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Types of journal articles

It is helpful to familiarise yourself with the different types of articles published by journals. Although it may appear there are a large number of types of articles published due to the wide variety of names they are published under, most articles published are one of the following types; Original Research, Review Articles, Short reports or Letters, Case Studies, Methodologies.

Original Research:

This is the most common type of journal manuscript used to publish full reports of data from research. It may be called an  Original Article, Research Article, Research, or just  Article, depending on the journal. The Original Research format is suitable for many different fields and different types of studies. It includes full Introduction, Methods, Results, and Discussion sections.

Short reports or Letters:

These papers communicate brief reports of data from original research that editors believe will be interesting to many researchers, and that will likely stimulate further research in the field. As they are relatively short the format is useful for scientists with results that are time sensitive (for example, those in highly competitive or quickly-changing disciplines). This format often has strict length limits, so some experimental details may not be published until the authors write a full Original Research manuscript. These papers are also sometimes called Brief communications .

Review Articles:

Review Articles provide a comprehensive summary of research on a certain topic, and a perspective on the state of the field and where it is heading. They are often written by leaders in a particular discipline after invitation from the editors of a journal. Reviews are often widely read (for example, by researchers looking for a full introduction to a field) and highly cited. Reviews commonly cite approximately 100 primary research articles.

TIP: If you would like to write a Review but have not been invited by a journal, be sure to check the journal website as some journals to not consider unsolicited Reviews. If the website does not mention whether Reviews are commissioned it is wise to send a pre-submission enquiry letter to the journal editor to propose your Review manuscript before you spend time writing it.  

Case Studies:

These articles report specific instances of interesting phenomena. A goal of Case Studies is to make other researchers aware of the possibility that a specific phenomenon might occur. This type of study is often used in medicine to report the occurrence of previously unknown or emerging pathologies.

Methodologies or Methods

These articles present a new experimental method, test or procedure. The method described may either be completely new, or may offer a better version of an existing method. The article should describe a demonstrable advance on what is currently available.

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

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

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

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

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

Table of contents

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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is a case study a journal article

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

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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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Reproductive rights in America

Research at the heart of a federal case against the abortion pill has been retracted.

Selena Simmons-Duffin

Selena Simmons-Duffin

is a case study a journal article

The Supreme Court will hear the case against the abortion pill mifepristone on March 26. It's part of a two-drug regimen with misoprostol for abortions in the first 10 weeks of pregnancy. Anna Moneymaker/Getty Images hide caption

The Supreme Court will hear the case against the abortion pill mifepristone on March 26. It's part of a two-drug regimen with misoprostol for abortions in the first 10 weeks of pregnancy.

A scientific paper that raised concerns about the safety of the abortion pill mifepristone was retracted by its publisher this week. The study was cited three times by a federal judge who ruled against mifepristone last spring. That case, which could limit access to mifepristone throughout the country, will soon be heard in the Supreme Court.

The now retracted study used Medicaid claims data to track E.R. visits by patients in the month after having an abortion. The study found a much higher rate of complications than similar studies that have examined abortion safety.

Sage, the publisher of the journal, retracted the study on Monday along with two other papers, explaining in a statement that "expert reviewers found that the studies demonstrate a lack of scientific rigor that invalidates or renders unreliable the authors' conclusions."

It also noted that most of the authors on the paper worked for the Charlotte Lozier Institute, the research arm of anti-abortion lobbying group Susan B. Anthony Pro-Life America, and that one of the original peer reviewers had also worked for the Lozier Institute.

The Sage journal, Health Services Research and Managerial Epidemiology , published all three research articles, which are still available online along with the retraction notice. In an email to NPR, a spokesperson for Sage wrote that the process leading to the retractions "was thorough, fair, and careful."

The lead author on the paper, James Studnicki, fiercely defends his work. "Sage is targeting us because we have been successful for a long period of time," he says on a video posted online this week . He asserts that the retraction has "nothing to do with real science and has everything to do with a political assassination of science."

He says that because the study's findings have been cited in legal cases like the one challenging the abortion pill, "we have become visible – people are quoting us. And for that reason, we are dangerous, and for that reason, they want to cancel our work," Studnicki says in the video.

In an email to NPR, a spokesperson for the Charlotte Lozier Institute said that they "will be taking appropriate legal action."

Role in abortion pill legal case

Anti-abortion rights groups, including a group of doctors, sued the federal Food and Drug Administration in 2022 over the approval of mifepristone, which is part of a two-drug regimen used in most medication abortions. The pill has been on the market for over 20 years, and is used in more than half abortions nationally. The FDA stands by its research that finds adverse events from mifepristone are extremely rare.

Judge Matthew Kacsmaryk, the district court judge who initially ruled on the case, pointed to the now-retracted study to support the idea that the anti-abortion rights physicians suing the FDA had the right to do so. "The associations' members have standing because they allege adverse events from chemical abortion drugs can overwhelm the medical system and place 'enormous pressure and stress' on doctors during emergencies and complications," he wrote in his decision, citing Studnicki. He ruled that mifepristone should be pulled from the market nationwide, although his decision never took effect.

is a case study a journal article

Matthew Kacsmaryk at his confirmation hearing for the federal bench in 2017. AP hide caption

Matthew Kacsmaryk at his confirmation hearing for the federal bench in 2017.

Kacsmaryk is a Trump appointee who was a vocal abortion opponent before becoming a federal judge.

"I don't think he would view the retraction as delegitimizing the research," says Mary Ziegler , a law professor and expert on the legal history of abortion at U.C. Davis. "There's been so much polarization about what the reality of abortion is on the right that I'm not sure how much a retraction would affect his reasoning."

Ziegler also doubts the retractions will alter much in the Supreme Court case, given its conservative majority. "We've already seen, when it comes to abortion, that the court has a propensity to look at the views of experts that support the results it wants," she says. The decision that overturned Roe v. Wade is an example, she says. "The majority [opinion] relied pretty much exclusively on scholars with some ties to pro-life activism and didn't really cite anybody else even or really even acknowledge that there was a majority scholarly position or even that there was meaningful disagreement on the subject."

In the mifepristone case, "there's a lot of supposition and speculation" in the argument about who has standing to sue, she explains. "There's a probability that people will take mifepristone and then there's a probability that they'll get complications and then there's a probability that they'll get treatment in the E.R. and then there's a probability that they'll encounter physicians with certain objections to mifepristone. So the question is, if this [retraction] knocks out one leg of the stool, does that somehow affect how the court is going to view standing? I imagine not."

It's impossible to know who will win the Supreme Court case, but Ziegler thinks that this retraction probably won't sway the outcome either way. "If the court is skeptical of standing because of all these aforementioned weaknesses, this is just more fuel to that fire," she says. "It's not as if this were an airtight case for standing and this was a potentially game-changing development."

Oral arguments for the case, Alliance for Hippocratic Medicine v. FDA , are scheduled for March 26 at the Supreme Court. A decision is expected by summer. Mifepristone remains available while the legal process continues.

  • Abortion policy
  • abortion pill
  • judge matthew kacsmaryk
  • mifepristone
  • retractions
  • Abortion rights
  • Supreme Court
  • Open access
  • Published: 27 June 2011

The case study approach

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

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

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

Peer Review reports

Introduction

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

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

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

What is a case study?

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

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

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

What are case studies used for?

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

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

How are case studies conducted?

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

Defining the case

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

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

Selecting the case(s)

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

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

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

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

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

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

Collecting the data

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

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

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

Analysing, interpreting and reporting case studies

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

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

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

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

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

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

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

Conclusions

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

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Acknowledgements

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

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

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Critical transitions in the Amazon forest system

  • Bernardo M. Flores   ORCID: orcid.org/0000-0003-4555-5598 1 ,
  • Encarni Montoya   ORCID: orcid.org/0000-0002-4690-190X 2 ,
  • Boris Sakschewski   ORCID: orcid.org/0000-0002-7230-9723 3 ,
  • Nathália Nascimento   ORCID: orcid.org/0000-0003-4819-0811 4 ,
  • Arie Staal   ORCID: orcid.org/0000-0001-5409-1436 5 ,
  • Richard A. Betts   ORCID: orcid.org/0000-0002-4929-0307 6 , 7 ,
  • Carolina Levis   ORCID: orcid.org/0000-0002-8425-9479 1 ,
  • David M. Lapola 8 ,
  • Adriane Esquível-Muelbert   ORCID: orcid.org/0000-0001-5335-1259 9 , 10 ,
  • Catarina Jakovac   ORCID: orcid.org/0000-0002-8130-852X 11 ,
  • Carlos A. Nobre 4 ,
  • Rafael S. Oliveira   ORCID: orcid.org/0000-0002-6392-2526 12 ,
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  • Niklas Boers   ORCID: orcid.org/0000-0002-1239-9034 3 , 14 ,
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  • Hans ter Steege   ORCID: orcid.org/0000-0002-8738-2659 16 , 17 ,
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  • Marina Hirota   ORCID: orcid.org/0000-0002-1958-3651 1 , 12 , 25  

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  • Climate and Earth system modelling
  • Ecosystem ecology
  • Ecosystem services
  • Sustainability

The possibility that the Amazon forest system could soon reach a tipping point, inducing large-scale collapse, has raised global concern 1 , 2 , 3 . For 65 million years, Amazonian forests remained relatively resilient to climatic variability. Now, the region is increasingly exposed to unprecedented stress from warming temperatures, extreme droughts, deforestation and fires, even in central and remote parts of the system 1 . Long existing feedbacks between the forest and environmental conditions are being replaced by novel feedbacks that modify ecosystem resilience, increasing the risk of critical transition. Here we analyse existing evidence for five major drivers of water stress on Amazonian forests, as well as potential critical thresholds of those drivers that, if crossed, could trigger local, regional or even biome-wide forest collapse. By combining spatial information on various disturbances, we estimate that by 2050, 10% to 47% of Amazonian forests will be exposed to compounding disturbances that may trigger unexpected ecosystem transitions and potentially exacerbate regional climate change. Using examples of disturbed forests across the Amazon, we identify the three most plausible ecosystem trajectories, involving different feedbacks and environmental conditions. We discuss how the inherent complexity of the Amazon adds uncertainty about future dynamics, but also reveals opportunities for action. Keeping the Amazon forest resilient in the Anthropocene will depend on a combination of local efforts to end deforestation and degradation and to expand restoration, with global efforts to stop greenhouse gas emissions.

The Amazon forest is a complex system of interconnected species, ecosystems and human cultures that contributes to the well-being of people globally 1 . The Amazon forest holds more than 10% of Earth’s terrestrial biodiversity, stores an amount of carbon equivalent to 15–20 years of global CO 2 emissions (150–200 Pg C), and has a net cooling effect (from evapotranspiration) that helps to stabilize the Earth’s climate 1 , 2 , 3 . The forest contributes up to 50% of rainfall in the region and is crucial for moisture supply across South America 4 , allowing other biomes and economic activities to thrive in regions that would otherwise be more arid, such as the Pantanal wetlands and the La Plata river basin 1 . Large parts of the Amazon forest, however, are projected to experience mass mortality events due to climatic and land use-related disturbances in the coming decades 5 , 6 , potentially accelerating climate change through carbon emissions and feedbacks with the climate system 2 , 3 . These impacts would also involve irreversible loss of biodiversity, socioeconomic and cultural values 1 , 7 , 8 , 9 . The Amazon is home to more than 40 million people, including 2.2 million Indigenous peoples of more than 300 ethnicities, as well as afrodescendent and local traditional communities 1 . Indigenous peoples and local communities (IPLCs) would be harmed by forest loss in terms of their livelihoods, lifeways and knowledge systems that inspire societies globally 1 , 7 , 9 .

Understanding the risk of such catastrophic behaviour requires addressing complex factors that shape ecosystem resilience 10 . A major question is whether a large-scale collapse of the Amazon forest system could actually happen within the twenty-first century, and if this would be associated with a particular tipping point. Here we synthesize evidence from paleorecords, observational data and modelling studies of critical drivers of stress on the system. We assess potential thresholds of those drivers and the main feedbacks that could push the Amazon forest towards a tipping point. From examples of disturbed forests across the Amazon, we analyse the most plausible ecosystem trajectories that may lead to alternative stable states 10 . Moreover, inspired by the framework of ‘planetary boundaries’ 11 , we identify climatic and land use boundaries that reveal a safe operating space for the Amazon forest system in the Anthropocene epoch 12 .

Theory and concepts

Over time, environmental conditions fluctuate and may cause stress on ecosystems (for example, lack of water for plants). When stressing conditions intensify, some ecosystems may change their equilibrium state gradually, whereas others may shift abruptly between alternative stable states 10 . A ‘tipping point’ is the critical threshold value of an environmental stressing condition at which a small disturbance may cause an abrupt shift in the ecosystem state 2 , 3 , 13 , 14 , accelerated by positive feedbacks 15 (see Extended Data Table 1 ). This type of behaviour in which the system gets into a phase of self-reinforcing (runaway) change is often referred to as ‘critical transition’ 16 . As ecosystems approach a tipping point, they often lose resilience while still remaining close to equilibrium 17 . Thus, monitoring changes in ecosystem resilience and in key environmental conditions may enable societies to manage and avoid critical transitions. We adopt the concept of ‘ecological resilience’ 18 (hereafter ‘resilience’), which refers to the ability of an ecosystem to persist with similar structure, functioning and interactions, despite disturbances that push it to an alternative stable state. The possibility that alternative stable states (or bistability) may exist in a system has important implications, because the crossing of tipping points may be irreversible for the time scales that matter to societies 10 . Tropical terrestrial ecosystems are a well-known case in which critical transitions between alternative stable states may occur (Extended Data Fig. 1 ).

Past dynamics

The Amazon system has been mostly covered by forest throughout the Cenozoic era 19 (for 65 million years). Seven million years ago, the Amazon river began to drain the massive wetlands that covered most of the western Amazon, allowing forests to expand over grasslands in that region. More recently, during the drier and cooler conditions of the Last Glacial Maximum 20 (LGM) (around 21,000 years ago) and of the mid-Holocene epoch 21 (around 6,000 years ago), forests persisted even when humans were already present in the landscape 22 . Nonetheless, savannas expanded in peripheral parts of the southern Amazon basin during the LGM and mid-Holocene 23 , as well as in the northeastern Amazon during the early Holocene (around 11,000 years ago), probably influenced by drier climatic conditions and fires ignited by humans 24 , 25 . Throughout the core of the Amazon forest biome, patches of white-sand savanna also expanded in the past 20,000–7,000 years, driven by sediment deposition along ancient rivers 26 , and more recently (around 800 years ago) owing to Indigenous fires 27 . However, during the past 3,000 years, forests have been mostly expanding over savanna in the southern Amazon driven by increasingly wet conditions 28 .

Although palaeorecords suggest that a large-scale Amazon forest collapse did not occur within the past 65 million years 19 , they indicate that savannas expanded locally, particularly in the more seasonal peripheral regions when fires ignited by humans were frequent 23 , 24 . Patches of white-sand savanna also expanded within the Amazon forest owing to geomorphological dynamics and fires 26 , 27 . Past drought periods were usually associated with much lower atmospheric CO 2 concentrations, which may have reduced water-use efficiency of trees 29 (that is, trees assimilated less carbon during transpiration). However, these periods also coincided with cooler temperatures 20 , 21 , which probably reduced water demand by trees 30 . Past drier climatic conditions were therefore very different from the current climatic conditions, in which observed warming trends may exacerbate drought impacts on the forest by exposing trees to unprecedented levels of water stress 31 , 32 .

Global change impacts on forest resilience

Satellite observations from across the Amazon suggest that forest resilience has been decreasing since the early 2000s 33 , possibly as a result of global changes. In this section, we synthesize three global change impacts that vary spatially and temporally across the Amazon system, affecting forest resilience and the risk of critical transitions.

Regional climatic conditions

Within the twenty-first century, global warming may cause long-term changes in Amazonian climatic conditions 2 . Human greenhouse gas emissions continue to intensify global warming, but the warming rate also depends on feedbacks in the climate system that remain uncertain 2 , 3 . Recent climate models of the 6th phase of the Coupled Model Intercomparison Project (CMIP6) agree that in the coming decades, rainfall conditions will become more seasonal in the eastern and southern Amazonian regions, and temperatures will become higher across the entire Amazon 1 , 2 . By 2050, models project that a significant increase in the number of consecutive dry days by 10−30 days and in annual maximum temperatures by 2–4 °C, depending on the greenhouse gas emission scenario 2 . These climatic conditions could expose the forest to unprecedented levels of vapour pressure deficit 31 and consequently water stress 30 .

Satellite observations of climatic variability 31 confirm model projections 2 , showing that since the early 1980s, the Amazonian region has been warming significantly at an average rate of 0.27 °C per decade during the dry season, with the highest rates of up to 0.6 °C per decade in the centre and southeast of the biome (Fig. 1a ). Only a few small areas in the west of the biome are significantly cooling by around 0.1 °C per decade (Fig. 1a ). Dry season mean temperature is now more than 2 °C higher than it was 40 years ago in large parts of the central and southeastern Amazon. If trends continue, these areas could potentially warm by over 4 °C by 2050. Maximum temperatures during the dry season follow a similar trend, rising across most of the biome (Extended Data Fig. 2 ), exposing the forest 34 and local peoples 35 to potentially unbearable heat. Rising temperatures will increase thermal stress, potentially reducing forest productivity and carbon storage capacity 36 and causing widespread leaf damage 34 .

figure 1

a , Changes in the dry season (July–October) mean temperature reveal widespread warming, estimated using simple regressions between time and temperature observed between 1981 and 2020 (with P  < 0.1). b , Potential ecosystem stability classes estimated for year 2050, adapted from current stability classes (Extended Data Fig. 1b ) by considering only areas with significant regression slopes between time and annual rainfall observed from 1981 through 2020 (with P  < 0.1) (see Extended Data Fig. 3 for areas with significant changes). c , Repeated extreme drought events between 2001–2018 (adapted from ref. 39 ). d , Road network from where illegal deforestation and degradation may spread. e , Protected areas and Indigenous territories reduce deforestation and fire disturbances. f , Ecosystem transition potential (the possibility of forest shifting into an alternative structural or compositional state) across the Amazon biome by year 2050 inferred from compounding disturbances ( a – d ) and high-governance areas ( e ). We excluded accumulated deforestation until 2020 and savannas. Transition potential rises with compounding disturbances and varies as follows: less than 0 (in blue) as low; between 1 and 2 as moderate (in yellow); more than 2 as high (orange–red). Transition potential represents the sum of: (1) slopes of dry season mean temperature (as in a , multiplied by 10); (2) ecosystem stability classes estimated for year 2050 (as in b ), with 0 for stable forest, 1 for bistable and 2 for stable savanna; (3) accumulated impacts from extreme drought events, with 0.2 for each event; (4) road proximity as proxy for degrading activities, with 1 for pixels within 10 km from a road; (5) areas with higher governance within protected areas and Indigenous territories, with −1 for pixels inside these areas. For more details, see  Methods .

Since the early 1980s, rainfall conditions have also changed 31 . Peripheral and central parts of the Amazon forest are drying significantly, such as in the southern Bolivian Amazon, where annual rainfall reduced by up to 20 mm yr −1 (Extended Data Fig. 3a ). By contrast, parts of the western and eastern Amazon forest are becoming wetter, with annual rainfall increasing by up to 20 mm yr −1 . If these trends continue, ecosystem stability (as in Extended Data Fig. 1 ) will probably change in parts of the Amazon by 2050, reshaping forest resilience to disturbances (Fig. 1b and Extended Data Fig. 3b ). For example, 6% of the biome may change from stable forest to a bistable regime in parts of the southern and central Amazon. Another 3% of the biome may pass the critical threshold in annual rainfall into stable savanna in the southern Bolivian Amazon. Bistable areas covering 8% of the biome may turn into stable forest in the western Amazon (Peru and Bolivia), thus becoming more resilient to disturbances. For comparison with satellite observations, we used projections of ecosystem stability by 2050 based on CMIP6 model ensembles for a low (SSP2–4.5) and a high (SSP5–8.5) greenhouse gas emission scenario (Extended Data Fig. 4 and Supplementary Table 1 ). An ensemble with the 5 coupled models that include a dynamic vegetation module indicates that 18–27% of the biome may transition from stable forest to bistable and that 2–6% may transition to stable savanna (depending on the scenario), mostly in the northeastern Amazon. However, an ensemble with all 33 models suggests that 35–41% of the biome could become bistable, including large areas of the southern Amazon. The difference between both ensembles is possibly related to the forest–rainfall feedback included in the five coupled models, which increases total annual rainfall and therefore the stable forest area along the southern Amazon, but only when deforestation is not included in the simulations 4 , 37 . Nonetheless, both model ensembles agree that bistable regions will expand deeper into the Amazon, increasing the risk of critical transitions due to disturbances (as implied by the existence of alternative stable states; Extended Data Fig. 1 ).

Disturbance regimes

Within the remaining Amazon forest area, 17% has been degraded by human disturbances 38 , such as logging, edge effects and understory fires, but if we consider also the impacts from repeated extreme drought events in the past decades, 38% of the Amazon could be degraded 39 . Increasing rainfall variability is causing extreme drought events to become more widespread and frequent across the Amazon (Fig. 1c ), together with extreme wet events and convective storms that result in more windthrow disturbances 40 . Drought regimes are intensifying across the region 41 , possibly due to deforestation 42 that continues to expand within the system (Extended Data Fig. 5 ). As a result, new fire regimes are burning larger forest areas 43 , emitting more carbon to the atmosphere 44 and forcing IPLCs to readapt 45 . Road networks (Fig. 1d ) facilitate illegal activities, promoting more deforestation, logging and fire spread throughout the core of the Amazon forest 38 , 39 . The impacts of these pervasive disturbances on biodiversity and on IPLCs will probably affect ecosystem adaptability (Box 1 ), and consequently forest resilience to global changes.

Currently, 86% of the Amazon biome may be in a stable forest state (Extended Data Fig. 1b ), but some of these stable forests are showing signs of fragility 33 . For instance, field evidence from long-term monitoring sites across the Amazon shows that tree mortality rates are increasing in most sites, reducing carbon storage 46 , while favouring the replacement by drought-affiliated species 47 . Aircraft measurements of vertical carbon flux between the forest and atmosphere reveal how southeastern forests are already emitting more carbon than they absorb, probably because of deforestation and fire 48 .

As bistable forests expand deeper into the system (Fig. 1b and Extended Data Fig. 4 ), the distribution of compounding disturbances may indicate where ecosystem transitions are more likely to occur in the coming decades (Fig. 1f ). For this, we combined spatial information on warming and drying trends, repeated extreme drought events, together with road networks, as proxy for future deforestation and degradation 38 , 39 . We also included protected areas and Indigenous territories as areas with high forest governance, where deforestation and fire regimes are among the lowest within the Amazon 49 (Fig. 1e ). This simple additive approach does not consider synergies between compounding disturbances that could trigger unexpected ecosystem transitions. However, by exploring only these factors affecting forest resilience and simplifying the enormous Amazonian complexity, we aimed to produce a simple and comprehensive map that can be useful for guiding future governance. We found that 10% of the Amazon forest biome has a relatively high transition potential (more than 2 disturbance types; Fig. 1f ), including bistable forests that could transition into a low tree cover state near savannas of Guyana, Venezuela, Colombia and Peru, as well as stable forests that could transition into alternative compositional states within the central Amazon, such as along the BR319 and Trans-Amazonian highways. Smaller areas with high transition potential were found scattered within deforestation frontiers, where most forests have been carved by roads 50 , 51 . Moreover, 47% of the biome has a moderate transition potential (more than 1 disturbance type; Fig. 1f ), including relatively remote parts of the central Amazon where warming trends and repeated extreme drought events overlap (Fig. 1a,c ). By contrast, large remote areas covering 53% of the biome have low transition potential, mostly reflecting the distribution of protected areas and Indigenous territories (Fig. 1e ). If these estimates, however, considered projections from CMIP6 models and their relatively broader areas of bistability (Extended Data Fig. 4 ), the proportion of the Amazon forest that could transition into a low tree cover state would be much larger.

Box 1 Ecosystem adaptability

We define ‘ecosystem adaptability’ as the capacity of an ecosystem to reorganize and persist in the face of environmental changes. In the past, many internal mechanisms have probably contributed to ecosystem adaptability, allowing Amazonian forests to persist during times of climate change. In this section we synthesize two of these internal mechanisms, which are now being undermined by global change.

Biodiversity

Amazonian forests are home to more than 15,000 tree species, of which 1% are dominant and the other 99% are mostly rare 107 . A single forest hectare in the central and northwestern Amazon can contain more than 300 tree species (Extended Data Fig. 7a ). Such tremendous tree species diversity can increase forest resilience by different mechanisms. Tree species complementarity increases carbon storage, accelerating forest recovery after disturbances 108 . Tree functional diversity increases forest adaptability to climate chance by offering various possibilities of functioning 99 . Rare species provide ‘ecological redundancy’, increasing opportunities for replacement of lost functions when dominant species disappear 109 . Diverse forests are also more likely to resist severe disturbances owing to ‘response diversity’ 110 —that is, some species may die, while others persist. For instance, in the rainy western Amazon, drought-resistant species are rare but present within tree communities 111 , implying that they could replace the dominant drought-sensitive species in a drier future. Diversity of other organisms, such as frugivores and pollinators, also increases forest resilience by stabilizing ecological networks 15 , 112 . Considering that half of Amazonian tree species are estimated to become threatened (IUCN Red list) by 2050 owing to climate change, deforestation and degradation 8 , biodiversity losses could contribute to further reducing forest resilience.

Indigenous peoples and local communities

Globally, Indigenous peoples and local communities (IPLCs) have a key role in maintaining ecosystems resilient to global change 113 . Humans have been present in the Amazon for at least 12,000 years 114 and extensively managing landscapes for 6,000 years 22 . Through diverse ecosystem management practices, humans built thousands of earthworks and ‘Amazon Dark Earth’ sites, and domesticated plants and landscapes across the Amazon forest 115 , 116 . By creating new cultural niches, humans partly modified the Amazonian flora 117 , 118 , increasing their food security even during times of past climate change 119 , 120 without the need for large-scale deforestation 117 . Today, IPLCs have diverse ecological knowledge about Amazonian plants, animals and landscapes, which allows them to quickly identify and respond to environmental changes with mitigation and adaptation practices 68 , 69 . IPLCs defend their territories against illegal deforestation and land use disturbances 49 , 113 , and they also promote forest restoration by expanding diverse agroforestry systems 121 , 122 . Amazonian regions with the highest linguistic diversity (a proxy for ecological knowledge diversity 123 ) are found in peripheral parts of the system, particularly in the north-west (Extended Data Fig. 7b ). However, consistent loss of Amazonian languages is causing an irreversible disruption of ecological knowledge systems, mostly driven by road construction 7 . Continued loss of ecological knowledge will undermine the capacity of IPLCs to manage and protect Amazonian forests, further reducing their resilience to global changes 9 .

CO 2 fertilization

Rising atmospheric CO 2 concentrations are expected to increase the photosynthetic rates of trees, accelerating forest growth and biomass accumulation on a global scale 52 . In addition, CO 2 may reduce water stress by increasing tree water-use efficiency 29 . As result, a ‘CO 2 fertilization effect’ could increase forest resilience to climatic variability 53 , 54 . However, observations from across the Amazon 46 suggest that CO 2 -driven accelerations of tree growth may have contributed to increasing tree mortality rates (trees grow faster but also die earlier), which could eventually neutralize the forest carbon sink in the coming decades 55 . Moreover, increases in tree water-use efficiency may reduce forest transpiration and consequently atmospheric moisture flow across the Amazon 53 , 56 , potentially reducing forest resilience in the southwest of the biome 4 , 37 . Experimental evidence suggests that CO 2 fertilization also depends on soil nutrient availability, particularly nitrogen and phosphorus 57 , 58 . Thus, it is possible that in the fertile soils of the western Amazon and Várzea floodplains, forests may gain resilience from increasing atmospheric CO 2 (depending on how it affects tree mortality rates), whereas on the weathered (nutrient-poor) soils across most of the Amazon basin 59 , forests might not respond to atmospheric CO 2 increase, particularly on eroded soils within deforestation frontiers 60 . In sum, owing to multiple interacting factors, potential responses of Amazonian forests to CO 2 fertilization are still poorly understood. Forest responses depend on scale, with resilience possibly increasing at the local scale on relatively more fertile soils, but decreasing at the regional scale due to reduced atmospheric moisture flow.

Local versus systemic transition

Environmental heterogeneity.

Environmental heterogeneity can reduce the risk of systemic transition (large-scale forest collapse) because when stressing conditions intensify (for example, rainfall declines), heterogeneous forests may transition gradually (first the less resilient forest patches, followed by the more resilient ones), compared to homogeneous forests that may transition more abruptly 17 (all forests transition in synchrony). Amazonian forests are heterogeneous in their resilience to disturbances, which may have contributed to buffering large-scale transitions in the past 37 , 61 , 62 . At the regional scale, a fundamental heterogeneity factor is rainfall and how it translates into water stress. Northwestern forests rarely experience water stress, which makes them relatively more resilient than southeastern forests that may experience water stress in the dry season, and therefore are more likely to shift into a low tree cover state. As a result of low exposure to water deficit, most northwestern forests have trees with low drought resistance and could suffer massive mortality if suddenly exposed to severe water stress 32 . However, this scenario seems unlikely to occur in the near future (Fig. 1 ). By contrast, most seasonal forest trees have various strategies to cope with water deficit owing to evolutionary and adaptive responses to historical drought events 32 , 63 . These strategies may allow seasonal forests to resist current levels of rainfall fluctuations 32 , but seasonal forests are also closer to the critical rainfall thresholds (Extended Data Fig. 1 ) and may experience unprecedented water stress in the coming decades (Fig. 1 ).

Other key heterogeneity factors (Extended Data Fig. 6 ) include topography, which determines plant access to groundwater 64 , and seasonal flooding, which increases forest vulnerability to wildfires 65 . Future changes in rainfall regimes will probably affect hydrological regimes 66 , exposing plateau (hilltop) forests to unprecedented water stress, and floodplain forests to extended floods, droughts and wildfires. Soil fertility is another heterogeneity factor that may affect forest resilience 59 , and which may be undermined by disturbances that cause topsoil erosion 60 . Moreover, as human disturbances intensify throughout the Amazon (Fig. 1 ), the spread of invasive grasses and fires can make the system increasingly homogeneous. Effects of heterogeneity on Amazon forest resilience have been poorly investigated so far (but see refs. 37 , 61 , 62 ) and many questions remain open, such as how much heterogeneity exists in the system and whether it can mitigate a systemic transition.

Sources of connectivity

Connectivity across Amazonian landscapes and regions can contribute to synchronize forest dynamics, causing different forests to behave more similarly 17 . Depending on the processes involved, connectivity can either increase or decrease the risk of systemic transition 17 . For instance, connectivity may facilitate forest recovery after disturbances through seed dispersal, but also it may spread disturbances, such as fire. In the Amazon, an important source of connectivity enhancing forest resilience is atmospheric moisture flow westward (Fig. 2 ), partly maintained by forest evapotranspiration 4 , 37 , 67 . Another example of connectivity that may increase social-ecological resilience is knowledge exchange among IPLCs about how to adapt to global change 68 , 69 (see Box 1 ). However, complex systems such as the Amazon can be particularly vulnerable to sources of connectivity that spread disturbances and increase the risk of systemic transition 70 . For instance, roads carving through the forest are well-known sources of illegal activities, such as logging and burning, which increase forest flammability 38 , 39 .

figure 2

Brazil holds 60% of the Amazon forest biome and has a major responsibility towards its neighbouring countries in the west. Brazil is the largest supplier of rainfall to western Amazonian countries. Up to one-third of the total annual rainfall in Amazonian territories of Bolivia, Peru, Colombia and Ecuador depends on water originating from Brazil’s portion of the Amazon forest. This international connectivity illustrates how policies related to deforestation, especially in the Brazilian Amazon, will affect the climate in other countries. Arrow widths are proportional to the percentage of the annual rainfall received by each country within their Amazonian areas. We only show flows with percentages higher than 10% (see  Methods for details).

Five critical drivers of water stress

Global warming.

Most CMIP6 models agree that a large-scale dieback of the Amazon is unlikely in response to global warming above pre-industrial levels 2 , but this ecosystem response is based on certain assumptions, such as a large CO 2 -fertilization effect 53 . Forests across the Amazon are already responding with increasing tree mortality rates that are not simulated by these models 46 , possibly because of compounding disturbance regimes (Fig. 1 ). Nonetheless, a few global climate models 3 , 14 , 71 , 72 , 73 , 74 indicate a broad range for a potential critical threshold in global warming between 2 and 6 °C (Fig. 3a ). These contrasting results can be explained by general differences between numerical models and their representation of the complex Amazonian system. While some models with dynamic vegetation indicate local-scale tipping events in peripheral parts of the Amazon 5 , 6 , other models suggest an increase in biomass and forest cover (for example, in refs. 53 , 54 ). For instance, a study found that when considering only climatic variability, a large-scale Amazon forest dieback is unlikely, even under a high greenhouse gas emission scenario 75 . However, most updated CMIP6 models agree that droughts in the Amazon region will increase in length and intensity, and that exceptionally hot droughts will become more common 2 , creating conditions that will probably boost other types of disturbances, such as large and destructive forest fires 76 , 77 . To avoid broad-scale ecosystem transitions due to synergies between climatic and land use disturbances (Fig. 3b ), we suggest a safe boundary for the Amazon forest at 1.5 °C for global warming above pre-industrial levels, in concert with the Paris Agreement goals.

figure 3

a , Five critical drivers of water stress on Amazonian forests affect (directly or indirectly) the underlying tipping point of the system. For each driver, we indicate potential critical thresholds and safe boundaries that define a safe operating space for keeping the Amazon forest resilient 11 , 12 . We followed the precautionary principle and considered the most conservative thresholds within the ranges, when confidence was low. b , Conceptual model showing how the five drivers may interact (arrows indicate positive effects) and how these interactions may strengthen a positive feedback between water stress and forest loss. These emerging positive feedback loops could accelerate a systemic transition of the Amazon forest 15 . At global scales, driver 1 (global warming) intensifies with greenhouse gas emissions, including emissions from deforestation. At local scales, driver 5 (accumulated deforestation) intensifies with land use changes. Drivers 2 to 4 (regional rainfall conditions) intensify in response to drivers 1 and 5. The intensification of these drivers may cause widespread tree mortality for instance because of extreme droughts and fires 76 . Water stress affects vegetation resilience globally 79 , 104 , but other stressors, such as heat stress 34 , 36 , may also have a role. In the coming decades, these five drivers could change at different rates, with some approaching a critical threshold faster than others. Therefore, monitoring them separately can provide vital information to guide mitigation and adaptation strategies.

Annual rainfall

Satellite observations of tree cover distributions across tropical South America suggest a critical threshold between 1,000 and 1,250 mm of annual rainfall 78 , 79 . On the basis of our reanalysis using tree cover data from the Amazon basin (Extended Data Fig. 1a ), we confirm a potential threshold at 1,000 mm of annual rainfall (Fig. 3a ), below which forests become rare and unstable. Between 1,000 and 1,800 mm of annual rainfall, high and low tree cover ecosystems exist in the Amazon as two alternative stable states (see Extended Data Table 2 for uncertainty ranges). Within the bistability range in annual rainfall conditions, forests are relatively more likely to collapse when severely disturbed, when compared to forests in areas with annual rainfall above 1,800 mm (Extended Data Fig. 1a ). For floodplain ecosystems covering 14% of the forest biome, a different critical threshold has been estimated at 1,500 mm of annual rainfall 65 , implying that floodplain forests may be the first to collapse in a drier future. To avoid local-scale ecosystem transitions due to compounding disturbances, we suggest a safe boundary in annual rainfall conditions at 1,800 mm.

Rainfall seasonality intensity

Satellite observations of tree cover distributions across tropical South America suggest a critical threshold in rainfall seasonality intensity at −400 mm of the maximum cumulative water deficit 37 , 80 (MCWD). Our reanalysis of the Amazon basin (Extended Data Fig. 1c ) confirms the critical threshold at approximately −450 mm in the MCWD (Fig. 3a ), and suggests a bistability range between approximately −350 and −450 mm (see Extended Data Table 2 for uncertainty ranges), in which forests are more likely to collapse when severely disturbed than forests in areas with MCWD below −350 mm. To avoid local-scale ecosystem transitions due to compounding disturbances, we suggest a safe boundary of MCWD at −350 mm.

Dry season length

Satellite observations of tree cover distributions across tropical South America suggest a critical threshold at 7 months of dry season length 79 (DSL). Our reanalysis of the Amazon basin (Extended Data Fig. 1d ) suggests a critical threshold at eight months of DSL (Fig. 3a ), with a bistability range between approximately five and eight months (see Extended Data Table 2 for uncertainty ranges), in which forests are more likely to collapse when severely disturbed than forests in areas with DSL below five months. To avoid local-scale ecosystem transitions due to compounding disturbances, we suggest a safe boundary of DSL at five months.

Accumulated deforestation

A potential vegetation model 81 found a critical threshold at 20% of accumulated deforestation (Fig. 3a ) by simulating Amazon forest responses to different scenarios of accumulated deforestation (with associated fire events) and of greenhouse gas emissions, and by considering a CO 2 fertilization effect of 25% of the maximum photosynthetic assimilation rate. Beyond 20% deforestation, forest mortality accelerated, causing large reductions in regional rainfall and consequently an ecosystem transition of 50−60% of the Amazon, depending on the emissions scenario. Another study using a climate-vegetation model found that with accumulated deforestation of 30−50%, rainfall in non-deforested areas downwind would decline 67 by 40% (ref.  67 ), potentially causing more forest loss 4 , 37 . Other more recent models incorporating fire disturbances support a potential broad-scale transition of the Amazon forest, simulating a biomass loss of 30–40% under a high-emission scenario 5 , 82 (SSP5–8.5 at 4 °C). The Amazon biome has already lost 13% of its original forest area due to deforestation 83 (or 15% of the biome if we consider also young secondary forests 83 that provide limited contribution to moisture flow 84 ). Among the remaining old-growth forests, at least 38% have been degraded by land use disturbances and repeated extreme droughts 39 , with impacts on moisture recycling that are still uncertain. Therefore, to avoid broad-scale ecosystem transitions due to runaway forest loss (Fig. 3b ), we suggest a safe boundary of accumulated deforestation of 10% of the original forest biome cover, which requires ending large-scale deforestation and restoring at least 5% of the biome.

Three alternative ecosystem trajectories

Degraded forest.

In stable forest regions of the Amazon with annual rainfall above 1,800 mm (Extended Data Fig. 1b ), forest cover usually recovers within a few years or decades after disturbances, yet forest composition and functioning may remain degraded for decades or centuries 84 , 85 , 86 , 87 . Estimates from across the Amazon indicate that approximately 30% of areas previously deforested are in a secondary forest state 83 (covering 4% of the biome). An additional 38% of the forest biome has been damaged by extreme droughts, fires, logging and edge effects 38 , 39 . These forests may naturally regrow through forest succession, yet because of feedbacks 15 , succession can become arrested, keeping forests persistently degraded (Fig. 4 ). Different types of degraded forests have been identified in the Amazon, each one associated with a particular group of dominant opportunistic plants. For instance, Vismia forests are common in old abandoned pastures managed with fire 85 , and are relatively stable, because Vismia trees favour recruitment of Vismia seedlings in detriment of other tree species 88 , 89 . Liana forests can also be relatively stable, because lianas self-perpetuate by causing physical damage to trees, allowing lianas to remain at high density 90 , 91 . Liana forests are expected to expand with increasing aridity, disturbance regimes and CO 2 fertilization 90 . Guadua bamboo forests are common in the southwestern Amazon 92 , 93 . Similar to lianas, bamboos self-perpetuate by causing physical damage to trees and have been expanding over burnt forests in the region 92 . Degraded forests are usually dominated by native opportunistic species, and their increasing expansion over disturbed forests could affect Amazonian functioning and resilience in the future.

figure 4

From examples of disturbed forests across the Amazon, we identify the three most plausible ecosystem trajectories related to the types of disturbances, feedbacks and local environmental conditions. These alternative trajectories may be irreversible or transient depending on the strength of the novel interactions 15 . Particular combinations of interactions (arrows show positive effects described in the literature) may form feedback loops 15 that propel the ecosystem through these trajectories. In the ‘degraded forest’ trajectory, feedbacks often involve competition between trees and other opportunistic plants 85 , 90 , 92 , as well as interactions between deforestation, fire and seed limitation 84 , 87 , 105 . At the landscape scale, secondary forests are more likely to be cleared than mature forests, thus keeping forests persistently young and landscapes fragmented 83 . In the ‘degraded open-canopy ecosystem’ trajectory, feedbacks involve interactions among low tree cover and fire 97 , soil erosion 60 , seed limitation 105 , invasive grasses and opportunistic plants 96 . At the regional scale, a self-reinforcing feedback between forest loss and reduced atmospheric moisture flow may increase the resilience of these open-canopy degraded ecosystems 42 . In the ‘white-sand savanna’ trajectory, the main feedbacks result from interactions among low tree cover and fire, soil erosion, and seed limitation 106 . Bottom left, floodplain forest transition to white-sand savanna after repeated fires (photo credit: Bernardo Flores); bottom centre, forest transition to degraded open-canopy ecosystem after repeated fires (photo credit: Paulo Brando); bottom right, forest transition to Vismia degraded forest after slash-and-burn agriculture (photo credit: Catarina Jakovac).

White-sand savanna

White-sand savannas are ancient ecosystems that occur in patches within the Amazon forest biome, particularly in seasonally waterlogged or flooded areas 94 . Their origin has been attributed to geomorphological dynamics and past Indigenous fires 26 , 27 , 94 . In a remote landscape far from large agricultural frontiers, within a stable forest region of the Amazon (Extended Data Fig. 1b ), satellite and field evidence revealed that white-sand savannas are expanding where floodplain forests were repeatedly disturbed by fires 95 . After fire, the topsoil of burnt forests changes from clayey to sandy, favouring the establishment of savanna trees and native herbaceous plants 95 . Shifts from forest to white-sand savanna (Fig. 4 ) are probably stable (that is, the ecosystem is unlikely to recover back to forest within centuries), based on the relatively long persistence of these savannas in the landscape 94 . Although these ecosystem transitions have been confirmed only in the Negro river basin (central Amazon), floodplain forests in other parts of the Amazon were shown to be particularly vulnerable to collapse 45 , 64 , 65 .

Degraded open-canopy ecosystem

In bistable regions of the Amazon forest with annual rainfall below 1,800 mm (Extended Data Fig. 1b ), shifts to degraded open-canopy ecosystems are relatively common after repeated disturbances by fire 45 , 96 . The ecosystem often becomes dominated by fire-tolerant tree and palm species, together with alien invasive grasses and opportunistic herbaceous plants 96 , 97 , such as vines and ferns. Estimates from the southern Amazon indicate that 5−6% of the landscape has already shifted into degraded open-canopy ecosystems due to deforestation and fires 45 , 96 . It is still unclear, however, whether degraded open-canopy ecosystems are stable or transient (Fig. 4 ). Palaeorecords from the northern Amazon 98 show that burnt forests may spend centuries in a degraded open-canopy state before they eventually shift into a savanna. Today, invasion by alien flammable grasses is a novel stabilizing mechanism 96 , 97 , but the long-term persistence of these grasses in the ecosystem is also uncertain.

Prospects for modelling Amazon forest dynamics

Several aspects of the Amazon forest system may help improve earth system models (ESMs) to more accurately simulate ecosystem dynamics and feedbacks with the climate system. Simulating individual trees can improve the representation of growth and mortality dynamics, which ultimately affect forest dynamics (for example, refs. 61 , 62 , 99 ). Significant effects on simulation results may emerge from increasing plant functional diversity, representation of key physiological trade-offs and other features that determine water stress on plants, and also allowing for community adjustment to environmental heterogeneity and global change 32 , 55 , 62 , 99 . For now, most ESMs do not simulate a dynamic vegetation cover (Supplementary Table 1 ) and biomes are represented based on few plant functional types, basically simulating monocultures on the biome level. In reality, tree community adaptation to a heterogenous and dynamic environment feeds into the whole-system dynamics, and not covering such aspects makes a true Amazon tipping assessment more challenging.

Our findings also indicate that Amazon forest resilience is affected by compounding disturbances (Fig. 1 ). ESMs need to include different disturbance scenarios and potential synergies for creating more realistic patterns of disturbance regimes. For instance, logging and edge effects can make a forest patch more flammable 39 , but these disturbances are often not captured by ESMs. Improvements in the ability of ESMs to predict future climatic conditions are also required. One way is to identify emergent constraints 100 , lowering ESMs variations in their projections of the Amazonian climate. Also, fully coupled ESMs simulations are needed to allow estimates of land-atmosphere feedbacks, which may adjust climatic and ecosystem responses. Another way to improve our understanding of the critical thresholds for Amazonian resilience and how these link to climatic conditions and to greenhouse gas concentrations is through factorial simulations with ESMs. In sum, although our study may not deliver a set of reliable and comprehensive equations to parameterize processes impacting Amazon forest dynamics, required for implementation in ESMs, we highlight many of the missing modelled processes.

Implications for governance

Forest resilience is changing across the Amazon as disturbance regimes intensify (Fig. 1 ). Although most recent models agree that a large-scale collapse of the Amazon forest is unlikely within the twenty-first century 2 , our findings suggest that interactions and synergies among different disturbances (for example, frequent extreme hot droughts and forest fires) could trigger unexpected ecosystem transitions even in remote and central parts of the system 101 . In 2012, Davidson et al. 102 demonstrated how the Amazon basin was experiencing a transition to a ‘disturbance-dominated regime’ related to climatic and land use changes, even though at the time, annual deforestation rates were declining owing to new forms of governance 103 . Recent policy and approaches to Amazon development, however, accelerated deforestation that reached 13,000 km 2 in the Brazilian Amazon in 2021 ( http://terrabrasilis.dpi.inpe.br ). The southeastern region has already turned into a source of greenhouse gases to the atmosphere 48 . The consequences of losing the Amazon forest, or even parts of it, imply that we must follow a precautionary approach—that is, we must take actions that contribute to maintain the Amazon forest within safe boundaries 12 . Keeping the Amazon forest resilient depends firstly on humanity’s ability to stop greenhouse gas emissions, mitigating the impacts of global warming on regional climatic conditions 2 . At the local scale, two practical and effective actions need to be addressed to reinforce forest–rainfall feedbacks that are crucial for the resilience of the Amazon forest 4 , 37 : (1) ending deforestation and forest degradation; and (2) promoting forest restoration in degraded areas. Expanding protected areas and Indigenous territories can largely contribute to these actions. Our findings suggest a list of thresholds, disturbances and feedbacks that, if well managed, can help maintain the Amazon forest within a safe operating space for future generations.

Our study site was the area of the Amazon basin, considering large areas of tropical savanna biome along the northern portion of the Brazilian Cerrado, the Gran Savana in Venezuela and the Llanos de Moxos in Bolivia, as well as the Orinoco basin to the north, and eastern parts of the Andes to the west. The area includes also high Andean landscapes with puna and paramo ecosystems. We chose this contour to allow better communication with the MapBiomas Amazonian Project (2022; https://amazonia.mapbiomas.org ). For specific interpretation of our results, we considered the contour of the current extension of the Amazon forest biome, which excludes surrounding tropical savanna biomes.

We used the Moderate Resolution Imaging Spectroradiometer (MODIS) Vegetation Continuous Fields (VCF) data (MOD44B version 6; https://lpdaac.usgs.gov/products/mod44bv006/ ) for the year 2001 at 250-m resolution 124 to reanalyse tree cover distributions within the Amazon basin, refining estimates of bistability ranges and critical thresholds in rainfall conditions from previous studies. Although MODIS VCF can contain errors within lower tree cover ranges and should not be used to test for bistability between grasslands and savannas 125 , the dataset is relatively robust for assessing bistability within the tree cover range of forests and savannas 126 , as also shown by low uncertainty (standard deviation of tree cover estimates) across the Amazon (Extended Data Fig. 8 ).

We used the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS; https://www.chc.ucsb.edu/data/chirps ) 127 to estimate mean annual rainfall and rainfall seasonality for the present across the Amazon basin, based on monthly means from 1981 to 2020, at a 0.05° spatial resolution.

We used the Climatic Research Unit (CRU; https://www.uea.ac.uk/groups-and-centres/climatic-research-unit ) 128 to estimate mean annual temperature for the present across the Amazon basin, based on monthly means from 1981 to 2020, at a 0.5° spatial resolution.

To mask deforested areas until 2020, we used information from the MapBiomas Amazonia Project (2022), collection 3, of Amazonian Annual Land Cover and Land Use Map Series ( https://amazonia.mapbiomas.org ).

To assess forest fire distribution across the Amazon forest biome and in relation to road networks, we used burnt area fire data obtained from the AQUA sensor onboard the MODIS satellite. Only active fires with a confidence level of 80% or higher were selected. The data are derived from MODIS MCD14ML (collection 6) 129 , available in Fire Information for Resource Management System (FIRMS). The data were adjusted to a spatial resolution of 1 km.

Potential analysis

Using potential analysis 130 , an empirical stability landscape was constructed based on spatial distributions of tree cover (excluding areas deforested until 2020; https://amazonia.mapbiomas.org ) against mean annual precipitation, MCWD and DSL. Here we followed the methodology of Hirota et al. 104 . For bins of each of the variables, the probability density of tree cover was determined using the MATLAB function ksdensity. Local maxima of the resulting probability density function are considered to be stable equilibria, in which local maxima below a threshold value of 0.005 were ignored. Based on sensitivity tests (see below), we chose the intermediate values of the sensitivity parameter for each analysis, which resulted in the critical thresholds most similar to the ones previously published in the literature.

Sensitivity tests of the potential analysis

We smoothed the densities of tree cover with the MATLAB kernel smoothing function ksdensity. Following Hirota et al. 104 , we used a flexible bandwidth ( h ) according to Silverman’s rule of thumb 131 : h  = 1.06 σn 1/5 , where σ is the standard deviation of the tree cover distribution and n is the number of points. To ignore small bumps in the frequency distributions, we used a dimensionless sensitivity parameter. This parameter filters out weak modes in the distributions such that a higher value implies a stricter criterion to detect a significant mode. In the manuscript, we used a value of 0.005. For different values of this sensitivity parameter, we here test the estimated critical thresholds and bistability ranges (Extended Data Table 2 ). We inferred stable and unstable states of tree cover (minima and maxima in the potentials) for moving windows of the climatic variables. For mean annual precipitation, we used increments of 10 mm yr −1 between 0 and 3500 mm yr −1 . For dry season length, we used increments of 0.1 months between 0 and 12 months. For MCWD, we used increments of 10 mm between −800 mm and 0 mm.

Transition potential

We quantified a relative ecosystem transition potential across the Amazon forest biome (excluding accumulated deforestation; https://amazonia.mapbiomas.org ) to produce a simple spatial measure that can be useful for governance. For this, we combined information per pixel, at 5 km resolution, about different disturbances related to climatic and human disturbances, as well as high-governance areas within protected areas and Indigenous territories. We used values of significant slopes of the dry season (July–October) mean temperature between 1981 and 2020 ( P  < 0.1), estimated using simple linear regressions (at 0.5° resolution from CRU) (Fig. 1a ). Ecosystem stability classes (stable forest, bistable and stable savanna as in Extended Data Fig. 1 ) were estimated using simple linear regression slopes of annual rainfall between 1981 and 2020 ( P  < 0.1) (at 0.05° resolution from CHIRPS), which we extrapolated to 2050 (Fig. 1b and Extended Data Fig. 3 ). Distribution of areas affected by repeated extreme drought events (Fig. 1c ) were defined when the time series (2001–2018) of the MCWD reached two standard deviation anomalies from historical mean. Extreme droughts were obtained from Lapola et al. 39 , based on Climatic Research Unit gridded Time Series (CRU TS 4.0) datasets for precipitation and evapotranspiration. The network of roads (paved and unpaved) across the Amazon forest biome (Fig. 1d ) was obtained from the Amazon Network of Georeferenced Socio-Environmental Information (RAISG; https://geo2.socioambiental.org/raisg ). Protected areas (PAs) and Indigenous territories (Fig. 1e ) were also obtained from RAISG, and include both sustainable-use and restricted-use protected areas managed by national or sub-national governments, together with officially recognized and proposed Indigenous territories. We combined these different disturbance layers by adding a value for each layer in the following way: (1) slopes of dry season temperature change (as in Fig. 1a , multiplied by 10, thus between −0.1 and +0.6); (2) ecosystem stability classes estimated for year 2050 (as in Fig. 1b ), with 0 for stable forest, +1 for bistable and +2 for stable savanna; (3) accumulated impacts from repeated extreme drought events (from 0 to 5 events), with +0.2 for each event; (4) road-related human impacts, with +1 for pixels within 10 km from a road; and (5) protected areas and Indigenous territories as areas with lower exposure to human (land use) disturbances, such as deforestation and forest fires, with −1 for pixels inside these areas. The sum of these layers revealed relative spatial variation in ecosystem transition potential by 2050 across the Amazon (Fig. 1f ), ranging from −1 (low potential) to 4 (very high potential).

Atmospheric moisture tracking

To determine the atmospheric moisture flows between the Amazonian countries, we use the Lagrangian atmospheric moisture tracking model UTrack 132 . The model tracks the atmospheric trajectories of parcels of moisture, updates their coordinates at each time step of 0.1 h and allocates moisture to a target location in case of precipitation. For each millimetre of evapotranspiration, 100 parcels are released into the atmosphere. Their trajectories are forced with evaporation, precipitation, and wind speed estimates from the ERA5 reanalysis product at 0.25° horizontal resolution for 25 atmospheric layers 133 . Here we use the runs from Tuinenburg et al. 134 , who published monthly climatological mean (2008–2017) moisture flows between each pair of 0.5° grid cells on Earth. We aggregated these monthly flows, resulting in mean annual moisture flows between all Amazonian countries during 2008–2017. For more details of the model runs, we refer to Tuinenburg and Staal 132 and Tuinenburg et al. 134 .

Reporting summary

Further information on research design is available in the  Nature Portfolio Reporting Summary linked to this article.

Data availability

All data supporting the findings of this study are openly available and their sources are presented in the Methods.

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Acknowledgements

This work was inspired by the Science Panel for the Amazon (SPA) initiative ( https://www.theamazonwewant.org/ ) that produced the first Amazon Assessment Report (2021). The authors thank C. Smith for providing deforestation rates data used in Extended Data Fig. 5b . B.M.F. and M.H. were supported by Instituto Serrapilheira (Serra-1709-18983) and C.J. (R-2111-40341). A.S. acknowledges funding from the Dutch Research Council (NWO) under the Talent Program Grant VI.Veni.202.170. R.A.B. and D.M.L. were supported by the AmazonFACE programme funded by the UK Foreign, Commonwealth and Development Office (FCDO) and Brazilian Ministry of Science, Technology and Innovation (MCTI). R.A.B. was additionally supported by the Met Office Climate Science for Service Partnership (CSSP) Brazil project funded by the UK Department for Science, Innovation and Technology (DSIT), and D.M.L. was additionally supported by FAPESP (grant no. 2020/08940-6) and CNPq (grant no. 309074/2021-5). C.L. thanks CNPq (proc. 159440/2018-1 and 400369/2021-4) and Brazil LAB (Princeton University) for postdoctoral fellowships. A.E.-M. is supported by the UKRI TreeScapes MEMBRA (NE/V021346/1), the Royal Society (RGS\R1\221115), the ERC TreeMort project (758873) and the CESAB Syntreesys project. R.S.O. received a CNPq productivity scholarship and funding from NERC-FAPESP 2019/07773-1. S.B.H. is supported by the Geneva Graduate Institute research funds, and UCLA’s committee on research. J.A.M. is supported by the National Institute of Science and Technology for Climate Change Phase 2 under CNPq grant 465501/2014-1; FAPESP grants 2014/50848-9, the National Coordination for Higher Education and Training (CAPES) grant 88887.136402-00INCT. L.S.B. received FAPESP grant 2013/50531-0. D.N. and N.B. acknowledge funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 820970. N.B. has received further funding from the Volkswagen foundation, the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement no. 956170, as well as from the German Federal Ministry of Education and Research under grant no. 01LS2001A.

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Graduate Program in Ecology, Federal University of Santa Catarina, Florianopolis, Brazil

Bernardo M. Flores, Carolina Levis & Marina Hirota

Geosciences Barcelona, Spanish National Research Council, Barcelona, Spain

Encarni Montoya

Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, Potsdam, Germany

Boris Sakschewski, Da Nian & Niklas Boers

Institute of Advanced Studies, University of São Paulo, São Paulo, Brazil

Nathália Nascimento & Carlos A. Nobre

Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, The Netherlands

Met Office Hadley Centre, Exeter, UK

Richard A. Betts

Global Systems Institute, University of Exeter, Exeter, UK

Center for Meteorological and Climatic Research Applied to Agriculture, University of Campinas, Campinas, Brazil

David M. Lapola

School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK

Adriane Esquível-Muelbert

Birmingham Institute of Forest Research, University of Birmingham, Birmingham, UK

Department of Plant Sciences, Federal University of Santa Catarina, Florianopolis, Brazil

Catarina Jakovac

Department of Plant Biology, University of Campinas, Campinas, Brazil

Rafael S. Oliveira & Marina Hirota

Division of Impacts, Adaptation and Vulnerabilities (DIIAV), National Institute for Space Research, São José dos Campos, Brazil

Laura S. Borma & Luciana V. Gatti

Earth System Modelling, School of Engineering and Design, Technical University of Munich, Munich, Germany

Niklas Boers

Luskin School for Public Affairs and Institute of the Environment, University of California, Los Angeles, CA, USA

Susanna B. Hecht

Naturalis Biodiversity Center, Leiden, The Netherlands

Hans ter Steege

Quantitative Biodiversity Dynamics, Utrecht University, Utrecht, The Netherlands

Science Panel for the Amazon (SPA), São José dos Campos, Brazil

Julia Arieira

Sustainable Development Solutions Network, New York, NY, USA

Isabella L. Lucas

Environmental Change Institute, University of Oxford, Oxford, UK

Erika Berenguer

Centro Nacional de Monitoramento e Alerta de Desastres Naturais, São José dos Campos, Brazil

José A. Marengo

Graduate Program in Natural Disasters, UNESP/CEMADEN, São José dos Campos, Brazil

Graduate School of International Studies, Korea University, Seoul, Korea

Program in Atmospheric and Oceanic Sciences, Princeton University, Princeton, NJ, USA

Caio R. C. Mattos

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Contributions

B.M.F. and M.H. conceived the study. B.M.F. reviewed the literature, with inputs from all authors. B.M.F., M.H., N.N., A.S., C.L., D.N, H.t.S. and C.R.C.M. assembled datasets. M.H. analysed temperature and rainfall trends. B.M.F. and N.N. produced the maps in main figures and calculated transition potential. A.S. performed potential analysis and atmospheric moisture tracking. B.M.F. produced the figures and wrote the manuscript, with substantial inputs from all authors. B.S. wrote the first version of the ‘Prospects for modelling Amazon forest dynamics’ section, with inputs from B.M.F and M.H.

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Correspondence to Bernardo M. Flores or Marina Hirota .

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Extended data figures and tables

Extended data fig. 1 alternative stable states in amazonian tree cover relative to rainfall conditions..

Potential analysis of tree cover distributions across rainfall gradients in the Amazon basin suggest the existence of critical thresholds and alternative stable states in the system. For this, we excluded accumulated deforestation until 2020 and included large areas of tropical savanna biome in the periphery of the Amazon basin (see  Methods ). Solid black lines indicate two stable equilibria. Small grey arrows indicate the direction towards equilibrium. (a) The overlap between ~ 1,000 and 1,800 mm of annual rainfall suggests that two alternative stable states may exist (bistability): a high tree cover state ~ 80 % (forests), and a low tree cover state ~ 20% (savannas). Tree cover around 50 % is rare, indicating an unstable state. Below 1,000 mm of annual rainfall, forests are rare, indicating a potential critical threshold for abrupt forest transition into a low tree cover state 79 , 104 (arrow 1). Between 1,000 and 1,800 mm of annual rainfall, the existence of alternative stable states implies that forests can shift to a low tree cover stable state in response to disturbances (arrow 2). Above 1,800 mm of annual rainfall, low tree cover becomes rare, indicating a potential critical threshold for an abrupt transition into a high tree cover state. In this stable forest state, forests are expected to always recover after disturbances (arrow 3), although composition may change 47 , 85 . (b) Currently, the stable savanna state covers 1 % of the Amazon forest biome, bistable areas cover 13 % of the biome (less than previous analysis using broader geographical ranges 78 ) and the stable forest state covers 86 % of the biome. Similar analyses using the maximum cumulative water deficit (c) and the dry season length (d) also suggest the existence of critical thresholds and alternative stable states. When combined, these critical thresholds in rainfall conditions could result in a tipping point of the Amazon forest in terms of water stress, but other factors may play a role, such as groundwater availability 64 . MODIS VCF may contain some level of uncertainty for low tree cover values, as shown by the standard deviation of tree cover estimates across the Amazon (Extended Data Fig. 8 ). However, the dataset is relatively robust for assessing bistability within the tree cover range between forest and savanna 126 .

Extended Data Fig. 2 Changes in dry-season temperatures across the Amazon basin.

(a) Dry season temperature averaged from mean annual data observed between 1981 and 2010. (b) Changes in dry season mean temperature based on the difference between the projected future (2021−2050) and observed historical (1981−2010) climatologies. Future climatology was obtained from the estimated slopes using historical CRU data 128 (shown in Fig. 1a ). (c, d) Changes in the distributions of dry season mean and maximum temperatures for the Amazon basin. (e) Correlation between dry-season mean and maximum temperatures observed (1981–2010) across the Amazon basin ( r  = 0.95).

Extended Data Fig. 3 Changes in annual precipitation and ecosystem stability across the Amazon forest biome.

(a) Slopes of annual rainfall change between 1981 and 2020 estimated using simple regressions (only areas with significant slopes, p  < 0.1). (b) Changes in ecosystem stability classes projected for year 2050, based on significant slopes in (a) and critical thresholds in annual rainfall conditions estimated in Extended Data Fig. 1 . Data obtained from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), at 0.05° spatial resolution 127 .

Extended Data Fig. 4 Changes in ecosystem stability by 2050 across the Amazon based on annual rainfall projected by CMIP6 models.

(a) Changes in stability classes estimated using an ensemble with the five CMIP6 models that include vegetation modules (coupled for climate-vegetation feedbacks) for two emission scenarios (Shared Socio-economic Pathways - SSPs). (b) Changes in stability classes estimated using an ensemble with all 33 CMIP6 models for the same emission scenarios. Stability changes may occur between stable forest (F), stable savanna (S) and bistable (B) classes, based on the bistability range of 1,000 – 1,800 mm in annual rainfall, estimated from current rainfall conditions (see Extended Data Fig. 1 ). Projections are based on climate models from the 6 th Phase of the Coupled Model Intercomparison Project (CMIP6). SSP2-4.5 is a low-emission scenario of future global warming and SSP5-8.5 is a high-emission scenario. The five coupled models analysed separately in (a) were: EC-Earth3-Veg, GFDL-ESM4, MPI-ESM1-2-LR, TaiESM1 and UKESM1-0-LL (Supplementary Information Table 1 ).

Extended Data Fig. 5 Deforestation continues to expand within the Amazon forest system.

(a) Map highlighting deforestation and fire activity between 2012 and 2021, a period when environmental governance began to weaken again, as indicated by increasing rates of annual deforestation in (b). In (b), annual deforestation rates for the entire Amazon biome were adapted with permission from Smith et al. 83 .

Extended Data Fig. 6 Environmental heterogeneity in the Amazon forest system.

Heterogeneity involves myriad factors, but two in particular, related to water availability, were shown to contribute to landscape-scale heterogeneity in forest resilience; topography shapes fine-scale variations of forest drought-tolerance 135 , 136 , and floodplains may reduce forest resilience by increasing vulnerability to wildfires 65 . Datasets: topography is shown by the Shuttle Radar Topography Mission (SRTM; https://earthexplorer.usgs.gov/ ) 137 at 90 m resolution; floodplains and uplands are separated with the Amazon wetlands mask 138 at 90 m resolution.

Extended Data Fig. 7 The Amazon is biologically and culturally diverse.

(a) Tree species richness and (b) language richness illustrate how biological and cultural diversity varies across the Amazon. Diverse tree communities and human cultures contribute to increasing forest resilience in various ways that are being undermined by land-use and climatic changes. Datasets: (a) Amazon Tree Diversity Network (ATDN, https://atdn.myspecies.info ). (b) World Language Mapping System (WLMS) obtained under license from Ethnologue 139 .

Extended Data Fig. 8 Uncertainty of the MODIS VCF dataset across the Amazon basin.

Map shows standard deviation (SD) of tree cover estimates from MODIS VCF 124 . We masked deforested areas until 2020 using the MapBiomas Amazonia Project (2022; https://amazonia.mapbiomas.org ).

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Flores, B.M., Montoya, E., Sakschewski, B. et al. Critical transitions in the Amazon forest system. Nature 626 , 555–564 (2024). https://doi.org/10.1038/s41586-023-06970-0

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Continuing to enhance the quality of case study methodology in health services research

Shannon l. sibbald.

1 Faculty of Health Sciences, Western University, London, Ontario, Canada.

2 Department of Family Medicine, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.

3 The Schulich Interfaculty Program in Public Health, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.

Stefan Paciocco

Meghan fournie, rachelle van asseldonk, tiffany scurr.

Case study methodology has grown in popularity within Health Services Research (HSR). However, its use and merit as a methodology are frequently criticized due to its flexible approach and inconsistent application. Nevertheless, case study methodology is well suited to HSR because it can track and examine complex relationships, contexts, and systems as they evolve. Applied appropriately, it can help generate information on how multiple forms of knowledge come together to inform decision-making within healthcare contexts. In this article, we aim to demystify case study methodology by outlining its philosophical underpinnings and three foundational approaches. We provide literature-based guidance to decision-makers, policy-makers, and health leaders on how to engage in and critically appraise case study design. We advocate that researchers work in collaboration with health leaders to detail their research process with an aim of strengthening the validity and integrity of case study for its continued and advanced use in HSR.

Introduction

The popularity of case study research methodology in Health Services Research (HSR) has grown over the past 40 years. 1 This may be attributed to a shift towards the use of implementation research and a newfound appreciation of contextual factors affecting the uptake of evidence-based interventions within diverse settings. 2 Incorporating context-specific information on the delivery and implementation of programs can increase the likelihood of success. 3 , 4 Case study methodology is particularly well suited for implementation research in health services because it can provide insight into the nuances of diverse contexts. 5 , 6 In 1999, Yin 7 published a paper on how to enhance the quality of case study in HSR, which was foundational for the emergence of case study in this field. Yin 7 maintains case study is an appropriate methodology in HSR because health systems are constantly evolving, and the multiple affiliations and diverse motivations are difficult to track and understand with traditional linear methodologies.

Despite its increased popularity, there is debate whether a case study is a methodology (ie, a principle or process that guides research) or a method (ie, a tool to answer research questions). Some criticize case study for its high level of flexibility, perceiving it as less rigorous, and maintain that it generates inadequate results. 8 Others have noted issues with quality and consistency in how case studies are conducted and reported. 9 Reporting is often varied and inconsistent, using a mix of approaches such as case reports, case findings, and/or case study. Authors sometimes use incongruent methods of data collection and analysis or use the case study as a default when other methodologies do not fit. 9 , 10 Despite these criticisms, case study methodology is becoming more common as a viable approach for HSR. 11 An abundance of articles and textbooks are available to guide researchers through case study research, including field-specific resources for business, 12 , 13 nursing, 14 and family medicine. 15 However, there remains confusion and a lack of clarity on the key tenets of case study methodology.

Several common philosophical underpinnings have contributed to the development of case study research 1 which has led to different approaches to planning, data collection, and analysis. This presents challenges in assessing quality and rigour for researchers conducting case studies and stakeholders reading results.

This article discusses the various approaches and philosophical underpinnings to case study methodology. Our goal is to explain it in a way that provides guidance for decision-makers, policy-makers, and health leaders on how to understand, critically appraise, and engage in case study research and design, as such guidance is largely absent in the literature. This article is by no means exhaustive or authoritative. Instead, we aim to provide guidance and encourage dialogue around case study methodology, facilitating critical thinking around the variety of approaches and ways quality and rigour can be bolstered for its use within HSR.

Purpose of case study methodology

Case study methodology is often used to develop an in-depth, holistic understanding of a specific phenomenon within a specified context. 11 It focuses on studying one or multiple cases over time and uses an in-depth analysis of multiple information sources. 16 , 17 It is ideal for situations including, but not limited to, exploring under-researched and real-life phenomena, 18 especially when the contexts are complex and the researcher has little control over the phenomena. 19 , 20 Case studies can be useful when researchers want to understand how interventions are implemented in different contexts, and how context shapes the phenomenon of interest.

In addition to demonstrating coherency with the type of questions case study is suited to answer, there are four key tenets to case study methodologies: (1) be transparent in the paradigmatic and theoretical perspectives influencing study design; (2) clearly define the case and phenomenon of interest; (3) clearly define and justify the type of case study design; and (4) use multiple data collection sources and analysis methods to present the findings in ways that are consistent with the methodology and the study’s paradigmatic base. 9 , 16 The goal is to appropriately match the methods to empirical questions and issues and not to universally advocate any single approach for all problems. 21

Approaches to case study methodology

Three authors propose distinct foundational approaches to case study methodology positioned within different paradigms: Yin, 19 , 22 Stake, 5 , 23 and Merriam 24 , 25 ( Table 1 ). Yin is strongly post-positivist whereas Stake and Merriam are grounded in a constructivist paradigm. Researchers should locate their research within a paradigm that explains the philosophies guiding their research 26 and adhere to the underlying paradigmatic assumptions and key tenets of the appropriate author’s methodology. This will enhance the consistency and coherency of the methods and findings. However, researchers often do not report their paradigmatic position, nor do they adhere to one approach. 9 Although deliberately blending methodologies may be defensible and methodologically appropriate, more often it is done in an ad hoc and haphazard way, without consideration for limitations.

Cross-analysis of three case study approaches, adapted from Yazan 2015

The post-positive paradigm postulates there is one reality that can be objectively described and understood by “bracketing” oneself from the research to remove prejudice or bias. 27 Yin focuses on general explanation and prediction, emphasizing the formulation of propositions, akin to hypothesis testing. This approach is best suited for structured and objective data collection 9 , 11 and is often used for mixed-method studies.

Constructivism assumes that the phenomenon of interest is constructed and influenced by local contexts, including the interaction between researchers, individuals, and their environment. 27 It acknowledges multiple interpretations of reality 24 constructed within the context by the researcher and participants which are unlikely to be replicated, should either change. 5 , 20 Stake and Merriam’s constructivist approaches emphasize a story-like rendering of a problem and an iterative process of constructing the case study. 7 This stance values researcher reflexivity and transparency, 28 acknowledging how researchers’ experiences and disciplinary lenses influence their assumptions and beliefs about the nature of the phenomenon and development of the findings.

Defining a case

A key tenet of case study methodology often underemphasized in literature is the importance of defining the case and phenomenon. Researches should clearly describe the case with sufficient detail to allow readers to fully understand the setting and context and determine applicability. Trying to answer a question that is too broad often leads to an unclear definition of the case and phenomenon. 20 Cases should therefore be bound by time and place to ensure rigor and feasibility. 6

Yin 22 defines a case as “a contemporary phenomenon within its real-life context,” (p13) which may contain a single unit of analysis, including individuals, programs, corporations, or clinics 29 (holistic), or be broken into sub-units of analysis, such as projects, meetings, roles, or locations within the case (embedded). 30 Merriam 24 and Stake 5 similarly define a case as a single unit studied within a bounded system. Stake 5 , 23 suggests bounding cases by contexts and experiences where the phenomenon of interest can be a program, process, or experience. However, the line between the case and phenomenon can become muddy. For guidance, Stake 5 , 23 describes the case as the noun or entity and the phenomenon of interest as the verb, functioning, or activity of the case.

Designing the case study approach

Yin’s approach to a case study is rooted in a formal proposition or theory which guides the case and is used to test the outcome. 1 Stake 5 advocates for a flexible design and explicitly states that data collection and analysis may commence at any point. Merriam’s 24 approach blends both Yin and Stake’s, allowing the necessary flexibility in data collection and analysis to meet the needs.

Yin 30 proposed three types of case study approaches—descriptive, explanatory, and exploratory. Each can be designed around single or multiple cases, creating six basic case study methodologies. Descriptive studies provide a rich description of the phenomenon within its context, which can be helpful in developing theories. To test a theory or determine cause and effect relationships, researchers can use an explanatory design. An exploratory model is typically used in the pilot-test phase to develop propositions (eg, Sibbald et al. 31 used this approach to explore interprofessional network complexity). Despite having distinct characteristics, the boundaries between case study types are flexible with significant overlap. 30 Each has five key components: (1) research question; (2) proposition; (3) unit of analysis; (4) logical linking that connects the theory with proposition; and (5) criteria for analyzing findings.

Contrary to Yin, Stake 5 believes the research process cannot be planned in its entirety because research evolves as it is performed. Consequently, researchers can adjust the design of their methods even after data collection has begun. Stake 5 classifies case studies into three categories: intrinsic, instrumental, and collective/multiple. Intrinsic case studies focus on gaining a better understanding of the case. These are often undertaken when the researcher has an interest in a specific case. Instrumental case study is used when the case itself is not of the utmost importance, and the issue or phenomenon (ie, the research question) being explored becomes the focus instead (eg, Paciocco 32 used an instrumental case study to evaluate the implementation of a chronic disease management program). 5 Collective designs are rooted in an instrumental case study and include multiple cases to gain an in-depth understanding of the complexity and particularity of a phenomenon across diverse contexts. 5 , 23 In collective designs, studying similarities and differences between the cases allows the phenomenon to be understood more intimately (for examples of this in the field, see van Zelm et al. 33 and Burrows et al. 34 In addition, Sibbald et al. 35 present an example where a cross-case analysis method is used to compare instrumental cases).

Merriam’s approach is flexible (similar to Stake) as well as stepwise and linear (similar to Yin). She advocates for conducting a literature review before designing the study to better understand the theoretical underpinnings. 24 , 25 Unlike Stake or Yin, Merriam proposes a step-by-step guide for researchers to design a case study. These steps include performing a literature review, creating a theoretical framework, identifying the problem, creating and refining the research question(s), and selecting a study sample that fits the question(s). 24 , 25 , 36

Data collection and analysis

Using multiple data collection methods is a key characteristic of all case study methodology; it enhances the credibility of the findings by allowing different facets and views of the phenomenon to be explored. 23 Common methods include interviews, focus groups, observation, and document analysis. 5 , 37 By seeking patterns within and across data sources, a thick description of the case can be generated to support a greater understanding and interpretation of the whole phenomenon. 5 , 17 , 20 , 23 This technique is called triangulation and is used to explore cases with greater accuracy. 5 Although Stake 5 maintains case study is most often used in qualitative research, Yin 17 supports a mix of both quantitative and qualitative methods to triangulate data. This deliberate convergence of data sources (or mixed methods) allows researchers to find greater depth in their analysis and develop converging lines of inquiry. For example, case studies evaluating interventions commonly use qualitative interviews to describe the implementation process, barriers, and facilitators paired with a quantitative survey of comparative outcomes and effectiveness. 33 , 38 , 39

Yin 30 describes analysis as dependent on the chosen approach, whether it be (1) deductive and rely on theoretical propositions; (2) inductive and analyze data from the “ground up”; (3) organized to create a case description; or (4) used to examine plausible rival explanations. According to Yin’s 40 approach to descriptive case studies, carefully considering theory development is an important part of study design. “Theory” refers to field-relevant propositions, commonly agreed upon assumptions, or fully developed theories. 40 Stake 5 advocates for using the researcher’s intuition and impression to guide analysis through a categorical aggregation and direct interpretation. Merriam 24 uses six different methods to guide the “process of making meaning” (p178) : (1) ethnographic analysis; (2) narrative analysis; (3) phenomenological analysis; (4) constant comparative method; (5) content analysis; and (6) analytic induction.

Drawing upon a theoretical or conceptual framework to inform analysis improves the quality of case study and avoids the risk of description without meaning. 18 Using Stake’s 5 approach, researchers rely on protocols and previous knowledge to help make sense of new ideas; theory can guide the research and assist researchers in understanding how new information fits into existing knowledge.

Practical applications of case study research

Columbia University has recently demonstrated how case studies can help train future health leaders. 41 Case studies encompass components of systems thinking—considering connections and interactions between components of a system, alongside the implications and consequences of those relationships—to equip health leaders with tools to tackle global health issues. 41 Greenwood 42 evaluated Indigenous peoples’ relationship with the healthcare system in British Columbia and used a case study to challenge and educate health leaders across the country to enhance culturally sensitive health service environments.

An important but often omitted step in case study research is an assessment of quality and rigour. We recommend using a framework or set of criteria to assess the rigour of the qualitative research. Suitable resources include Caelli et al., 43 Houghten et al., 44 Ravenek and Rudman, 45 and Tracy. 46

New directions in case study

Although “pragmatic” case studies (ie, utilizing practical and applicable methods) have existed within psychotherapy for some time, 47 , 48 only recently has the applicability of pragmatism as an underlying paradigmatic perspective been considered in HSR. 49 This is marked by uptake of pragmatism in Randomized Control Trials, recognizing that “gold standard” testing conditions do not reflect the reality of clinical settings 50 , 51 nor do a handful of epistemologically guided methodologies suit every research inquiry.

Pragmatism positions the research question as the basis for methodological choices, rather than a theory or epistemology, allowing researchers to pursue the most practical approach to understanding a problem or discovering an actionable solution. 52 Mixed methods are commonly used to create a deeper understanding of the case through converging qualitative and quantitative data. 52 Pragmatic case study is suited to HSR because its flexibility throughout the research process accommodates complexity, ever-changing systems, and disruptions to research plans. 49 , 50 Much like case study, pragmatism has been criticized for its flexibility and use when other approaches are seemingly ill-fit. 53 , 54 Similarly, authors argue that this results from a lack of investigation and proper application rather than a reflection of validity, legitimizing the need for more exploration and conversation among researchers and practitioners. 55

Although occasionally misunderstood as a less rigourous research methodology, 8 case study research is highly flexible and allows for contextual nuances. 5 , 6 Its use is valuable when the researcher desires a thorough understanding of a phenomenon or case bound by context. 11 If needed, multiple similar cases can be studied simultaneously, or one case within another. 16 , 17 There are currently three main approaches to case study, 5 , 17 , 24 each with their own definitions of a case, ontological and epistemological paradigms, methodologies, and data collection and analysis procedures. 37

Individuals’ experiences within health systems are influenced heavily by contextual factors, participant experience, and intricate relationships between different organizations and actors. 55 Case study research is well suited for HSR because it can track and examine these complex relationships and systems as they evolve over time. 6 , 7 It is important that researchers and health leaders using this methodology understand its key tenets and how to conduct a proper case study. Although there are many examples of case study in action, they are often under-reported and, when reported, not rigorously conducted. 9 Thus, decision-makers and health leaders should use these examples with caution. The proper reporting of case studies is necessary to bolster their credibility in HSR literature and provide readers sufficient information to critically assess the methodology. We also call on health leaders who frequently use case studies 56 – 58 to report them in the primary research literature.

The purpose of this article is to advocate for the continued and advanced use of case study in HSR and to provide literature-based guidance for decision-makers, policy-makers, and health leaders on how to engage in, read, and interpret findings from case study research. As health systems progress and evolve, the application of case study research will continue to increase as researchers and health leaders aim to capture the inherent complexities, nuances, and contextual factors. 7

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  • Volume 33, Issue 3
  • What can Safety Cases offer for patient safety? A multisite case study
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  • http://orcid.org/0000-0003-4981-1210 Elisa Giulia Liberati 1 ,
  • http://orcid.org/0000-0003-1979-7577 Graham P Martin 1 ,
  • http://orcid.org/0000-0001-9514-1890 Guillaume Lamé 1 , 2 ,
  • Justin Waring 3 ,
  • http://orcid.org/0000-0001-7356-5342 Carolyn Tarrant 4 ,
  • http://orcid.org/0000-0002-7886-3223 Janet Willars 4 ,
  • Mary Dixon-Woods 1
  • 1 THIS Institute (The Healthcare Improvement Studies Institute), Department of Public Health and Primary Care , University of Cambridge , Cambridge , UK
  • 2 Laboratoire Genie Industriel , CentraleSupélec, Paris Saclay University , Gif-sur-Yvette , France
  • 3 Health Services Management Centre , University of Birmingham , Birmingham , UK
  • 4 Department of Population Health Sciences , University of Leicester , Leicester , UK
  • Correspondence to Dr Elisa Giulia Liberati, THIS Institute (Public Health and Primary Care), University of Cambridge, Cambridge, UK; elisa.liberati{at}thisinstitute.cam.ac.uk

Background The Safety Case is a regulatory technique that requires organisations to demonstrate to regulators that they have systematically identified hazards in their systems and reduced risks to being as low as reasonably practicable. It is used in several high-risk sectors, but only in a very limited way in healthcare. We examined the first documented attempt to apply the Safety Case methodology to clinical pathways.

Methods Data are drawn from a mixed-methods evaluation of the Safer Clinical Systems programme. The development of a Safety Case for a defined clinical pathway was a centrepiece of the programme. We base our analysis on 143 interviews covering all aspects of the programme and on analysis of 13 Safety Cases produced by clinical teams.

Results The principles behind a proactive, systematic approach to identifying and controlling risk that could be curated in a single document were broadly welcomed by participants, but was not straightforward to deliver. Compiling Safety Cases helped teams to identify safety hazards in clinical pathways, some of which had been previously occluded. However, the work of compiling Safety Cases was demanding of scarce skill and resource. Not all problems identified through proactive methods were tractable to the efforts of front-line staff. Some persistent hazards, originating from institutional and organisational vulnerabilities, appeared also to be out of the scope of control of even the board level of organisations. A particular dilemma for organisational senior leadership was whether to prioritise fixing the risks proactively identified in Safety Cases over other pressing issues, including those that had already resulted in harm.

Conclusions The Safety Case approach was recognised by those involved in the Safer Clinical Systems programme as having potential value. However, it is also fraught with challenge, highlighting the limitations of efforts to transfer safety management practices to healthcare from other sectors.

  • Patient safety
  • Qualitative research
  • Risk management

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https://doi.org/10.1136/bmjqs-2023-016042

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WHAT IS ALREADY KNOWN ON THIS TOPIC

Safety Cases are a well-established regulatory technique in some areas, requiring organisations to make the case to the relevant regulator that they have put in place adequate measures to reduce risks in their systems to a level ‘as low as reasonably practicable’ (ALARP).

Importing of safety practices from other sectors has a long track record in healthcare, but little is known about the potential of the Safety Case approach when applied to clinical pathways.

WHAT THIS STUDY ADDS

It was difficult for clinical teams to use the Safety Case as intended (to show that risks had been reduced to ALARP), not least because they often identified issues that front-line staff could not address.

Safety Cases were sometimes used instead to attract senior leaders’ attention and to make the case for better support and resourcing, but some issues were beyond the control even of organisational leadership.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

Safety Cases may have some potential in healthcare, but their optimal use in this sector may require modifications, particularly if they are considered for regulatory purposes.

Introduction

Patient safety remains a major challenge for healthcare, despite more than two decades of sustained policy, practice and research attention. 1 2 The initial enthusiasm for borrowing practices and methods from other safety-critical industries (such as aviation) at the outset of the patient safety movement 3–5 has been tempered by experience. 6–12 It is now widely recognised that attempts to transfer approaches between contexts require care and caution, and should be supported by theory and empirical evaluation. 13–15 This paper seeks to contribute to addressing this need through examination of an attempt to introduce into healthcare a specific safety approach—the Safety Case—that is already used in other industries (including oil, transport and mining) both as a regulatory technique, 16 and, more rarely, as a quality management approach without regulatory mandate (eg, in the automotive industry). 17 18

The specifics of the Safety Case approach vary between sectors and regulators, 19 but the general principles are listed in box 1 . In brief, a claim to operational safety is justified through a series of linked arguments that explain how safety has been secured, with supporting evidence , including the processes in place to control risk. Where used as a regulatory technique, Safety Cases are produced by organisations to ‘make the case’ to the relevant regulator that they have put in place adequate measures to reduce risks in a product or system to a level ‘as low as reasonably practicable’ (often abbreviated as ALARP). The regulator then reviews the Safety Case and either grants the organisation licence to operate, or may require further risk assessments, justification of the measures proposed or additional risk mitigations. 20

Typical features of safety cases

Safety Cases are developed to ‘make the case’ that risk has been reduced to a level ‘as low as reasonably practicable’ (ALARP). To do so, Safety Cases integrate various forms of prospective risk management analysis, based on the idea that operators are better placed than external regulators to assess risks in their own systems. The core of the Safety Case is typically a risk-based argument and corresponding evidence to demonstrate that all risks associated with a particular system have been identified, that appropriate risk controls have been put in place, and that there are appropriate processes in place to monitor the effectiveness of the risk controls and the safety performance of the system on an ongoing basis. 23

Safety cases typically contain:

A description of the system and its operational context;

How safe the system is claimed to be and the criteria by which safety is assessed;

How hazards have been identified and how the risks they pose have been assessed;

What kind of risk control measures have been put into place and why they are effective; and

Why the residual level of risk is acceptable. 23

Safety Cases are typically reviewed and assessed by an external regulator, for example, in the nuclear or petrochemical industries in the UK. However, some industrial sectors have also deployed the approach outside of a regulatory requirement. For example, the automotive industry uses Safety Cases that are part of the ISO26262 standard, but this is not mandated by regulators. 17 18

As an approach requiring organisations to proactively describe what procedures and actions they are putting in place to control risk, Safety Cases can be contrasted with prescriptive, compliance-oriented approaches, where organisations are required to show that they have met externally imposed safety standards. 21 Because they are written for a specific system and its context of use, they are intended to be more adaptable to specific situations than generic safety standards, and also more responsive to rapid change in technologies or practices. 22

On the face of it, the Safety Case would appear to have value as an approach to safety management in healthcare, particularly in its potential for prospective identification and control of risk. However, the Safety Case approach has only rarely been used in healthcare, and only in a very limited number of applications (eg, development of information systems and medical devices). 23 24 In this article, we develop an analysis of the application the Safety Case approach within the UK National Health Service (NHS) using a case study of the first documented attempt to apply the principles of the methodology to clinical pathways. As the approach was deployed outside a regulatory context, our analysis focuses on the transferability of an approach to risk management that is proactive, structured, and tailored in nature and that presents evidence about the safety of specific clinical systems and existing mitigations in a single ‘case’ document.

Case study: the Safer Clinical Systems programme

Our analysis draws on an evaluation we conducted of a programme known as Safer Clinical Systems, which is designed to improve the safety and reliability of clinical pathways based on learning adapted from a range of hazardous industries. It seeks to enable organisations to make improvements to local clinical systems and pathways through a structured methodology for identifying risks and re-engineering systems to control risk and enhance resilience. 25 26 Use of the principles of the Safety Case approach is a centrepiece of the Safer Clinical Systems programme, although outside a regulatory context.

Funded by the Health Foundation, the Safer Clinical Systems programme was developed by a team at Warwick University and tested over a number of phases. Following initial development, a ‘testing phase’ involving eight NHS hospital sites (seven in England, one in Scotland) ran from 2011 to 2014. An ‘extension phase’ (2014 to 2016) involved further work by five of these sites and one new site.

Each participating hospital site ( table 1 ) was required to establish a multidisciplinary clinical team. Sites in the testing phase were advised by a support team of clinicians and experts, received inperson training, had access to other resources (such as a reference manual and telephone support) and were required to report their progress regularly. Sites in the extension phase had less bespoke support and were expected instead to build on their previous learning.

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Sites involved in the programme

A requirement of participating teams was that they use the Safer Clinical Systems approach to proactively assess risks and hazards in their clinical pathways and that they produce Safety Cases at the end of their projects describing the risks and how they were being mitigated. The Safety Cases were expected to be similar in format to those used in other sectors, 27 comprising a description of the clinical pathway covered, the key hazards identified through structured analysis using prescribed tools, the risk controls implemented, and, critically, a ‘safety claim’ and associated ‘confidence argument’—a pronouncement on the current safety of the system concerned, and a statement explaining how risks had been made ALARP. Rather than being presented to an external regulator, as would be the case if the Safety Case were being used as a regulatory technique, the principal intended audience in this programme was the senior leadership (executive and board level) within organisations.

Evaluation methods

To study the testing and extension phases of the Safer Clinical Systems programme, we used a mixed-methods, longitudinal design, involving interviews, ethnographic observations, and documentary analysis across the nine participating sites. The analysis we report here is based primarily on interviews and documentary analysis. Ethnographic observations (over 850 hours) provided valuable data on how clinical teams carried out their Safer Clinical Systems projects in practice in the context of existing and competing demands, but are not reported in detail here.

Across the nine sites, we conducted 89 semistructured interviews in the testing phase and 39 in the extension phase with participating clinical team members and programme leaders. Sampling at the sites sought to purposefully include a range of different roles in the programme, including the clinical leaders of each project and others. We also conducted 5 semistructured interviews in the testing phase, followed by 10 in the extension phase, with organisational senior leadership, comprising executive team/board members. Interviews explored general experiences of the programme as well as specific exploration of using the Safety Case approach. Participants were informed of the aims and commissioners of the evaluation. All interviews were conducted by experienced social scientists using topic guides ( online supplemental material 1 ). Interviews were conducted either in person or by telephone, between November 2012 and June 2016, and were digitally audio recorded and then transcribed for analysis.

Supplemental material

Analysis, conducted by EL and guided by the wider team, was based on the constant comparative method 28 combining inductive and deductive approaches. We coded interviews and observations using an inductive approach, deriving codes directly from each interview and then progressively clustering codes in higher order categories and themes. To strengthen explanatory power, this inductive strategy was complemented by theoretical concepts drawn from the wider literature.

GL and EL conducted a documentary analysis of the Safety Cases prepared by the clinical teams ( table 2 ). We used recommendations and guidelines for writing and maintaining safety cases in other sectors, 29–31 to organise the Safety Cases’ content thematically, and identified their main strengths and weaknesses in terms of completeness, presence of appropriate evidence and analyses to support the claims, consistency with the site’s safety improvement objectives, readability, and presence of a safety claim and confidence argument.

Format and content of 13 Safety Cases reviewed

Finally, we organised our higher order themes and overall reflections using concepts and themes proposed by recent works on the topic. 19 32 Regular team meetings and correspondence provided oversight of the analytical approach, consistency and adequacy of codes, and reporting. Given the nature of the programme, we did not undertake a formal test for theoretical saturation for the interviews or the Safety Cases.

Across the testing and extension phases of Safer Clinical Systems, we undertook 143 interviews with participants across programme leadership, clinical teams and organisational leadership. We analysed 13 submitted Safety Cases; although 14 should have been developed, one site from the extension phase struggled to implement the programme in full and did not produce a Safety Case.

In presenting our analysis below, we consider, first, participants’ views on the Safety Case as a novel approach to understanding and managing safety risk in healthcare, and second, the work that went into developing Safety Cases. We then turn to the analysis of Safety Cases themselves.

Views on the value of safety cases

By the end of the programme, members of the project teams and senior leadership in the participating organisations had largely come to see the Safety Case as a valuable approach, with the potential to make hazards visible in an accountable, systematic and scientific way. The analytical steps required to compile a Safety Case, such as process mapping the patient pathway, were seen to be particularly useful in proactively identifying threats to safety, rather than reactively managing incidents once they had happened. The role of Safety Cases in enabling an overarching, system-wide view of the hazards, rather than focusing on what happens in particular segments of the pathway, was also welcomed. Broadly, teams valued the possibilities of new ways of thinking about risk.

I like the idea that you just have one document that you can hand to somebody and say how safe is your system. I like the concept that you can say ‘Well this is what our system is like just now’. (Project participant)

Some organisational senior leaders agreed, at least in principle, that Safety Cases could offer value, and recognised the importance of a prospective approach to safety.

We have immensely complex systems which could be simplified and therefore made a bit more reliable. […] So something which looks at that could certainly be a useful thing, because it’s saying ‘Well actually here is a little nest of complexity which you can reduce, but it’s also a significant risk to the patient, because you’re missing information or you’re hurrying things through.’ […] (Senior leader)

Other senior leaders, however, were not always clear on the practicalities of the approach, and some found it difficult to identify the added value of Safety Cases. They suggested, for example, that existing risk management tools performed very similar functions.

If you look at our risk register, mitigation is the last box, we spend a good amount of time on the other things, but if we were to spend any time on a particular risk it would be on mitigation […]. And so that sounds like a very similar process, and so I’m back to what the delineation is between Safety Case and risk register. (Senior leader)

Some project teams saw the Safety Case as useful for a secondary reason: that of securing the attention and interest of senior leaders in their organisations. Their hope was that, by providing new evidence and analysis of the riskiness of clinical systems, senior management attention, support, and resources might be solicited.

So they’ve [senior management] actually kind of bought into it, so I think they will feel pressure to deliver. (Project participant)

However, as we explain below, the exact fit of Safety Cases into the existing ecology of tools and documents in healthcare was not clear to all participants.

Preparing safety cases

Project teams were required to learn new techniques to prepare the Safety Cases, including use of systematic methods to identify and assess risks in their clinical pathways, to propose risk controls and to identify metrics that could be used to monitor systems. Production and communication of Safety Cases also required skills in making persuasive claims, structuring arguments and presenting evidence compellingly. The participating teams were, understandably, unfamiliar with many of these skills, and expressed uncertainties about the expected structure, content and style of the Safety Case itself, especially in terms of what issues to emphasise and how to evidence them. Participants described compiling and drafting the Safety Case as labour-intensive and difficult.

I think the other bit that we have been challenged by is the actual writing of the Safety Case and again it is because it is fairly new to healthcare in general. I think we are going to go through a few reiterations before we fully understand what it is and how to use it. (Project participant)

Notwithstanding the training and support received in the ‘testing’ phase, teams continued to report difficulties with preparing and drafting Safety Cases well into the extension phase. A recurrent source of ambiguity related to the size and scope of the clinical system that the Safety Cases should target. The first, diagnostic, step in the Safer Clinical Systems process involved defining the clinical pathway of focus. However, determining the boundaries of the pathway was far from straightforward. Furthermore, clinical pathways typically involved dozens of technological systems (eg, infusion pumps, IT systems) and sociotechnical processes (eg, guidelines, multidisciplinary meetings). Each might be amenable to risk assessment and management individually, but making sense of their connections, aggregate risks and potential interactions was a much more complex task.

It’s not a linear process and you do go back trying to understand another bit of the process that you thought you understood, but actually didn't as (…) you had hoped. (Project participant)

Once the pathways and their components had been determined (or at least approximated), project teams used a range of methods recommended by the Safer Clinical Systems programme, mostly derived from similar activities in other industries, to assess hazards and risks. The teams found the processes often challenging and time-consuming, with much discussion about the relative merits of different sources of data and evidence. Despite the challenges, teams generally concluded that conducting a systematic risk assessment using structured tools offered important new insights about clinical pathways.

What I’ve loved doing is, is talking to the staff and actually understanding what goes on, because it’s only when you understand what goes on that you can put it right… You’ve worked in the hospital for years and there’s still things you didn’t realise actually went on and things that people did that you didn't realise that they actually did. That was quite an eye-opener. (Project participant)

This new understanding through structured risk assessment enabled teams to identify multiple shortcomings that had potential to harm patients. The hazards they unearthed varied greatly in scale, level of risk posed and tractability to intervention. Some problems identified were amenable to resolution by the project teams, typically those with their roots in suboptimal service planning and pathway design, failures in communication among staff, or unclear distribution of responsibility or ownership of key processes. In response to these, most, but not all, sites designed or implemented some risk controls and documented them in their Safety Cases.

[Staff are] given the freedom and the autonomy to go ahead and do whatever things they think might be necessary to make things better. And that’s what people do, there is very much a culture of promoting change there, so they talked about small cycles of change, doing PDSA [Plan Dp Study Act] cycles, and there’s a number of different projects that are running (Observation notes)

The extent to which these risk control interventions were consistent with the principles of the Safer Clinical Systems programme varied by site. Some project teams were able to draw on extensive experience, while others foundered at this stage. Common to all sites, however, was the identification of issues that were well beyond the scope of control of the front-line teams themselves. These vulnerabilities tended to originate from deep-rooted institutional and organisational pathologies or constraints. The importance of these problems, including, for example, staffing levels, was beyond doubt. Exactly what to do about them was less clear. Some project teams made valiant attempts to at least mitigate the risks through local work, but others appeared to accept that standard quality improvement efforts would not solve the issues. Some teams described the ongoing failure to mitigate the risks in their Safety Cases, in part, as noted above, in the hope that action from senior level might be provoked.

There were other things that were discussed at the [meeting] that they thought would be good as a team to change… but with some of them, they just knew it would be impossible to do so, so actually they didn't even bother to write them down. (Observation notes) And the team very bravely went to the board and said, you know, our Safety Case is showing and we're telling you that our processes are unsafe, so it alerted people to the issues. […] So that was the strength of it. (Project participant)

However, as we now describe, for senior organisational leaders, both the imperative offered by the Safety Case and their own ability to act were less clear.

Content of, and responses to, safety cases

Our documentary review showed that submitted Safety Cases were highly variable in format and length ( table 2 ). Some were highly structured, clearly written and precise in the use of evidence; others were harder to follow, lacking in clarity and less well organised. Our review also found that the descriptive elements (analysis of risk and hazards) were much better achieved than the assurance components (the safety claim and the confidence argument). Indicative, perhaps, of the intractability to local-level intervention of some of the hazards uncovered, or the lack of expert safety science input in the project teams, most Safety Cases focused more on what had been done to determine the risk than on the level of safety that had been achieved in mitigating it. The documents also varied in the extent to which they reported the residual risks—those that remained despite the implementation of risk controls—in a clear and transparent way. For instance, one Safety Case noted that the diagnostic process had found 99 ways in which the pathway could fail, that the level of reliability in the microsystem remained lower than acceptable, and that radical re-design was needed. Others were more circumspect. Accordingly, while they documented sometimes-extensive mitigations, none of the Safety Cases could make an unambiguous safety claim supported by a powerful confidence argument. Some teams were not clear about how the evidence gathered and analyses conducted would contribute to the safety claim. Some sites listed project activities in lieu of offering an actual safety claim, reporting what they had done rather than the level of safety they had reached.

It was a useful, […] a really good repository for all the stuff we've done in the project, which I find really good. And has been good when people ask ‘What did you do?’ then you can say that this is what we did, so that’s useful. I'm not sure about whether people use it for what it is meant to be, which is to prove the pathway is now safe, I’m not sure whether it is used for that really. (Project participant)

Sometimes, safety claims were reported for each identified hazard (comparing levels of risk before and after the interventions they had implemented) rather than at the level of the clinical system. No site explicitly discussed whether risks had been reduced ‘as low as reasonably practical’. Some sites claimed improvements as a result of the interventions they had implemented, but these did not always stand up to statistical scrutiny. 33

The response of senior leadership to the Safety Cases submitted by teams varied. Some focused on the potential of the Safety Case for supporting organisational-level decision making in relation to risk reduction, resource allocation and strategic prioritisation.

I think it would be easier to respond to a Safety Case rather than more so the [other quality and safety] data I get. Because it’s back to first principles, what are we actually here to do… Then if we have an unsafe system everything else needs to fall in behind that, no matter cost pressures, no matter personal opinion, no matter all the other complexities in a big system. If an element is at risk, then that will always be made a priority. (Senior leader)

Not all senior leaders, however, were so confident that the insight offered by Safety Cases would or should inevitably lead to action. Some of the issues identified in the Safety Cases were beyond the ability not only of front-line teams to solve, but also of organisational leaders. Issues such as staffing levels, IT interoperability, and securing timely discharge required at least interorganisational coordination, resourcing, coordination, and support across the whole healthcare system. Additionally, the prevailing approach to risk management, and the perceived unavoidability of risks in the complex systems of healthcare, meant that the insights offered by a Safety Case might be unwelcome or not necessarily candidates for priority attention. In a system that relied primarily on retrospective risk management approaches, such as incident reporting and investigations, the need to tackle risks of recurrence (where problems had already manifested as serious incidents or ‘near misses’, and might do again) could easily take precedence over addressing seemingly ‘theoretical’ risks (problems identified through a detailed prospective analysis but yet to occur).

Because you’re saying actually ‘That was a potential harm on our risk management system, and we knew about it, and we were accepting that we don’t have enough money to address all of these issues at one time’. So there is, if you like, a prioritisation and rationing of where we put money according to the level of risk. […] It’s a bit like county councils putting crossings on roads, or a zebra crossing. You’re waiting for the fatality to occur before actually that will get the funding. (Senior leader)

Some feared that, given the legal obligation of boards to take action in response to safety risks that were revealed to them, an unintended consequence of the Safety Case approach might be to distract organisational focus from areas that were at least as worthy of attention but lacked the spotlight offered by the Safety Case. There was a perception that to have a Safety Case for every pathway or area of practice would likely be impossible, and that too many Safety Cases would be overwhelming.

The complexity of health care is such that there are hundreds of complex connected pathways that patients are on and so… You in theory could write hundreds [of Safety Cases] and that would then become meaningless because if you write hundreds no one would ever read them. So, I think it might be helpful in some specific examples… Rather than being something that could cover everything that we do to patients. (Senior leader)

Consequently, Safety Cases might serve not to assure about control of risks, but to unnerve—and unnerve leaders who were not always well placed to act, given the scope of their control and the other priorities they faced. In a system where Safety Cases were new, without an established function in safety management, and covering only a small proportion of safety-critical activity, the information they provided was not always readily actionable from a managerial perspective and, moreover, had potential to create uncontrolled reputational risk.

The danger is that what you have is a legal requirement to spend money on a Safety Case that actually is of low, relative risk to harms that are occurring in the absence of Safety Cases. So what you get is a spurious diversion of money to a wheel that has been made very squeaky, but actually isn’t causing harm… There’s the risk of diversion to get a perfect patch in one part of the system while everything else is actually terrible. (Senior leader) (A danger) is, you know, if it does get into the wrong hands, particularly with the media, because there’s not the openness and the ability to manage some of this data, which needs explanation. But we do pride ourselves on being a very open and transparent board. (Senior leader)

Our examination of an attempt to introduce the principles and methodologies of the Safety Case approach into healthcare suggests that the approach was broadly welcomed by participants in our study, but was fraught with challenge. In other sectors, the Safety Case rests on the ALARP principle. While the Safety Cases produced by participating teams in the Safer Clinical Systems programme did present proactive analyses of risks, they did not show that the risks in clinical pathways on which they focused had been reduced as far as reasonably possible. Instead, teams identified multiple residual risks that had resisted efforts at control and mitigation by the teams themselves. These findings emphasise the importance of careful consideration of context and implementation when transferring safety management approaches from one setting to another. 12 34–36 The evidence underlying other industrial risk management techniques (eg, Failure Modes and Effects Analysis, 37 ‘5 Whys’ 10 or Root Case Analysis 11 ) is also weak, but the regulatory function of Safety Cases warrants specific caution. Sujan et al ’s review of various sectors nonetheless concluded that even with the differences in regulatory context, healthcare organisations could benefit from using the Safety Case approach to develop understanding and exposition of their current levels of risk. 19 Our study does suggest that Safety Cases show some promise as a way of structuring more responsive, adaptable and specific proactive safety management practices in healthcare settings, but further careful development and evaluation are needed, particularly if consideration is given to using them for regulatory purposes. 19

An important feature of the programme we examined—essentially a feasibility study—was that the Safety Case approach was being used outside the regulatory frameworks and infrastructures characteristic of use of the technique in most other sectors. Without an external regulatory requirement to satisfy, participating organisations in the Safer Clinical Systems programme may not have felt a strong imperative to make the responses that might otherwise be expected; absent the spectre of regulatory action, senior leadership may not have felt compelled to reduce the risks ALARP. However, even when Safety Cases are part of a regulatory framework, they are not always rigorous or successful in controlling risk 38 or showing they have been reduced ALARP. 39 While our study does not allow conclusions to be drawn about what might happen if Safety Cases were included in a regulatory regime in healthcare, it does allow insights into the nature of the challenges that might be anticipated should regulators consider introducing the approach in healthcare settings.

Some of the challenges we identified arose from the mismatch between the complexity and interdependencies of clinical pathways, with their often unbounded character, and the more tightly defined (and often more mechanical or technical) applications of the approach in other industries. 22 40 Future research might usefully clarify whether and how the scope of a Safety Case could best be defined for healthcare settings, noting that the highly dynamic and interdependent nature of multiple subsystems of care may defy attempts to impose clear boundaries. These kinds of questions are becoming increasingly prominent in safety science as recognition grows that the development of networked complex systems (eg, unmanned aircraft systems) requires a shift from relatively static prelaunch assessment to a dynamic approach that can accommodate changes in the system’s properties and behaviour during its life-cycle. 41 42

Other challenges arose in the demanding nature of the expertise, skill and time commitment required to engage in the tasks of conducting safety analyses, identifying and testing risk controls, and compiling a Safety Case. The variable quality of the Safety Cases submitted by clinical teams in this programme is likely to be linked to variable competencies and available capacity. In contrast, in safety-critical industries where these risk assessment techniques originated, the design of effective risk controls is the responsibility of safety/reliability engineers with extensive training and expertise. For healthcare, use of the Safety Case approach will require additional resource and new dedicated roles with specific expertise, rather than relying on making further demands of existing clinical teams. 40 43 The resourcing implications of a wholesale effort to shift the regulatory system and culture of an entire sector could, however, be enormous, especially given the volume and complexity of activity in healthcare and the number of diverse clinical pathways.

An additional set of challenges was more cultural in character, and related to the revelatory potential of the Safety Case. On one hand, participants—especially clinical teams—appreciated the value of the Safety Case in offering a proactive, prospective and rigorous approach to identifying safety risks. Some also saw it as a means of attracting managerial attention and obtaining resources. 44 But leaders in organisations were not always convinced that the approach offered much that was new, suggesting that more evidence would be needed to demonstrate the added value of Safety Cases—especially in moving beyond description to solution, 45 and adding value over current approaches such as risk registers. A further concern at the leadership level was that it was unclear whether areas that did have a Safety Case should be considered to have a stronger warrant for action than those that did not. A framework for supporting prioritisation of risks is likely to be helpful in any future use of Safety Cases. However, current tools, such as risk matrices, may be flawed, 46 47 so better tools should be investigated.

Even less tractable was what to do about some of the problems reported in the Safety Cases. Clinical teams had done their best to implement risk controls where they could, but they did not have sufficient power and access to resources to address those that were institutional or structural in character. They therefore often fell back on weaker administrative measures, like training or procedures. 8 Yet organisational leaders were often similarly challenged, given their limited capacity and resources for radical systems re-design, improved staffing, IT infrastructure, or other major re-engineering or influencing of activities outside the organisation itself. These findings are indicative of broader problems with the selection of risk controls in health services 44 48 that may need to be addressed before Safety Cases could achieve their potential.

Our study has a number of strengths, including its in-depth, mixed-methods, longitudinal design with engagement both with the project teams and senior leaders in organisations. It was limited in its ability to assess the impact of the Safety Case approach in improving safety, not least because of issues with data on processes and outcomes. 33

Conclusions

The Safety Case approach offers promise in principle as a safety management approach in healthcare, but substantial challenges need to be addressed before further deployment, particularly in regulation. Further experimentation with the use of Safety Cases in healthcare might therefore more profitably focus on how to make the most of their assets—including the new insights offered by prospective, system-wide risk analysis—while managing their potential unintended consequences.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

This study involves human participants and was approved by the East Midlands – Leicester Research Ethics Committee (12/EM/0228). Participants gave informed consent to participate in the study before taking part.

Acknowledgments

We thank the people from the nine sites who participated in the Safer Clinical Systems programme and the support team. We also thank colleagues on the evaluation team, including Sarah Chew, Liz Shaw, Liz Sutton, and Lisa Hallam.

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Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

  • Data supplement 1

Twitter @graham_p_martin, @carolynctarrant

Contributors EL and GL produced the first draft of the article, subsequently revised by GM, JWa, and MD-W. EL and JWi collected the data, analysed by EL and GL. All authors contributed to data interpretation, manuscript writing and reviewing, and approved the final version. MD-W was the study Chief Investigator and study guarantor.

Funding This study was funded by the Health Foundation, charity number 286967. The Healthcare Improvement Studies (THIS) Institute is supported by the Health Foundation – an independent charity committed to bringing about better health and health care for people in the UK. The views expressed in this publication are those of the authors and not necessarily those of the Health Foundation.

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

Linked Articles

  • Editorial Changing the patient safety mindset: can safety cases help? Mark Sujan Ibrahim Habli BMJ Quality & Safety 2023; 33 145-148 Published Online First: 24 Nov 2023. doi: 10.1136/bmjqs-2023-016652

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Covid vaccines linked to slight increases in heart, brain, blood disorders: study.

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COVID vaccines from companies like Pfizer, Moderna and AstraZeneca have been linked to rare occurrences of heart, brain and blood disorders, according to the largest vaccine study to date.

Researchers from the  Global Vaccine Data Network analyzed 99 million people who received jabs in eight countries and monitored for increases in 13 medical conditions, Bloomberg News reported .

The study, which was published in the journal Vaccine last week, found the vaccines were linked to a slight spike in neurological, blood and heart-related medical conditions.

COVID shot

Rare cases of myocarditis — inflammation of the heart muscle — were found in the first, second and third doses of Pfizer-BioNTech’s and Moderna’s mRNA vaccines.

Another heart condition, ​pericarditis, the inflammation of the cardiac muscle, had a 6.9-fold increased risk in those who received a third dose of AstraZeneca’s viral-vector shot, the study found.

Meanwhile, a first and fourth dose of Moderna’s jab had a 1.7-fold and 2.6-fold increased risk, respectively.

An increased risk also was identified of a type of blood clot in the brain from viral-vector shots such as the one developed by the University of Oxford and manufactured by AstraZeneca, Bloomberg said.

There was a 2.5 times greater risk of developing Guillain-Barre syndrome, a rare neurological disorder in which the immune system attacks the nerves, among people who received AstraZeneca’s jab, according to the study.

More than 13.5 billion doses have been administered worldwide since the start of the pandemic.

Possible safety signals for ​transverse myelitis, a spinal cord inflammation, were identified after viral-vector vaccines, as was acute disseminated encephalomyelitis, the inflammation and swelling in the brain and spinal cord, after both viral-vector and mRNA vaccines, the researchers found.

The experts at GVDV in New Zealand — a research arm of the World Health Organization — examined 13 medical conditions that they considered “adverse events of special interest” among the subjects, aiming to identify higher-than-expected cases after a vaccine.  

More than 13.5 billion doses have been administered worldwide since the start of the pandemic. A small proportion of those immunized were harmed by the shots, stoking debate about the benefits of the jabs versus the risks.

“The size of the population in this study increased the possibility of identifying rare potential vaccine safety signals,” lead author Kristýna Faksová of the Department of Epidemiology Research, Statens Serum Institut in Denmark, said in a release.

is a case study a journal article

“Single sites or regions are unlikely to have a large enough population to detect very rare signals,” she added.

One expert who was not involved in the study maintained that the benefits of the vaccines outweigh the risks.

“The odds of all of these adverse events is still much, much higher when infected with SARS-CoV-2 (COVID-19), so getting vaccinated is still by far the safer choice,” Jacob Glanville, CEO of biotech company Centivax, told Forbes .

Dr. Marc Siegel, clinical professor of medicine at NYU Langone Medical Center, shared a similar conclusion.

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“The massive study and review of the data reveals some rare association of the mRNA vaccines and myocarditis, especially after the second shot, as well as an association between the Oxford Astra Zeneca adenovirus vector vaccines and Guillain-Barre syndrome,” Siegel, who was not involved in the study, told Fox News Digital . “But these risks are rare and other studies show that the vaccine decreases the risk of myocarditis from COVID itself dramatically,” he said, adding that all vaccines have side effects.

“It always comes down to a risk/benefit analysis of what you are more afraid of — the vaccine’s side effects or the virus itself, which can have long-term side effects in terms of brain fog, fatigue, cough, and also heart issues,” Siegel said. “Denying or exaggerating a vaccine’s side effects is not good science — nor is underestimating the risks of the virus, especially in high-risk groups,” Siegel added.

Pfizer told The Post in a statement that while it “was not involved in this study, we welcome independent research and academic discourse to advance the study of COVID-19. 

“Safety is a top concern for all of us and Pfizer and BioNTech take reports of side effects that are potentially associated with our COVID-19 vaccine very seriously,” it said in the email.

“Since its initial authorization for use in December 2020, the Pfizer-BioNTech COVID-19 vaccine has been administered to more than 1.5 billion people, has demonstrated a favorable safety profile in all age groups, and has helped protect against severe COVID-19 outcomes, including hospitalization and death,” the company added.

Moderna and AstraZeneca did not immediately respond to requests for comment.

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is a case study a journal article

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  Journal of Linguistics and Language in Education Journal / Journal of Linguistics and Language in Education / Vol. 8 No. 2 (2014) / Articles (function() { function async_load(){ var s = document.createElement('script'); s.type = 'text/javascript'; s.async = true; var theUrl = 'https://www.journalquality.info/journalquality/ratings/2402-www-ajol-info-jlle'; s.src = theUrl + ( theUrl.indexOf("?") >= 0 ? "&" : "?") + 'ref=' + encodeURIComponent(window.location.href); var embedder = document.getElementById('jpps-embedder-ajol-jlle'); embedder.parentNode.insertBefore(s, embedder); } if (window.attachEvent) window.attachEvent('onload', async_load); else window.addEventListener('load', async_load, false); })();  

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An investigation of negative representation in media: a case study of scrutator, mokhoele a. hala-hala, maboleba a. kolobe.

The aim of this paper was to investigate negative representation of the National University of Lesotho (henceforth NUL) by the Scrutator in the weekly newspaper, the Lesotho Times. With a view that negative representation is a form of the media framing which seems to be increasingly taking up different dimensions worthy of attention for further conceptual understanding, we set out to examine the phenomenon. We set out with an assumption that the findings of the study would shed light on media operation, in general, and also help the media audiences observe how one of the local print media houses, the Lesotho Times, represents certain groups of Basotho society. The concept of negative representation is probably one of the phenomena which have drawn much attention from scholars of different disciplines within the social sciences, linguistics and communication studies. Adopting Content Analysis as a research instrument in selected issues of the Lesotho Times from 2010 to 2011, we investigated the Scrutator‘s negative representation of the NUL community in this particular newspaper. We, therefore, observe that negative representation is a perspectival projection of the newspaper; it is probably a strategic tool of manipulating people and making them develop a certain attitude towards the University as well as the University community despite its role as a leading tertiary institution in the Kingdom of Lesotho.

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    Journal of Linguistics and Language in Education ... A Case Study of Scrutator Mokhoele A. Hala-hala. Maboleba A. Kolobe. Abstract. The aim of this paper was to investigate negative representation of the National University of Lesotho (henceforth NUL) by the Scrutator in the weekly newspaper, the Lesotho Times. With a view that negative ...