitative studies [ 36 , 37 , 38 ] to a combination of qualitative and quantitative approaches such as comprehensive index methods [ 39 , 40 ] and econometric methods [ 41 , 42 ]. Although these findings provide methods for deconstructing CR, they tend to neglect the comprehensive impact by focusing on specific aspects. There is a two-way mutual perturbation and adaptation between residents' health activities and the environmental economy. This has important implications for the study of community resilience and community human settlements [ 43 , 44 ].

In addition, improving community habitat is a priority task for achieving high-quality urban development. It can promote the sustainable development of community habitat systems and effectively alleviate the contradiction between people's aspirations for a better life and urban development [ 45 , 46 , 47 ]. Currently, domestic and international scholars have focused on the conceptual understanding of human settlements [ 46 , 48 ] from the perspectives of sustainable development [ 49 , 50 , 51 ], livability [ 1 , 52 , 53 ], and vulnerability [ 54 , 55 ]. They have employed various qualitative and quantitative methods, such as resident questionnaires [ 56 , 57 ], entropy value methods [ 47 , 58 ], GIS spatial analysis [ 50 , 59 ], coupled coordination degree models [ 60 , 61 ], and geodetector models [ 62 ], to study human settlements. These studies have explored urban human settlement systems, clarified the essence and components of human settlement systems, and identified their evolutionary trends.

In order to gain a deeper understanding of community resilience, this paper provides a comprehensive assessment of the community resilience index based on the DPSIR model from five perspectives. The paper further assesses the similarity and spatial variability of human community resilience through the spatial Moran index and ArcGIS. Finally, the paper uses a geodetector model to provide a comprehensive analysis of the factors that may have an impact on community resilience. Compared with existing articles, the innovations of this paper are as follows. First, the paper incorporates the conflict between health activities and the environment into the evaluation system of community resilience. This provides fresh insights into clarifying the meaning and formation mechanisms of community resilience. Second, the paper provides a new perspective and approach to community resilience governance in Shanghai by analyzing spatial differences and similarities. Thirdly, the paper analyses the mechanisms influencing community resilience from the perspectives of the natural environment, socioeconomics and human health. Finally, the paper provides certain strategic methods for the improvement of the resilience of different human communities. This paper provides scientific basis and practical guidance for community development and human health by constructing a sustainable and healthy community habitat system.

Data and methods

Overview of the study area

Shanghai is located in eastern China. It is an important economic, financial, trade, shipping, scientific, cultural and educational center. Shanghai is located in the harbour of the Yangtze River Delta region, which is an important link between China's inland and the sea. The geographical location is very important. As a cosmopolitan city, Shanghai has the world's largest container port and the second largest financial center. The famous Pudong Financial and Trade Zone and Waigaoqiao Free Trade Zone as well as China's only free trade zone are located here. Moreover, Shanghai is a globally popular tourist destination. In short, Shanghai is one of the most important cities in China. It not only has significant influence and development potential domestically, but also plays an increasingly critical role on the global stage. The pursuit of high quality has become a focal point of Shanghai's development, and the level of CR has become an important criterion for testing whether its development quality is high or not.

Geographically, Shanghai spans an area of 6,340.5 square kilometers and consists of 16 districts. To address the complexities of population density, urban dynamics, and health activity challenges, the paper focuses on seven central districts: Hongkou, Huangpu, Jing'an, Putuo, Xuhui, Yangpu, and Changning (as shown in Fig.  1 ). These districts were selected based on data accessibility and coverage, ensuring the study's reliability.

Data subjects and sources

The model used in this study combines data on residents' health activities, socioeconomics, ecological environment and urban geography. The data primarily originates from the Shanghai Statistical Yearbook, Shanghai regional statistical bulletins, and regional environmental status bulletins. Meteorological data is sourced from the China Air Quality Online Monitoring and Analysis Platform ( https://www.aqistudy.cn/ ).Geospatial data is obtained from the Resource and Environmental Science Data center ( http://www.resdc.cn/ ). To capture residents' health activity trajectories, this paper utilizes jogging data from the Dorray Sports APP (as shown in Fig.  2 ). All data was collected in 2018. In order to achieve a balance between computational efficiency and matching accuracy, the spatial analysis unit is set as a regular grid with a side length of 500 m. Data pre-processing includes collection, cleaning, coordinate decoding, projection conversion, and other procedures.

Data map of residents' jogging trajectories

DPSIR model and indicator system construction

Figure  3 represents the DPSIR model of the CR evaluation system. The DPSIR model represents: “Driving forces (D)”, “Pressure (P)”, “State (S)”, “Impact (I)”, “Responses (R)” five dimensions respectively. It is an optimization and development of the PSR and DSR models, which can analyze the intrinsic links between activity, economic, social and environmental factors from a systemic perspective.

CR evaluation system DPSIR model

This study introduces the DPSIR model to assess the resilience of community human settlements. The model uses five levels and twenty-five indicators (Table 1 ). Within this model, drivers (D) exert pressures (P) on the environment, leading to changes in environmental states (S). This further affects human activities and health (I). Community environments respond (R) by providing feedback on drivers, pressures, states, and impacts (R) to promote healthy city development.

Drawing on previous research and experimental requirements [ 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 ], this study identifies key indicators for each criterion level. Drivers (D) encompass dynamic elements driving resilience in community human settlements. Selected indicators include regional GDP, Regional GNP, population density, total imports and exports, DEM, and climate factors [ 63 , 64 ]. They reflect economic, population, and trade dynamics. These drivers influence pressure factors, state factors, and response factors, affecting residents' health activities and the environment.

Pressure (P) refers to elements stressing the resilience of community human settlements. Indicators include CO 2 emissions, PM2.5 emissions, amount of dust fall, and average daily volume of wet and dry waste. They reflect environmental pressures and pollution in the community [ 65 , 66 ]. These factors impact state and response factors, affecting air quality and residents' health activities [ 67 ].

State (S) represents the current conditions of the health activity environment influenced by drivers and pressures. Indicators such as building, road, bus stop and metro density, density of the water system, and land-use mix reflect environmental conditions and community features [ 68 , 69 , 70 ]. These factors are influenced by drivers and pressures and also impact other factors and responses. For example, high building and road density may lead to congestion and transportation issues. This will be detrimental to the residents' health activities [ 71 , 72 ].

Impact (I) refers to the outcomes of environmental elements on human health activities. Indicators like number of jogging trajectories and total jogging length reflect community resources for physical exercise [ 73 , 74 , 75 ]. These indicators directly affect residents' health activities. This is because more trajectories and longer lengths provide more opportunities for exercise and encourage resident participation [ 73 , 74 ].

Response (R) indicators capture human feedback on the natural, social, and built environment and their impact on health activities. Indicators such as NDVI, green space density, nighttime lighting, facility functional mix, distance from metro station, and distance to bus stops reflect residents' responses and preferences related to health activities [ 76 , 77 , 78 ].

Calculation method of human settlement resilience evaluation index

This paper uses a combination of subjective and objective weights. The hierarchical analysis method determines the subjective weights, while the entropy weight method determines the objective weights. Through the combination of these two methods, we can get the comprehensive weights. It can reflect the importance of evaluation indicators more comprehensively and accurately. After determining the weights of the indicators in the evaluation model, we used the evaluation index formula to calculate the evaluation index for each criterion layer. Subsequently, we use the corresponding formula to derive the evaluation index for the human settlements resilience. The specific calculation of indicator weights is as follows:

1) Standardization of indicator data. The following formula is used:

where \({x}_{ij}\) is the standardised value of the \(j\) th indicator for the \(i\) th evaluation sample.

2) Entropy weighting method to calculate indicator weights, the formula is:

where \({Y}_{ij}\) denotes the weight value of the \(j\) th indicator for the \(i\) th evaluation sample. \({e}_{j}\) denotes the information entropy value of the \(j\) th indicator; \({g}_{j}\) denotes the information entropy redundancy of the \(j\) th indicator. \({W}_{j}\) denotes the value of the weight coefficient of the \(j\) th indicator.

3) Hierarchical analysis method to calculate the indicator weights at the criterion level, the formula is:

where \({a}_{jn}\) denotes Criterion layer indicator data; \(B\) denotes the judgment matrix. \({M}_{j}\) is the geometric mean of the row vector elements of the judgment matrix; \(n\) denotes the number of indicators; \({Q}_{j}\) is the weight of the jth evaluation indicator; \({\uplambda }_{max}\) is the maximum characteristic root; \(CI\) is the consistency indicator; \(RI\) is the random consistency indicator.

4) Calculate the human settlement resilience evaluation index. The formula for calculating the weights is:

where U is the human settlement resilience evaluation index. Combined with the index setting of the DPSIR model. D denotes the driving force index and \({W}_{Dj}\) is the weight corresponding to the jth indicator under the D criterion layer and \({Z}_{Dj}\) is the standardised value of the \(j\) th indicator under the D criterion layer and \({W}_{D}\) is the weight corresponding to the D quasi-lateral layer; P, S, I and R index are set and calculated in the same way as the D index.

ArcGIS spatial analysis

In the analysis process, we used the natural break method with the help of ArcGIS software to classify the CR class types based on CRI (Table 2 ). This can show the spatial changes of CR index in downtown Shanghai more intuitively.

The study used two spatial autocorrelation statistics, Global Moran's I and Local Moran's I, in the testing phase. The purpose of the methodology is to analyze the overall spatial autocorrelation characteristics and the local spatial autocorrelation characteristics of the human settlements resilience of the region.

1) Calculate the global Moran index. Where \({G}_{0}=\sum_{i=1}^{n}\sum_{j=1}^{n}{w}_{ij}\) , n is the total number of spatial cells, the \({y}_{i}\) and \({y}_{j}\) denote the attribute values of the \(i\) th spatial unit and the \(j\) th spatial unit respectively and \(\overline{y}\) is the mean value of the attribute values of all spatial units and \({w}_{ij}\) is the average value of the attribute values of all spatial units, and is the spatial weight value. The calculation formula is:

Calculate the local Moran index. where \({F}_{i}={y}_{i}-\overline{y}\) , \({F}_{j}={y}_{j}-\overline{y}\) , \({G}^{2}=\frac{1}{\mathrm{n}}\sum {({y}_{j}-\overline{y})}^{2}\) , \({w}_{ij}\) are the spatial weight values, n is the total number of all regions on the study area and \({I}_{i}\) then represents the local Moran index for the ith region. The formula is calculated as:

Geodetector model

Geodetector represents a statistical model extensively employed in the fields of geography and environmental science. It is used to examine the effects of various geographical factors, such as landforms, soils, and climate, on a specific phenomenon, including vegetation distribution, species occurrence, and land-use changes. This model dissects the phenomenon into a combination of geographical elements and quantifies the impact of each element on the phenomenon, thereby unraveling the intricate interplay between geographical factors and the observed phenomenon. Based on the analysis of spatial variation of geographical layers, this study uses factor detector to analyze the influence of internal driving factor X of five criteria layers on Y, i.e. CR. Interaction detection is used to identify the relationship among the factors that affect the resilience level of community human settlement [ 79 , 80 ]. The model is as follows:

where: \(q\) is the influence of the influence factor on the resilience of community human settlement; \(h\) represents the stratification of factor X. \({N}_{h}\) and \(N\) represent the number of cells in stratum \(h\) and the whole area, respectively; \({\sigma }_{h}^{2}\) and \({\sigma }^{2}\) represent the variance of Y values in stratum \(h\) and the whole area, respectively. The value range of \(q\) is [0, 1], with larger values indicating stronger explanatory power of factor X on attribute Y and vice versa.

Condition of regional human settlement resilience level

Based on the resilience index, the paper ranks the resilience level of the human environment in each district in Shanghai (Table 3 ). Xuhui District obtained the highest resilience index score of 6.62, which is much higher than the other six districts. This indicates that its resilience quality is very high. Putuo District and Yangpu District followed closely with resilience index scores of 4.23 and 4.01. This indicates that those two districts also have a high quality of resilience. Changning District and Jing'an District obtained resilience index scores of 3.22 and 3.05, respectively, indicating a medium quality of resilience. Huangpu District has a low resilience index of 2.56 but has the potential to improve towards medium quality. Hongkou District had the lowest resilience index score of 1.52, indicating a very low quality of resilience. The resilience index of Hongkou District is significantly different from the other districts.

Regarding the spatial distribution (Fig.  4 ), the overall pattern in the basin displayed a central area with lower resilience levels and a peripheral area with higher resilience levels. Xuhui District stood out as relatively high in resilience, followed by Putuo District and Yangpu District.

Spatial distribution of regional-scale human settlement resilience level

Condition of CR level

Based on Fig. 5 , we rank the CRI of each district from highest to lowest. It was observed that Xuhui and Putuo districts exhibited a gradual decline in the CRI, with relatively smooth curves. The CRI for Yangpu District initially shows a sharp downward trend, followed by a more stable downward trend. It eventually fluctuates slightly after it reaches a certain level. The downward trend of CRI in Changning District is similar to that of Xuhui District, but with some irregular fluctuations at the bend. Jing'an District displayed a linear and consistent decline in the CRI. Huangpu District initially had an irregular curve, but later exhibited a linear and steady decline after surpassing a specific threshold. Hongkou District experienced a drastic and irregular decline in the CRI.

Analysis of community-scale human settlement resilience Level by district

Overall, Xuhui District displayed the highest level of community resilience compared to the other six districts. Putuo District, Yangpu District, Jing'an District, Huangpu District, and Changning District maintained a relatively consistent level of community resilience. They differ in that Changning District has a higher level of human settlements resilience. In contrast, Hongkou District had significantly lower community resilience compared to the other district. This suggests that effective measures need to be taken to improve the resilience of the district.

Condition of high human settlement resilience communities by district

To gain a better understanding of communities with high human settlement resilience in each district, this study compared the top ten communities in each district (as shown in Table 4 and Fig.  6 ). The analysis reveals that Changning District exhibits the highest level of community resilience among the seven districts, showcasing its superior performance. Xuhui District demonstrates an overall high and consistent level of community resilience. Yangpu District also has a high level of community resilience, but there are significant differences within its range. The highest index reaches 0.0997, while the tenth ranked community scores only 0. 0404.The difference between the two is 0.0593.

Comparison of high-quality CR Level

The CRI values for Huangpu and Putuo districts range from 0.3 to 0.6. The values are stable but not outstanding. Only three communities in the Hongkou district have CRI values around 0.05. Both Hongkou District and Jing'an District generally display low CRI levels, ranging from 0.2 to 0.4. However, the top ten communities in Jing'an District show a tendency towards consistent CRI values. This indicates a relatively equitable development of resilience levels in the district.

Spatial characteristics of human settlement resilience

Cr spatial autocorrelation.

Based on the CRI, this study implemented a global spatial autocorrelation analysis with the help of Space/Univariate Moran's I in Geoda software. The results show that Moran's I value is 0.281. This indicates that there is a significant positive spatial autocorrelation for CRI, which exhibits spatial clustering (Fig.  7 ).

Scatterplot of Moran's I index of CR level by district in Shanghai

To assess the local spatial aggregation and analyze the similarity and spatial divergence of human settlement resilience levels among neighboring community units, we used ArcGIS 10.2. As shown in Fig.  8 , we have mapped the evolution of the aggregation of human settlements resilience levels across regional communities. The Moran's I index LISA plot in the "High-High" (HH) and "Low-Low" (LL) quadrants indicate a strong positive spatial correlation of CR levels. This suggests a homogeneous and aggregated distribution pattern across regions. Conversely, the "High-Low" (HL) and "Low–High" (LH) quadrants represent areas with a strong negative spatial correlation. This suggests spatial heterogeneity and discrete distribution patterns of CR levels across regions during the study period. The distribution of communities across the HH, LL, HL, and LH quadrants can be observed in Fig.  8 . Communities are more concentrated in the HH and LL quadrants than in the HL and LH quadrants. Additionally, there is a notable regional concentration of overall CR levels. Communities in the LL quadrant are concentrated in the north, while those in the HH quadrant are located mainly in the south. Communities in the HL and LH quadrants are scattered around communities in the HH and LL quadrants. Overall, there is a clear spatial dependence between CR levels in each region. This indicates clustering characteristics with neighboring regions. Within the study area, fewer gathering areas are displaying a "high-low" polarization effect and a "low–high" transitional type at a significance level of 0.05.

LISA chart of Moran's I index of CR level by district in Shanghai

Spatially descriptive statistics of CR by district

Based on the research formula, we calculated the human settlements resilience index for each area and derived the CRI. We then classified the CRIs into five categories: very low quality zone, low quality zone, medium quality zone, high quality zone, and very high quality zone using the natural interruption point grading method. The classification and quantity of human settlement resilience are presented in Tables 5 and 6 , and the spatial distribution of the proportion of communities in different grades in the participating cities is illustrated in Fig.  9 .

Spatial distribution proportion of communities with different human settlement resilience level in Shanghai

Table 5 reveals that low quality areas have the highest proportion of CR evaluations, with a total of 340, accounting for 34.62% of the total. Very low quality areas follow with 331 evaluations, accounting for 33.71% of the total. Medium quality areas have 243 evaluations, accounting for 24.75% of the total. On the other hand, the number of very high quality and high quality zones is the smallest, with 58 and 10 zones respectively, accounting for only 5.91% and 1.02% of the total.

Table 6 and Fig.  9 provide insights into the composition of different levels of communities in the participating cities. There are obvious regional differences in the level of community building in Shanghai, with an overall distribution pattern of "northwest to southeast bulge". The distribution of the index and the number of communities exhibit similar patterns. Generally, the southeastern part of the city demonstrates higher CR levels compared to the northwestern part. Xuhui District and Changning District have the highest proportion of very high and high quality communities, accounting for 21.4% and 31% respectively, serving as the leading "twin cores" in the development of Shanghai's CR quality. Jing'an District lacks very high and high quality communities, indicating a low level of development and emphasizing the need to accelerate the construction of high-quality human settlement resilience communities. Yangpu District and Putuo District have the highest percentage of very low and low quality communities, with 78.8% and 74.5% respectively, indicating a majority of communities with low quality. The government should prioritize the development of resilient qualities in community human settlement and solve the problems of "Weak Communities" and " Fragile Communities". The government should also focus on transforming "backward communities" into "resilient communities" as soon as possible.

Spatial heterogeneity of CR

To visualize the spatial characteristics of the CR level in each region of Shanghai, we utilized ArcGIS 10.2 software to generate Figs.  10 and 11 . The figures illustrate the spatial distribution of the CR level and subsystem indices.

Comprehensive CR evaluation for spatial heterogeneity characteristics

CR evaluation for spatial heterogeneity characteristics of each system

Figure  10 reveals clear spatial differentiation characteristics of CR levels. Communities with very high human settlement resilience exhibit a "pole-core" spatial pattern, clustering around the central areas of the district and the vicinity of the Huangpu River. Core communities with medium and high human settlement resilience display an irregular open pattern, forming a "ring-like agglomeration and radiation" type. Resilience values are dispersed across most of the region. Resilient communities with middle and high-value human settlements are primarily concentrated in the central and southeastern parts of the old city. Conversely, northern, western, and southern communities demonstrate a balanced yet low level of resilience, showing a "flake-like agglomeration and radiation" spatial pattern. Overall, the central city mainly consists of low and medium resilience zones, with wider distribution. On the other hand, the peripheral areas are dominated by very low resilience zones, forming a semi-humped spatial pattern of "low inner circle, high middle circle and low outer circle".

Figure  11 displays the spatial distribution of the subsystems in the CRI model, indicating significant variation. The driving force index (D-system) shows a typical pyramidal spatial pattern. Higher values are found in the centre and lower values in the peripheral areas. The reason may be that Huangpu and Xuhui districts are the most economically developed areas in Shanghai. The development of enterprises not only increases the GDP of the region, but also attracts a large number of labors. The stress index (P-system) exhibits a patchy characteristic due to its dependence on district and county-level environmental pollution data. It displays a basin-type spatial pattern of "low in the center and high in the periphery," reflecting the overall seriousness of environmental pollution in the old city. The areas with high values of the stress index cover a wide area, up to three "red areas" and one "orange area ". The state index (S-system) generally maintains a low level of balanced distribution, with more high-value neighborhoods near the Huangpu River. The overall spatial pattern of "low in the west and high in the east" is formed. The reason for this may be the dense concentration of businesses and population along the river. This often requires more buildings and transport facilities. The impact index (I-system) showcases a "polar core" spatial pattern, with scattered high-value areas. Finally, the response index (R-system) appears as a "mosaic" type spatial pattern. The overall distribution is freely dispersed. But most of the high value areas are distributed in the west. The reason may be that the economic development level of this area is not so developed compared with Huangpu and Hongkou districts. There are more green spaces to be developed in the region.

Driver factors analysis of community resilience for human settlement

The paper first calculates the standard deviation of the normalized indicator values. Then we use the geodetector technique to examine and analyze the impact on the resilience of human settlements.

Factor detection analysis

This study employed the GIS-Jenks Natural Breaks Method to classify the original numerical quantities of the five variables, transforming them into categorical values based on the classification results. Then we introduced the CRI and categorical values into the respective dependent variable Y and independent variable X in the geographical detector to identify influential factors. A higher q-value indicates a stronger explanatory power of the independent variable X on the dependent variable Y.

The results in Table 7 demonstrate that R6 (distance from bus stops) holds the highest rank with a q-value of 0.292. It indicates that it is the most influential factor affecting the resilience of human settlements in the community. The proximity to public transportation reflects the infrastructure development of a city and represents an external response to its economic level. Therefore, future community development efforts should focus on enhancing public transport service facilities and innovations in transport technology.

D7 (average annual temperature) and P1 (CO 2 emissions) both hold a q-value of 0.12, securing the second rank. This suggests that both D7 and P1 significantly impact community human settlement resilience. Sustainable urban development depends on the development of clean energy. Governments should increase the recycling rate of energy, reduce carbon dioxide emissions and mitigate the greenhouse effect.

S1 (building density) acquires a q-value of 0.11, ranking third. Although slightly lower than the second rank, this indicates that S1 has a notable influence on CR. It underscores the importance of building density as a crucial expression of community development.

I1 (number of jogging trajectories) holds the fifth rank with a q-value of 0.077, indicating a minor impact on CR. This suggests that human health activities have limited influence on human settlement resilience. However, it is important to note that human health activities cannot be dissociated from the environment and social support. Attention can be given to human health activities without compromising other aspects of community development.

Interaction detection analysis

Interaction detection was employed to assess whether the combined effect of factors increased or decreased the explanatory power for the level of CR (Table 8 ). The results of factor interactions revealed that the values of the factor effects in two-way interactions were higher than those of single factors, demonstrating enhanced and nonlinear effects of the two-factor interactions. This indicates that the combined action of factors augmented the explanatory capacity of the resilience level. Specifically, the two-factor interactions between D7 and S1, D7 and I1, P1 and S1, P1 and I1, S1 and R6, and I1 and R6 exhibited significant effects on CR levels, indicating a robust association between these factors.

Correlation analysis

As shown in Fig.  12 , we analyzed the correlation between CRI and drivers using R language software and Origin software. The results indicate a significant positive correlation between the CRI and D7, I1, and R6, while exhibiting a negative correlation with P1 and S1. Notably, R6 exhibited the strongest influence on CR, with the highest correlation coefficient of 0.53 in absolute value. Both D7 and I1 displayed the same correlation strength with CR, with an absolute value of 0.32. On the other hand, P1 exhibited the weakest correlation with CR, with an absolute value of 0.17.

CRI correlation

This study assessed the CRs in the study area based on the integrated evaluation index method of the DPSIR model. Also this study considered the interaction between health activities and environmental supply and demand.

The findings reveal that while some communities demonstrate excellent human settlement characteristics, well-developed infrastructure, and a strong capacity to withstand external disasters. However, the overall resilience of communities still needs to be improved. In general, most communities score lower in ecological environment, built environment, and social functions. Additionally, there is a significant disparity in human settlement resilience among communities, emphasizing the need for prompt improvement. This result can be attributed to severe urban growth. Urban growth has led to problems such as urban flooding, traffic congestion and ecological damage [ 81 , 82 , 83 ]. Consequently, this hinders the endogenous development momentum for human health activities [ 84 , 85 ]. A positive trend in this element is crucial for enhancing the CR. Residents are the main contributors to community activities. If they lack healthy activities, it is difficult to maintain endogenous development dynamics. This trend is detrimental to the stable development of the community human settlement system [ 86 , 87 ]. To enhance the resilience of the community human settlement system and achieve sustainable and high-quality development, it is necessary to adopt incentive response measures based on the current state of the system and its impact results. For instance, encouraging residents to engage in healthy physical activities and improving community sports facilities can bring positive feedback to the system.

The spatial distribution analysis reveals that at the district and county scale, CR follows a spatial pattern of being low in the center and high in the periphery. At the community scale, CR exhibits an irregular spatial pattern characterized by pole-core agglomeration and radiation. Communities with high resilience are predominantly found in the south-central and Huangpu River areas. The spatial patterns of the two types of systems vary considerably. This may be due to differences in the proportion of communities within the regional space. This leads to large differences in the comparison of resilience systems between districts and counties. The disparity in resilience between areas outside the polar nuclei and the polar nuclei can be attributed to the daily health activities of urban residents being concentrated and dispersed mainly in the monocentric clustering of polar nuclei in the district centers. The spatial clustering of resilience is moderately distributed in most areas. This reflects a spatial supply–demand mismatch or complementary relationship between health activities and the environment. This leads to a low-level equilibrium in the spatial distribution characteristics of CR, aligning with existing research [ 88 , 89 , 90 ]. Furthermore, it is observed that high resilience areas are primarily concentrated in the central and southeastern parts of Shanghai's old city, including Huangpu District, Xuhui District, and Jing'an District. These areas serve as the core regions for integrated urban functions, characterized by intensive and frequent daily health activities. On the other hand, the northern, northeastern, and western areas of the old city, and the southern end of the city exhibit weaker resilience capacity due to imperfect integrated functions and location levels of the activity environment. These areas also display less dynamism in terms of health activity [ 91 ]. To overcome the spatial layout inertia of one-way overdraft in the "center-periphery" pattern, efforts should focus on promoting the orderly distribution of resilient elements related to urban residents' health activities and environmental systems. This requires ensuring that spaces for everyday health activities are autonomous, balanced and inclusive, rather than relying solely on static differences in spatial hierarchical scales and functional positioning.

In addition, based on the results of the spatial distribution of subsystems, we recommend the following actions. Firstly, there is a need to accelerate the orderly decentralization and relocation of over-concentrated public service resources and population from the old city center to peripheral communities. This will promote comprehensive development, improved supporting facilities, and population concentration in the new central area, enhancing the concentration of modern and traditional living atmospheres. Secondly, the government should vigorously promote the construction of an integrated slow-moving transport network and the promotion of mixed use of various land uses among key communities. This can link health activities and environmental elements through multiple channels. This facilitates the micro-circulation of health activities within communities, forming balanced spatial clusters for daily health activities. In addition, it is necessary to promote the organic regeneration of older urban neighborhoods and the planned development of new towns. This enhances synergies and complementarities between communities in the region. This reduces the gradient among communities and optimizes two-way interaction, enhancing the efficiency, effectiveness, and quality of daily health activities.

Regarding the contribution results, it is evident that the construction of community public transport services can promote environmental and economic development, which constitutes the primary reason for the increase in CR in the study area [ 82 , 93 ]. Reducing the distance between the community and public transport stations can further enhance CR. The average annual temperature and CO 2 emissions also exert a significant impact on CR. Therefore, natural environmental stresses such as climate, air pollution and vegetation are key factors influencing changes in CR. Building density and the number of jogging trajectories serve as indicators of the vitality of human activity systems in the face of environmental disturbances. Communities with low building density and dense jogging trajectories demonstrate higher resilience. Furthermore, it is worth noting that the correlation between annual mean temperature, jogging activity, and CR exhibits a significantly positive and non-linearly increasing relationship. This suggests that human health activities are influenced by temperature, resulting in notable changes in resilience. Conversely, the non-linear increase in CO 2 and building density signifies an intensification of the greenhouse effect and severe urban sprawl due to human activities related to urbanization. These factors contribute to an overall low level of CR. Therefore, it is strongly recommended that governments worldwide focus on the rational use of ecological resources and control the extent of urban community growth during rapid urbanization. Simultaneously, efforts should be made to strengthen the protection of existing woodland and grassland vegetation, especially by promoting residents' engagement in health activities. These measures ensure the sustainability of community human settlements.

Advantages and limitations

The study of the resilience of human settlements is of great importance in the field of global geographic studies. While urban human settlements and urban resilience have gained attention, there is still a scarcity of academic research specifically focused on human settlement resilience. This paper incorporates the principle of resilience into the study of human settlements and addresses the spatial supply–demand contradiction related to daily health activities as a primary community conflict. By exploring the dynamic relationship between people and land, the study reveals the human values and micro-details of spatiotemporal interactions. And the paper establishes an organically integrated CR evaluation index system through comprehensive correlation and multiple characterization of resilience elements and capacities. This research contributes to the academic understanding of resilience.

The research methodology employed in this paper is reasonable. Based on the DPSIR model, this paper analyses the interactions between the elements from a system perspective. This paper further constructs an evaluation index system for urban habitat resilience. Previous studies have used various methods to investigate the influencing mechanisms of geographic environmental phenomena, but they often lack the identification of interactions among multiple variables. In contrast, this study utilizes geodetector technology to explore the driving forces that impact the level of CR. This approach effectively identifies relationships among multiple variables, leading to a better understanding of the mechanisms at play.

The feasibility of the research data is supported by geographic big data, which enables comprehensive assessment and spatial visualization of urban resilience. This solid foundation facilitates scientific governance practices and spatial carriers for urban resilience. The study offers valuable insights for expanding the research field, deepening theoretical understanding, improving measurement methods, and enhancing CR governance.

However, there are limitations in this paper. The community human settlement system is a complex and open system, and solely understanding the five major subsystems is insufficient. It is necessary to examine the interactions among various subsystems and enhance the knowledge of overall CR. Additionally, due to data acquisition limitations, this paper has selected relatively important and representative indicators. Further research should refine data acquisition and processing methods and improve the indicator system for measuring the CR. Furthermore, since community human settlement systems are constantly evolving, it is important to track their evolution over time and adjust the research methodology based on macroscopic observations. This will allow for continuous follow-up research on the resilience of community human settlement systems.

In the complex context of global environmental change and urbanization, the dynamic and evolving contradiction between the supply and demand for healthy living necessitates the promotion of a more resilient supply and demand process. This paper first constructs a CR evaluation index system based on the DPSIR model. Then this paper conducted a comprehensive evaluation of the resilience of Shanghai central habitat by integrating the AHP-entropy method, GIS spatial analysis and geographical detector method. The main findings of the study are as follows:

There are significant variations in the level of human settlement resilience across the study area, exhibiting a basic "slide-shaped" fluctuation tendency.

The spatial distribution of human settlement resilience shows two patterns. One is the " pole-core agglomeration radiation" type characterized by core colonies with very high resilience values. The other is the typical irregular, open "ring agglomeration radiation" type dominated by core colonies with medium and high resilience values.

Geographical detection, interaction detection, and correlation analysis highlight the dominant factors influencing CR. The analysis indicates that the CRI is positively correlated with average annual temperature and the number of jogging trajectories, while negatively correlated with CO 2 emissions and building density. In addition, the interactions between these factors enhanced resilience in a non-linear and bivariate manner.

The results of this study hold significant implications for countries and communities worldwide. Firstly, the findings emphasize the importance of evaluating CR, particularly about health activities and the balance between environmental supply and demand. This highlights the need for governments and communities to prioritize CR and enhance the quality of life and health of community residents. Secondly, the comprehensive evaluation methods and techniques employed in this study can serve as a reference to develop their evaluation indicator systems and methods suitable for local community human settlements. Finally, this study provides insights for countries to formulate relevant environmental policies and climate change adaptation strategies, so as to safeguard human health and promote environmentally sustainable development.

Availability of data and materials

The data that support the findings of this study are available from the Dorray Sports app. Restrictions apply to the availability of these data, which were used under license for this study.

Abbreviations

• Community human settlement resilience

Community human settlement resilience index

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Zhong, Q., Chen, Y. & Yan, J. Comprehensive evaluation of community human settlement resilience and spatial characteristics based on the supply–demand mismatch between health activities and environment: a case study of downtown Shanghai, China. Global Health 19 , 87 (2023). https://doi.org/10.1186/s12992-023-00976-z

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DOI : https://doi.org/10.1186/s12992-023-00976-z

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