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

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

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

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

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

Table of contents

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Research bias

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

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• Open access
• Published: 27 June 2011

The case study approach

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

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

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

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Introduction

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

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

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

What is a case study?

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

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

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

What are case studies used for?

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

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

How are case studies conducted?

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

Defining the case

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

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

Selecting the case(s)

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

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

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

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

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

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

Collecting the data

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

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

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

Analysing, interpreting and reporting case studies

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

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

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

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

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

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

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

Conclusions

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

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Acknowledgements

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

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Sarah Crowe & Anthony Avery

Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, UK

Kathrin Cresswell, Ann Robertson & Aziz Sheikh

School of Health in Social Science, The University of Edinburgh, Edinburgh, UK

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

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Home » Case Study – Methods, Examples and Guide

Case Study – Methods, Examples and Guide

Table of Contents

A case study is a research method that involves an in-depth examination and analysis of a particular phenomenon or case, such as an individual, organization, community, event, or situation.

It is a qualitative research approach that aims to provide a detailed and comprehensive understanding of the case being studied. Case studies typically involve multiple sources of data, including interviews, observations, documents, and artifacts, which are analyzed using various techniques, such as content analysis, thematic analysis, and grounded theory. The findings of a case study are often used to develop theories, inform policy or practice, or generate new research questions.

Types of Case Study

Types and Methods of Case Study are as follows:

Single-Case Study

A single-case study is an in-depth analysis of a single case. This type of case study is useful when the researcher wants to understand a specific phenomenon in detail.

For Example , A researcher might conduct a single-case study on a particular individual to understand their experiences with a particular health condition or a specific organization to explore their management practices. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a single-case study are often used to generate new research questions, develop theories, or inform policy or practice.

Multiple-Case Study

A multiple-case study involves the analysis of several cases that are similar in nature. This type of case study is useful when the researcher wants to identify similarities and differences between the cases.

For Example, a researcher might conduct a multiple-case study on several companies to explore the factors that contribute to their success or failure. The researcher collects data from each case, compares and contrasts the findings, and uses various techniques to analyze the data, such as comparative analysis or pattern-matching. The findings of a multiple-case study can be used to develop theories, inform policy or practice, or generate new research questions.

Exploratory Case Study

An exploratory case study is used to explore a new or understudied phenomenon. This type of case study is useful when the researcher wants to generate hypotheses or theories about the phenomenon.

For Example, a researcher might conduct an exploratory case study on a new technology to understand its potential impact on society. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as grounded theory or content analysis. The findings of an exploratory case study can be used to generate new research questions, develop theories, or inform policy or practice.

Descriptive Case Study

A descriptive case study is used to describe a particular phenomenon in detail. This type of case study is useful when the researcher wants to provide a comprehensive account of the phenomenon.

For Example, a researcher might conduct a descriptive case study on a particular community to understand its social and economic characteristics. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a descriptive case study can be used to inform policy or practice or generate new research questions.

Instrumental Case Study

An instrumental case study is used to understand a particular phenomenon that is instrumental in achieving a particular goal. This type of case study is useful when the researcher wants to understand the role of the phenomenon in achieving the goal.

For Example, a researcher might conduct an instrumental case study on a particular policy to understand its impact on achieving a particular goal, such as reducing poverty. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of an instrumental case study can be used to inform policy or practice or generate new research questions.

Case Study Data Collection Methods

Here are some common data collection methods for case studies:

Interviews involve asking questions to individuals who have knowledge or experience relevant to the case study. Interviews can be structured (where the same questions are asked to all participants) or unstructured (where the interviewer follows up on the responses with further questions). Interviews can be conducted in person, over the phone, or through video conferencing.

Observations

Observations involve watching and recording the behavior and activities of individuals or groups relevant to the case study. Observations can be participant (where the researcher actively participates in the activities) or non-participant (where the researcher observes from a distance). Observations can be recorded using notes, audio or video recordings, or photographs.

Documents can be used as a source of information for case studies. Documents can include reports, memos, emails, letters, and other written materials related to the case study. Documents can be collected from the case study participants or from public sources.

Surveys involve asking a set of questions to a sample of individuals relevant to the case study. Surveys can be administered in person, over the phone, through mail or email, or online. Surveys can be used to gather information on attitudes, opinions, or behaviors related to the case study.

Artifacts are physical objects relevant to the case study. Artifacts can include tools, equipment, products, or other objects that provide insights into the case study phenomenon.

How to conduct Case Study Research

Conducting a case study research involves several steps that need to be followed to ensure the quality and rigor of the study. Here are the steps to conduct case study research:

• Define the research questions: The first step in conducting a case study research is to define the research questions. The research questions should be specific, measurable, and relevant to the case study phenomenon under investigation.
• Select the case: The next step is to select the case or cases to be studied. The case should be relevant to the research questions and should provide rich and diverse data that can be used to answer the research questions.
• Collect data: Data can be collected using various methods, such as interviews, observations, documents, surveys, and artifacts. The data collection method should be selected based on the research questions and the nature of the case study phenomenon.
• Analyze the data: The data collected from the case study should be analyzed using various techniques, such as content analysis, thematic analysis, or grounded theory. The analysis should be guided by the research questions and should aim to provide insights and conclusions relevant to the research questions.
• Draw conclusions: The conclusions drawn from the case study should be based on the data analysis and should be relevant to the research questions. The conclusions should be supported by evidence and should be clearly stated.
• Validate the findings: The findings of the case study should be validated by reviewing the data and the analysis with participants or other experts in the field. This helps to ensure the validity and reliability of the findings.
• Write the report: The final step is to write the report of the case study research. The report should provide a clear description of the case study phenomenon, the research questions, the data collection methods, the data analysis, the findings, and the conclusions. The report should be written in a clear and concise manner and should follow the guidelines for academic writing.

Examples of Case Study

Here are some examples of case study research:

• The Hawthorne Studies : Conducted between 1924 and 1932, the Hawthorne Studies were a series of case studies conducted by Elton Mayo and his colleagues to examine the impact of work environment on employee productivity. The studies were conducted at the Hawthorne Works plant of the Western Electric Company in Chicago and included interviews, observations, and experiments.
• The Stanford Prison Experiment: Conducted in 1971, the Stanford Prison Experiment was a case study conducted by Philip Zimbardo to examine the psychological effects of power and authority. The study involved simulating a prison environment and assigning participants to the role of guards or prisoners. The study was controversial due to the ethical issues it raised.
• The Challenger Disaster: The Challenger Disaster was a case study conducted to examine the causes of the Space Shuttle Challenger explosion in 1986. The study included interviews, observations, and analysis of data to identify the technical, organizational, and cultural factors that contributed to the disaster.
• The Enron Scandal: The Enron Scandal was a case study conducted to examine the causes of the Enron Corporation’s bankruptcy in 2001. The study included interviews, analysis of financial data, and review of documents to identify the accounting practices, corporate culture, and ethical issues that led to the company’s downfall.
• The Fukushima Nuclear Disaster : The Fukushima Nuclear Disaster was a case study conducted to examine the causes of the nuclear accident that occurred at the Fukushima Daiichi Nuclear Power Plant in Japan in 2011. The study included interviews, analysis of data, and review of documents to identify the technical, organizational, and cultural factors that contributed to the disaster.

Application of Case Study

Case studies have a wide range of applications across various fields and industries. Here are some examples:

Business and Management

Case studies are widely used in business and management to examine real-life situations and develop problem-solving skills. Case studies can help students and professionals to develop a deep understanding of business concepts, theories, and best practices.

Case studies are used in healthcare to examine patient care, treatment options, and outcomes. Case studies can help healthcare professionals to develop critical thinking skills, diagnose complex medical conditions, and develop effective treatment plans.

Case studies are used in education to examine teaching and learning practices. Case studies can help educators to develop effective teaching strategies, evaluate student progress, and identify areas for improvement.

Social Sciences

Case studies are widely used in social sciences to examine human behavior, social phenomena, and cultural practices. Case studies can help researchers to develop theories, test hypotheses, and gain insights into complex social issues.

Law and Ethics

Case studies are used in law and ethics to examine legal and ethical dilemmas. Case studies can help lawyers, policymakers, and ethical professionals to develop critical thinking skills, analyze complex cases, and make informed decisions.

Purpose of Case Study

The purpose of a case study is to provide a detailed analysis of a specific phenomenon, issue, or problem in its real-life context. A case study is a qualitative research method that involves the in-depth exploration and analysis of a particular case, which can be an individual, group, organization, event, or community.

The primary purpose of a case study is to generate a comprehensive and nuanced understanding of the case, including its history, context, and dynamics. Case studies can help researchers to identify and examine the underlying factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and detailed understanding of the case, which can inform future research, practice, or policy.

Case studies can also serve other purposes, including:

• Illustrating a theory or concept: Case studies can be used to illustrate and explain theoretical concepts and frameworks, providing concrete examples of how they can be applied in real-life situations.
• Developing hypotheses: Case studies can help to generate hypotheses about the causal relationships between different factors and outcomes, which can be tested through further research.
• Providing insight into complex issues: Case studies can provide insights into complex and multifaceted issues, which may be difficult to understand through other research methods.
• Informing practice or policy: Case studies can be used to inform practice or policy by identifying best practices, lessons learned, or areas for improvement.

Advantages of Case Study Research

There are several advantages of case study research, including:

• In-depth exploration: Case study research allows for a detailed exploration and analysis of a specific phenomenon, issue, or problem in its real-life context. This can provide a comprehensive understanding of the case and its dynamics, which may not be possible through other research methods.
• Rich data: Case study research can generate rich and detailed data, including qualitative data such as interviews, observations, and documents. This can provide a nuanced understanding of the case and its complexity.
• Holistic perspective: Case study research allows for a holistic perspective of the case, taking into account the various factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and comprehensive understanding of the case.
• Theory development: Case study research can help to develop and refine theories and concepts by providing empirical evidence and concrete examples of how they can be applied in real-life situations.
• Practical application: Case study research can inform practice or policy by identifying best practices, lessons learned, or areas for improvement.
• Contextualization: Case study research takes into account the specific context in which the case is situated, which can help to understand how the case is influenced by the social, cultural, and historical factors of its environment.

Limitations of Case Study Research

There are several limitations of case study research, including:

• Limited generalizability : Case studies are typically focused on a single case or a small number of cases, which limits the generalizability of the findings. The unique characteristics of the case may not be applicable to other contexts or populations, which may limit the external validity of the research.
• Biased sampling: Case studies may rely on purposive or convenience sampling, which can introduce bias into the sample selection process. This may limit the representativeness of the sample and the generalizability of the findings.
• Subjectivity: Case studies rely on the interpretation of the researcher, which can introduce subjectivity into the analysis. The researcher’s own biases, assumptions, and perspectives may influence the findings, which may limit the objectivity of the research.
• Limited control: Case studies are typically conducted in naturalistic settings, which limits the control that the researcher has over the environment and the variables being studied. This may limit the ability to establish causal relationships between variables.
• Time-consuming: Case studies can be time-consuming to conduct, as they typically involve a detailed exploration and analysis of a specific case. This may limit the feasibility of conducting multiple case studies or conducting case studies in a timely manner.
• Resource-intensive: Case studies may require significant resources, including time, funding, and expertise. This may limit the ability of researchers to conduct case studies in resource-constrained settings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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28 Case Selection for Case‐Study Analysis: Qualitative and Quantitative Techniques

John Gerring is Professor of Political Science, Boston University.

• Published: 02 September 2009
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This article presents some guidance by cataloging nine different techniques for case selection: typical, diverse, extreme, deviant, influential, crucial, pathway, most similar, and most different. It also indicates that if the researcher is starting from a quantitative database, then methods for finding influential outliers can be used. In particular, the article clarifies the general principles that might guide the process of case selection in case-study research. Cases are more or less representative of some broader phenomenon and, on that score, may be considered better or worse subjects for intensive analysis. The article then draws attention to two ambiguities in case-selection strategies in case-study research. The first concerns the admixture of several case-selection strategies. The second concerns the changing status of a case as a study proceeds. Some case studies follow only one strategy of case selection.

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• Section 2: Home
• Developing the Quantitative Research Design
• Qualitative Descriptive Design
• Design and Development Research (DDR) For Instructional Design
• Qualitative Narrative Inquiry Research
• Action Research Resource
• Case Study Design in an Applied Doctorate

Qualitative Research Designs

Case study design, using case study design in the applied doctoral experience (ade), applicability of case study design to applied problem of practice, case study design references.

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The field of qualitative research there are a number of research designs (also referred to as “traditions” or “genres”), including case study, phenomenology, narrative inquiry, action research, ethnography, grounded theory, as well as a number of critical genres including Feminist theory, indigenous research, critical race theory and cultural studies. The choice of research design is directly tied to and must be aligned with your research problem and purpose. As Bloomberg & Volpe (2019) explain:

Choice of research design is directly tied to research problem and purpose. As the researcher, you actively create the link among problem, purpose, and design through a process of reflecting on problem and purpose, focusing on researchable questions, and considering how to best address these questions. Thinking along these lines affords a research study methodological congruence (p. 38).

Case study is an in-depth exploration from multiple perspectives of a bounded social phenomenon, be this a social system such as a program, event, institution, organization, or community (Stake, 1995, 2005; Yin, 2018). Case study is employed across disciplines, including education, health care, social work, sociology, and organizational studies. The purpose is to generate understanding and deep insights to inform professional practice, policy development, and community or social action (Bloomberg 2018).

Yin (2018) and Stake (1995, 2005), two of the key proponents of case study methodology, use different terms to describe case studies. Yin categorizes case studies as exploratory or descriptive . The former is used to explore those situations in which the intervention being evaluated has no clear single set of outcomes. The latter is used to describe an intervention or phenomenon and the real-life context in which it occurred. Stake identifies case studies as intrinsic or instrumental , and he proposes that a primary distinction in designing case studies is between single and multiple (or collective) case study designs. A single case study may be an instrumental case study (research focuses on an issue or concern in one bounded case) or an intrinsic case study (the focus is on the case itself because the case presents a unique situation). A longitudinal case study design is chosen when the researcher seeks to examine the same single case at two or more different points in time or to capture trends over time. A multiple case study design is used when a researcher seeks to determine the prevalence or frequency of a particular phenomenon. This approach is useful when cases are used for purposes of a cross-case analysis in order to compare, contrast, and synthesize perspectives regarding the same issue. The focus is on the analysis of diverse cases to determine how these confirm the findings within or between cases, or call the findings into question.

Case study affords significant interaction with research participants, providing an in-depth picture of the phenomenon (Bloomberg & Volpe, 2019). Research is extensive, drawing on multiple methods of data collection, and involves multiple data sources. Triangulation is critical in attempting to obtain an in-depth understanding of the phenomenon under study and adds rigor, breadth, and depth to the study and provides corroborative evidence of the data obtained. Analysis of data can be holistic or embedded—that is, dealing with the whole or parts of the case (Yin, 2018). With multiple cases the typical analytic strategy is to provide detailed description of themes within each case (within-case analysis), followed by thematic analysis across cases (cross-case analysis), providing insights regarding how individual cases are comparable along important dimensions. Research culminates in the production of a detailed description of a setting and its participants, accompanied by an analysis of the data for themes or patterns (Stake, 1995, 2005; Yin, 2018). In addition to thick, rich description, the researcher’s interpretations, conclusions, and recommendations contribute to the reader’s overall understanding of the case study.

Analysis of findings should show that the researcher has attended to all the data, should address the most significant aspects of the case, and should demonstrate familiarity with the prevailing thinking and discourse about the topic. The goal of case study design (as with all qualitative designs) is not generalizability but rather transferability —that is, how (if at all) and in what ways understanding and knowledge can be applied in similar contexts and settings. The qualitative researcher attempts to address the issue of transferability by way of thick, rich description that will provide the basis for a case or cases to have relevance and potential application across a broader context.

Qualitative research methods ask the questions of "what" and "how" a phenomenon is understood in a real-life context (Bloomberg & Volpe, 2019). In the education field, qualitative research methods uncover educational experiences and practices because qualitative research allows the researcher to reveal new knowledge and understanding. Moreover, qualitative descriptive case studies describe, analyze and interpret events that explain the reasoning behind specific phenomena (Bloomberg, 2018). As such, case study design can be the foundation for a rigorous study within the Applied Doctoral Experience (ADE).

Case study design is an appropriate research design to consider when conceptualizing and conducting a dissertation research study that is based on an applied problem of practice with inherent real-life educational implications. Case study researchers study current, real-life cases that are in progress so that they can gather accurate information that is current. This fits well with the ADE program, as students are typically exploring a problem of practice. Because of the flexibility of the methods used, a descriptive design provides the researcher with the opportunity to choose data collection methods that are best suited to a practice-based research purpose, and can include individual interviews, focus groups, observation, surveys, and critical incident questionnaires. Methods are triangulated to contribute to the study’s trustworthiness. In selecting the set of data collection methods, it is important that the researcher carefully consider the alignment between research questions and the type of data that is needed to address these. Each data source is one piece of the “puzzle,” that contributes to the researcher’s holistic understanding of a phenomenon. The various strands of data are woven together holistically to promote a deeper understanding of the case and its application to an educationally-based problem of practice.

Research studies within the Applied Doctoral Experience (ADE) will be practical in nature and focus on problems and issues that inform educational practice.  Many of the types of studies that fall within the ADE framework are exploratory, and align with case study design. Case study design fits very well with applied problems related to educational practice, as the following set of examples illustrate:

Elementary Bilingual Education Teachers’ Self-Efficacy in Teaching English Language Learners: A Qualitative Case Study

The problem to be addressed in the proposed study is that some elementary bilingual education teachers’ beliefs about their lack of preparedness to teach the English language may negatively impact the language proficiency skills of Hispanic ELLs (Ernst-Slavit & Wenger, 2016; Fuchs et al., 2018; Hoque, 2016). The purpose of the proposed qualitative descriptive case study was to explore the perspectives and experiences of elementary bilingual education teachers regarding their perceived lack of preparedness to teach the English language and how this may impact the language proficiency of Hispanic ELLs.

Exploring Minority Teachers Experiences Pertaining to their Value in Education: A Single Case Study of Teachers in New York City

The problem is that minority K-12 teachers are underrepresented in the United States, with research indicating that school leaders and teachers in schools that are populated mainly by black students, staffed mostly by white teachers who may be unprepared to deal with biases and stereotypes that are ingrained in schools (Egalite, Kisida, & Winters, 2015; Milligan & Howley, 2015). The purpose of this qualitative exploratory single case study was to develop a clearer understanding of minority teachers’ experiences concerning the under-representation of minority K-12 teachers in urban school districts in the United States since there are so few of them.

Exploring the Impact of an Urban Teacher Residency Program on Teachers’ Cultural Intelligence: A Qualitative Case Study

The problem to be addressed by this case study is that teacher candidates often report being unprepared and ill-equipped to effectively educate culturally diverse students (Skepple, 2015; Beutel, 2018). The purpose of this study was to explore and gain an in-depth understanding of the perceived impact of an urban teacher residency program in urban Iowa on teachers’ cultural competence using the cultural intelligence (CQ) framework (Earley & Ang, 2003).

Qualitative Case Study that Explores Self-Efficacy and Mentorship on Women in Academic Administrative Leadership Roles

The problem was that female school-level administrators might be less likely to experience mentorship, thereby potentially decreasing their self-efficacy (Bing & Smith, 2019; Brown, 2020; Grant, 2021). The purpose of this case study was to determine to what extent female school-level administrators in the United States who had a mentor have a sense of self-efficacy and to examine the relationship between mentorship and self-efficacy.

Suburban Teacher and Administrator Perceptions of Culturally Responsive Teaching to Promote Connectedness in Students of Color: A Qualitative Case Study

The problem to be addressed in this study is the racial discrimination experienced by students of color in suburban schools and the resulting negative school experience (Jara & Bloomsbury, 2020; Jones, 2019; Kohli et al., 2017; Wandix-White, 2020). The purpose of this case study is to explore how culturally responsive practices can counteract systemic racism and discrimination in suburban schools thereby meeting the needs of students of color by creating positive learning experiences. 

As you can see, all of these studies were well suited to qualitative case study design. In each of these studies, the applied research problem and research purpose were clearly grounded in educational practice as well as directly aligned with qualitative case study methodology. In the Applied Doctoral Experience (ADE), you will be focused on addressing or resolving an educationally relevant research problem of practice. As such, your case study, with clear boundaries, will be one that centers on a real-life authentic problem in your field of practice that you believe is in need of resolution or improvement, and that the outcome thereof will be educationally valuable.

Bloomberg, L. D. (2018). Case study method. In B. B. Frey (Ed.), The SAGE Encyclopedia of educational research, measurement, and evaluation (pp. 237–239). SAGE. https://go.openathens.net/redirector/nu.edu?url=https%3A%2F%2Fmethods.sagepub.com%2FReference%2Fthe-sage-encyclopedia-of-educational-research-measurement-and-evaluation%2Fi4294.xml

Bloomberg, L. D. & Volpe, M. (2019). Completing your qualitative dissertation: A road map from beginning to end . (4th Ed.). SAGE.

Stake, R. E. (1995). The art of case study research. SAGE.

Stake, R. E. (2005). Qualitative case studies. In N. K. Denzin and Y. S. Lincoln (Eds.), The SAGE handbook of qualitative research (3rd ed., pp. 443–466). SAGE.

Yin, R. (2018). Case study research and applications: Designs and methods. SAGE.

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Critical case sampling

A critical case is one that permits analytic generalisation, as, if a theory can work in the conditions of the critical case, it's likely to be able to work anywhere.

Characteristics of particular cases may make them critical – level of education of the population, level of pollution of the environment, level of resistance to government intervention of a community. The purpose of the evaluation is to investigate the success of the program in this particular critical case. Commissioners of the evaluation may be interested in the results of the evaluation for logical generalisation to other sites.

Polar regions and small island states are identified by scientists as critical cases in investigating the phenomenon of climate change. These sites are monitored closely for environmental changes. By investigating these sites in depth, scientists hope to develop knowledge that can be applied to other sites.

Suppose national policymakers want to get local communities involved in making decisions about how their local program will be run, but they aren't sure that the communities will understand the complex regulations governing their involvement. The first critical case is to evaluate the regulations in a community of well-educated citizens. If they can't understand the regulations, then less-educated folks are sure to find the regulations incomprehensible. Or, conversely, one might consider the critical case to be a community consisting of people with quite low levels of education: 'If they can understand the regulations, anyone can.' (Patton 2014: 276)

Focuses on identifying ‘outliers’ – those with exceptional outcomes - and understanding their experience as compared to others.

Analytical generalisation involves making projections about the likely transferability of findings from an evaluation, based on a theoretical analysis of the factors producing outcomes and the effect of context.

Patton, M. Q. (2014).  Qualitative Research & Evaluation Methods: Integrative Theory and Practice ​. SAGE Publications.

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Design of a Case Control Study

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• First Online: 31 May 2024
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• Yuichi Hoshino 5  

Case-control studies are categorized in a retrospective study and explore the risks of some exposure(s) for an outcome of interest. Although randomized control trials are known as the highest quality of a study design, case-control studies can be more efficient and suitable when the outcome of interest is rare and/or takes a long time to develop. Case-control studies are also considered when randomization may be unethical. Due to their retrospective nature, case-control studies can be completed with a shorter time and smaller cost than prospective studies. The measure of risk that is calculated in case-control studies is the odds ratio, which is the odds of having the exposure if you have the outcome of interest. The results of case-control studies can lead to strategies to reduce the risk of injury or to improve the clinical outcomes of our treatments. Although study design and protocol should be well structured to avoid some biases, case-control studies can make important contributions to the literature in orthopedic sports medicine research.

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Department of Orthopaedic Surgery, Kobe University Graduate School of Medicine, Kobe, Japan

Yuichi Hoshino

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FIFA Medical Centre of Excellence, Clínica Espregueira, Porto, Portugal

João Espregueira-Mendes

Dept. Orthopaedics, Sahlgrenska University Hospital, Mölndal, Sweden

Jón Karlsson

UPMC Freddie Fu SportsMed Ctr, Orth Surg, University of Pittsburgh, Pittsburgh, PA, USA

Volker Musahl

McMaster University, Hamilton, ON, Canada

Olufemi R. Ayeni

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UPMC Freddie Fu Sports Medicine Center, Department of Orthopaedic Surgery, University of Pittsburgh, Pittsburgh, PA, USA

Volker Musahl MD

Division of Orthopaedic Surgery, McMaster University, Hamilton, ON, Canada

Mohit Bhandari

Mark R. Neaman Family Chair of Orthopaedic Surgery and Director, Orthopaedic & Spine Institute, NorthShore University HealthSystem, Skokie IL, Skokie, IL, USA

Jason L. Koh

Sports Clinic, Centre Hospitalier de Luxembourg – Clinique d’Eich, Luxembourg City, Luxembourg

Caroline Mouton

Luxembourg Institute of Research in Orthopaedics, Sports Medicine and Science (LIROMS), Luxembourg City, Luxembourg

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Hoshino, Y. (2024). Design of a Case Control Study. In: Espregueira-Mendes, J., Karlsson, J., Musahl, V., Ayeni, O.R. (eds) Orthopaedic Sports Medicine. Springer, Cham. https://doi.org/10.1007/978-3-030-65430-6_117-1

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Please note you do not have access to teaching notes, learning sustainable work through critical design: a case study of a hackathon to prepare the future workforce.

Journal of Workplace Learning

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Article publication date: 4 November 2020

Issue publication date: 13 November 2020

This paper aims to explore the future of work by investigating how work can be practiced to meet global sustainability goals. The authors draw from empirical findings from a case of critical design session with university students. The aim of the design session was, on the one hand, to embed sustainability into education and, on the other hand, to prepare students with necessary conceptual tools to be prepared for future work. The research questions explored are: What do students learn through engagement in critical design, and how can that foster sustainable work?

Design/methodology/approach

The research approach is a case study, drawing on critical design activities with 45 students at a university course. The data consists of students’ reflections on their design efforts and one researcher’s field notes from the design session.

The findings show that the students engaged in critical design learn different aspects of sustainable work: how to be solution oriented, how to use technology to do good in the world and outside-the-box thinking skills.

Originality/value

The authors contribute extended insight into what it means to work for sustainable development, hence doing sustainable work, and how sustainable work can be conducted in practice. The authors discuss three dimensions of sustainable work that we argue are essential to understand how professionals can work towards increased sustainability. The three dimensions are: participation-based work, practice-based work and context-based work.

• Sustainability
• Critical design
• Future work
• Sustainable work

Islind, A.S. and Norström, L. (2020), "Learning sustainable work through critical design: a case study of a hackathon to prepare the future workforce", Journal of Workplace Learning , Vol. 32 No. 8, pp. 641-651. https://doi.org/10.1108/JWL-05-2020-0082

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Published on 17.6.2024 in Vol 26 (2024)

Key Considerations for Designing Clinical Studies to Evaluate Digital Health Solutions

Authors of this article:

• Elaina Bolinger 1 * , PhD   ; 
• Benoit Tyl 2 * , MD  

1 Integrated Evidence Generation & Business Innovation, Bayer AG, Berlin, Germany

2 Integrated Evidence Generation & Business Innovation, Bayer HealthCare SAS, La Garenne Colombes, France

*all authors contributed equally

Corresponding Author:

Benoit Tyl, MD

Integrated Evidence Generation & Business Innovation

Bayer HealthCare SAS

10 Place de Belgique

La Garenne Colombes, F-92254

Phone: 33 6 80 29 07 79

Email: [email protected]

Evidence of clinical impact is critical to unlock the potential of digital health solutions (DHSs), yet many solutions are failing to deliver positive clinical results. We argue in this viewpoint that this failure is linked to current approaches to DHS evaluation design, which neglect numerous key characteristics (KCs) requiring specific scientific and design considerations. We first delineate the KCs of DHSs: (1) they are implemented at health care system and patient levels; (2) they are “complex” interventions; (3) they can drive multiple clinical outcomes indirectly through a multitude of smaller clinical benefits; (4) their mechanism of action can vary between individuals and change over time based on patient needs; and (5) they develop through short, iterative cycles—optimally within a real-world use context. Following our objective to drive better alignment between clinical evaluation design and the unique traits of DHSs, we then provide methodological suggestions that better address these KCs, including tips on mechanism-of-action mapping, alternative randomization methods, control-arm adaptations, and novel end-point selection, as well as innovative methods utilizing real-world data and platform research.

Introduction

Digital health solutions (DHSs) can improve health care access, patient equity, operational efficiency, and cost-effectiveness for health care organizations while delivering clinical outcomes for patients. Despite the rapid proliferation of DHSs, most lack convincing evidence supporting their clinical impact [ 1 ], preventing their uptake within the health care system and blocking subsequent development cycles required to realize their full clinical potential. Closing this evidence gap and producing strong evidence in a timely and cost-effective manner is critical for the establishment of trust in DHSs and imperative for their adoption and implementation—prerequisites for unlocking digital health’s potential to truly transform health care [ 2 ].

Randomized controlled trials (RCTs) using placebo control groups; individual randomization; and strict, arguably artificial clinical settings are the gold standard for evaluating drug efficacy and safety [ 3 ]. But contrary to pharmacological treatments, in which efficacy is driven by the modulation of biology at the molecular level, DHSs belong to a specific interventional class known as “complex interventions” [ 4 ]. By definition, the impact of this type of intervention is not solely biological but also encompasses psychological, behavioral, and systems-level effects, indicating context-dependency [ 5 ]. These attributes may, for example, help explain why effect sizes for pharmaceutical products are generally higher in traditional RCTs compared to research conducted under conditions reflecting real-world conditions [ 6 , 7 ], whereas DHS effect sizes tend to be higher when using designs that mimic real-world conditions [ 8 ]. The unique attributes of DHSs and the “complex” class of interventions they deliver may therefore necessitate a more tailored approach to their evaluation to measure their true impact.

In this viewpoint, we discuss our perspective on what must be considered when designing clinical evaluations of DHSs. We specifically aimed to (1) delineate a series of key characteristics (KCs) of DHSs that make them different from pharmacological agents and should be considered while designing their evaluation, and (2) offer methodological solutions to adapt research to the requirements of DHSs, addressing randomization; control-arm design; end-point selection; and nontraditional, innovative adaptations.

DHS Key Characteristics

Kc1: dhss are often implemented at health care system and patient levels.

While patients may generate most of the data, DHSs frequently involve other individuals such as health care professionals (HCPs) and caregivers, who must integrate the solutions into their workflows for the DHS to reach full effectiveness. The benefits of using DHSs frequently expand beyond patients to caregivers, HCPs, and the whole health care organization. For instance, implementing a remote patient monitoring DHS in a single health care center can have permeating systemic effects, with the product improving outcomes of the patients monitored as well as those of the other patients, either by decreasing readmission and then shifting clinical staff resources to preventive care or by improving health care efficiency (streamlined workflow, optimized patient engagement strategies, etc). Within an evaluation setting, HCPs in the control group may adapt their behavior via learning from those included in the intervention group and change their clinical strategies (ie, leading to contamination). Therefore, it is important to control not just at the patient level but also at the health care site level [ 9 ].

KC2: DHSs Are “Complex” Interventions

Owing to their multiuser designs and dependencies on real-world health care systems, the mechanism of action (MoA) of DHSs depends on the historical, situational, environmental, and psychological factors in which treatments are delivered. Contextual dependencies include but are not limited to: HCP characteristics; patient-HCP relationships; perceived intervention credibility; delivery modality; psychological state of the individual; and societal, economic, and cultural factors. Even seemingly small nuances, such as a patient having previously been asked about their health, can have a significant impact on their health-related behavior and consequently also on health outcomes [ 10 - 12 ]. Many of these contextual factors are unintentionally, artificially modified in pharmaceutical RCTs to maximize internal validity. For instance, the Hawthorn effect, which is an increase in engagement when people are observed [ 13 ], and other research participation effects [ 14 ] are controlled between groups by using placebos. Yet this engagement is in fact a designed benefit of several DHSs; therefore, adding measurement points that would not occur in real-world situations to a DHS control group can render the control noninert. For example, measuring and regularly reporting blood pressure improves engagement and hypertension control [ 15 ], and similarly, reporting symptoms improves cancer self-management practices [ 16 ]. The artificial contexts and measurement conditions traditionally used in pharmaceutical RCTs can therefore limit the ecological validity of how the DHS is used. Consequently, conclusions drawn from such designs may lack external validity.

KC3: DHSs May Drive Multiple Clinical Outcomes Indirectly Through a Multitude of Smaller Clinical Benefits

DHSs are frequently “holistic” interventions that provide a broad spectrum of solutions to induce diverse changes, mainly behavioral, which then work as levers to deliver clinically meaningful outcomes. For instance, a remote patient monitoring platform for patients with diabetes that reduces time to treatment adjustment and thereby improves pharmaceutical adherence should consequently improve blood glucose regulation. Similarly, any improvement of sleep behavior by a sleep coaching DHS may also improve cardiovascular risk through better exercise, decreased weight, better eating habits, decreased cholesterol, and improved glucose regulation. While the magnitude of effect of the DHS on each of these end points may be limited, the cumulative effects may lead to a clinically significant benefit. Choosing a single primary clinical end point during evaluation therefore may not capture the complexity of the DHS’s intended purpose nor its true performance.

KC4: The MoA Driving Clinical Outcomes in DHSs Can Vary Between Individuals and Change Over Time Based on Patient Needs

Many DHS interventions include several separate, situationally activated components or features (HCP-facing interface, symptom monitoring, activity tracking, etc) that can bring unique benefits. For example, one patient might use feature A, which indirectly improves cholesterol levels; another might prefer feature B and experience an improvement in blood pressure, with smaller changes observed in cholesterol; and some patients might benefit from both. The effect size of the intervention for a single end point may therefore depend on how the product is used. Moreover, the second patient may begin to prefer feature A, but only later during use. The effect size of the intervention for a single end point can therefore be weakened when the DHS as a whole rather than specific feature use is considered as the intervention. What is more, many DHSs employ adaptive algorithms that are specifically designed to adjust the intervention over time. Depending on the DHS being considered, researchers might therefore anticipate that due to user-dependent variability in the MoA and emerging synergistic influences (ie, better product engagement following use-based personalization), the clinical impact may require a longer treatment period to be detected.

KC5: DHSs Develop Through Short, Iterative Cycles—Often Within a Real-World Use Context

Contrary to active pharmacological ingredients that cannot change, DHSs continuously evolve in terms of their functionality with each subsequent release. Because DHSs must meet their users’ needs in the real world, an environment where many factors remain unknown [ 17 ], developers often perform accelerated, iterative tests to both discover product performance factors and adapt them before the next release. Due to the number of factors that must be discovered, how they can influence each other, and how influential certain factors can be (ie, a seemingly small adjustment of written content to an audio format might completely change engagement and therefore clinical outcomes), the solution often must stay moderately malleable, as product design hypotheses are validated over a continuum of nonclinical tests. Clinical researchers often opt to evaluate a “frozen” version of the product to optimize homogeneity in the intervention arm, but these approaches may limit external validity, as the marketed solution may drastically evolve over time and the versions tested by the RCT may be outdated at the time of study completion.

Recalibrating Research Design to Meet the Scientific Canvas of DHSs

Considering the KCs described above, alternative assessment strategies are needed to address the unique challenges of DHS evaluation while maintaining internal validity (unbiased study design), external validity (applicability to different contexts), and ecological validity (generalizability to real-world settings). The solutions discussed below are summarized in Figure 1 .

The first step to design a DHS evaluation is to take the time to delineate the MoA of the solution and the context. This includes a map of behavioral changes required from patients and all other individuals who are affected by the product (KC1), as well as the contextual environment of use (KC2). Given the limitations of an active control arm described above (KC2), the use of usual care—usually named treatment as usual (TAU)—may serve as an appropriate control. TAU corresponds to the actual routine care and may differ from the state-of-the-art, guideline-adherent clinical care. Therefore, a prerequisite for this approach would be a detailed understanding of the procedural standard of care, which includes, but is not limited to, local (ie, site-specific) procedures, treatment recommendations, information delivered (eg, health literacy counseling), and frequency of contacts with HCPs. This task is nontrivial, as evidenced by standard-of-care descriptions being generally underreported [ 18 ], and can pose exceptional challenges due to the number of factors in a real-world environment. Combining patient journeys, DHS user journeys, and HCP patient management protocols is a helpful first step to identify how the product induces change within its context of use. Process evaluation techniques [ 19 ] can also be employed to extract MoAs for complex interventions during preliminary implementation research [ 5 ]. With the MoA delineated in detail, one can begin designing an appropriate evaluation employing a fit-for-purpose scientific approach.

As many have suggested before [ 9 , 20 ], cluster randomization by health care site, cities, or region is a methodologically sound approach to control for contamination between arms while taking into account DHS benefits, which depend on factors extending beyond the treated patient (KC1). This design, however, can necessitate larger sample sizes, and site matching can be challenging. Pragmatic designs [ 9 ], which anchor RCTs in real-world settings and minimize research-related contact outside of TAU, can help maximize the ecological validity of both the experimental (+TAU) and TAU arms (KC2). Keeping the trial decentralized can minimize research-related contact while increasing trial accessibility and make the research population more representative of the target population (KC2). While DHSs, which digitally collect data by nature, are particularly suitable for such designs, limitations secondary to the reduced investigators oversight, including data quality and outcome assessment, persist.

Even with these tools in mind, designing a control arm with high internal validity remains challenging when evaluating DHSs. A reference DHS is an appropriate control but rarely exists. While some have argued that a “sham” app (ie, as defined by the Food and Drug Administration, an app without the “active” features anticipated to drive the MoA [ 21 ]) offers optimal internal validity, in that it is a form of “placebo” technology, this design can pose critical threats to external and ecological validity, particularly when the MoA itself is not fully understood. Providing even minimalistic digital support that is nevertheless seemingly endorsed by HCPs (as would be the case in a clinical trial) might still produce a similar, albeit muted, effect as the DHS. For example, a sham app delivering some health literature is not inert, as it can improve health literacy and consequently health-related behaviors. The use of a sham app as a control is therefore challenging unless it is possible to exclude all active ingredients of the MoA, including engagement and interaction with the real world, from the sham app. On the other hand, the use of TAU as a control can potentially inflate effect size with some interventions (KC2). The traditional “waitlist” design used in medical device evaluation may also be appropriate but can inflate effect sizes by decreasing behavioral activation in the control arm (in essence, inducing the opposite of the Hawthorne effect) [ 22 , 23 ]. Researchers considering having a waitlist TAU design as the comparator might use an appropriate run-in period before randomization, during which both study arms receive TAU to minimize the influence of treatment expectancy effects [ 24 ] within the comparator arm (KC2). Finally, it is important to consider how the nature of the intervention and the control arm may impact the risk of attrition in the study. Beyond minimizing attrition in general, it is crucial to ensure that the attrition rates between the active and control arms are balanced. Significant differences in dropout rates between both arms may lead to variations in the clinical characteristics of the remaining patients, potentially biasing the overall analysis.

DHS researchers may also explore alternate evaluation designs. The use of synthetic control arms built using real-world data sources such as electronic health records, claims databases, and disease registries may address certain limitations inherent to the conventional control group. However, the creation of these synthetic arms needs to be considered carefully, as they pose their own set of challenges and are not devoid of their own limitations. In case of products already on the market, epidemiological methods could be used to examine causal inference in product registry data—again minimizing research participation effects. These approaches may in some cases both be more cost-effective and provide higher quality data on product performance.

Designing a trial that accounts for the holistic impact of DHSs is also critical for demonstrating performance and efficacy. Contrary to pharmacological agents that usually improve markedly a single biomarker (hemoglobin A 1c , C-reactive protein, etc), DHSs frequently improve modestly several biomarkers (physical activity, lipids, weight, etc; KC3). Here, rather than examining the effect on a single end point, researchers might employ a risk score that better reflects the holistic nature of the intervention. Win ratios are also an elegant way to analyze multiple, equally valuable end points [ 25 ]. Adaptive designs, such as those incorporating sample size re-estimation, hypothesis-adaptive, or response-adaptive designs [ 26 ], could also be both powerful and appropriate given the novel nature of many DHS interventions and the different use patterns and emergent interventions that can arise (KC4). Given the dynamic and personalized nature of DHSs, the evaluation design should also carefully consider anticipated effect size at each time point during planning.

The above can greatly improve the evaluation of DHS clinical performance but do not address the practical issue of evaluating rapidly and continuously evolving DHSs (KC5). While there is no definitive way to address this, a few options exist beyond freezing the product. During evaluation planning, planned future modifications of the product can be scrutinized to determine whether they constitute major changes to the MoA or intended use and would therefore require protocol modification during study execution. By combining strict product design control practices with a Trials of Intervention Principles approach [ 27 ], researchers can aggregate groups of users who may have used product versions with minor design variations not anticipated to change the MoA, allowing the product to continue to organically develop (KC5). Platform trials that incorporate key product design and clinical value hypotheses in master protocols can be leveraged to have the successive versions of the DHS tested and the results of the substudies combined to maximize sample sizes, rather than performing several insufficiently powered successive trials, while keeping analyses anchored in clearly documented starting hypotheses and protocols ( Figure 2 ) [ 20 , 28 ]. Likewise, factorial research designs can be used to investigate the efficacy of new features as they are added to the product [ 29 , 30 ].

DHSs need to be rigorously evaluated to fulfill the needs of the various stakeholders, including HCPs, patients, regulators, and payers. In this viewpoint, we proposed that their unique characteristics and MoA create a critical need for tailored, innovative approaches that move beyond traditional pharmaceutical RCTs in order to create fit-for-purpose, robust, and scientifically optimized evaluations. While no one-size-fits-all design exists, both researcher and stakeholders should embrace nontraditional methodologies that match the key characteristics of this emerging type of health care intervention.

Acknowledgments

We thank Jason Lott for his feedback and comments.

Authors' Contributions

Both authors equally contributed to the manuscript.

Conflicts of Interest

Both authors are full-time employees of Bayer.

Overview of key characteristics (KCs) of the digital health solutions (DHSs) and potential methodological solutions to improve their clinical assessment. EHR: electronic health record; MoA: mechanism of action.

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Abbreviations

Edited by T de Azevedo Cardoso; submitted 13.11.23; peer-reviewed by F Denis, M Savolainen; comments to author 14.02.24; revised version received 05.03.24; accepted 17.05.24; published 17.06.24.

©Elaina Bolinger, Benoit Tyl. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 17.06.2024.

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

The promises and pitfalls of disaster aid platforms: a case study of Lebanon's 3RF

• Bloemeke, Sophie
• Atallah, Sami
• Zoughaib, Sami

PurposeUsing critical disaster studies and state theory, we assess the disaster aid platform named Lebanon Reconstruction, Reform and Recovery Framework (3RF) that was put in place by international donors in the aftermath of the Beirut Port Blast in August 2020, in order to examine the effectiveness of its inclusive decision-making architecture, as well as its institutional building and legislative reform efforts.Design/methodology/approachThe paper uses the case study approaach and relies on two original data sets compiled by authors, using desk reviews of academic literature and secondary data, in addition to 24 semi-structured expert interviews and participant observation for two years.FindingsThe aid platform appears innovative, participatory and effectively functioning toward recovery and reform. However, in practice, the government dismisses CSOs, undermines reforms and dodges state building, whereas the 3RF is structured in incoherent ways and operates according to conflicting logics, generating inertia and pitfalls that hinder effective participatory governance, prevent institutional building, and delay the making of projects.Research limitations/implicationsThe research contributes to critical scholarship as it addresses an important research gap concerning disaster aid platforms' institutional design and governance that are under-studied in critical disaster studies and political studies. It also highlights the need for critical disaster studies to engage with state theory and vice-versa.Practical implicationsThe research contributes to evaluations of disaster recovery processes and outcomes. It highlights the limits of disaster aid platforms' claims for participatory decision-making, institutional-building and reforms.Originality/valueThe paper amplifies critical disaster studies, through the reflexive analysis of a case-study of an aid platform.

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Trong Nhan Nguyen , Van Da Huynh; Exploring the Impact of Tourism Environment on Tourist Satisfaction in Tourist Sites: An Example of Phong Dien Tourism Village, Vietnam . Case Studies in the Environment 5 April 2024; 8 (1): 2281531. doi: https://doi.org/10.1525/cse.2024.2281531

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The quality of the natural, socioeconomic, and cultural environment plays a pivotal role in shaping tourist satisfaction, serving as a critical driver in assessing the success of tourism activities. This study seeks to examine the intricate relationship between the tourism environment and tourist satisfaction, aiming to provide valuable insights into this dynamic interplay. Through a questionnaire survey, 270 valid responses were collected from tourists who visited the study area. The research employed various analytical methods, including scale reliability tests, exploratory factor analysis, and multivariable linear regression, to meticulously process the collected data. The findings reveal that the tourism environment is multifaceted, encompassing cultural, socioeconomic, and natural dimensions. Interestingly, these factors exhibit a positive yet diminishing impact on tourist satisfaction. Specifically, the cultural tourism environment contributes 38.9%, the socioeconomic tourism environment adds 33.4%, and the natural tourism environment contributes 27.7% to overall tourist satisfaction. This research not only provides important theoretical understanding but also holds practical significance for the tourism industry. By recognizing the nuanced relationship between the tourism environment and tourist satisfaction, this study establishes a foundation for improving the quality of tourism experiences. The implications derived from the findings offer valuable recommendations for enhancing both the tourism environment and overall tourist satisfaction.

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• Share a link. Present a slideshow. Embed. Download a PDF/PNG. Your case study seamlessly adapts to your workflow. No more jumping from tool-to-tool to create different types of deliverables.
• Reuse and repurpose. Save your own custom case study templates. Or copy and merge into other documents.

Follow along step-by-step with the Case Study how-to guide .

What is a case study?

An effective case study is a great way to show potential clients, customers, and stakeholders how valuable your product or service is by explaining how your business solved a particularly challenging client problem.

Marketing case studies examine a single client situation in-depth and provide a detailed analysis of how your organization resolved the challenge.

The best case studies not only tell a story about your company but also contain some hard measurable metrics. This allows you to highlight your successes in a way that will make an ideal potential customer become your customer. Essentially, a case study is an effective way to learn about your business and a great marketing tool.

When looking for potential projects to use for a case study, look for ones that:

• Involved a particular challenge that required a unique set of skills that your company possesses
• Received special awards, press coverage or accolades
• Involved a high profile project
• Involved a well-known (preferably Fortune 500) brand or company

The most important element of your case study is that it must show a real-life example to relate to your target client. While a good case study showcases your company, a great case study makes the reader want to start a conversation with you.

What information should be included in a case study?

The first thing to consider is who will be reading your case studies. Messages and their delivery resonate differently, depending on who is on the receiving end. For example, a thirty-something software entrepreneur will measure success differently than a fifty-something CEO of a large corporation. Understanding your target audience will help you tell your case study in a way that will effectively speak to them.

When gathering information for your case study, interview happy customers and ask questions to your potential case study subject that align with the story you are trying to tell. No case study will be the same, and your questions will vary from client to client.

Before you contact the customer, consider interview questions so you have an idea of what you need to produce a compelling case study demonstrating your potential to succeed.

At the end of the information-gathering process, you should have a solid understanding of the following to outline how your product was the best solution for the customers’ particular challenge:

• The client’s initial challenge
• Why did the client choose your company
• Your company’s approach to the problem
• The solution and implementation process
• The results and final measures of success

Some questions to ask your client during the initial interview:

• Can you give a brief description of your company?
• How did you first hear about our product or service?
• What challenges or pain points prompted using our product? 
• What were you looking for in a solution to your problem? 
• Did you have any roadblocks while using our product? 

Don’t forget to talk to your colleagues and get their perspectives on the project when writing your case study. You may also want to include some quotes from internal stakeholders or project leads to make an even more compelling case study.

How do you write a case study?

When writing a case study, make sure you know who you’re talking to. Your audience, i.e. who would be interested in your product or service, should be your main focus when you create a case study. Once you’ve compiled your facts, format the story so that it will appeal to potential customers.

The format and content of case study templates vary, but in general, your business case study should look like a strong landing page: brief, pictorial, and engaging.

Xtensio’s case study template includes instructional copy to show you everything you need to know to create a real-life example of your company’s strengths. The template is organized into sections and modules designed to make your case study flow like a well-planned story and we’ve broken the template into three main sections: the snapshot, the body and the footer. 

The Snapshot

This section is designed to give a quick overview of your story and prompt readers to want to learn more. Consider it an executive summary, a book cover, or a brief description in an online store. It should have enough information to grab a potential customer’s attention, but not so much that they will stop reading. Include client details, the project name, and a brief description of the problem, as well as quantitative metrics that demonstrate your accomplishment.

You can also include the date the case study was originally published here to help potential customers identify if your product or service is a good fit for them right now. 

This section is the meat of your case study and will focus on customer results. Like any good story, it will have a beginning, a middle and an end. Classic western storytelling uses a pretty standard formula that includes a problem, the approach taken to solve it, the solution and the end results. The body of Xtensio’s case study template is divided into four key areas that align to these story elements: the Challenge, the Approach, the Solution and the Results. Here, make sure you explain using your product for a certain use case and describe how your service helped the client.

To close your case study, end with a short paragraph about who your company is, as well as your contact information. This is handy if your business case study becomes separated from your company’s website information somehow.

If you plan on sharing the case study online, make sure to add the links to your website and social media handles, using our social media module. If you are planning to print, then don’t forget to spell out the name of your website and/or add a contact phone number and email address.

Invite feedback and participation by your colleagues and the client by inviting them to collaborate on the case study template in real-time. Once you are satisfied with your case study, you can add it to your website, share it on your social channels, use it in presentations, or send out emails to potential clients. You can also download a pdf version that can be printed and shared. 

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Daily use of Listerine mouthwash linked to bacteria that may increase risk of deadly cancers in shock study

Listerine Cool Mint mouthwash linked to risk of esophageal and colorectal cancer in new study

By Adam Chapman

Published: 17/06/2024

Updated: 17/06/2024

• Listerine Cool Mint mouthwash linked to risk of esophageal and colorectal cancer
• The alcohol-based mouthwash promotes growth of bacteria linked to cancer
• Listerine should be used with caution and careful consideration, study authors say

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Daily use of Listerine mouthwash may increase the risk of two serious cancers, warns a new study.

Researchers found that the alcohol-based mouthwash contributed to different levels of oral bacterial populations linked to an increased risk of esophageal and colorectal cancer.

For the study , conducted at the Institute of Tropical Medicine in Antwerp, Belgium, the researchers investigated the impact of daily mouthwash use on STI risk among gay men.

They specifically set out to find ways of reducing the incidence of gonorrhea, chlamydia, or syphilis in men who have sex with men.

Researchers found two species of bacteria linked to cancer significantly abundant after using the mouthwash daily.

Bloomberg via Getty Images

The 59 participants enrolled in the study used Listerine daily for three months followed by three months of placebo mouthwash or vice versa.

The researchers found a significant difference in the composition and number of bacteria in the participants’ oral microbiome after using alcohol-based Listerine Cool Mint mouthwash.

They reported that fusobacterium nucleatum and streptococcus anginosus were significantly abundant after using the mouthwash daily.

These two species of bacteria have been linked to several diseases, including gum disease and esophageal and colorectal cancer.

The scientists also noted a decrease in a beneficial bacteria strain called Actinobacteria . This strain of bacteria regulates blood pressure and is thought to have potent anti-cancer properties .

There are some important limitations to the study.

The researchers did not collect information on the participants’ dietary habits or smoking. It is therefore not possible isolate a single factor that may contributed to the risk of cancer.

Other imitations included:

• Swabs of areas of the mouth were limited to tonsillar pillars and the posterior oropharynx. The authors note that the results may not represent the entire oral cavity.
• Adherence to using the mouthwash was not controlled.
• Changes were not confirmed with a second methodology.
• Only men who have sex with men were included in the study. Therefore, the results might not be generalisable to the general public.

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Researchers recommend exercising caution and careful consideration over the regular use of Listerine

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With these uncertainties in mind, the researchers are unwilling to state that the public should stop using alcohol-based mouthwash altogether.

Instead, they recommend exercising caution and careful consideration over the regular use of Listerine.

Study author Professor Kenyon and his colleagues only tested Listerine but he says the impact on bacteria would likely also be seen following use of other alcohol-based mouthwashes.

Doctor Jolein Laumen, first author of the study, added: “Alcohol-based mouthwashes are widely available. The public may use them daily to tackle bad breath or prevent periodontitis, but they should be aware of the potential implications.

“Ideally, long-term usage should be guided by healthcare professionals.”

In response to a request for comment, Kenvue, which owns the Listerine brand, told GB News: Studies on the impact of LISTERINE ® on oral health have been published in hundreds of peer-reviewed publications for more than a century, making it one of the most extensively tested oral mouthwash brands in the world. We continuously evaluate the latest science. There is no evidence that LISTERINE ® causes cancer."

What might explain this link?

We’ve known for a long time now that alcohol increases the risk of mouth cancer, and it’s not a particularly new concept.

So the idea that using mouthwash that contains alcohol could increase the risk of mouth cancer does make sense, but the evidence around this link is inconsistent, and the link to esophageal and colorectal cancer is even less clear. To date, no direct link has been established.

According to Alliance Dental , most mouthwashes found in pharmacies contain alcohol.

The alcohol destroys almost all the bacteria in the mouth — both the good and the bad.

Alcohol-free mouthwash does not destroy all the bacteria but creates a new balance of bacteria in the mouth.

This might have contributed to the risk but again more research needs to be done before conclusions can be drawn.

As Cancer Research UK rightly points out, the most important risk factors for mouth cancer are smoking and drinking more than three units of alcohol a day.

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• v.23(Suppl 4); 2019 Dec

Understanding Research Study Designs

Priya ranganathan.

Department of Anesthesiology, Critical Care and Pain, Tata Memorial Hospital, Mumbai, Maharashtra, India

In this article, we will look at the important features of various types of research study designs used commonly in biomedical research.

How to cite this article

Ranganathan P. Understanding Research Study Designs. Indian J Crit Care Med 2019;23(Suppl 4):S305–S307.

We use a variety of research study designs in biomedical research. In this article, the main features of each of these designs are summarized.

TERMS USED IN RESEARCH DESIGNS

Exposure vs outcome.

Exposure refers to any factor that may be associated with the outcome of interest. It is also called the predictor variable or independent variable or risk factor. Outcome refers to the variable that is studied to assess the impact of the exposure on the population. It is also known as the predicted variable or the dependent variable. For example, in a study looking at nerve damage after organophosphate (OPC) poisoning, the exposure would be OPC and the outcome would be nerve damage.

Longitudinal vs Transversal Studies

In longitudinal studies, participants are followed over time to determine the association between exposure and outcome (or outcome and exposure). On the other hand, in transversal studies, observations about exposure and outcome are made at a single point in time.

Forward vs Backward Directed Studies

In forward-directed studies, the direction of enquiry moves from exposure to outcome. In backward-directed studies, the line of enquiry starts with outcome and then determines exposure.

Prospective vs Retrospective Studies

In prospective studies, the outcome has not occurred at the time of initiation of the study. The researcher determines exposure and follows participants into the future to assess outcomes. In retrospective studies, the outcome of interest has already occurred when the study commences.

CLASSIFICATION OF STUDY DESIGNS

Broadly, study designs can be classified as descriptive or analytical (inferential) studies.

Descriptive Studies

Descriptive studies describe the characteristics of interest in the study population (also referred to as sample, to differentiate it from the entire population in the universe). These studies do not have a comparison group. The simplest type of descriptive study is the case report. In a case report, the researcher describes his/her experience with symptoms, signs, diagnosis, or treatment of a patient. Sometimes, a group of patients having a similar experience may be grouped to form a case series.

Case reports and case series form the lowest level of evidence in biomedical research and, as such, are considered hypothesis-generating studies. However, they are easy to write and may be a good starting point for the budding researcher. The recognition of some important associations in the field of medicine—such as that of thalidomide with phocomelia and Kaposi's sarcoma with HIV infection—resulted from case reports and case series. The reader can look up several published case reports and case series related to complications after OPC poisoning. 1 , 2

Analytical (Inferential) Studies

Analytical or inferential studies try to prove a hypothesis and establish an association between an exposure and an outcome. These studies usually have a comparator group. Analytical studies are further classified as observational or interventional studies.

In observational studies, there is no intervention by the researcher. The researcher merely observes outcomes in different groups of participants who, for natural reasons, have or have not been exposed to a particular risk factor. Examples of observational studies include cross-sectional, case–control, and cohort studies.

Cross-sectional Studies

These are transversal studies where data are collected from the study population at a single point in time. Exposure and outcome are determined simultaneously. Cross-sectional studies are easy to conduct, involve no follow-up, and need limited resources. They offer useful information on prevalence of health conditions and possible associations between risk factors and outcomes. However, there are two major limitations of cross-sectional studies. First, it may not be possible to establish a clear cause–benefit relationship. For example, in a study of association between colon cancer and dietary fiber intake, it may be difficult to establish whether the low fiber intake preceded the symptoms of colon cancer or whether the symptoms of colon cancer resulted in a change in dietary fiber intake. Another important limitation of cross-sectional studies is survival bias. For example, in a study looking at alcohol intake vs mortality due to chronic liver disease, among the participants with the highest alcohol intake, several may have died of liver disease; this will not be picked up by the study and will give biased results. An example of a cross-sectional study is a survey on nurses’ knowledge and practices of initial management of acute poisoning. 3

Case–control Studies

Case–control studies are backward-directed studies. Here, the direction of enquiry begins with the outcome and then proceeds to exposure. Case–control studies are always retrospective, i.e., the outcome of interest has occurred when the study begins. The researcher identifies participants who have developed the outcome of interest (cases) and chooses matching participants who do not have the outcome (controls). Matching is done based on factors that are likely to influence the exposure or outcome (e.g., age, gender, socioeconomic status). The researcher then proceeds to determine exposure in cases and controls. If cases have a higher incidence of exposure than controls, it suggests an association between exposure and outcome. Case–control studies are relatively quick to conduct, need limited resources, and are useful when the outcome is rare. They also allow the researcher to study multiple exposures for a particular outcome. However, they have several limitations. First, matching of cases with controls may not be easy since many unknown confounders may affect exposure and outcome. Second, there may be biased in the way the history of exposure is determined in cases vs controls; one way to overcome this is to have a blinded assessor determining the exposure using a standard technique (e.g., a standardized questionnaire). However, despite this, it has been shown that cases are far more likely than controls to recall history of exposure—the “recall bias.” For example, mothers of babies born with congenital anomalies may provide a more detailed history of drugs ingested during their pregnancy than those with normal babies. Also, since case-control studies do not begin with a population at risk, it is not possible to determine the true risk of outcome. Instead, one can only calculate the odds of association between exposure and outcome.

Kendrick and colleagues designed a case–control study to look at the association between domestic poison prevention practices and medically attended poisoning in children. They identified children presenting with unintentional poisoning at home (cases with the outcome), matched them with community participants (controls without the outcome), and then elicited data from parents and caregivers on home safety practices (exposure). 4

Cohort Studies

Cohort studies resemble clinical trials except that the exposure is naturally determined instead of being decided by the investigator. Here, the direction of enquiry begins with the exposure and then proceeds to outcome. The researcher begins with a group of individuals who are free of outcome at baseline; of these, some have the exposure (study cohort) while others do not (control group). The groups are followed up over a period of time to determine occurrence of outcome. Cohort studies may be prospective (involving a period of follow-up after the start of the study) or retrospective (e.g., using medical records or registry data). Cohort studies are considered the strongest among the observational study designs. They provide proof of temporal relationship (exposure occurred before outcome), allow determination of risk, and permit multiple outcomes to be studied for a single exposure. However, they are expensive to conduct and time-consuming, there may be several losses to follow-up, and they are not suitable for studying rare outcomes. Also, there may be unknown confounders other than the exposure affecting the occurrence of the outcome.

Jayasinghe conducted a cohort study to look at the effect of acute organophosphorus poisoning on nerve function. They recruited 70 patients with OPC poisoning (exposed group) and 70 matched controls without history of pesticide exposure (unexposed controls). Participants were followed up or 6 weeks for neurophysiological assessments to determine nerve damage (outcome). Hung carried out a retrospective cohort study using a nationwide research database to look at the long-term effects of OPC poisoning on cardiovascular disease. From the database, he identified an OPC-exposed cohort and an unexposed control cohort (matched for gender and age) from several years back and then examined later records to look at the development of cardiovascular diseases in both groups. 5

Interventional Studies

In interventional studies (also known as experimental studies or clinical trials), the researcher deliberately allots participants to receive one of several interventions; of these, some may be experimental while others may be controls (either standard of care or placebo). Allotment of participants to a particular treatment arm is carried out through the process of randomization, which ensures that every participant has a similar chance of being in any of the arms, eliminating bias in selection. There are several other aspects crucial to the validity of the results of a clinical trial such as allocation concealment, blinding, choice of control, and statistical analysis plan. These will be discussed in a separate article.

The randomized controlled clinical trial is considered the gold standard for evaluating the efficacy of a treatment. Randomization leads to equal distribution of known and unknown confounders between treatment arms; therefore, we can be reasonably certain that any difference in outcome is a treatment effect and not due to other factors. The temporal sequence of cause and effect is established. It is possible to determine risk of the outcome in each treatment arm accurately. However, randomized controlled trials have their limitations and may not be possible in every situation. For example, it is unethical to randomize participants to an intervention that is likely to cause harm—e.g., smoking. In such cases, well-designed observational studies are the only option. Also, these trials are expensive to conduct and resource-intensive.

In a randomized controlled trial, Li et al. randomly allocated patients of paraquat poisoning to receive either conventional therapy (control group) or continuous veno-venous hemofiltration (intervention). Patients were followed up to look for mortality or other adverse events (outcome). 6

Researchers need to understand the features of different study designs, with their advantages and limitations so that the most appropriate design can be chosen for a particular research question. The Centre for Evidence Based Medicine offers an useful tool to determine the type of research design used in a particular study. 7

Source of support: Nil

Conflict of interest: None

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