a case study evaluation

• Case Study Evaluation Approach
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A case study evaluation approach can be an incredibly powerful tool for monitoring and evaluating complex programs and policies. By identifying common themes and patterns, this approach allows us to better understand the successes and challenges faced by the program. In this article, we’ll explore the benefits of using a case study evaluation approach in the monitoring and evaluation of projects, programs, and public policies.

Table of Contents

Introduction to Case Study Evaluation Approach

The advantages of a case study evaluation approach, types of case studies, potential challenges with a case study evaluation approach, guiding principles for successful implementation of a case study evaluation approach.

• Benefits of Incorporating the Case Study Evaluation Approach in the Monitoring and Evaluation of Projects and Programs

A case study evaluation approach is a great way to gain an in-depth understanding of a particular issue or situation. This type of approach allows the researcher to observe, analyze, and assess the effects of a particular situation on individuals or groups.

An individual, a location, or a project may serve as the focal point of a case study’s attention. Quantitative and qualitative data are frequently used in conjunction with one another.

It also allows the researcher to gain insights into how people react to external influences. By using a case study evaluation approach, researchers can gain insights into how certain factors such as policy change or a new technology have impacted individuals and communities. The data gathered through this approach can be used to formulate effective strategies for responding to changes and challenges. Ultimately, this monitoring and evaluation approach helps organizations make better decision about the implementation of their plans.

This approach can be used to assess the effectiveness of a policy, program, or initiative by considering specific elements such as implementation processes, outcomes, and impact. A case study evaluation approach can provide an in-depth understanding of the effectiveness of a program by closely examining the processes involved in its implementation. This includes understanding the context, stakeholders, and resources to gain insight into how well a program is functioning or has been executed. By evaluating these elements, it can help to identify areas for improvement and suggest potential solutions. The findings from this approach can then be used to inform decisions about policies, programs, and initiatives for improved outcomes.

It is also useful for determining if other policies, programs, or initiatives could be applied to similar situations in order to achieve similar results or improved outcomes. All in all, the case study monitoring evaluation approach is an effective method for determining the effectiveness of specific policies, programs, or initiatives. By researching and analyzing the successes of previous cases, this approach can be used to identify similar approaches that could be applied to similar situations in order to achieve similar results or improved outcomes.

A case study evaluation approach offers the advantage of providing in-depth insight into a particular program or policy. This can be accomplished by analyzing data and observations collected from a range of stakeholders such as program participants, service providers, and community members. The monitoring and evaluation approach is used to assess the impact of programs and inform the decision-making process to ensure successful implementation. The case study monitoring and evaluation approach can help identify any underlying issues that need to be addressed in order to improve program effectiveness. It also provides a reality check on how successful programs are actually working, allowing organizations to make adjustments as needed. Overall, a case study monitoring and evaluation approach helps to ensure that policies and programs are achieving their objectives while providing valuable insight into how they are performing overall.

By taking a qualitative approach to data collection and analysis, case study evaluations are able to capture nuances in the context of a particular program or policy that can be overlooked when relying solely on quantitative methods. Using this approach, insights can be gleaned from looking at the individual experiences and perspectives of actors involved, providing a more detailed understanding of the impact of the program or policy than is possible with other evaluation methodologies. As such, case study monitoring evaluation is an invaluable tool in assessing the effectiveness of a particular initiative, enabling more informed decision-making as well as more effective implementation of programs and policies.

Furthermore, this approach is an effective way to uncover experiential information that can help to inform the ongoing improvement of policy and programming over time All in all, the case study monitoring evaluation approach offers an effective way to uncover experiential information necessary to inform the ongoing improvement of policy and programming. By analyzing the data gathered from this systematic approach, stakeholders can gain deeper insight into how best to make meaningful and long-term changes in their respective organizations.

Case studies come in a variety of forms, each of which can be put to a unique set of evaluation tasks. Evaluators have come to a consensus on describing six distinct sorts of case studies, which are as follows: illustrative, exploratory, critical instance, program implementation, program effects, and cumulative.

Illustrative Case Study

An illustrative case study is a type of case study that is used to provide a detailed and descriptive account of a particular event, situation, or phenomenon. It is often used in research to provide a clear understanding of a complex issue, and to illustrate the practical application of theories or concepts.

An illustrative case study typically uses qualitative data, such as interviews, surveys, or observations, to provide a detailed account of the unit being studied. The case study may also include quantitative data, such as statistics or numerical measurements, to provide additional context or to support the qualitative data.

The goal of an illustrative case study is to provide a rich and detailed description of the unit being studied, and to use this information to illustrate broader themes or concepts. For example, an illustrative case study of a successful community development project may be used to illustrate the importance of community engagement and collaboration in achieving development goals.

One of the strengths of an illustrative case study is its ability to provide a detailed and nuanced understanding of a particular issue or phenomenon. By focusing on a single case, the researcher is able to provide a detailed and in-depth analysis that may not be possible through other research methods.

However, one limitation of an illustrative case study is that the findings may not be generalizable to other contexts or populations. Because the case study focuses on a single unit, it may not be representative of other similar units or situations.

A well-executed case study can shed light on wider research topics or concepts through its thorough and descriptive analysis of a specific event or phenomenon.

Exploratory Case Study

An exploratory case study is a type of case study that is used to investigate a new or previously unexplored phenomenon or issue. It is often used in research when the topic is relatively unknown or when there is little existing literature on the topic.

Exploratory case studies are typically qualitative in nature and use a variety of methods to collect data, such as interviews, observations, and document analysis. The focus of the study is to gather as much information as possible about the phenomenon being studied and to identify new and emerging themes or patterns.

The goal of an exploratory case study is to provide a foundation for further research and to generate hypotheses about the phenomenon being studied. By exploring the topic in-depth, the researcher can identify new areas of research and generate new questions to guide future research.

One of the strengths of an exploratory case study is its ability to provide a rich and detailed understanding of a new or emerging phenomenon. By using a variety of data collection methods, the researcher can gather a broad range of data and perspectives to gain a more comprehensive understanding of the phenomenon being studied.

However, one limitation of an exploratory case study is that the findings may not be generalizable to other contexts or populations. Because the study is focused on a new or previously unexplored phenomenon, the findings may not be applicable to other situations or populations.

Exploratory case studies are an effective research strategy for learning about novel occurrences, developing research hypotheses, and gaining a deep familiarity with a topic of study.

Critical Instance Case Study

A critical instance case study is a type of case study that focuses on a specific event or situation that is critical to understanding a broader issue or phenomenon. The goal of a critical instance case study is to analyze the event in depth and to draw conclusions about the broader issue or phenomenon based on the analysis.

A critical instance case study typically uses qualitative data, such as interviews, observations, or document analysis, to provide a detailed and nuanced understanding of the event being studied. The data are analyzed using various methods, such as content analysis or thematic analysis, to identify patterns and themes that emerge from the data.

The critical instance case study is often used in research when a particular event or situation is critical to understanding a broader issue or phenomenon. For example, a critical instance case study of a successful disaster response effort may be used to identify key factors that contributed to the success of the response, and to draw conclusions about effective disaster response strategies more broadly.

One of the strengths of a critical instance case study is its ability to provide a detailed and in-depth analysis of a particular event or situation. By focusing on a critical instance, the researcher is able to provide a rich and nuanced understanding of the event, and to draw conclusions about broader issues or phenomena based on the analysis.

However, one limitation of a critical instance case study is that the findings may not be generalizable to other contexts or populations. Because the case study focuses on a specific event or situation, the findings may not be applicable to other similar events or situations.

A critical instance case study is a valuable research method that can provide a detailed and nuanced understanding of a particular event or situation and can be used to draw conclusions about broader issues or phenomena based on the analysis.

Program Implementation Program Implementation

A program implementation case study is a type of case study that focuses on the implementation of a particular program or intervention. The goal of the case study is to provide a detailed and comprehensive account of the program implementation process, and to identify factors that contributed to the success or failure of the program.

Program implementation case studies typically use qualitative data, such as interviews, observations, and document analysis, to provide a detailed and nuanced understanding of the program implementation process. The data are analyzed using various methods, such as content analysis or thematic analysis, to identify patterns and themes that emerge from the data.

The program implementation case study is often used in research to evaluate the effectiveness of a particular program or intervention, and to identify strategies for improving program implementation in the future. For example, a program implementation case study of a school-based health program may be used to identify key factors that contributed to the success or failure of the program, and to make recommendations for improving program implementation in similar settings.

One of the strengths of a program implementation case study is its ability to provide a detailed and comprehensive account of the program implementation process. By using qualitative data, the researcher is able to capture the complexity and nuance of the implementation process, and to identify factors that may not be captured by quantitative data alone.

However, one limitation of a program implementation case study is that the findings may not be generalizable to other contexts or populations. Because the case study focuses on a specific program or intervention, the findings may not be applicable to other programs or interventions in different settings.

An effective research tool, a case study of program implementation may illuminate the intricacies of the implementation process and point the way towards future enhancements.

Program Effects Case Study

A program effects case study is a research method that evaluates the effectiveness of a particular program or intervention by examining its outcomes or effects. The purpose of this type of case study is to provide a detailed and comprehensive account of the program’s impact on its intended participants or target population.

A program effects case study typically employs both quantitative and qualitative data collection methods, such as surveys, interviews, and observations, to evaluate the program’s impact on the target population. The data is then analyzed using statistical and thematic analysis to identify patterns and themes that emerge from the data.

The program effects case study is often used to evaluate the success of a program and identify areas for improvement. For example, a program effects case study of a community-based HIV prevention program may evaluate the program’s effectiveness in reducing HIV transmission rates among high-risk populations and identify factors that contributed to the program’s success.

One of the strengths of a program effects case study is its ability to provide a detailed and nuanced understanding of a program’s impact on its intended participants or target population. By using both quantitative and qualitative data, the researcher can capture both the objective and subjective outcomes of the program and identify factors that may have contributed to the outcomes.

However, a limitation of the program effects case study is that it may not be generalizable to other populations or contexts. Since the case study focuses on a particular program and population, the findings may not be applicable to other programs or populations in different settings.

A program effects case study is a good way to do research because it can give a detailed look at how a program affects the people it is meant for. This kind of case study can be used to figure out what needs to be changed and how to make programs that work better.

Cumulative Case Study

A cumulative case study is a type of case study that involves the collection and analysis of multiple cases to draw broader conclusions. Unlike a single-case study, which focuses on one specific case, a cumulative case study combines multiple cases to provide a more comprehensive understanding of a phenomenon.

The purpose of a cumulative case study is to build up a body of evidence through the examination of multiple cases. The cases are typically selected to represent a range of variations or perspectives on the phenomenon of interest. Data is collected from each case using a range of methods, such as interviews, surveys, and observations.

The data is then analyzed across cases to identify common themes, patterns, and trends. The analysis may involve both qualitative and quantitative methods, such as thematic analysis and statistical analysis.

The cumulative case study is often used in research to develop and test theories about a phenomenon. For example, a cumulative case study of successful community-based health programs may be used to identify common factors that contribute to program success, and to develop a theory about effective community-based health program design.

One of the strengths of the cumulative case study is its ability to draw on a range of cases to build a more comprehensive understanding of a phenomenon. By examining multiple cases, the researcher can identify patterns and trends that may not be evident in a single case study. This allows for a more nuanced understanding of the phenomenon and helps to develop more robust theories.

However, one limitation of the cumulative case study is that it can be time-consuming and resource-intensive to collect and analyze data from multiple cases. Additionally, the selection of cases may introduce bias if the cases are not representative of the population of interest.

In summary, a cumulative case study is a valuable research method that can provide a more comprehensive understanding of a phenomenon by examining multiple cases. This type of case study is particularly useful for developing and testing theories and identifying common themes and patterns across cases.

When conducting a case study evaluation approach, one of the main challenges is the need to establish a contextually relevant research design that accounts for the unique factors of the case being studied. This requires close monitoring of the case, its environment, and relevant stakeholders. In addition, the researcher must build a framework for the collection and analysis of data that is able to draw meaningful conclusions and provide valid insights into the dynamics of the case. Ultimately, an effective case study monitoring evaluation approach will allow researchers to form an accurate understanding of their research subject.

Additionally, depending on the size and scope of the case, there may be concerns regarding the availability of resources and personnel that could be allocated to data collection and analysis. To address these issues, a case study monitoring evaluation approach can be adopted, which would involve a mix of different methods such as interviews, surveys, focus groups and document reviews. Such an approach could provide valuable insights into the effectiveness and implementation of the case in question. Additionally, this type of evaluation can be tailored to the specific needs of the case study to ensure that all relevant data is collected and respected.

When dealing with a highly sensitive or confidential subject matter within a case study, researchers must take extra measures to prevent bias during data collection as well as protect participant anonymity while also collecting valid data in order to ensure reliable results

Moreover, when conducting a case study evaluation it is important to consider the potential implications of the data gathered. By taking extra measures to prevent bias and protect participant anonymity, researchers can ensure reliable results while also collecting valid data. Maintaining confidentiality and deploying ethical research practices are essential when conducting a case study to ensure an unbiased and accurate monitoring evaluation.

When planning and implementing a case study evaluation approach, it is important to ensure the guiding principles of research quality, data collection, and analysis are met. To ensure these principles are upheld, it is essential to develop a comprehensive monitoring and evaluation plan. This plan should clearly outline the steps to be taken during the data collection and analysis process. Furthermore, the plan should provide detailed descriptions of the project objectives, target population, key indicators, and timeline. It is also important to include metrics or benchmarks to monitor progress and identify any potential areas for improvement. By implementing such an approach, it will be possible to ensure that the case study evaluation approach yields valid and reliable results.

To ensure successful implementation, it is essential to establish a reliable data collection process that includes detailed information such as the scope of the study, the participants involved, and the methods used to collect data. Additionally, it is important to have a clear understanding of what will be examined through the evaluation process and how the results will be used. All in all, it is essential to establish a sound monitoring evaluation approach for a successful case study implementation. This includes creating a reliable data collection process that encompasses the scope of the study, the participants involved, and the methods used to collect data. It is also imperative to have an understanding of what will be examined and how the results will be utilized. Ultimately, effective planning is key to ensure that the evaluation process yields meaningful insights.

Benefits of Incorporating the Case Study Evaluation Approach in the Monitoring and Evaluation of Projects and Programmes

Using a case study approach in monitoring and evaluation allows for a more detailed and in-depth exploration of the project’s success, helping to identify key areas of improvement and successes that may have been overlooked through traditional evaluation. Through this case study method, specific data can be collected and analyzed to identify trends and different perspectives that can support the evaluation process. This data can allow stakeholders to gain a better understanding of the project’s successes and failures, helping them make informed decisions on how to strengthen current activities or shape future initiatives. From a monitoring and evaluation standpoint, this approach can provide an increased level of accuracy in terms of accurately assessing the effectiveness of the project.

This can provide valuable insights into what works—and what doesn’t—when it comes to implementing projects and programs, aiding decision-makers in making future plans that better meet their objectives However, monitoring and evaluation is just one approach to assessing the success of a case study. It does provide a useful insight into what initiatives may be successful, but it is important to note that there are other effective research methods, such as surveys and interviews, that can also help to further evaluate the success of a project or program.

In conclusion, a case study evaluation approach can be incredibly useful in monitoring and evaluating complex programs and policies. By exploring key themes, patterns and relationships, organizations can gain a detailed understanding of the successes, challenges and limitations of their program or policy. This understanding can then be used to inform decision-making and improve outcomes for those involved. With its ability to provide an in-depth understanding of a program or policy, the case study evaluation approach has become an invaluable tool for monitoring and evaluation professionals.

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• Open access
• Published: 27 November 2020

Designing process evaluations using case study to explore the context of complex interventions evaluated in trials

• Aileen Grant 1 ,
• Carol Bugge 2 &
• Mary Wells 3  

Trials volume  21 , Article number:  982 ( 2020 ) Cite this article

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Process evaluations are an important component of an effectiveness evaluation as they focus on understanding the relationship between interventions and context to explain how and why interventions work or fail, and whether they can be transferred to other settings and populations. However, historically, context has not been sufficiently explored and reported resulting in the poor uptake of trial results. Therefore, suitable methodologies are needed to guide the investigation of context. Case study is one appropriate methodology, but there is little guidance about what case study design can offer the study of context in trials. We address this gap in the literature by presenting a number of important considerations for process evaluation using a case study design.

In this paper, we define context, the relationship between complex interventions and context, and describe case study design methodology. A well-designed process evaluation using case study should consider the following core components: the purpose; definition of the intervention; the trial design, the case, the theories or logic models underpinning the intervention, the sampling approach and the conceptual or theoretical framework. We describe each of these in detail and highlight with examples from recently published process evaluations.

Conclusions

There are a number of approaches to process evaluation design in the literature; however, there is a paucity of research on what case study design can offer process evaluations. We argue that case study is one of the best research designs to underpin process evaluations, to capture the dynamic and complex relationship between intervention and context during implementation. We provide a comprehensive overview of the issues for process evaluation design to consider when using a case study design.

Trial registration

DQIP - ClinicalTrials.gov number, NCT01425502 - OPAL - ISRCTN57746448

Peer Review reports

Contribution to the literature

We illustrate how case study methodology can explore the complex, dynamic and uncertain relationship between context and interventions within trials.

We depict different case study designs and illustrate there is not one formula and that design needs to be tailored to the context and trial design.

Case study can support comparisons between intervention and control arms and between cases within arms to uncover and explain differences in detail.

We argue that case study can illustrate how components have evolved and been redefined through implementation.

Key issues for consideration in case study design within process evaluations are presented and illustrated with examples.

Process evaluations are an important component of an effectiveness evaluation as they focus on understanding the relationship between interventions and context to explain how and why interventions work or fail and whether they can be transferred to other settings and populations. However, historically, not all trials have had a process evaluation component, nor have they sufficiently reported aspects of context, resulting in poor uptake of trial findings [ 1 ]. Considerations of context are often absent from published process evaluations, with few studies acknowledging, taking account of or describing context during implementation, or assessing the impact of context on implementation [ 2 , 3 ]. At present, evidence from trials is not being used in a timely manner [ 4 , 5 ], and this can negatively impact on patient benefit and experience [ 6 ]. It takes on average 17 years for knowledge from research to be implemented into practice [ 7 ]. Suitable methodologies are therefore needed that allow for context to be exposed; one appropriate methodological approach is case study [ 8 , 9 ].

In 2015, the Medical Research Council (MRC) published guidance for process evaluations [ 10 ]. This was a key milestone in legitimising as well as providing tools, methods and a framework for conducting process evaluations. Nevertheless, as with all guidance, there is a need for reflection, challenge and refinement. There have been a number of critiques of the MRC guidance, including that interventions should be considered as events in systems [ 11 , 12 , 13 , 14 ]; a need for better use, critique and development of theories [ 15 , 16 , 17 ]; and a need for more guidance on integrating qualitative and quantitative data [ 18 , 19 ]. Although the MRC process evaluation guidance does consider appropriate qualitative and quantitative methods, it does not mention case study design and what it can offer the study of context in trials.

The case study methodology is ideally suited to real-world, sustainable intervention development and evaluation because it can explore and examine contemporary complex phenomena, in depth, in numerous contexts and using multiple sources of data [ 8 ]. Case study design can capture the complexity of the case, the relationship between the intervention and the context and how the intervention worked (or not) [ 8 ]. There are a number of textbooks on a case study within the social science fields [ 8 , 9 , 20 ], but there are no case study textbooks and a paucity of useful texts on how to design, conduct and report case study within the health arena. Few examples exist within the trial design and evaluation literature [ 3 , 21 ]. Therefore, guidance to enable well-designed process evaluations using case study methodology is required.

We aim to address the gap in the literature by presenting a number of important considerations for process evaluation using a case study design. First, we define the context and describe the relationship between complex health interventions and context.

What is context?

While there is growing recognition that context interacts with the intervention to impact on the intervention’s effectiveness [ 22 ], context is still poorly defined and conceptualised. There are a number of different definitions in the literature, but as Bate et al. explained ‘almost universally, we find context to be an overworked word in everyday dialogue but a massively understudied and misunderstood concept’ [ 23 ]. Ovretveit defines context as ‘everything the intervention is not’ [ 24 ]. This last definition is used by the MRC framework for process evaluations [ 25 ]; however; the problem with this definition is that it is highly dependent on how the intervention is defined. We have found Pfadenhauer et al.’s definition useful:

Context is conceptualised as a set of characteristics and circumstances that consist of active and unique factors that surround the implementation. As such it is not a backdrop for implementation but interacts, influences, modifies and facilitates or constrains the intervention and its implementation. Context is usually considered in relation to an intervention or object, with which it actively interacts. A boundary between the concepts of context and setting is discernible: setting refers to the physical, specific location in which the intervention is put into practice. Context is much more versatile, embracing not only the setting but also roles, interactions and relationships [ 22 ].

Traditionally, context has been conceptualised in terms of barriers and facilitators, but what is a barrier in one context may be a facilitator in another, so it is the relationship and dynamics between the intervention and context which are the most important [ 26 ]. There is a need for empirical research to really understand how different contextual factors relate to each other and to the intervention. At present, research studies often list common contextual factors, but without a depth of meaning and understanding, such as government or health board policies, organisational structures, professional and patient attitudes, behaviours and beliefs [ 27 ]. The case study methodology is well placed to understand the relationship between context and intervention where these boundaries may not be clearly evident. It offers a means of unpicking the contextual conditions which are pertinent to effective implementation.

The relationship between complex health interventions and context

Health interventions are generally made up of a number of different components and are considered complex due to the influence of context on their implementation and outcomes [ 3 , 28 ]. Complex interventions are often reliant on the engagement of practitioners and patients, so their attitudes, behaviours, beliefs and cultures influence whether and how an intervention is effective or not. Interventions are context-sensitive; they interact with the environment in which they are implemented. In fact, many argue that interventions are a product of their context, and indeed, outcomes are likely to be a product of the intervention and its context [ 3 , 29 ]. Within a trial, there is also the influence of the research context too—so the observed outcome could be due to the intervention alone, elements of the context within which the intervention is being delivered, elements of the research process or a combination of all three. Therefore, it can be difficult and unhelpful to separate the intervention from the context within which it was evaluated because the intervention and context are likely to have evolved together over time. As a result, the same intervention can look and behave differently in different contexts, so it is important this is known, understood and reported [ 3 ]. Finally, the intervention context is dynamic; the people, organisations and systems change over time, [ 3 ] which requires practitioners and patients to respond, and they may do this by adapting the intervention or contextual factors. So, to enable researchers to replicate successful interventions, or to explain why the intervention was not successful, it is not enough to describe the components of the intervention, they need to be described by their relationship to their context and resources [ 3 , 28 ].

What is a case study?

Case study methodology aims to provide an in-depth, holistic, balanced, detailed and complete picture of complex contemporary phenomena in its natural context [ 8 , 9 , 20 ]. In this case, the phenomena are the implementation of complex interventions in a trial. Case study methodology takes the view that the phenomena can be more than the sum of their parts and have to be understood as a whole [ 30 ]. It is differentiated from a clinical case study by its analytical focus [ 20 ].

The methodology is particularly useful when linked to trials because some of the features of the design naturally fill the gaps in knowledge generated by trials. Given the methodological focus on understanding phenomena in the round, case study methodology is typified by the use of multiple sources of data, which are more commonly qualitatively guided [ 31 ]. The case study methodology is not epistemologically specific, like realist evaluation, and can be used with different epistemologies [ 32 ], and with different theories, such as Normalisation Process Theory (which explores how staff work together to implement a new intervention) or the Consolidated Framework for Implementation Research (which provides a menu of constructs associated with effective implementation) [ 33 , 34 , 35 ]. Realist evaluation can be used to explore the relationship between context, mechanism and outcome, but case study differs from realist evaluation by its focus on a holistic and in-depth understanding of the relationship between an intervention and the contemporary context in which it was implemented [ 36 ]. Case study enables researchers to choose epistemologies and theories which suit the nature of the enquiry and their theoretical preferences.

Designing a process evaluation using case study

An important part of any study is the research design. Due to their varied philosophical positions, the seminal authors in the field of case study have different epistemic views as to how a case study should be conducted [ 8 , 9 ]. Stake takes an interpretative approach (interested in how people make sense of their world), and Yin has more positivistic leanings, arguing for objectivity, validity and generalisability [ 8 , 9 ].

Regardless of the philosophical background, a well-designed process evaluation using case study should consider the following core components: the purpose; the definition of the intervention, the trial design, the case, and the theories or logic models underpinning the intervention; the sampling approach; and the conceptual or theoretical framework [ 8 , 9 , 20 , 31 , 33 ]. We now discuss these critical components in turn, with reference to two process evaluations that used case study design, the DQIP and OPAL studies [ 21 , 37 , 38 , 39 , 40 , 41 ].

The purpose of a process evaluation is to evaluate and explain the relationship between the intervention and its components, to context and outcome. It can help inform judgements about validity (by exploring the intervention components and their relationship with one another (construct validity), the connections between intervention and outcomes (internal validity) and the relationship between intervention and context (external validity)). It can also distinguish between implementation failure (where the intervention is poorly delivered) and intervention failure (intervention design is flawed) [ 42 , 43 ]. By using a case study to explicitly understand the relationship between context and the intervention during implementation, the process evaluation can explain the intervention effects and the potential generalisability and optimisation into routine practice [ 44 ].

The DQIP process evaluation aimed to qualitatively explore how patients and GP practices responded to an intervention designed to reduce high-risk prescribing of nonsteroidal anti-inflammatory drugs (NSAIDs) and/or antiplatelet agents (see Table  1 ) and quantitatively examine how change in high-risk prescribing was associated with practice characteristics and implementation processes. The OPAL process evaluation (see Table  2 ) aimed to quantitatively understand the factors which influenced the effectiveness of a pelvic floor muscle training intervention for women with urinary incontinence and qualitatively explore the participants’ experiences of treatment and adherence.

Defining the intervention and exploring the theories or assumptions underpinning the intervention design

Process evaluations should also explore the utility of the theories or assumptions underpinning intervention design [ 49 ]. Not all theories underpinning interventions are based on a formal theory, but they based on assumptions as to how the intervention is expected to work. These can be depicted as a logic model or theory of change [ 25 ]. To capture how the intervention and context evolve requires the intervention and its expected mechanisms to be clearly defined at the outset [ 50 ]. Hawe and colleagues recommend defining interventions by function (what processes make the intervention work) rather than form (what is delivered) [ 51 ]. However, in some cases, it may be useful to know if some of the components are redundant in certain contexts or if there is a synergistic effect between all the intervention components.

The DQIP trial delivered two interventions, one intervention was delivered to professionals with high fidelity and then professionals delivered the other intervention to patients by form rather than function allowing adaptations to the local context as appropriate. The assumptions underpinning intervention delivery were prespecified in a logic model published in the process evaluation protocol [ 52 ].

Case study is well placed to challenge or reinforce the theoretical assumptions or redefine these based on the relationship between the intervention and context. Yin advocates the use of theoretical propositions; these direct attention to specific aspects of the study for investigation [ 8 ] can be based on the underlying assumptions and tested during the course of the process evaluation. In case studies, using an epistemic position more aligned with Yin can enable research questions to be designed, which seek to expose patterns of unanticipated as well as expected relationships [ 9 ]. The OPAL trial was more closely aligned with Yin, where the research team predefined some of their theoretical assumptions, based on how the intervention was expected to work. The relevant parts of the data analysis then drew on data to support or refute the theoretical propositions. This was particularly useful for the trial as the prespecified theoretical propositions linked to the mechanisms of action on which the intervention was anticipated to have an effect (or not).

Tailoring to the trial design

Process evaluations need to be tailored to the trial, the intervention and the outcomes being measured [ 45 ]. For example, in a stepped wedge design (where the intervention is delivered in a phased manner), researchers should try to ensure process data are captured at relevant time points or in a two-arm or multiple arm trial, ensure data is collected from the control group(s) as well as the intervention group(s). In the DQIP trial, a stepped wedge trial, at least one process evaluation case, was sampled per cohort. Trials often continue to measure outcomes after delivery of the intervention has ceased, so researchers should also consider capturing ‘follow-up’ data on contextual factors, which may continue to influence the outcome measure. The OPAL trial had two active treatment arms so collected process data from both arms. In addition, as the trial was interested in long-term adherence, the trial and the process evaluation collected data from participants for 2 years after the intervention was initially delivered, providing 24 months follow-up data, in line with the primary outcome for the trial.

Defining the case

Case studies can include single or multiple cases in their design. Single case studies usually sample typical or unique cases, their advantage being the depth and richness that can be achieved over a long period of time. The advantages of multiple case study design are that cases can be compared to generate a greater depth of analysis. Multiple case study sampling may be carried out in order to test for replication or contradiction [ 8 ]. Given that trials are often conducted over a number of sites, a multiple case study design is more sensible for process evaluations, as there is likely to be variation in implementation between sites. Case definition may occur at a variety of levels but is most appropriate if it reflects the trial design. For example, a case in an individual patient level trial is likely to be defined as a person/patient (e.g. a woman with urinary incontinence—OPAL trial) whereas in a cluster trial, a case is like to be a cluster, such as an organisation (e.g. a general practice—DQIP trial). Of course, the process evaluation could explore cases with less distinct boundaries, such as communities or relationships; however, the clarity with which these cases are defined is important, in order to scope the nature of the data that will be generated.

Carefully sampled cases are critical to a good case study as sampling helps inform the quality of the inferences that can be made from the data [ 53 ]. In both qualitative and quantitative research, how and how many participants to sample must be decided when planning the study. Quantitative sampling techniques generally aim to achieve a random sample. Qualitative research generally uses purposive samples to achieve data saturation, occurring when the incoming data produces little or no new information to address the research questions. The term data saturation has evolved from theoretical saturation in conventional grounded theory studies; however, its relevance to other types of studies is contentious as the term saturation seems to be widely used but poorly justified [ 54 ]. Empirical evidence suggests that for in-depth interview studies, saturation occurs at 12 interviews for thematic saturation, but typically more would be needed for a heterogenous sample higher degrees of saturation [ 55 , 56 ]. Both DQIP and OPAL case studies were huge with OPAL designed to interview each of the 40 individual cases four times and DQIP designed to interview the lead DQIP general practitioner (GP) twice (to capture change over time), another GP and the practice manager from each of the 10 organisational cases. Despite the plethora of mixed methods research textbooks, there is very little about sampling as discussions typically link to method (e.g. interviews) rather than paradigm (e.g. case study).

Purposive sampling can improve the generalisability of the process evaluation by sampling for greater contextual diversity. The typical or average case is often not the richest source of information. Outliers can often reveal more important insights, because they may reflect the implementation of the intervention using different processes. Cases can be selected from a number of criteria, which are not mutually exclusive, to enable a rich and detailed picture to be built across sites [ 53 ]. To avoid the Hawthorne effect, it is recommended that process evaluations sample from both intervention and control sites, which enables comparison and explanation. There is always a trade-off between breadth and depth in sampling, so it is important to note that often quantity does not mean quality and that carefully sampled cases can provide powerful illustrative examples of how the intervention worked in practice, the relationship between the intervention and context and how and why they evolved together. The qualitative components of both DQIP and OPAL process evaluations aimed for maximum variation sampling. Please see Table  1 for further information on how DQIP’s sampling frame was important for providing contextual information on processes influencing effective implementation of the intervention.

Conceptual and theoretical framework

A conceptual or theoretical framework helps to frame data collection and analysis [ 57 ]. Theories can also underpin propositions, which can be tested in the process evaluation. Process evaluations produce intervention-dependent knowledge, and theories help make the research findings more generalizable by providing a common language [ 16 ]. There are a number of mid-range theories which have been designed to be used with process evaluation [ 34 , 35 , 58 ]. The choice of the appropriate conceptual or theoretical framework is, however, dependent on the philosophical and professional background of the research. The two examples within this paper used our own framework for the design of process evaluations, which proposes a number of candidate processes which can be explored, for example, recruitment, delivery, response, maintenance and context [ 45 ]. This framework was published before the MRC guidance on process evaluations, and both the DQIP and OPAL process evaluations were designed before the MRC guidance was published. The DQIP process evaluation explored all candidates in the framework whereas the OPAL process evaluation selected four candidates, illustrating that process evaluations can be selective in what they explore based on the purpose, research questions and resources. Furthermore, as Kislov and colleagues argue, we also have a responsibility to critique the theoretical framework underpinning the evaluation and refine theories to advance knowledge [ 59 ].

Data collection

An important consideration is what data to collect or measure and when. Case study methodology supports a range of data collection methods, both qualitative and quantitative, to best answer the research questions. As the aim of the case study is to gain an in-depth understanding of phenomena in context, methods are more commonly qualitative or mixed method in nature. Qualitative methods such as interviews, focus groups and observation offer rich descriptions of the setting, delivery of the intervention in each site and arm, how the intervention was perceived by the professionals delivering the intervention and the patients receiving the intervention. Quantitative methods can measure recruitment, fidelity and dose and establish which characteristics are associated with adoption, delivery and effectiveness. To ensure an understanding of the complexity of the relationship between the intervention and context, the case study should rely on multiple sources of data and triangulate these to confirm and corroborate the findings [ 8 ]. Process evaluations might consider using routine data collected in the trial across all sites and additional qualitative data across carefully sampled sites for a more nuanced picture within reasonable resource constraints. Mixed methods allow researchers to ask more complex questions and collect richer data than can be collected by one method alone [ 60 ]. The use of multiple sources of data allows data triangulation, which increases a study’s internal validity but also provides a more in-depth and holistic depiction of the case [ 20 ]. For example, in the DQIP process evaluation, the quantitative component used routinely collected data from all sites participating in the trial and purposively sampled cases for a more in-depth qualitative exploration [ 21 , 38 , 39 ].

The timing of data collection is crucial to study design, especially within a process evaluation where data collection can potentially influence the trial outcome. Process evaluations are generally in parallel or retrospective to the trial. The advantage of a retrospective design is that the evaluation itself is less likely to influence the trial outcome. However, the disadvantages include recall bias, lack of sensitivity to nuances and an inability to iteratively explore the relationship between intervention and outcome as it develops. To capture the dynamic relationship between intervention and context, the process evaluation needs to be parallel and longitudinal to the trial. Longitudinal methodological design is rare, but it is needed to capture the dynamic nature of implementation [ 40 ]. How the intervention is delivered is likely to change over time as it interacts with context. For example, as professionals deliver the intervention, they become more familiar with it, and it becomes more embedded into systems. The OPAL process evaluation was a longitudinal, mixed methods process evaluation where the quantitative component had been predefined and built into trial data collection systems. Data collection in both the qualitative and quantitative components mirrored the trial data collection points, which were longitudinal to capture adherence and contextual changes over time.

There is a lot of attention in the recent literature towards a systems approach to understanding interventions in context, which suggests interventions are ‘events within systems’ [ 61 , 62 ]. This framing highlights the dynamic nature of context, suggesting that interventions are an attempt to change systems dynamics. This conceptualisation would suggest that the study design should collect contextual data before and after implementation to assess the effect of the intervention on the context and vice versa.

Data analysis

Designing a rigorous analysis plan is particularly important for multiple case studies, where researchers must decide whether their approach to analysis is case or variable based. Case-based analysis is the most common, and analytic strategies must be clearly articulated for within and across case analysis. A multiple case study design can consist of multiple cases, where each case is analysed at the case level, or of multiple embedded cases, where data from all the cases are pulled together for analysis at some level. For example, OPAL analysis was at the case level, but all the cases for the intervention and control arms were pulled together at the arm level for more in-depth analysis and comparison. For Yin, analytical strategies rely on theoretical propositions, but for Stake, analysis works from the data to develop theory. In OPAL and DQIP, case summaries were written to summarise the cases and detail within-case analysis. Each of the studies structured these differently based on the phenomena of interest and the analytic technique. DQIP applied an approach more akin to Stake [ 9 ], with the cases summarised around inductive themes whereas OPAL applied a Yin [ 8 ] type approach using theoretical propositions around which the case summaries were structured. As the data for each case had been collected through longitudinal interviews, the case summaries were able to capture changes over time. It is beyond the scope of this paper to discuss different analytic techniques; however, to ensure the holistic examination of the intervention(s) in context, it is important to clearly articulate and demonstrate how data is integrated and synthesised [ 31 ].

There are a number of approaches to process evaluation design in the literature; however, there is a paucity of research on what case study design can offer process evaluations. We argue that case study is one of the best research designs to underpin process evaluations, to capture the dynamic and complex relationship between intervention and context during implementation [ 38 ]. Case study can enable comparisons within and across intervention and control arms and enable the evolving relationship between intervention and context to be captured holistically rather than considering processes in isolation. Utilising a longitudinal design can enable the dynamic relationship between context and intervention to be captured in real time. This information is fundamental to holistically explaining what intervention was implemented, understanding how and why the intervention worked or not and informing the transferability of the intervention into routine clinical practice.

Case study designs are not prescriptive, but process evaluations using case study should consider the purpose, trial design, the theories or assumptions underpinning the intervention, and the conceptual and theoretical frameworks informing the evaluation. We have discussed each of these considerations in turn, providing a comprehensive overview of issues for process evaluations using a case study design. There is no single or best way to conduct a process evaluation or a case study, but researchers need to make informed choices about the process evaluation design. Although this paper focuses on process evaluations, we recognise that case study design could also be useful during intervention development and feasibility trials. Elements of this paper are also applicable to other study designs involving trials.

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Abbreviations

Data-driven Quality Improvement in Primary Care

Medical Research Council

Nonsteroidal anti-inflammatory drugs

Optimizing Pelvic Floor Muscle Exercises to Achieve Long-term benefits

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Grant, A., Bugge, C. & Wells, M. Designing process evaluations using case study to explore the context of complex interventions evaluated in trials. Trials 21 , 982 (2020). https://doi.org/10.1186/s13063-020-04880-4

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Qualitative Research: Case study evaluation

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Case study evaluations, using one or more qualitative methods, have been used to investigate important practical and policy questions in health care. This paper describes the features of a well designed case study and gives examples showing how qualitative methods are used in evaluations of health services and health policy.

This is the last in a series of seven articles describing non-quantitative techniques and showing their value in health research

Introduction

The medical approach to understanding disease has traditionally drawn heavily on qualitative data, and in particular on case studies to illustrate important or interesting phenomena. The tradition continues today, not least in regular case reports in this and other medical journals. Moreover, much of the everyday work of doctors and other health professionals still involves decisions that are qualitative rather than quantitative in nature.

This paper discusses the use of qualitative research methods, not in clinical care but in case study evaluations of health service interventions. It is useful for doctors to understand the principles guiding the design and conduct of these evaluations, because they are frequently used by both researchers and inspectorial agencies (such as the Audit Commission in the United Kingdom and the Office of Technology Assessment in the United States) to investigate the work of doctors and other health professionals.

We briefly discuss the circumstances in which case study research can usefully be undertaken in health service settings and the ways in which qualitative methods are used within case studies. Examples show how qualitative methods are applied, both in purely qualitative studies and alongside quantitative methods.

Case study evaluations

Doctors often find themselves asking important practical questions, such as should we be involved in the management of hospitals and, if so, how? how will new government policies affect the lives of our patients? and how can we cope with changes …

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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.

Prevent plagiarism. Run a free check.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
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15.7 Evaluation: Presentation and Analysis of Case Study

Learning outcomes.

By the end of this section, you will be able to:

• Revise writing to follow the genre conventions of case studies.
• Evaluate the effectiveness and quality of a case study report.

Case studies follow a structure of background and context , methods , findings , and analysis . Body paragraphs should have main points and concrete details. In addition, case studies are written in formal language with precise wording and with a specific purpose and audience (generally other professionals in the field) in mind. Case studies also adhere to the conventions of the discipline’s formatting guide ( APA Documentation and Format in this study). Compare your case study with the following rubric as a final check.

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Case study research for better evaluations of complex interventions: rationale and challenges

• Sara Paparini   ORCID: orcid.org/0000-0002-1909-2481 1 ,
• Judith Green 2 ,
• Chrysanthi Papoutsi 1 ,
• Jamie Murdoch 3 ,
• Mark Petticrew 4 ,
• Trish Greenhalgh 1 ,
• Benjamin Hanckel 5 &
• Sara Shaw 1  

BMC Medicine volume  18 , Article number:  301 ( 2020 ) Cite this article

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The need for better methods for evaluation in health research has been widely recognised. The ‘complexity turn’ has drawn attention to the limitations of relying on causal inference from randomised controlled trials alone for understanding whether, and under which conditions, interventions in complex systems improve health services or the public health, and what mechanisms might link interventions and outcomes. We argue that case study research—currently denigrated as poor evidence—is an under-utilised resource for not only providing evidence about context and transferability, but also for helping strengthen causal inferences when pathways between intervention and effects are likely to be non-linear.

Case study research, as an overall approach, is based on in-depth explorations of complex phenomena in their natural, or real-life, settings. Empirical case studies typically enable dynamic understanding of complex challenges and provide evidence about causal mechanisms and the necessary and sufficient conditions (contexts) for intervention implementation and effects. This is essential evidence not just for researchers concerned about internal and external validity, but also research users in policy and practice who need to know what the likely effects of complex programmes or interventions will be in their settings. The health sciences have much to learn from scholarship on case study methodology in the social sciences. However, there are multiple challenges in fully exploiting the potential learning from case study research. First are misconceptions that case study research can only provide exploratory or descriptive evidence. Second, there is little consensus about what a case study is, and considerable diversity in how empirical case studies are conducted and reported. Finally, as case study researchers typically (and appropriately) focus on thick description (that captures contextual detail), it can be challenging to identify the key messages related to intervention evaluation from case study reports.

Whilst the diversity of published case studies in health services and public health research is rich and productive, we recommend further clarity and specific methodological guidance for those reporting case study research for evaluation audiences.

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The need for methodological development to address the most urgent challenges in health research has been well-documented. Many of the most pressing questions for public health research, where the focus is on system-level determinants [ 1 , 2 ], and for health services research, where provisions typically vary across sites and are provided through interlocking networks of services [ 3 ], require methodological approaches that can attend to complexity. The need for methodological advance has arisen, in part, as a result of the diminishing returns from randomised controlled trials (RCTs) where they have been used to answer questions about the effects of interventions in complex systems [ 4 , 5 , 6 ]. In conditions of complexity, there is limited value in maintaining the current orientation to experimental trial designs in the health sciences as providing ‘gold standard’ evidence of effect.

There are increasing calls for methodological pluralism [ 7 , 8 ], with the recognition that complex intervention and context are not easily or usefully separated (as is often the situation when using trial design), and that system interruptions may have effects that are not reducible to linear causal pathways between intervention and outcome. These calls are reflected in a shifting and contested discourse of trial design, seen with the emergence of realist [ 9 ], adaptive and hybrid (types 1, 2 and 3) [ 10 , 11 ] trials that blend studies of effectiveness with a close consideration of the contexts of implementation. Similarly, process evaluation has now become a core component of complex healthcare intervention trials, reflected in MRC guidance on how to explore implementation, causal mechanisms and context [ 12 ].

Evidence about the context of an intervention is crucial for questions of external validity. As Woolcock [ 4 ] notes, even if RCT designs are accepted as robust for maximising internal validity, questions of transferability (how well the intervention works in different contexts) and generalisability (how well the intervention can be scaled up) remain unanswered [ 5 , 13 ]. For research evidence to have impact on policy and systems organisation, and thus to improve population and patient health, there is an urgent need for better methods for strengthening external validity, including a better understanding of the relationship between intervention and context [ 14 ].

Policymakers, healthcare commissioners and other research users require credible evidence of relevance to their settings and populations [ 15 ], to perform what Rosengarten and Savransky [ 16 ] call ‘careful abstraction’ to the locales that matter for them. They also require robust evidence for understanding complex causal pathways. Case study research, currently under-utilised in public health and health services evaluation, can offer considerable potential for strengthening faith in both external and internal validity. For example, in an empirical case study of how the policy of free bus travel had specific health effects in London, UK, a quasi-experimental evaluation (led by JG) identified how important aspects of context (a good public transport system) and intervention (that it was universal) were necessary conditions for the observed effects, thus providing useful, actionable evidence for decision-makers in other contexts [ 17 ].

The overall approach of case study research is based on the in-depth exploration of complex phenomena in their natural, or ‘real-life’, settings. Empirical case studies typically enable dynamic understanding of complex challenges rather than restricting the focus on narrow problem delineations and simple fixes. Case study research is a diverse and somewhat contested field, with multiple definitions and perspectives grounded in different ways of viewing the world, and involving different combinations of methods. In this paper, we raise awareness of such plurality and highlight the contribution that case study research can make to the evaluation of complex system-level interventions. We review some of the challenges in exploiting the current evidence base from empirical case studies and conclude by recommending that further guidance and minimum reporting criteria for evaluation using case studies, appropriate for audiences in the health sciences, can enhance the take-up of evidence from case study research.

Case study research offers evidence about context, causal inference in complex systems and implementation

Well-conducted and described empirical case studies provide evidence on context, complexity and mechanisms for understanding how, where and why interventions have their observed effects. Recognition of the importance of context for understanding the relationships between interventions and outcomes is hardly new. In 1943, Canguilhem berated an over-reliance on experimental designs for determining universal physiological laws: ‘As if one could determine a phenomenon’s essence apart from its conditions! As if conditions were a mask or frame which changed neither the face nor the picture!’ ([ 18 ] p126). More recently, a concern with context has been expressed in health systems and public health research as part of what has been called the ‘complexity turn’ [ 1 ]: a recognition that many of the most enduring challenges for developing an evidence base require a consideration of system-level effects [ 1 ] and the conceptualisation of interventions as interruptions in systems [ 19 ].

The case study approach is widely recognised as offering an invaluable resource for understanding the dynamic and evolving influence of context on complex, system-level interventions [ 20 , 21 , 22 , 23 ]. Empirically, case studies can directly inform assessments of where, when, how and for whom interventions might be successfully implemented, by helping to specify the necessary and sufficient conditions under which interventions might have effects and to consolidate learning on how interdependencies, emergence and unpredictability can be managed to achieve and sustain desired effects. Case study research has the potential to address four objectives for improving research and reporting of context recently set out by guidance on taking account of context in population health research [ 24 ], that is to (1) improve the appropriateness of intervention development for specific contexts, (2) improve understanding of ‘how’ interventions work, (3) better understand how and why impacts vary across contexts and (4) ensure reports of intervention studies are most useful for decision-makers and researchers.

However, evaluations of complex healthcare interventions have arguably not exploited the full potential of case study research and can learn much from other disciplines. For evaluative research, exploratory case studies have had a traditional role of providing data on ‘process’, or initial ‘hypothesis-generating’ scoping, but might also have an increasing salience for explanatory aims. Across the social and political sciences, different kinds of case studies are undertaken to meet diverse aims (description, exploration or explanation) and across different scales (from small N qualitative studies that aim to elucidate processes, or provide thick description, to more systematic techniques designed for medium-to-large N cases).

Case studies with explanatory aims vary in terms of their positioning within mixed-methods projects, with designs including (but not restricted to) (1) single N of 1 studies of interventions in specific contexts, where the overall design is a case study that may incorporate one or more (randomised or not) comparisons over time and between variables within the case; (2) a series of cases conducted or synthesised to provide explanation from variations between cases; and (3) case studies of particular settings within RCT or quasi-experimental designs to explore variation in effects or implementation.

Detailed qualitative research (typically done as ‘case studies’ within process evaluations) provides evidence for the plausibility of mechanisms [ 25 ], offering theoretical generalisations for how interventions may function under different conditions. Although RCT designs reduce many threats to internal validity, the mechanisms of effect remain opaque, particularly when the causal pathways between ‘intervention’ and ‘effect’ are long and potentially non-linear: case study research has a more fundamental role here, in providing detailed observational evidence for causal claims [ 26 ] as well as producing a rich, nuanced picture of tensions and multiple perspectives [ 8 ].

Longitudinal or cross-case analysis may be best suited for evidence generation in system-level evaluative research. Turner [ 27 ], for instance, reflecting on the complex processes in major system change, has argued for the need for methods that integrate learning across cases, to develop theoretical knowledge that would enable inferences beyond the single case, and to develop generalisable theory about organisational and structural change in health systems. Qualitative Comparative Analysis (QCA) [ 28 ] is one such formal method for deriving causal claims, using set theory mathematics to integrate data from empirical case studies to answer questions about the configurations of causal pathways linking conditions to outcomes [ 29 , 30 ].

Nonetheless, the single N case study, too, provides opportunities for theoretical development [ 31 ], and theoretical generalisation or analytical refinement [ 32 ]. How ‘the case’ and ‘context’ are conceptualised is crucial here. Findings from the single case may seem to be confined to its intrinsic particularities in a specific and distinct context [ 33 ]. However, if such context is viewed as exemplifying wider social and political forces, the single case can be ‘telling’, rather than ‘typical’, and offer insight into a wider issue [ 34 ]. Internal comparisons within the case can offer rich possibilities for logical inferences about causation [ 17 ]. Further, case studies of any size can be used for theory testing through refutation [ 22 ]. The potential lies, then, in utilising the strengths and plurality of case study to support theory-driven research within different methodological paradigms.

Evaluation research in health has much to learn from a range of social sciences where case study methodology has been used to develop various kinds of causal inference. For instance, Gerring [ 35 ] expands on the within-case variations utilised to make causal claims. For Gerring [ 35 ], case studies come into their own with regard to invariant or strong causal claims (such as X is a necessary and/or sufficient condition for Y) rather than for probabilistic causal claims. For the latter (where experimental methods might have an advantage in estimating effect sizes), case studies offer evidence on mechanisms: from observations of X affecting Y, from process tracing or from pattern matching. Case studies also support the study of emergent causation, that is, the multiple interacting properties that account for particular and unexpected outcomes in complex systems, such as in healthcare [ 8 ].

Finally, efficacy (or beliefs about efficacy) is not the only contributor to intervention uptake, with a range of organisational and policy contingencies affecting whether an intervention is likely to be rolled out in practice. Case study research is, therefore, invaluable for learning about contextual contingencies and identifying the conditions necessary for interventions to become normalised (i.e. implemented routinely) in practice [ 36 ].

The challenges in exploiting evidence from case study research

At present, there are significant challenges in exploiting the benefits of case study research in evaluative health research, which relate to status, definition and reporting. Case study research has been marginalised at the bottom of an evidence hierarchy, seen to offer little by way of explanatory power, if nonetheless useful for adding descriptive data on process or providing useful illustrations for policymakers [ 37 ]. This is an opportune moment to revisit this low status. As health researchers are increasingly charged with evaluating ‘natural experiments’—the use of face masks in the response to the COVID-19 pandemic being a recent example [ 38 ]—rather than interventions that take place in settings that can be controlled, research approaches using methods to strengthen causal inference that does not require randomisation become more relevant.

A second challenge for improving the use of case study evidence in evaluative health research is that, as we have seen, what is meant by ‘case study’ varies widely, not only across but also within disciplines. There is indeed little consensus amongst methodologists as to how to define ‘a case study’. Definitions focus, variously, on small sample size or lack of control over the intervention (e.g. [ 39 ] p194), on in-depth study and context [ 40 , 41 ], on the logic of inference used [ 35 ] or on distinct research strategies which incorporate a number of methods to address questions of ‘how’ and ‘why’ [ 42 ]. Moreover, definitions developed for specific disciplines do not capture the range of ways in which case study research is carried out across disciplines. Multiple definitions of case study reflect the richness and diversity of the approach. However, evidence suggests that a lack of consensus across methodologists results in some of the limitations of published reports of empirical case studies [ 43 , 44 ]. Hyett and colleagues [ 43 ], for instance, reviewing reports in qualitative journals, found little match between methodological definitions of case study research and how authors used the term.

This raises the third challenge we identify that case study reports are typically not written in ways that are accessible or useful for the evaluation research community and policymakers. Case studies may not appear in journals widely read by those in the health sciences, either because space constraints preclude the reporting of rich, thick descriptions, or because of the reported lack of willingness of some biomedical journals to publish research that uses qualitative methods [ 45 ], signalling the persistence of the aforementioned evidence hierarchy. Where they do, however, the term ‘case study’ is used to indicate, interchangeably, a qualitative study, an N of 1 sample, or a multi-method, in-depth analysis of one example from a population of phenomena. Definitions of what constitutes the ‘case’ are frequently lacking and appear to be used as a synonym for the settings in which the research is conducted. Despite offering insights for evaluation, the primary aims may not have been evaluative, so the implications may not be explicitly drawn out. Indeed, some case study reports might properly be aiming for thick description without necessarily seeking to inform about context or causality.

Acknowledging plurality and developing guidance

We recognise that definitional and methodological plurality is not only inevitable, but also a necessary and creative reflection of the very different epistemological and disciplinary origins of health researchers, and the aims they have in doing and reporting case study research. Indeed, to provide some clarity, Thomas [ 46 ] has suggested a typology of subject/purpose/approach/process for classifying aims (e.g. evaluative or exploratory), sample rationale and selection and methods for data generation of case studies. We also recognise that the diversity of methods used in case study research, and the necessary focus on narrative reporting, does not lend itself to straightforward development of formal quality or reporting criteria.

Existing checklists for reporting case study research from the social sciences—for example Lincoln and Guba’s [ 47 ] and Stake’s [ 33 ]—are primarily orientated to the quality of narrative produced, and the extent to which they encapsulate thick description, rather than the more pragmatic issues of implications for intervention effects. Those designed for clinical settings, such as the CARE (CAse REports) guidelines, provide specific reporting guidelines for medical case reports about single, or small groups of patients [ 48 ], not for case study research.

The Design of Case Study Research in Health Care (DESCARTE) model [ 44 ] suggests a series of questions to be asked of a case study researcher (including clarity about the philosophy underpinning their research), study design (with a focus on case definition) and analysis (to improve process). The model resembles toolkits for enhancing the quality and robustness of qualitative and mixed-methods research reporting, and it is usefully open-ended and non-prescriptive. However, even if it does include some reflections on context, the model does not fully address aspects of context, logic and causal inference that are perhaps most relevant for evaluative research in health.

Hence, for evaluative research where the aim is to report empirical findings in ways that are intended to be pragmatically useful for health policy and practice, this may be an opportune time to consider how to best navigate plurality around what is (minimally) important to report when publishing empirical case studies, especially with regards to the complex relationships between context and interventions, information that case study research is well placed to provide.

The conventional scientific quest for certainty, predictability and linear causality (maximised in RCT designs) has to be augmented by the study of uncertainty, unpredictability and emergent causality [ 8 ] in complex systems. This will require methodological pluralism, and openness to broadening the evidence base to better understand both causality in and the transferability of system change intervention [ 14 , 20 , 23 , 25 ]. Case study research evidence is essential, yet is currently under exploited in the health sciences. If evaluative health research is to move beyond the current impasse on methods for understanding interventions as interruptions in complex systems, we need to consider in more detail how researchers can conduct and report empirical case studies which do aim to elucidate the contextual factors which interact with interventions to produce particular effects. To this end, supported by the UK’s Medical Research Council, we are embracing the challenge to develop guidance for case study researchers studying complex interventions. Following a meta-narrative review of the literature, we are planning a Delphi study to inform guidance that will, at minimum, cover the value of case study research for evaluating the interrelationship between context and complex system-level interventions; for situating and defining ‘the case’, and generalising from case studies; as well as provide specific guidance on conducting, analysing and reporting case study research. Our hope is that such guidance can support researchers evaluating interventions in complex systems to better exploit the diversity and richness of case study research.

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Abbreviations

Qualitative comparative analysis

Quasi-experimental design

Randomised controlled trial

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This work was funded by the Medical Research Council - MRC Award MR/S014632/1 HCS: Case study, Context and Complex interventions (TRIPLE C). SP was additionally funded by the University of Oxford's Higher Education Innovation Fund (HEIF).

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Paparini, S., Green, J., Papoutsi, C. et al. Case study research for better evaluations of complex interventions: rationale and challenges. BMC Med 18 , 301 (2020). https://doi.org/10.1186/s12916-020-01777-6

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On This Page:

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

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

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

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

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

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

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

 Famous Case Studies

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

Clinical Case Studies

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

Child Psychology Case Studies

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

Types of Case Studies

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

Where Do You Find Data for a Case Study?

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

1. Primary sources

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

2. Secondary sources

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

3. Archival records

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

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

4. Organizational records

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

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

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

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

How do I Write a Case Study in Psychology?

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

1. Introduction

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

2. Case Presentation

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

3. Management and Outcome

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

4. Discussion

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

5. Additional Items

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

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

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

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

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

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

Limitations

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Further Information

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

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Case study research for better evaluations of complex interventions: rationale and challenges

Sara paparini.

1 Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK

Judith Green

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

Chrysanthi Papoutsi

Jamie murdoch.

3 School of Health Sciences, University of East Anglia, Norwich, UK

Mark Petticrew

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

Trish Greenhalgh

Benjamin hanckel.

5 Institute for Culture and Society, Western Sydney University, Penrith, Australia

Associated Data

Not applicable (article based on existing available academic publications)

The need for better methods for evaluation in health research has been widely recognised. The ‘complexity turn’ has drawn attention to the limitations of relying on causal inference from randomised controlled trials alone for understanding whether, and under which conditions, interventions in complex systems improve health services or the public health, and what mechanisms might link interventions and outcomes. We argue that case study research—currently denigrated as poor evidence—is an under-utilised resource for not only providing evidence about context and transferability, but also for helping strengthen causal inferences when pathways between intervention and effects are likely to be non-linear.

Case study research, as an overall approach, is based on in-depth explorations of complex phenomena in their natural, or real-life, settings. Empirical case studies typically enable dynamic understanding of complex challenges and provide evidence about causal mechanisms and the necessary and sufficient conditions (contexts) for intervention implementation and effects. This is essential evidence not just for researchers concerned about internal and external validity, but also research users in policy and practice who need to know what the likely effects of complex programmes or interventions will be in their settings. The health sciences have much to learn from scholarship on case study methodology in the social sciences. However, there are multiple challenges in fully exploiting the potential learning from case study research. First are misconceptions that case study research can only provide exploratory or descriptive evidence. Second, there is little consensus about what a case study is, and considerable diversity in how empirical case studies are conducted and reported. Finally, as case study researchers typically (and appropriately) focus on thick description (that captures contextual detail), it can be challenging to identify the key messages related to intervention evaluation from case study reports.

Whilst the diversity of published case studies in health services and public health research is rich and productive, we recommend further clarity and specific methodological guidance for those reporting case study research for evaluation audiences.

The need for methodological development to address the most urgent challenges in health research has been well-documented. Many of the most pressing questions for public health research, where the focus is on system-level determinants [ 1 , 2 ], and for health services research, where provisions typically vary across sites and are provided through interlocking networks of services [ 3 ], require methodological approaches that can attend to complexity. The need for methodological advance has arisen, in part, as a result of the diminishing returns from randomised controlled trials (RCTs) where they have been used to answer questions about the effects of interventions in complex systems [ 4 – 6 ]. In conditions of complexity, there is limited value in maintaining the current orientation to experimental trial designs in the health sciences as providing ‘gold standard’ evidence of effect.

There are increasing calls for methodological pluralism [ 7 , 8 ], with the recognition that complex intervention and context are not easily or usefully separated (as is often the situation when using trial design), and that system interruptions may have effects that are not reducible to linear causal pathways between intervention and outcome. These calls are reflected in a shifting and contested discourse of trial design, seen with the emergence of realist [ 9 ], adaptive and hybrid (types 1, 2 and 3) [ 10 , 11 ] trials that blend studies of effectiveness with a close consideration of the contexts of implementation. Similarly, process evaluation has now become a core component of complex healthcare intervention trials, reflected in MRC guidance on how to explore implementation, causal mechanisms and context [ 12 ].

Evidence about the context of an intervention is crucial for questions of external validity. As Woolcock [ 4 ] notes, even if RCT designs are accepted as robust for maximising internal validity, questions of transferability (how well the intervention works in different contexts) and generalisability (how well the intervention can be scaled up) remain unanswered [ 5 , 13 ]. For research evidence to have impact on policy and systems organisation, and thus to improve population and patient health, there is an urgent need for better methods for strengthening external validity, including a better understanding of the relationship between intervention and context [ 14 ].

Policymakers, healthcare commissioners and other research users require credible evidence of relevance to their settings and populations [ 15 ], to perform what Rosengarten and Savransky [ 16 ] call ‘careful abstraction’ to the locales that matter for them. They also require robust evidence for understanding complex causal pathways. Case study research, currently under-utilised in public health and health services evaluation, can offer considerable potential for strengthening faith in both external and internal validity. For example, in an empirical case study of how the policy of free bus travel had specific health effects in London, UK, a quasi-experimental evaluation (led by JG) identified how important aspects of context (a good public transport system) and intervention (that it was universal) were necessary conditions for the observed effects, thus providing useful, actionable evidence for decision-makers in other contexts [ 17 ].

The overall approach of case study research is based on the in-depth exploration of complex phenomena in their natural, or ‘real-life’, settings. Empirical case studies typically enable dynamic understanding of complex challenges rather than restricting the focus on narrow problem delineations and simple fixes. Case study research is a diverse and somewhat contested field, with multiple definitions and perspectives grounded in different ways of viewing the world, and involving different combinations of methods. In this paper, we raise awareness of such plurality and highlight the contribution that case study research can make to the evaluation of complex system-level interventions. We review some of the challenges in exploiting the current evidence base from empirical case studies and conclude by recommending that further guidance and minimum reporting criteria for evaluation using case studies, appropriate for audiences in the health sciences, can enhance the take-up of evidence from case study research.

Case study research offers evidence about context, causal inference in complex systems and implementation

Well-conducted and described empirical case studies provide evidence on context, complexity and mechanisms for understanding how, where and why interventions have their observed effects. Recognition of the importance of context for understanding the relationships between interventions and outcomes is hardly new. In 1943, Canguilhem berated an over-reliance on experimental designs for determining universal physiological laws: ‘As if one could determine a phenomenon’s essence apart from its conditions! As if conditions were a mask or frame which changed neither the face nor the picture!’ ([ 18 ] p126). More recently, a concern with context has been expressed in health systems and public health research as part of what has been called the ‘complexity turn’ [ 1 ]: a recognition that many of the most enduring challenges for developing an evidence base require a consideration of system-level effects [ 1 ] and the conceptualisation of interventions as interruptions in systems [ 19 ].

The case study approach is widely recognised as offering an invaluable resource for understanding the dynamic and evolving influence of context on complex, system-level interventions [ 20 – 23 ]. Empirically, case studies can directly inform assessments of where, when, how and for whom interventions might be successfully implemented, by helping to specify the necessary and sufficient conditions under which interventions might have effects and to consolidate learning on how interdependencies, emergence and unpredictability can be managed to achieve and sustain desired effects. Case study research has the potential to address four objectives for improving research and reporting of context recently set out by guidance on taking account of context in population health research [ 24 ], that is to (1) improve the appropriateness of intervention development for specific contexts, (2) improve understanding of ‘how’ interventions work, (3) better understand how and why impacts vary across contexts and (4) ensure reports of intervention studies are most useful for decision-makers and researchers.

However, evaluations of complex healthcare interventions have arguably not exploited the full potential of case study research and can learn much from other disciplines. For evaluative research, exploratory case studies have had a traditional role of providing data on ‘process’, or initial ‘hypothesis-generating’ scoping, but might also have an increasing salience for explanatory aims. Across the social and political sciences, different kinds of case studies are undertaken to meet diverse aims (description, exploration or explanation) and across different scales (from small N qualitative studies that aim to elucidate processes, or provide thick description, to more systematic techniques designed for medium-to-large N cases).

Case studies with explanatory aims vary in terms of their positioning within mixed-methods projects, with designs including (but not restricted to) (1) single N of 1 studies of interventions in specific contexts, where the overall design is a case study that may incorporate one or more (randomised or not) comparisons over time and between variables within the case; (2) a series of cases conducted or synthesised to provide explanation from variations between cases; and (3) case studies of particular settings within RCT or quasi-experimental designs to explore variation in effects or implementation.

Detailed qualitative research (typically done as ‘case studies’ within process evaluations) provides evidence for the plausibility of mechanisms [ 25 ], offering theoretical generalisations for how interventions may function under different conditions. Although RCT designs reduce many threats to internal validity, the mechanisms of effect remain opaque, particularly when the causal pathways between ‘intervention’ and ‘effect’ are long and potentially non-linear: case study research has a more fundamental role here, in providing detailed observational evidence for causal claims [ 26 ] as well as producing a rich, nuanced picture of tensions and multiple perspectives [ 8 ].

Longitudinal or cross-case analysis may be best suited for evidence generation in system-level evaluative research. Turner [ 27 ], for instance, reflecting on the complex processes in major system change, has argued for the need for methods that integrate learning across cases, to develop theoretical knowledge that would enable inferences beyond the single case, and to develop generalisable theory about organisational and structural change in health systems. Qualitative Comparative Analysis (QCA) [ 28 ] is one such formal method for deriving causal claims, using set theory mathematics to integrate data from empirical case studies to answer questions about the configurations of causal pathways linking conditions to outcomes [ 29 , 30 ].

Nonetheless, the single N case study, too, provides opportunities for theoretical development [ 31 ], and theoretical generalisation or analytical refinement [ 32 ]. How ‘the case’ and ‘context’ are conceptualised is crucial here. Findings from the single case may seem to be confined to its intrinsic particularities in a specific and distinct context [ 33 ]. However, if such context is viewed as exemplifying wider social and political forces, the single case can be ‘telling’, rather than ‘typical’, and offer insight into a wider issue [ 34 ]. Internal comparisons within the case can offer rich possibilities for logical inferences about causation [ 17 ]. Further, case studies of any size can be used for theory testing through refutation [ 22 ]. The potential lies, then, in utilising the strengths and plurality of case study to support theory-driven research within different methodological paradigms.

Evaluation research in health has much to learn from a range of social sciences where case study methodology has been used to develop various kinds of causal inference. For instance, Gerring [ 35 ] expands on the within-case variations utilised to make causal claims. For Gerring [ 35 ], case studies come into their own with regard to invariant or strong causal claims (such as X is a necessary and/or sufficient condition for Y) rather than for probabilistic causal claims. For the latter (where experimental methods might have an advantage in estimating effect sizes), case studies offer evidence on mechanisms: from observations of X affecting Y, from process tracing or from pattern matching. Case studies also support the study of emergent causation, that is, the multiple interacting properties that account for particular and unexpected outcomes in complex systems, such as in healthcare [ 8 ].

Finally, efficacy (or beliefs about efficacy) is not the only contributor to intervention uptake, with a range of organisational and policy contingencies affecting whether an intervention is likely to be rolled out in practice. Case study research is, therefore, invaluable for learning about contextual contingencies and identifying the conditions necessary for interventions to become normalised (i.e. implemented routinely) in practice [ 36 ].

The challenges in exploiting evidence from case study research

At present, there are significant challenges in exploiting the benefits of case study research in evaluative health research, which relate to status, definition and reporting. Case study research has been marginalised at the bottom of an evidence hierarchy, seen to offer little by way of explanatory power, if nonetheless useful for adding descriptive data on process or providing useful illustrations for policymakers [ 37 ]. This is an opportune moment to revisit this low status. As health researchers are increasingly charged with evaluating ‘natural experiments’—the use of face masks in the response to the COVID-19 pandemic being a recent example [ 38 ]—rather than interventions that take place in settings that can be controlled, research approaches using methods to strengthen causal inference that does not require randomisation become more relevant.

A second challenge for improving the use of case study evidence in evaluative health research is that, as we have seen, what is meant by ‘case study’ varies widely, not only across but also within disciplines. There is indeed little consensus amongst methodologists as to how to define ‘a case study’. Definitions focus, variously, on small sample size or lack of control over the intervention (e.g. [ 39 ] p194), on in-depth study and context [ 40 , 41 ], on the logic of inference used [ 35 ] or on distinct research strategies which incorporate a number of methods to address questions of ‘how’ and ‘why’ [ 42 ]. Moreover, definitions developed for specific disciplines do not capture the range of ways in which case study research is carried out across disciplines. Multiple definitions of case study reflect the richness and diversity of the approach. However, evidence suggests that a lack of consensus across methodologists results in some of the limitations of published reports of empirical case studies [ 43 , 44 ]. Hyett and colleagues [ 43 ], for instance, reviewing reports in qualitative journals, found little match between methodological definitions of case study research and how authors used the term.

This raises the third challenge we identify that case study reports are typically not written in ways that are accessible or useful for the evaluation research community and policymakers. Case studies may not appear in journals widely read by those in the health sciences, either because space constraints preclude the reporting of rich, thick descriptions, or because of the reported lack of willingness of some biomedical journals to publish research that uses qualitative methods [ 45 ], signalling the persistence of the aforementioned evidence hierarchy. Where they do, however, the term ‘case study’ is used to indicate, interchangeably, a qualitative study, an N of 1 sample, or a multi-method, in-depth analysis of one example from a population of phenomena. Definitions of what constitutes the ‘case’ are frequently lacking and appear to be used as a synonym for the settings in which the research is conducted. Despite offering insights for evaluation, the primary aims may not have been evaluative, so the implications may not be explicitly drawn out. Indeed, some case study reports might properly be aiming for thick description without necessarily seeking to inform about context or causality.

Acknowledging plurality and developing guidance

We recognise that definitional and methodological plurality is not only inevitable, but also a necessary and creative reflection of the very different epistemological and disciplinary origins of health researchers, and the aims they have in doing and reporting case study research. Indeed, to provide some clarity, Thomas [ 46 ] has suggested a typology of subject/purpose/approach/process for classifying aims (e.g. evaluative or exploratory), sample rationale and selection and methods for data generation of case studies. We also recognise that the diversity of methods used in case study research, and the necessary focus on narrative reporting, does not lend itself to straightforward development of formal quality or reporting criteria.

Existing checklists for reporting case study research from the social sciences—for example Lincoln and Guba’s [ 47 ] and Stake’s [ 33 ]—are primarily orientated to the quality of narrative produced, and the extent to which they encapsulate thick description, rather than the more pragmatic issues of implications for intervention effects. Those designed for clinical settings, such as the CARE (CAse REports) guidelines, provide specific reporting guidelines for medical case reports about single, or small groups of patients [ 48 ], not for case study research.

The Design of Case Study Research in Health Care (DESCARTE) model [ 44 ] suggests a series of questions to be asked of a case study researcher (including clarity about the philosophy underpinning their research), study design (with a focus on case definition) and analysis (to improve process). The model resembles toolkits for enhancing the quality and robustness of qualitative and mixed-methods research reporting, and it is usefully open-ended and non-prescriptive. However, even if it does include some reflections on context, the model does not fully address aspects of context, logic and causal inference that are perhaps most relevant for evaluative research in health.

Hence, for evaluative research where the aim is to report empirical findings in ways that are intended to be pragmatically useful for health policy and practice, this may be an opportune time to consider how to best navigate plurality around what is (minimally) important to report when publishing empirical case studies, especially with regards to the complex relationships between context and interventions, information that case study research is well placed to provide.

The conventional scientific quest for certainty, predictability and linear causality (maximised in RCT designs) has to be augmented by the study of uncertainty, unpredictability and emergent causality [ 8 ] in complex systems. This will require methodological pluralism, and openness to broadening the evidence base to better understand both causality in and the transferability of system change intervention [ 14 , 20 , 23 , 25 ]. Case study research evidence is essential, yet is currently under exploited in the health sciences. If evaluative health research is to move beyond the current impasse on methods for understanding interventions as interruptions in complex systems, we need to consider in more detail how researchers can conduct and report empirical case studies which do aim to elucidate the contextual factors which interact with interventions to produce particular effects. To this end, supported by the UK’s Medical Research Council, we are embracing the challenge to develop guidance for case study researchers studying complex interventions. Following a meta-narrative review of the literature, we are planning a Delphi study to inform guidance that will, at minimum, cover the value of case study research for evaluating the interrelationship between context and complex system-level interventions; for situating and defining ‘the case’, and generalising from case studies; as well as provide specific guidance on conducting, analysing and reporting case study research. Our hope is that such guidance can support researchers evaluating interventions in complex systems to better exploit the diversity and richness of case study research.

Acknowledgements

Not applicable

Abbreviations

Authors’ contributions

JG, MP, SP, JM, TG, CP and SS drafted the initial paper; all authors contributed to the drafting of the final version, and read and approved the final manuscript.

This work was funded by the Medical Research Council - MRC Award MR/S014632/1 HCS: Case study, Context and Complex interventions (TRIPLE C). SP was additionally funded by the University of Oxford's Higher Education Innovation Fund (HEIF).

Availability of data and materials

Ethics approval and consent to participate, consent for publication, competing interests.

The authors declare that they have no competing interests.

Publisher’s Note

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

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Case study evaluation

Affiliation.

• 1 Brunel University, Uxbridge, Middlesex.
• PMID: 7640596
• PMCID: PMC2550500
• DOI: 10.1136/bmj.311.7002.444

Case study evaluations, using one or more qualitative methods, have been used to investigate important practical and policy questions in health care. This paper describes the features of a well designed case study and gives examples showing how qualitative methods are used in evaluations of health services and health policy.

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• Case report
• Open access
• Published: 18 August 2024

Presentation of mitral valve cleft with concurrent atrial septal defect and ventricular septal defect detected by three-dimensional transesophageal echocardiography: a case report

• Azin Alizadehasl 1 ,
• Ehsan Amini-Salehi 2 ,
• Seyedeh Fatemeh Hosseini Jebelli 1 ,
• Kaveh Hosseini 3 ,
• Azam Yalameh Aliabadi 1 ,
• Rosa Yazzaf 1 &
• Sara Nobakht 2  

Journal of Medical Case Reports volume  18 , Article number:  387 ( 2024 ) Cite this article

Metrics details

Cleft in the mitral valve leaflet is a primary cause of congenital mitral regurgitation, stemming from developmental anomalies in the mitral valve and frequently associated with other congenital heart defects. Concurrent presence of cleft in mitral valve leaflet with atrial septal defect and ventricular septal defect is relatively rare. Echocardiography, especially transesophageal echocardiography, is essential in diagnosing cleft mitral valve leaflet and related congenital heart defects, providing critical, detailed imagery for accurate assessment. This study presents a young female patient whose anterior mitral cleft, along with atrial septal defect and ventricular septal defect, was revealed through three-dimensional transesophageal echocardiography.

Case presentation

A 25-year-old Iranian female, experiencing progressive dyspnea and diminished physical capacity over 3 months, was referred to our hospital. Initial examination and transthoracic echocardiography indicated severe mitral regurgitation. Further evaluation with transesophageal echocardiography corroborated these findings and identified a cleft in the anterior mitral valve leaflet, coupled with mild left ventricular enlargement and significant left atrial enlargement. The complexity of the patient’s condition was heightened by the diagnosis of cleft mitral valve leaflet in conjunction with atrial septal defect and ventricular septal defect, showing the complex nature of congenital defects.

This case emphasizes the critical role of transthoracic echocardiography in diagnosing cleft of mitral valve leaflet and associated cardiac anomalies, showcasing its superiority over transthoracic echocardiography for detailed visualization of cardiac structures. The identification of multiple congenital defects highlights the necessity for a comprehensive diagnostic approach to manage and treat patients with complex congenital heart diseases effectively. Future research should aim to refine diagnostic methodologies to enhance patient outcomes for cleft of mitral valve leaflets and related congenital conditions.

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Introduction

Cleft mitral valve leaflet (CMVL) represents the predominant cause of congenital mitral regurgitation (MR), a condition characterized by improper closure of the mitral valve, leading to backward flow of blood from the left ventricle into the left atrium. Originating from congenital anomalies in the mitral valve’s development, specifically mitral hypoplasia, CMVL frequently coexists with other congenital heart defects. The most common of these are atrioventricular septal defects, which underscore the complex nature of congenital cardiac anomalies [ 1 , 2 , 3 , 4 , 5 , 6 ].

The clinical manifestation of CMVL varies widely, with the severity of MR ranging from mild to severe. In its initial stages, particularly in younger patients, CMVL may only induce mild MR, often going undetected owing to the absence of significant symptoms. However, as patients age, the severity of MR can escalate, leading to more significant cardiac complications [ 3 , 7 ].

Echocardiography is essential for diagnosing mitral valve anomalies, but transthoracic echocardiography (TTE) has limitations [ 8 , 9 , 10 , 11 ]. Transesophageal echocardiography (TEE), however, offers a more direct and detailed view of the mitral valve and cardiac structures, overcoming the shortcomings of TTE and providing crucial imaging for identifying complex cardiac abnormalities such as CMVL, atrial septal defect (ASD), and ventricular septal defect (VSD) [ 12 , 13 , 14 , 15 ].

In this report, we explore the case of a young female patient presenting with severe symptoms of MR. Utilizing TEE, we identified not only an anterior mitral cleft but also concurrent ASD and VSD, illustrating the complex interplay of congenital defects in patients with CMVL.

We report the case of a 25-year-old female Iranian patient who was referred to our clinic with 3-month history of progressive dyspnea and limitations in daily activities. The patient described a gradual onset of symptoms, which had increasingly interfered with her ability to perform routine tasks.

Upon initial evaluation, the patient appeared in mild distress due to dyspnea. Other vital signs were within normal limits, with a blood pressure of 110/70 mmHg and a heart rate of 90 beats per minute. Physical examination was notable for a 2–3/6 grade holosystolic murmur best heard at the left sternal border, suggesting valvular heart disease as a potential underlying cause.

Given the clinical presentation and the physical examination findings, the patient underwent a TTE to further evaluate the suspected valvular pathology. In the TTE evaluation, the findings were as follows: The ejection fraction (EF) was 55%, indicating preserved systolic function. There was mild left ventricular enlargement with left ventricular end-diastolic volume index (LVEDVI) of 69 cc/m 2 . Severe left atrial (LA) enlargement was noted, with left atrial volume index (LAVI) of 48 cc/m 2 . The mitral valve (MV) appeared myxomatous, with suspicion of the flail of the posterior mitral valve leaflet (PMVL), leading to MR evidenced by two distinct regurgitant jets. Additionally, moderate tricuspid regurgitation (TR) was observed.

Following the initial diagnostic evaluation with TTE, which suggested severe MR among other findings, a comprehensive TEE was performed to enable a more detailed assessment of the mitral valve anatomy and associated cardiac structures. The procedure was carried out under local anesthesia and mild conscious sedation, following proper preparation and draping of the patient.

The TEE findings corroborated some of the TTE results and provided additional insights into the patient’s cardiac condition. Mild left ventricular enlargement was confirmed, with LVEDVI of 69 cc/m 2 , and EF remained stable at 55%, indicating preserved systolic function. Severe LA enlargement was observed, with LAVI of 48 cc/m 2 , consistent with the volume overload from severe MR. Small size primum ASD (6 mm) with a left-to-right shunt and a tiny perimembranous VSD were also observed. The MV was noted to be thickened with a cleft in the anterior mitral valve leaflet (AMVL). Moderate TR was also noted. The pulmonary to systemic flow ratio (Qp:Qs ratio) was 1.1 (Figs.  1 , 2 , 3 , 4 ).

Mid-esophageal four-chamber view showing small-size atrial septal defect (6 mm) with left to right shunt

Mid-esophageal long-axis view showing central mitral valve regurgitation

Mid-esophageal commissure view showing severe mitral valve regurgitation due to anterior mitral valve cleft

Three-dimensional echocardiography at the end face mitral valve view showing a profound indentation (cleft) at 2 o’clock position

Despite the Qp:Qs ratio being below 1.5 with no significant shunt, indicating no significant right-to-left shunt, the patient was a candidate for surgery owing to the presence of severe MR caused by a cleft, and EF below 60%.

Clefts, which are narrow openings or imperfections, are believed to stem from a partial manifestation of an endocardial cushion defect, primarily affecting the anterior mitral valve leaflet, with a frequency of 1:1340 in children. In adults, this condition is rare and accounts for 33% of congenital mitral valve regurgitation cases [ 16 , 17 ]. However, if the atrioventricular junction is intact and MR is minor, individuals can remain symptom-free for an extended period, and the mitral cleft might be discovered incidentally [ 8 ]. Although cleft is the primary cause of MR, it is frequently exacerbated by anterior leaflet restriction and annular dilatation. The degree of regurgitation is the result of interactions between the papillary muscles, accessory chordal attachment, left atrium, and free wall of the left ventricle [ 7 , 8 ].

Several instances of mitral cleft have been documented. For example, Mohammadi et al . described a case involving a woman experiencing heart failure symptoms during her eighth decade of life. A more detailed investigation uncovered a rare occurrence of clefts in both anterior and posterior segments of the mitral valve [ 17 ]. Similarly, Muller et al . reported on a unique case featuring isolated multiple mitral clefts, with the patient having two clefts in the posterior and one in the anterior segment of the mitral valve [ 18 ]. The term “isolated mitral cleft” refers to a condition where the mitral valve cleft exists without any association with an atrioventricular septal defect or a common atrioventricular junction [ 19 ].

One important aspect of defects is their co-occurrence with other congenital anomalies. As an example, partial anomalous pulmonary venous connection (PAPVC) is often associated with ASD. PAPVC can be isolated or occur with other cardiac congenital diseases, including ASD, VSD, or PDA. The type and location of PAPVC can influence the severity of symptoms and the likelihood of associated anomalies. For example, PAPVC with superior anomalous drainage is frequently associated with superior sinus venosus ASD, while PAPVC with inferior anomalous drainage is often linked to inferior sinus venosus ASD. Accurate diagnosis and early management are crucial to address complex cardiac anomalies and optimize outcomes.

Echocardiography stands as the premier choice for imaging when evaluating congenital anomalies of the mitral valve, providing intricate details on the valve’s anatomy and morphology, as well as the mechanism and extent of mitral regurgitation. While two-dimensional (2D) echocardiography might present challenges in assessing mitral clefts, three-dimensional (3D) echocardiography can offer a more detailed and sophisticated analysis of the valve’s three-dimensional structure [ 1 ]. Three-dimensional echocardiography enhances the visualization of the mitral leaflets and annulus, the subvalvular apparatus, and their spatial relationships with surrounding structures, offering real-time anatomical views of the mitral valve [ 20 ].

The integration of 2D and 3D echocardiography techniques is particularly beneficial for diagnosing clefts and providing precise guidance for repair surgeries. Surgeries informed by this combined echocardiographic approach have demonstrated a high success rate of 93% [ 21 , 22 ]. In the case under discussion, echocardiography played a crucial role in diagnosing the cleft.

In our study, although an experienced echocardiographer performed TEE, it is essential to consider the utility of magnetic resonance imaging (MRI) in identifying congenital abnormalities. MRI demonstrates significant advantages over TEE in this regard. Its superior spatial resolution and excellent soft tissue contrast allow for detailed visualization of complex anatomical structures and small intracardiac lesions [ 23 , 24 , 25 ]. MRI provides a comprehensive, three-dimensional view of the heart and surrounding structures, free from the limitations of acoustic windows that affect TEE, facilitating a more holistic assessment of both cardiac and extracardiac anomalies. Additionally, MRI is noninvasive, which makes it safer and more patient-friendly, particularly for pediatric patients. Unlike TEE, which is invasive and can cause discomfort and risks such as esophageal injury, MRI offers a more comfortable and risk-free alternative for patients [ 26 , 27 ].

This study highlights a rare case of AMVL with ASD and VSD, illustrating the importance of detailed imaging. However, its nature as a single case report limits the ability to generalize the findings. While TEE was essential for the diagnosis, it may not be available in all settings.

Conducting thorough cardiac imaging, particularly through TEE, is crucial for identifying valvular abnormalities, especially in specific patients presenting with symptoms suggestive of significant valvular pathology. While TTE is an initial and valuable screening tool, TEE offers enhanced visualization and can reveal pathologies that may be missed or inadequately characterized on TTE alone.

In the case presented, the patient’s symptoms of severe MR prompted initial evaluation with TTE, which provided valuable information but did not fully outline the other coexisting cardiac abnormalities. However, TEE, with its superior spatial resolution and ability to obtain closer proximity to the heart structures, offered a more detailed assessment, revealing additional abnormalities.

Data availability

The data of the current study are available on reasonable request from the corresponding author.

Abbreviations

• Atrial septal defect

Cleft mitral valve leaflet

Ejection fraction

Left atrial

Left atrial volume index

Left ventricular end-diastolic volume index

Mitral regurgitation

Posterior mitral valve leaflet

Transesophageal echocardiography

Transthoracic echocardiography

Tricuspid regurgitation

• Ventricular septal defect

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Cardio-Oncology Research Center, Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Science, Tehran, Iran

Azin Alizadehasl, Seyedeh Fatemeh Hosseini Jebelli, Azam Yalameh Aliabadi & Rosa Yazzaf

Guilan University of Medical Sciences, Razi Hospital, Sardar-Jangle Ave., P.O. Box 41448-95655, Rasht, Iran

Ehsan Amini-Salehi & Sara Nobakht

Tehran Heart Center, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran

Kaveh Hosseini

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A.A. and S.F.H. diagnosed and treated the patient. E.A.S. and S.N. identified the patient’s record and drafted the manuscript. R.Y. designed the graphics and drafted the manuscript. All authors read and approved the final manuscript.

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Correspondence to Ehsan Amini-Salehi or Sara Nobakht .

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Alizadehasl, A., Amini-Salehi, E., Jebelli, S.F.H. et al. Presentation of mitral valve cleft with concurrent atrial septal defect and ventricular septal defect detected by three-dimensional transesophageal echocardiography: a case report. J Med Case Reports 18 , 387 (2024). https://doi.org/10.1186/s13256-024-04704-y

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A New Method to Estimate and Predict the Variation of Dry Friction Coefficient in Ultra-Long Distance Rock Pipe Jacking: A Case Study in Guanjingkou

• Original Paper
• Published: 18 August 2024

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• Chao Li 1 , 2 ,
• Xinrong Liu   ORCID: orcid.org/0000-0003-2532-4709 2 , 3 , 4 ,
• Zuliang Zhong 2 , 3 , 4 ,
• Xiaohan Zhou 2 , 3 , 4 &
• Nanyun Wang 2 , 3 , 4  

Non-lubricated jacking will be predominantly employed to achieve cost reduction and efficiency during the initial stages of rock pipe jacking. However, a lack of comprehensive scientific understanding regarding dry friction characteristics may significantly elevate the probability of major engineering accidents. The pivotal determinant for these characteristics lies in the dynamic friction coefficient, which inevitably undergoes substantial variations due to changes in jacking distance, speed, and pipe weight. Therefore, in this work, a developed dynamic friction coefficient prediction model with a correlation between the shear velocity (representing the speed of pipe jacking), test times (indicating the distance covered during pipe jacking), and normal pressure (reflecting variations in pipe jacking weight) have been proposed. The results consistently demonstrate that the order of grey relational degree for the test numbers, shear velocity, and normal pressure is determined as V  <  N t  <  F n . When the jacking distance is less than 25 m (500 tests), the dynamic friction coefficient ranges from 0.412 to 0.453; and when exceeding 500 tests, it can be considered that the dynamic friction coefficient stabilizes at approximately 0.404 with negligible variation. In addition, considering the variable dynamic friction coefficient allows for a more precise evaluation of the jacking force, providing a crucial scientific foundation for cost reduction and efficiency engineering development.

The dynamic friction coefficient prediction model (DFPM) has been established.

The grey relational order of the 3TI factors has been determined as V< Nt< Fn.

The DFPM with shear velocity, test times and normal force has been analyzed.

The DFPM with jacking speed, distance and pipe weight has been established.

The reliability of DFPM has been finally validated.

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Acknowledgements

This work is supported by the National Natural Science Foundations for Young Scientists of China (52208391 and 52104076). Doctoral Foundation Project of Guizhou University (2021-78).

This work is funded by National Natural Science Foundations for Young Scientists of China (52208391, Chao Li, 52104076, Xiaohan Zhou), Doctoral Foundation Project of Guizhou University (2021-78, Chao Li).

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Chao Li, Xinrong Liu, Zuliang Zhong, Xiaohan Zhou & Nanyun Wang

State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing, 400044, China

Xinrong Liu, Zuliang Zhong, Xiaohan Zhou & Nanyun Wang

National Joint Engineering Research Center of Geohazards Prevention in the Reservoir Areas, Chongqing University, Chongqing, 400045, China

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Chao Li: conceptualization, methodology, investigation, and writing—original draft. Xinrong Liu: conceptualization and methodology. Zuliang Zhong: conceptualization, supervision, and visualization. Xiaohan Zhou: conceptualization, supervision, and visualization. Nanyun Wang: visualization, writing—review and editing.

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Li, C., Liu, X., Zhong, Z. et al. A New Method to Estimate and Predict the Variation of Dry Friction Coefficient in Ultra-Long Distance Rock Pipe Jacking: A Case Study in Guanjingkou. Rock Mech Rock Eng (2024). https://doi.org/10.1007/s00603-024-04019-w

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Received : 08 January 2024

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Published : 18 August 2024

DOI : https://doi.org/10.1007/s00603-024-04019-w

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An ice loss evaluation of lake-terminating glaciers based on lake bathymetry—a case study of the jiongpu glacier.

1. Introduction

2. materials and methods, 2.1. study region, 2.2. delineation of the glacier and glacial lake, 2.3. bathymetry of the glacial lake, 2.4. dataset of digital elevation models, 2.5. ice loss pattern and spatial classification, 2.6. ice loss calculation in different parts, 3.1. area dynamics and volume investigation of jiongpu co, 3.2. total ice loss of the jiongpu glacier during 2000 to 2020, 4. discussion, 4.1. new volume record with underestimation result of glacial lake, 4.2. ice loss underestimation of the jiongpu glacier, 4.3. limitations and prospects, 5. conclusions, supplementary materials, author contributions, data availability statement, acknowledgments, conflicts of interest.

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Li, D.; Shangguan, D.; Han, T.; Butt, A.Q.; Pan, B.; Cao, B.; Wang, M.; Wang, R.; Li, Y. An Ice Loss Evaluation of Lake-Terminating Glaciers Based on Lake Bathymetry—A Case Study of the Jiongpu Glacier. Remote Sens. 2024 , 16 , 3027. https://doi.org/10.3390/rs16163027

Li D, Shangguan D, Han T, Butt AQ, Pan B, Cao B, Wang M, Wang R, Li Y. An Ice Loss Evaluation of Lake-Terminating Glaciers Based on Lake Bathymetry—A Case Study of the Jiongpu Glacier. Remote Sensing . 2024; 16(16):3027. https://doi.org/10.3390/rs16163027

Li, Da, Donghui Shangguan, Tianding Han, Asim Qayyum Butt, Baotian Pan, Bo Cao, Meixia Wang, Rongjun Wang, and Yaojun Li. 2024. "An Ice Loss Evaluation of Lake-Terminating Glaciers Based on Lake Bathymetry—A Case Study of the Jiongpu Glacier" Remote Sensing 16, no. 16: 3027. https://doi.org/10.3390/rs16163027

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