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Case Study – Methods, Examples and Guide

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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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The Advantages and Limitations of Single Case Study Analysis

As Andrew Bennett and Colin Elman have recently noted, qualitative research methods presently enjoy “an almost unprecedented popularity and vitality… in the international relations sub-field”, such that they are now “indisputably prominent, if not pre-eminent” (2010: 499). This is, they suggest, due in no small part to the considerable advantages that case study methods in particular have to offer in studying the “complex and relatively unstructured and infrequent phenomena that lie at the heart of the subfield” (Bennett and Elman, 2007: 171). Using selected examples from within the International Relations literature[1], this paper aims to provide a brief overview of the main principles and distinctive advantages and limitations of single case study analysis. Divided into three inter-related sections, the paper therefore begins by first identifying the underlying principles that serve to constitute the case study as a particular research strategy, noting the somewhat contested nature of the approach in ontological, epistemological, and methodological terms. The second part then looks to the principal single case study types and their associated advantages, including those from within the recent ‘third generation’ of qualitative International Relations (IR) research. The final section of the paper then discusses the most commonly articulated limitations of single case studies; while accepting their susceptibility to criticism, it is however suggested that such weaknesses are somewhat exaggerated. The paper concludes that single case study analysis has a great deal to offer as a means of both understanding and explaining contemporary international relations.

The term ‘case study’, John Gerring has suggested, is “a definitional morass… Evidently, researchers have many different things in mind when they talk about case study research” (2006a: 17). It is possible, however, to distil some of the more commonly-agreed principles. One of the most prominent advocates of case study research, Robert Yin (2009: 14) defines it as “an empirical enquiry that investigates a contemporary phenomenon in depth and within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident”. What this definition usefully captures is that case studies are intended – unlike more superficial and generalising methods – to provide a level of detail and understanding, similar to the ethnographer Clifford Geertz’s (1973) notion of ‘thick description’, that allows for the thorough analysis of the complex and particularistic nature of distinct phenomena. Another frequently cited proponent of the approach, Robert Stake, notes that as a form of research the case study “is defined by interest in an individual case, not by the methods of inquiry used”, and that “the object of study is a specific, unique, bounded system” (2008: 443, 445). As such, three key points can be derived from this – respectively concerning issues of ontology, epistemology, and methodology – that are central to the principles of single case study research.

First, the vital notion of ‘boundedness’ when it comes to the particular unit of analysis means that defining principles should incorporate both the synchronic (spatial) and diachronic (temporal) elements of any so-called ‘case’. As Gerring puts it, a case study should be “an intensive study of a single unit… a spatially bounded phenomenon – e.g. a nation-state, revolution, political party, election, or person – observed at a single point in time or over some delimited period of time” (2004: 342). It is important to note, however, that – whereas Gerring refers to a single unit of analysis – it may be that attention also necessarily be given to particular sub-units. This points to the important difference between what Yin refers to as an ‘holistic’ case design, with a single unit of analysis, and an ’embedded’ case design with multiple units of analysis (Yin, 2009: 50-52). The former, for example, would examine only the overall nature of an international organization, whereas the latter would also look to specific departments, programmes, or policies etc.

Secondly, as Tim May notes of the case study approach, “even the most fervent advocates acknowledge that the term has entered into understandings with little specification or discussion of purpose and process” (2011: 220). One of the principal reasons for this, he argues, is the relationship between the use of case studies in social research and the differing epistemological traditions – positivist, interpretivist, and others – within which it has been utilised. Philosophy of science concerns are obviously a complex issue, and beyond the scope of much of this paper. That said, the issue of how it is that we know what we know – of whether or not a single independent reality exists of which we as researchers can seek to provide explanation – does lead us to an important distinction to be made between so-called idiographic and nomothetic case studies (Gerring, 2006b). The former refers to those which purport to explain only a single case, are concerned with particularisation, and hence are typically (although not exclusively) associated with more interpretivist approaches. The latter are those focused studies that reflect upon a larger population and are more concerned with generalisation, as is often so with more positivist approaches[2]. The importance of this distinction, and its relation to the advantages and limitations of single case study analysis, is returned to below.

Thirdly, in methodological terms, given that the case study has often been seen as more of an interpretivist and idiographic tool, it has also been associated with a distinctly qualitative approach (Bryman, 2009: 67-68). However, as Yin notes, case studies can – like all forms of social science research – be exploratory, descriptive, and/or explanatory in nature. It is “a common misconception”, he notes, “that the various research methods should be arrayed hierarchically… many social scientists still deeply believe that case studies are only appropriate for the exploratory phase of an investigation” (Yin, 2009: 6). If case studies can reliably perform any or all three of these roles – and given that their in-depth approach may also require multiple sources of data and the within-case triangulation of methods – then it becomes readily apparent that they should not be limited to only one research paradigm. Exploratory and descriptive studies usually tend toward the qualitative and inductive, whereas explanatory studies are more often quantitative and deductive (David and Sutton, 2011: 165-166). As such, the association of case study analysis with a qualitative approach is a “methodological affinity, not a definitional requirement” (Gerring, 2006a: 36). It is perhaps better to think of case studies as transparadigmatic; it is mistaken to assume single case study analysis to adhere exclusively to a qualitative methodology (or an interpretivist epistemology) even if it – or rather, practitioners of it – may be so inclined. By extension, this also implies that single case study analysis therefore remains an option for a multitude of IR theories and issue areas; it is how this can be put to researchers’ advantage that is the subject of the next section.

Having elucidated the defining principles of the single case study approach, the paper now turns to an overview of its main benefits. As noted above, a lack of consensus still exists within the wider social science literature on the principles and purposes – and by extension the advantages and limitations – of case study research. Given that this paper is directed towards the particular sub-field of International Relations, it suggests Bennett and Elman’s (2010) more discipline-specific understanding of contemporary case study methods as an analytical framework. It begins however, by discussing Harry Eckstein’s seminal (1975) contribution to the potential advantages of the case study approach within the wider social sciences.

Eckstein proposed a taxonomy which usefully identified what he considered to be the five most relevant types of case study. Firstly were so-called configurative-idiographic studies, distinctly interpretivist in orientation and predicated on the assumption that “one cannot attain prediction and control in the natural science sense, but only understanding ( verstehen )… subjective values and modes of cognition are crucial” (1975: 132). Eckstein’s own sceptical view was that any interpreter ‘simply’ considers a body of observations that are not self-explanatory and “without hard rules of interpretation, may discern in them any number of patterns that are more or less equally plausible” (1975: 134). Those of a more post-modernist bent, of course – sharing an “incredulity towards meta-narratives”, in Lyotard’s (1994: xxiv) evocative phrase – would instead suggest that this more free-form approach actually be advantageous in delving into the subtleties and particularities of individual cases.

Eckstein’s four other types of case study, meanwhile, promote a more nomothetic (and positivist) usage. As described, disciplined-configurative studies were essentially about the use of pre-existing general theories, with a case acting “passively, in the main, as a receptacle for putting theories to work” (Eckstein, 1975: 136). As opposed to the opportunity this presented primarily for theory application, Eckstein identified heuristic case studies as explicit theoretical stimulants – thus having instead the intended advantage of theory-building. So-called p lausibility probes entailed preliminary attempts to determine whether initial hypotheses should be considered sound enough to warrant more rigorous and extensive testing. Finally, and perhaps most notably, Eckstein then outlined the idea of crucial case studies , within which he also included the idea of ‘most-likely’ and ‘least-likely’ cases; the essential characteristic of crucial cases being their specific theory-testing function.

Whilst Eckstein’s was an early contribution to refining the case study approach, Yin’s (2009: 47-52) more recent delineation of possible single case designs similarly assigns them roles in the applying, testing, or building of theory, as well as in the study of unique cases[3]. As a subset of the latter, however, Jack Levy (2008) notes that the advantages of idiographic cases are actually twofold. Firstly, as inductive/descriptive cases – akin to Eckstein’s configurative-idiographic cases – whereby they are highly descriptive, lacking in an explicit theoretical framework and therefore taking the form of “total history”. Secondly, they can operate as theory-guided case studies, but ones that seek only to explain or interpret a single historical episode rather than generalise beyond the case. Not only does this therefore incorporate ‘single-outcome’ studies concerned with establishing causal inference (Gerring, 2006b), it also provides room for the more postmodern approaches within IR theory, such as discourse analysis, that may have developed a distinct methodology but do not seek traditional social scientific forms of explanation.

Applying specifically to the state of the field in contemporary IR, Bennett and Elman identify a ‘third generation’ of mainstream qualitative scholars – rooted in a pragmatic scientific realist epistemology and advocating a pluralistic approach to methodology – that have, over the last fifteen years, “revised or added to essentially every aspect of traditional case study research methods” (2010: 502). They identify ‘process tracing’ as having emerged from this as a central method of within-case analysis. As Bennett and Checkel observe, this carries the advantage of offering a methodologically rigorous “analysis of evidence on processes, sequences, and conjunctures of events within a case, for the purposes of either developing or testing hypotheses about causal mechanisms that might causally explain the case” (2012: 10).

Harnessing various methods, process tracing may entail the inductive use of evidence from within a case to develop explanatory hypotheses, and deductive examination of the observable implications of hypothesised causal mechanisms to test their explanatory capability[4]. It involves providing not only a coherent explanation of the key sequential steps in a hypothesised process, but also sensitivity to alternative explanations as well as potential biases in the available evidence (Bennett and Elman 2010: 503-504). John Owen (1994), for example, demonstrates the advantages of process tracing in analysing whether the causal factors underpinning democratic peace theory are – as liberalism suggests – not epiphenomenal, but variously normative, institutional, or some given combination of the two or other unexplained mechanism inherent to liberal states. Within-case process tracing has also been identified as advantageous in addressing the complexity of path-dependent explanations and critical junctures – as for example with the development of political regime types – and their constituent elements of causal possibility, contingency, closure, and constraint (Bennett and Elman, 2006b).

Bennett and Elman (2010: 505-506) also identify the advantages of single case studies that are implicitly comparative: deviant, most-likely, least-likely, and crucial cases. Of these, so-called deviant cases are those whose outcome does not fit with prior theoretical expectations or wider empirical patterns – again, the use of inductive process tracing has the advantage of potentially generating new hypotheses from these, either particular to that individual case or potentially generalisable to a broader population. A classic example here is that of post-independence India as an outlier to the standard modernisation theory of democratisation, which holds that higher levels of socio-economic development are typically required for the transition to, and consolidation of, democratic rule (Lipset, 1959; Diamond, 1992). Absent these factors, MacMillan’s single case study analysis (2008) suggests the particularistic importance of the British colonial heritage, the ideology and leadership of the Indian National Congress, and the size and heterogeneity of the federal state.

Most-likely cases, as per Eckstein above, are those in which a theory is to be considered likely to provide a good explanation if it is to have any application at all, whereas least-likely cases are ‘tough test’ ones in which the posited theory is unlikely to provide good explanation (Bennett and Elman, 2010: 505). Levy (2008) neatly refers to the inferential logic of the least-likely case as the ‘Sinatra inference’ – if a theory can make it here, it can make it anywhere. Conversely, if a theory cannot pass a most-likely case, it is seriously impugned. Single case analysis can therefore be valuable for the testing of theoretical propositions, provided that predictions are relatively precise and measurement error is low (Levy, 2008: 12-13). As Gerring rightly observes of this potential for falsification:

“a positivist orientation toward the work of social science militates toward a greater appreciation of the case study format, not a denigration of that format, as is usually supposed” (Gerring, 2007: 247, emphasis added).

In summary, the various forms of single case study analysis can – through the application of multiple qualitative and/or quantitative research methods – provide a nuanced, empirically-rich, holistic account of specific phenomena. This may be particularly appropriate for those phenomena that are simply less amenable to more superficial measures and tests (or indeed any substantive form of quantification) as well as those for which our reasons for understanding and/or explaining them are irreducibly subjective – as, for example, with many of the normative and ethical issues associated with the practice of international relations. From various epistemological and analytical standpoints, single case study analysis can incorporate both idiographic sui generis cases and, where the potential for generalisation may exist, nomothetic case studies suitable for the testing and building of causal hypotheses. Finally, it should not be ignored that a signal advantage of the case study – with particular relevance to international relations – also exists at a more practical rather than theoretical level. This is, as Eckstein noted, “that it is economical for all resources: money, manpower, time, effort… especially important, of course, if studies are inherently costly, as they are if units are complex collective individuals ” (1975: 149-150, emphasis added).

Limitations

Single case study analysis has, however, been subject to a number of criticisms, the most common of which concern the inter-related issues of methodological rigour, researcher subjectivity, and external validity. With regard to the first point, the prototypical view here is that of Zeev Maoz (2002: 164-165), who suggests that “the use of the case study absolves the author from any kind of methodological considerations. Case studies have become in many cases a synonym for freeform research where anything goes”. The absence of systematic procedures for case study research is something that Yin (2009: 14-15) sees as traditionally the greatest concern due to a relative absence of methodological guidelines. As the previous section suggests, this critique seems somewhat unfair; many contemporary case study practitioners – and representing various strands of IR theory – have increasingly sought to clarify and develop their methodological techniques and epistemological grounding (Bennett and Elman, 2010: 499-500).

A second issue, again also incorporating issues of construct validity, concerns that of the reliability and replicability of various forms of single case study analysis. This is usually tied to a broader critique of qualitative research methods as a whole. However, whereas the latter obviously tend toward an explicitly-acknowledged interpretive basis for meanings, reasons, and understandings:

“quantitative measures appear objective, but only so long as we don’t ask questions about where and how the data were produced… pure objectivity is not a meaningful concept if the goal is to measure intangibles [as] these concepts only exist because we can interpret them” (Berg and Lune, 2010: 340).

The question of researcher subjectivity is a valid one, and it may be intended only as a methodological critique of what are obviously less formalised and researcher-independent methods (Verschuren, 2003). Owen (1994) and Layne’s (1994) contradictory process tracing results of interdemocratic war-avoidance during the Anglo-American crisis of 1861 to 1863 – from liberal and realist standpoints respectively – are a useful example. However, it does also rest on certain assumptions that can raise deeper and potentially irreconcilable ontological and epistemological issues. There are, regardless, plenty such as Bent Flyvbjerg (2006: 237) who suggest that the case study contains no greater bias toward verification than other methods of inquiry, and that “on the contrary, experience indicates that the case study contains a greater bias toward falsification of preconceived notions than toward verification”.

The third and arguably most prominent critique of single case study analysis is the issue of external validity or generalisability. How is it that one case can reliably offer anything beyond the particular? “We always do better (or, in the extreme, no worse) with more observation as the basis of our generalization”, as King et al write; “in all social science research and all prediction, it is important that we be as explicit as possible about the degree of uncertainty that accompanies out prediction” (1994: 212). This is an unavoidably valid criticism. It may be that theories which pass a single crucial case study test, for example, require rare antecedent conditions and therefore actually have little explanatory range. These conditions may emerge more clearly, as Van Evera (1997: 51-54) notes, from large-N studies in which cases that lack them present themselves as outliers exhibiting a theory’s cause but without its predicted outcome. As with the case of Indian democratisation above, it would logically be preferable to conduct large-N analysis beforehand to identify that state’s non-representative nature in relation to the broader population.

There are, however, three important qualifiers to the argument about generalisation that deserve particular mention here. The first is that with regard to an idiographic single-outcome case study, as Eckstein notes, the criticism is “mitigated by the fact that its capability to do so [is] never claimed by its exponents; in fact it is often explicitly repudiated” (1975: 134). Criticism of generalisability is of little relevance when the intention is one of particularisation. A second qualifier relates to the difference between statistical and analytical generalisation; single case studies are clearly less appropriate for the former but arguably retain significant utility for the latter – the difference also between explanatory and exploratory, or theory-testing and theory-building, as discussed above. As Gerring puts it, “theory confirmation/disconfirmation is not the case study’s strong suit” (2004: 350). A third qualification relates to the issue of case selection. As Seawright and Gerring (2008) note, the generalisability of case studies can be increased by the strategic selection of cases. Representative or random samples may not be the most appropriate, given that they may not provide the richest insight (or indeed, that a random and unknown deviant case may appear). Instead, and properly used , atypical or extreme cases “often reveal more information because they activate more actors… and more basic mechanisms in the situation studied” (Flyvbjerg, 2006). Of course, this also points to the very serious limitation, as hinted at with the case of India above, that poor case selection may alternatively lead to overgeneralisation and/or grievous misunderstandings of the relationship between variables or processes (Bennett and Elman, 2006a: 460-463).

As Tim May (2011: 226) notes, “the goal for many proponents of case studies […] is to overcome dichotomies between generalizing and particularizing, quantitative and qualitative, deductive and inductive techniques”. Research aims should drive methodological choices, rather than narrow and dogmatic preconceived approaches. As demonstrated above, there are various advantages to both idiographic and nomothetic single case study analyses – notably the empirically-rich, context-specific, holistic accounts that they have to offer, and their contribution to theory-building and, to a lesser extent, that of theory-testing. Furthermore, while they do possess clear limitations, any research method involves necessary trade-offs; the inherent weaknesses of any one method, however, can potentially be offset by situating them within a broader, pluralistic mixed-method research strategy. Whether or not single case studies are used in this fashion, they clearly have a great deal to offer.

References 

Bennett, A. and Checkel, J. T. (2012) ‘Process Tracing: From Philosophical Roots to Best Practice’, Simons Papers in Security and Development, No. 21/2012, School for International Studies, Simon Fraser University: Vancouver.

Bennett, A. and Elman, C. (2006a) ‘Qualitative Research: Recent Developments in Case Study Methods’, Annual Review of Political Science , 9, 455-476.

Bennett, A. and Elman, C. (2006b) ‘Complex Causal Relations and Case Study Methods: The Example of Path Dependence’, Political Analysis , 14, 3, 250-267.

Bennett, A. and Elman, C. (2007) ‘Case Study Methods in the International Relations Subfield’, Comparative Political Studies , 40, 2, 170-195.

Bennett, A. and Elman, C. (2010) Case Study Methods. In C. Reus-Smit and D. Snidal (eds) The Oxford Handbook of International Relations . Oxford University Press: Oxford. Ch. 29.

Berg, B. and Lune, H. (2012) Qualitative Research Methods for the Social Sciences . Pearson: London.

Bryman, A. (2012) Social Research Methods . Oxford University Press: Oxford.

David, M. and Sutton, C. D. (2011) Social Research: An Introduction . SAGE Publications Ltd: London.

Diamond, J. (1992) ‘Economic development and democracy reconsidered’, American Behavioral Scientist , 35, 4/5, 450-499.

Eckstein, H. (1975) Case Study and Theory in Political Science. In R. Gomm, M. Hammersley, and P. Foster (eds) Case Study Method . SAGE Publications Ltd: London.

Flyvbjerg, B. (2006) ‘Five Misunderstandings About Case-Study Research’, Qualitative Inquiry , 12, 2, 219-245.

Geertz, C. (1973) The Interpretation of Cultures: Selected Essays by Clifford Geertz . Basic Books Inc: New York.

Gerring, J. (2004) ‘What is a Case Study and What Is It Good for?’, American Political Science Review , 98, 2, 341-354.

Gerring, J. (2006a) Case Study Research: Principles and Practices . Cambridge University Press: Cambridge.

Gerring, J. (2006b) ‘Single-Outcome Studies: A Methodological Primer’, International Sociology , 21, 5, 707-734.

Gerring, J. (2007) ‘Is There a (Viable) Crucial-Case Method?’, Comparative Political Studies , 40, 3, 231-253.

King, G., Keohane, R. O. and Verba, S. (1994) Designing Social Inquiry: Scientific Inference in Qualitative Research . Princeton University Press: Chichester.

Layne, C. (1994) ‘Kant or Cant: The Myth of the Democratic Peace’, International Security , 19, 2, 5-49.

Levy, J. S. (2008) ‘Case Studies: Types, Designs, and Logics of Inference’, Conflict Management and Peace Science , 25, 1-18.

Lipset, S. M. (1959) ‘Some Social Requisites of Democracy: Economic Development and Political Legitimacy’, The American Political Science Review , 53, 1, 69-105.

Lyotard, J-F. (1984) The Postmodern Condition: A Report on Knowledge . University of Minnesota Press: Minneapolis.

MacMillan, A. (2008) ‘Deviant Democratization in India’, Democratization , 15, 4, 733-749.

Maoz, Z. (2002) Case study methodology in international studies: from storytelling to hypothesis testing. In F. P. Harvey and M. Brecher (eds) Evaluating Methodology in International Studies . University of Michigan Press: Ann Arbor.

May, T. (2011) Social Research: Issues, Methods and Process . Open University Press: Maidenhead.

Owen, J. M. (1994) ‘How Liberalism Produces Democratic Peace’, International Security , 19, 2, 87-125.

Seawright, J. and Gerring, J. (2008) ‘Case Selection Techniques in Case Study Research: A Menu of Qualitative and Quantitative Options’, Political Research Quarterly , 61, 2, 294-308.

Stake, R. E. (2008) Qualitative Case Studies. In N. K. Denzin and Y. S. Lincoln (eds) Strategies of Qualitative Inquiry . Sage Publications: Los Angeles. Ch. 17.

Van Evera, S. (1997) Guide to Methods for Students of Political Science . Cornell University Press: Ithaca.

Verschuren, P. J. M. (2003) ‘Case study as a research strategy: some ambiguities and opportunities’, International Journal of Social Research Methodology , 6, 2, 121-139.

Yin, R. K. (2009) Case Study Research: Design and Methods . SAGE Publications Ltd: London.

[1] The paper follows convention by differentiating between ‘International Relations’ as the academic discipline and ‘international relations’ as the subject of study.

[2] There is some similarity here with Stake’s (2008: 445-447) notion of intrinsic cases, those undertaken for a better understanding of the particular case, and instrumental ones that provide insight for the purposes of a wider external interest.

[3] These may be unique in the idiographic sense, or in nomothetic terms as an exception to the generalising suppositions of either probabilistic or deterministic theories (as per deviant cases, below).

[4] Although there are “philosophical hurdles to mount”, according to Bennett and Checkel, there exists no a priori reason as to why process tracing (as typically grounded in scientific realism) is fundamentally incompatible with various strands of positivism or interpretivism (2012: 18-19). By extension, it can therefore be incorporated by a range of contemporary mainstream IR theories.

— Written by: Ben Willis Written at: University of Plymouth Written for: David Brockington Date written: January 2013

Further Reading on E-International Relations

• Identity in International Conflicts: A Case Study of the Cuban Missile Crisis
• Imperialism’s Legacy in the Study of Contemporary Politics: The Case of Hegemonic Stability Theory
• Recreating a Nation’s Identity Through Symbolism: A Chinese Case Study
• Ontological Insecurity: A Case Study on Israeli-Palestinian Conflict in Jerusalem
• Terrorists or Freedom Fighters: A Case Study of ETA
• A Critical Assessment of Eco-Marxism: A Ghanaian Case Study

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2.2 Approaches to Research

Learning objectives.

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

• Describe the different research methods used by psychologists
• Discuss the strengths and weaknesses of case studies, naturalistic observation, surveys, and archival research
• Compare longitudinal and cross-sectional approaches to research
• Compare and contrast correlation and causation

There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it. Some methods rely on observational techniques. Other approaches involve interactions between the researcher and the individuals who are being studied—ranging from a series of simple questions to extensive, in-depth interviews—to well-controlled experiments.

Each of these research methods has unique strengths and weaknesses, and each method may only be appropriate for certain types of research questions. For example, studies that rely primarily on observation produce incredible amounts of information, but the ability to apply this information to the larger population is somewhat limited because of small sample sizes. Survey research, on the other hand, allows researchers to easily collect data from relatively large samples. While this allows for results to be generalized to the larger population more easily, the information that can be collected on any given survey is somewhat limited and subject to problems associated with any type of self-reported data. Some researchers conduct archival research by using existing records. While this can be a fairly inexpensive way to collect data that can provide insight into a number of research questions, researchers using this approach have no control on how or what kind of data was collected. All of the methods described thus far are correlational in nature. This means that researchers can speak to important relationships that might exist between two or more variables of interest. However, correlational data cannot be used to make claims about cause-and-effect relationships.

Correlational research can find a relationship between two variables, but the only way a researcher can claim that the relationship between the variables is cause and effect is to perform an experiment. In experimental research, which will be discussed later in this chapter, there is a tremendous amount of control over variables of interest. While this is a powerful approach, experiments are often conducted in artificial settings. This calls into question the validity of experimental findings with regard to how they would apply in real-world settings. In addition, many of the questions that psychologists would like to answer cannot be pursued through experimental research because of ethical concerns.

Clinical or Case Studies

In 2011, the New York Times published a feature story on Krista and Tatiana Hogan, Canadian twin girls. These particular twins are unique because Krista and Tatiana are conjoined twins, connected at the head. There is evidence that the two girls are connected in a part of the brain called the thalamus, which is a major sensory relay center. Most incoming sensory information is sent through the thalamus before reaching higher regions of the cerebral cortex for processing.

Link to Learning

Watch this CBC video about Krista's and Tatiana's lives to learn more.

The implications of this potential connection mean that it might be possible for one twin to experience the sensations of the other twin. For instance, if Krista is watching a particularly funny television program, Tatiana might smile or laugh even if she is not watching the program. This particular possibility has piqued the interest of many neuroscientists who seek to understand how the brain uses sensory information.

These twins represent an enormous resource in the study of the brain, and since their condition is very rare, it is likely that as long as their family agrees, scientists will follow these girls very closely throughout their lives to gain as much information as possible (Dominus, 2011).

Over time, it has become clear that while Krista and Tatiana share some sensory experiences and motor control, they remain two distinct individuals, which provides invaluable insight for researchers interested in the mind and the brain (Egnor, 2017).

In observational research, scientists are conducting a clinical or case study when they focus on one person or just a few individuals. Indeed, some scientists spend their entire careers studying just 10–20 individuals. Why would they do this? Obviously, when they focus their attention on a very small number of people, they can gain a precious amount of insight into those cases. The richness of information that is collected in clinical or case studies is unmatched by any other single research method. This allows the researcher to have a very deep understanding of the individuals and the particular phenomenon being studied.

If clinical or case studies provide so much information, why are they not more frequent among researchers? As it turns out, the major benefit of this particular approach is also a weakness. As mentioned earlier, this approach is often used when studying individuals who are interesting to researchers because they have a rare characteristic. Therefore, the individuals who serve as the focus of case studies are not like most other people. If scientists ultimately want to explain all behavior, focusing attention on such a special group of people can make it difficult to generalize any observations to the larger population as a whole. Generalizing refers to the ability to apply the findings of a particular research project to larger segments of society. Again, case studies provide enormous amounts of information, but since the cases are so specific, the potential to apply what’s learned to the average person may be very limited.

Naturalistic Observation

If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances are that almost everyone in the classroom will raise their hand, but do you think hand washing after every trip to the restroom is really that universal?

This is very similar to the phenomenon mentioned earlier in this chapter: many individuals do not feel comfortable answering a question honestly. But if we are committed to finding out the facts about hand washing, we have other options available to us.

Suppose we send a classmate into the restroom to actually watch whether everyone washes their hands after using the restroom. Will our observer blend into the restroom environment by wearing a white lab coat, sitting with a clipboard, and staring at the sinks? We want our researcher to be inconspicuous—perhaps standing at one of the sinks pretending to put in contact lenses while secretly recording the relevant information. This type of observational study is called naturalistic observation : observing behavior in its natural setting. To better understand peer exclusion, Suzanne Fanger collaborated with colleagues at the University of Texas to observe the behavior of preschool children on a playground. How did the observers remain inconspicuous over the duration of the study? They equipped a few of the children with wireless microphones (which the children quickly forgot about) and observed while taking notes from a distance. Also, the children in that particular preschool (a “laboratory preschool”) were accustomed to having observers on the playground (Fanger, Frankel, & Hazen, 2012).

It is critical that the observer be as unobtrusive and as inconspicuous as possible: when people know they are being watched, they are less likely to behave naturally. If you have any doubt about this, ask yourself how your driving behavior might differ in two situations: In the first situation, you are driving down a deserted highway during the middle of the day; in the second situation, you are being followed by a police car down the same deserted highway ( Figure 2.7 ).

It should be pointed out that naturalistic observation is not limited to research involving humans. Indeed, some of the best-known examples of naturalistic observation involve researchers going into the field to observe various kinds of animals in their own environments. As with human studies, the researchers maintain their distance and avoid interfering with the animal subjects so as not to influence their natural behaviors. Scientists have used this technique to study social hierarchies and interactions among animals ranging from ground squirrels to gorillas. The information provided by these studies is invaluable in understanding how those animals organize socially and communicate with one another. The anthropologist Jane Goodall , for example, spent nearly five decades observing the behavior of chimpanzees in Africa ( Figure 2.8 ). As an illustration of the types of concerns that a researcher might encounter in naturalistic observation, some scientists criticized Goodall for giving the chimps names instead of referring to them by numbers—using names was thought to undermine the emotional detachment required for the objectivity of the study (McKie, 2010).

The greatest benefit of naturalistic observation is the validity , or accuracy, of information collected unobtrusively in a natural setting. Having individuals behave as they normally would in a given situation means that we have a higher degree of ecological validity, or realism, than we might achieve with other research approaches. Therefore, our ability to generalize the findings of the research to real-world situations is enhanced. If done correctly, we need not worry about people or animals modifying their behavior simply because they are being observed. Sometimes, people may assume that reality programs give us a glimpse into authentic human behavior. However, the principle of inconspicuous observation is violated as reality stars are followed by camera crews and are interviewed on camera for personal confessionals. Given that environment, we must doubt how natural and realistic their behaviors are.

The major downside of naturalistic observation is that they are often difficult to set up and control. In our restroom study, what if you stood in the restroom all day prepared to record people’s hand washing behavior and no one came in? Or, what if you have been closely observing a troop of gorillas for weeks only to find that they migrated to a new place while you were sleeping in your tent? The benefit of realistic data comes at a cost. As a researcher you have no control of when (or if) you have behavior to observe. In addition, this type of observational research often requires significant investments of time, money, and a good dose of luck.

Sometimes studies involve structured observation. In these cases, people are observed while engaging in set, specific tasks. An excellent example of structured observation comes from Strange Situation by Mary Ainsworth (you will read more about this in the chapter on lifespan development). The Strange Situation is a procedure used to evaluate attachment styles that exist between an infant and caregiver. In this scenario, caregivers bring their infants into a room filled with toys. The Strange Situation involves a number of phases, including a stranger coming into the room, the caregiver leaving the room, and the caregiver’s return to the room. The infant’s behavior is closely monitored at each phase, but it is the behavior of the infant upon being reunited with the caregiver that is most telling in terms of characterizing the infant’s attachment style with the caregiver.

Another potential problem in observational research is observer bias . Generally, people who act as observers are closely involved in the research project and may unconsciously skew their observations to fit their research goals or expectations. To protect against this type of bias, researchers should have clear criteria established for the types of behaviors recorded and how those behaviors should be classified. In addition, researchers often compare observations of the same event by multiple observers, in order to test inter-rater reliability : a measure of reliability that assesses the consistency of observations by different observers.

Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally ( Figure 2.9 ). Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.

Surveys allow researchers to gather data from larger samples than may be afforded by other research methods . A sample is a subset of individuals selected from a population , which is the overall group of individuals that the researchers are interested in. Researchers study the sample and seek to generalize their findings to the population. Generally, researchers will begin this process by calculating various measures of central tendency from the data they have collected. These measures provide an overall summary of what a typical response looks like. There are three measures of central tendency: mode, median, and mean. The mode is the most frequently occurring response, the median lies at the middle of a given data set, and the mean is the arithmetic average of all data points. Means tend to be most useful in conducting additional analyses like those described below; however, means are very sensitive to the effects of outliers, and so one must be aware of those effects when making assessments of what measures of central tendency tell us about a data set in question.

There is both strength and weakness of the survey in comparison to case studies. By using surveys, we can collect information from a larger sample of people. A larger sample is better able to reflect the actual diversity of the population, thus allowing better generalizability. Therefore, if our sample is sufficiently large and diverse, we can assume that the data we collect from the survey can be generalized to the larger population with more certainty than the information collected through a case study. However, given the greater number of people involved, we are not able to collect the same depth of information on each person that would be collected in a case study.

Another potential weakness of surveys is something we touched on earlier in this chapter: People don't always give accurate responses. They may lie, misremember, or answer questions in a way that they think makes them look good. For example, people may report drinking less alcohol than is actually the case.

Any number of research questions can be answered through the use of surveys. One real-world example is the research conducted by Jenkins, Ruppel, Kizer, Yehl, and Griffin (2012) about the backlash against the US Arab-American community following the terrorist attacks of September 11, 2001. Jenkins and colleagues wanted to determine to what extent these negative attitudes toward Arab-Americans still existed nearly a decade after the attacks occurred. In one study, 140 research participants filled out a survey with 10 questions, including questions asking directly about the participant’s overt prejudicial attitudes toward people of various ethnicities. The survey also asked indirect questions about how likely the participant would be to interact with a person of a given ethnicity in a variety of settings (such as, “How likely do you think it is that you would introduce yourself to a person of Arab-American descent?”). The results of the research suggested that participants were unwilling to report prejudicial attitudes toward any ethnic group. However, there were significant differences between their pattern of responses to questions about social interaction with Arab-Americans compared to other ethnic groups: they indicated less willingness for social interaction with Arab-Americans compared to the other ethnic groups. This suggested that the participants harbored subtle forms of prejudice against Arab-Americans, despite their assertions that this was not the case (Jenkins et al., 2012).

Archival Research

Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research . Archival research relies on looking at past records or data sets to look for interesting patterns or relationships.

For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and calculate how long it took them to complete their degrees, as well as course loads, grades, and extracurricular involvement. Archival research could provide important information about who is most likely to complete their education, and it could help identify important risk factors for struggling students ( Figure 2.10 ).

In comparing archival research to other research methods, there are several important distinctions. For one, the researcher employing archival research never directly interacts with research participants. Therefore, the investment of time and money to collect data is considerably less with archival research. Additionally, researchers have no control over what information was originally collected. Therefore, research questions have to be tailored so they can be answered within the structure of the existing data sets. There is also no guarantee of consistency between the records from one source to another, which might make comparing and contrasting different data sets problematic.

Longitudinal and Cross-Sectional Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again at age 40.

Another approach is cross-sectional research. In cross-sectional research , a researcher compares multiple segments of the population at the same time. Using the dietary habits example above, the researcher might directly compare different groups of people by age. Instead of studying a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old individuals. While cross-sectional research requires a shorter-term investment, it is also limited by differences that exist between the different generations (or cohorts) that have nothing to do with age per se, but rather reflect the social and cultural experiences of different generations of individuals that make them different from one another.

To illustrate this concept, consider the following survey findings. In recent years there has been significant growth in the popular support of same-sex marriage. Many studies on this topic break down survey participants into different age groups. In general, younger people are more supportive of same-sex marriage than are those who are older (Jones, 2013). Does this mean that as we age we become less open to the idea of same-sex marriage, or does this mean that older individuals have different perspectives because of the social climates in which they grew up? Longitudinal research is a powerful approach because the same individuals are involved in the research project over time, which means that the researchers need to be less concerned with differences among cohorts affecting the results of their study.

Often longitudinal studies are employed when researching various diseases in an effort to understand particular risk factors. Such studies often involve tens of thousands of individuals who are followed for several decades. Given the enormous number of people involved in these studies, researchers can feel confident that their findings can be generalized to the larger population. The Cancer Prevention Study-3 (CPS-3) is one of a series of longitudinal studies sponsored by the American Cancer Society aimed at determining predictive risk factors associated with cancer. When participants enter the study, they complete a survey about their lives and family histories, providing information on factors that might cause or prevent the development of cancer. Then every few years the participants receive additional surveys to complete. In the end, hundreds of thousands of participants will be tracked over 20 years to determine which of them develop cancer and which do not.

Clearly, this type of research is important and potentially very informative. For instance, earlier longitudinal studies sponsored by the American Cancer Society provided some of the first scientific demonstrations of the now well-established links between increased rates of cancer and smoking (American Cancer Society, n.d.) ( Figure 2.11 ).

As with any research strategy, longitudinal research is not without limitations. For one, these studies require an incredible time investment by the researcher and research participants. Given that some longitudinal studies take years, if not decades, to complete, the results will not be known for a considerable period of time. In addition to the time demands, these studies also require a substantial financial investment. Many researchers are unable to commit the resources necessary to see a longitudinal project through to the end.

Research participants must also be willing to continue their participation for an extended period of time, and this can be problematic. People move, get married and take new names, get ill, and eventually die. Even without significant life changes, some people may simply choose to discontinue their participation in the project. As a result, the attrition rates, or reduction in the number of research participants due to dropouts, in longitudinal studies are quite high and increase over the course of a project. For this reason, researchers using this approach typically recruit many participants fully expecting that a substantial number will drop out before the end. As the study progresses, they continually check whether the sample still represents the larger population, and make adjustments as necessary.

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Case Study Research Method in Psychology

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

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

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

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

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

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

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

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

 Famous Case Studies

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

Clinical Case Studies

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

Child Psychology Case Studies

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

Types of Case Studies

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

Where Do You Find Data for a Case Study?

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

1. Primary sources

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

2. Secondary sources

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

3. Archival records

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

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

4. Organizational records

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

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

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

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

How do I Write a Case Study in Psychology?

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

1. Introduction

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

2. Case Presentation

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

3. Management and Outcome

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

4. Discussion

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

5. Additional Items

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

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

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

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

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

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

Limitations

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Further Information

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

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• 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.

Yin RK: Case study research, design and method. 2009, London: Sage Publications Ltd., 4

Google Scholar  

Keen J, Packwood T: Qualitative research; case study evaluation. BMJ. 1995, 311: 444-446.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Sheikh A, Halani L, Bhopal R, Netuveli G, Partridge M, Car J, et al: Facilitating the Recruitment of Minority Ethnic People into Research: Qualitative Case Study of South Asians and Asthma. PLoS Med. 2009, 6 (10): 1-11.

Article   Google Scholar  

Pinnock H, Huby G, Powell A, Kielmann T, Price D, Williams S, et al: The process of planning, development and implementation of a General Practitioner with a Special Interest service in Primary Care Organisations in England and Wales: a comparative prospective case study. Report for the National Co-ordinating Centre for NHS Service Delivery and Organisation R&D (NCCSDO). 2008, [ http://www.sdo.nihr.ac.uk/files/project/99-final-report.pdf ]

Robertson A, Cresswell K, Takian A, Petrakaki D, Crowe S, Cornford T, et al: Prospective evaluation of the implementation and adoption of NHS Connecting for Health's national electronic health record in secondary care in England: interim findings. BMJ. 2010, 41: c4564-

Pearson P, Steven A, Howe A, Sheikh A, Ashcroft D, Smith P, the Patient Safety Education Study Group: Learning about patient safety: organisational context and culture in the education of healthcare professionals. J Health Serv Res Policy. 2010, 15: 4-10. 10.1258/jhsrp.2009.009052.

Article   PubMed   Google Scholar  

van Harten WH, Casparie TF, Fisscher OA: The evaluation of the introduction of a quality management system: a process-oriented case study in a large rehabilitation hospital. Health Policy. 2002, 60 (1): 17-37. 10.1016/S0168-8510(01)00187-7.

Stake RE: The art of case study research. 1995, London: Sage Publications Ltd.

Sheikh A, Smeeth L, Ashcroft R: Randomised controlled trials in primary care: scope and application. Br J Gen Pract. 2002, 52 (482): 746-51.

PubMed   PubMed Central   Google Scholar  

King G, Keohane R, Verba S: Designing Social Inquiry. 1996, Princeton: Princeton University Press

Doolin B: Information technology as disciplinary technology: being critical in interpretative research on information systems. Journal of Information Technology. 1998, 13: 301-311. 10.1057/jit.1998.8.

George AL, Bennett A: Case studies and theory development in the social sciences. 2005, Cambridge, MA: MIT Press

Eccles M, the Improved Clinical Effectiveness through Behavioural Research Group (ICEBeRG): Designing theoretically-informed implementation interventions. Implementation Science. 2006, 1: 1-8. 10.1186/1748-5908-1-1.

Article   PubMed Central   Google Scholar  

Netuveli G, Hurwitz B, Levy M, Fletcher M, Barnes G, Durham SR, Sheikh A: Ethnic variations in UK asthma frequency, morbidity, and health-service use: a systematic review and meta-analysis. Lancet. 2005, 365 (9456): 312-7.

Sheikh A, Panesar SS, Lasserson T, Netuveli G: Recruitment of ethnic minorities to asthma studies. Thorax. 2004, 59 (7): 634-

CAS   PubMed   PubMed Central   Google Scholar  

Hellström I, Nolan M, Lundh U: 'We do things together': A case study of 'couplehood' in dementia. Dementia. 2005, 4: 7-22. 10.1177/1471301205049188.

Som CV: Nothing seems to have changed, nothing seems to be changing and perhaps nothing will change in the NHS: doctors' response to clinical governance. International Journal of Public Sector Management. 2005, 18: 463-477. 10.1108/09513550510608903.

Lincoln Y, Guba E: Naturalistic inquiry. 1985, Newbury Park: Sage Publications

Barbour RS: Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?. BMJ. 2001, 322: 1115-1117. 10.1136/bmj.322.7294.1115.

Mays N, Pope C: Qualitative research in health care: Assessing quality in qualitative research. BMJ. 2000, 320: 50-52. 10.1136/bmj.320.7226.50.

Mason J: Qualitative researching. 2002, London: Sage

Brazier A, Cooke K, Moravan V: Using Mixed Methods for Evaluating an Integrative Approach to Cancer Care: A Case Study. Integr Cancer Ther. 2008, 7: 5-17. 10.1177/1534735407313395.

Miles MB, Huberman M: Qualitative data analysis: an expanded sourcebook. 1994, CA: Sage Publications Inc., 2

Pope C, Ziebland S, Mays N: Analysing qualitative data. Qualitative research in health care. BMJ. 2000, 320: 114-116. 10.1136/bmj.320.7227.114.

Cresswell KM, Worth A, Sheikh A: Actor-Network Theory and its role in understanding the implementation of information technology developments in healthcare. BMC Med Inform Decis Mak. 2010, 10 (1): 67-10.1186/1472-6947-10-67.

Article   PubMed   PubMed Central   Google Scholar  

Malterud K: Qualitative research: standards, challenges, and guidelines. Lancet. 2001, 358: 483-488. 10.1016/S0140-6736(01)05627-6.

Article   CAS   PubMed   Google Scholar  

Yin R: Case study research: design and methods. 1994, Thousand Oaks, CA: Sage Publishing, 2

Yin R: Enhancing the quality of case studies in health services research. Health Serv Res. 1999, 34: 1209-1224.

Green J, Thorogood N: Qualitative methods for health research. 2009, Los Angeles: Sage, 2

Howcroft D, Trauth E: Handbook of Critical Information Systems Research, Theory and Application. 2005, Cheltenham, UK: Northampton, MA, USA: Edward Elgar

Book   Google Scholar  

Blakie N: Approaches to Social Enquiry. 1993, Cambridge: Polity Press

Doolin B: Power and resistance in the implementation of a medical management information system. Info Systems J. 2004, 14: 343-362. 10.1111/j.1365-2575.2004.00176.x.

Bloomfield BP, Best A: Management consultants: systems development, power and the translation of problems. Sociological Review. 1992, 40: 533-560.

Shanks G, Parr A: Positivist, single case study research in information systems: A critical analysis. Proceedings of the European Conference on Information Systems. 2003, Naples

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Acknowledgements

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

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

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“The person who can combine frames of reference and draw connections between ostensibly unrelated points of view is likely to be the one who makes the creative breakthrough.” —Denise Shekerjian

In the previous section, our framework describing the interaction of multiple competing messages provided a useful way to describe how risk communicators should create convergence and understanding with their audiences in pre-crisis, crisis, and post-crisis situations. In addition, the identification of best practices offers a way to identify why particular risk messages may have more influence than others on how audiences respond. Adding to the complexity of the situation for risk communicators are multiple publics who may not share the same understanding or willingness to respond to the messages due to how the risk or potential crisis may affect them in what we described as spheres of ethnocentricity.

In the complex communication context of risk communication, one research methodology is particularly appropriate, due to its capacity to explore, describe, or explain the dynamics of the situation. The case study approach to research in the social sciences is a fitting method for identifying the interaction between individuals, messages, and context. Yin ) summarizes, “The case study method allows investigators to retain the holistic and meaningful characteristics of real-life events” (p. 2). The case study approach works well to identify best practices for risk communication because individual situations are defined or isolated, relevant data are collected about the situation, and the findings are presented in such a way that a more complete understanding is reached regarding how messages shape perceptions and serve to prompt particular responses from those hearing the messages.

We consider the case study method as both an approach to research and a choice of what to study (Patton, 2002 ). Therefore, in the construction of the case studies presented in this book, a consistent methodological approach was followed. In order to establish common areas of analysis within the research design, we focused on risk situations involving the unintentional or intentional contamination or compromise of the food system. A conceptual framework based upon the best practices explained in Chapter 2 and a chronological exposition of the pre-crisis, crisis, and post-crisis messages created consistency as we drew implications about what happened, how it happened, and why. Collectively, the cases allowed us to generalize about the best practices as a whole.

Individually, the choice of cases provided opportunities to demonstrate various aspects of the best practices. Each of the forthcoming cases includes particular situations and context-sensitive information whereby the best practices for risk communication could be identified and studied. In some cases, preemptive communication strategies designed to promote compliant behavior are found. In others, the exposition of the crisis revealed how risks were not anticipated or communicated effectively to the public. In fact, as demonstrated by how a crisis actually unfolded, the evidence suggests that those managing the crisis were not always mindfully considering the competing arguments. Rather than seeking congruence, reliance on economic or social models enabled decision-makers to simplify the risk situation at a time when complexity should have been acknowledged. In such situations, the value of the best practices may not have been recognized until after the crisis had passed.

Justification for the Case Study Approach

We selected the case study approach as a way to illustrate the interactive process involved in the convergence of ris(2003k messages for several reasons. Case studies have been used frequently by scholars and practitioners in public health, agriculture, education, psychology, and the social sciences as a legitimate methodological approach to research (Rogers, 2003 ; Tuschman & Anderson, 1997 ). In addition, they provide a method to investigate a contemporary event involving risk within a real life context; and they contribute to enhanced knowledge of complex social phenomena.

Legitimacy as a Methodological Approach

The case study approach has been used to study many different situations involving individual, group, organizational, social, political, and related phenomena (Yin, 2003). Throughout his treatise on diffusion theory, Rogers ( 2003 ) offers cases to illustrate the following: social systems (Iowa hybrid corn case), pro-innovation bias (Egyptian villages pure drinking water case), socioeconomic status (California hard tomatoes case), the reinvention process (horse culture among the Plains Indians case), attributions of innovations (photovoltaics, cellular telephones case), adopter types (Old Order Amish case), opinion leadership (Alpha Pups in the viral marketing of an electronics game case), diffusion networks (London Cholera epidemic case), change agents (Baltimore needle-exchange project case), stages in the innovation process (Santa Monica freeway diamond lane experiment case), and the consequences of innovations (steel axes for stone-age Aborigines case), to name but a few.

In their collection of readings on managing strategic innovation and change, Tuschman and Anderson ( 1997 ) offer numerous case studies involving technology cycles, design changes, power dynamics in organizations, managing research and development, product development, cross-functional linkages, and leadership styles. Similarly, risk and crisis scholars have used case studies to illustrate best practices and organizational learning.

Sellnow and Littlefield ( 2005 ) use case studies describing both accidental and intentional contamination to demonstrate lessons learned about protecting America's food supply. Three cases focused on particular companies and their experiences managing a crisis: Schwan's demonstration of social responsibility in response to a Salmonella contamination crisis, Chi-Chi's inability to survive a Hepatitis A outbreak despite apologia, and Jack in the Box restaurants' organizational learning following an E. coli outbreak in Seattle, Washington. A case involving interagency coordination and the tainted strawberries in the National School Lunch Program revealed how various stakeholders affect crisis planning efforts. Two cases of potentially intentional contamination—one by Monsanto, a major producer of genetically engineered wheat and the other by the Boghwan Shree Rajneesh cult in an Oregon community—explored the effect of public opinion and outrage.

In their work, Ulmer et al. ( 2007 ) provide case studies revealing lessons learned about managing uncertainty, effective communication, and demonstrating leadership. They focused on four areas: industrial disasters (Exxon and the Valdez oil tanker, and the fires at Malden Mills and Cole Hardwoods), food borne illness (Jack in the Box's E. coli O157:H7, Hepatitis A at a Chi-Chi's restaurant, and the Schwan's Salmonella crisis), terrorism (the case of 9/11, the Oklahoma City bombing, and the CDC's handling of the SARS outbreak), and natural disasters (the 1997 Red River Valley floods, the Tsunami and the Red Cross, and the 2003 San Diego County fires).

Exploring risk and crisis situations in public health, Seeger et al. ( 2008 ) categorize case studies focusing on bioterrorism, food borne illness, infectious disease outbreaks, and crisis prevention and responses. Cases of bioterrorism focused on lessons learned from the 2001 Anthrax crisis through the U.S. Postal System; the threat of agro-terrorism in high reliability organizations and organizational responses to the Chi-Chi's Hepatitis A outbreak provided cases demonstrating the risk of food-borne illness and the need for crisis prevention; and the strategies used by communities, nations, and the world when dealing with the risk of West Nile Virus, SARS, Encephalitis, HIV and AIDS provided cases where infectious disease outbreaks required effective risk and crisis responses. These collections and others similarly have found value in studying particular examples of an identified phenomenon for the benefit of understanding more about what, how, and why something happened.

Multiple Sources of Information

One of the reasons supporting the legitimacy of the case study approach is its use of multiple sources of information to establish claims about a particular situation.

Multiple sources may include textual materials, on-line websites and resources, interviews, media accounts, and personal observations. Due to the nature of the case study approach, choices must be made about the kinds of information to be utilized. Accessibility often dictates the kinds of information to be included, in which case the researchers must continually cross reference to be sure that the most accurate depiction of the situation is conveyed.

For the case studies included within this volume, text-based materials provided the majority of the information consulted (Fig. 4.1 ). Information drawn from national newspapers (e.g., New York Times and The Wall Street Journal ), regional newspapers (e.g., The Boston Globe) or—as in the New Zealand foot and mouth hoax case—international outlets (e.g., Financial Times and The Dominion Post ) provided contextual material enabling the researcher to establish the time frame and variables at work in each case. Websites and on-line materials, such as those offered by governmental and industrial groups provided insight from the perspective of those in positions to respond to the risk or crisis situation. A number of groups were accessed through such websites, including the U.S. Department of Health and Human Services, the Department for the Environment, Food, and Rural Affairs, Odwalla, Inc., KidSource Online, and ConAgra Foods. Interviews were conducted with individuals holding positions of responsibility, enhancing the researcher's understanding of the dynamics of the situation in New Zealand.

Multiple sources of information used in case studies

When interviewing was impossible, official comments from key decision-makers were drawn from the available textual sources. Together, these multiple sources enabled the observer to engage in triangulation, a process where more than one source of information is used when drawing inferences or conclusions about a given situation. Stake ( 2000 ) argues that triangulation was valuable not only to clarify meaning, but also to identify “different ways the phenomenon is being seen” (p. 444).

Need for Theoretical Framework

In addition to the need for multiple sources of data to understand the complexity of a risk or crisis situation, another reason researchers use the case study approach stems from the way theoretical propositions may be used to guide data collection and analysis. Case study researchers can set the parameters for what will be included within the analysis. As such, the introduction of a theoretical framework provides an overlay for the data that the researcher may use as a way to explore, describe, or explain what happened. In the selected cases included in this volume, the researchers utilized existing theoretical perspectives about risk and crisis drawn from the professional journals of the field, including Journal of Applied Communication Research, Management Communication Quarterly, Journal of Epidemiol Community Health , and The New England Journal of Medicine . The existing theoretical framework provided a backdrop for considering each case.

Specifically for this volume, best practices for risk communication were used as a theoretical framework (Fig. 4.2 ). As already explained in Chapter 2 , these best practices are theory driven and stem from the work previously done through a collaboration of risk and crisis communicators who introduced the ten best practices for crisis communication through the National Center for Food Protection and Defense (Seeger, 2006 ). Each of the case studies used these best practices to help to reveal problems faced by risk and crisis communicators, as well as to identify the strategies used as individuals, organizations, and communities worked to move through the crisis to recovery and in some cases, renewal.

Best practices of risk communication

Utility for Investigation into Contemporary Events

In addition to the case study method being multidimensional, researchers value the approach because it provides an empirical way to investigate a contemporary phenomenon within a real life context. There are differences between the case study approach and studies utilizing a more structured research methodology. For example, in an experimental setting, variables may be controlled or accounted for as particular actions are taken to affect the outcome. In this closed environment, researchers can make generalizations based upon the sophistication of their design.

However, situations where risk messages are communicated through the media and events are reported and presented as they unfold, researchers have less control over how competing risk message are transmitted and received by diverse groups within the public. The range of variables that cannot be controlled or manipulated further complicates the coverage of contemporary events outside of the laboratory. For example, Chapter 8 examines the case of in the tainted Odwalla juice, the Cryp-tosporidium outbreak case, or in the case of finding Salmonella in ConAgra Foods pot pies, human error could not have been predicted with certainty. In disasters like Hurricane Katrina, elements of nature could not be controlled. They happened. In the New Zealand hoax case, the potential threat of a terrorist's intentional foot and mouth disease could not have been precluded. The realization that a host of variables are interacting in a real-world setting affords the scholar a unique opportunity to explore, describe, and explain events as they occur.

The opportunity to examine what transpired in a particular crisis situation is unique to the case study approach. Due to the dynamic, chaotic nature of crisis events that are not always represented in cause-to-effect relationships, the case study approach enabled us to examine and understand situations in ways that might not have been foreseen prior to the start of our investigation. While not statistically generalizable, after examining several cases, the identification of the presence or absence of the best practices provides researchers with the arguments needed to find consistency about the situation that may have applicability to other similar risk situations. By using the case study framework to separate the pre-crisis from the crisis, observers may note events leading up to the crisis, factors that may have contributed to the way the risks were presented, and what happened (or should have happened) as a result of the way these messages were processed and acted upon.

Enhancement of Knowledge About Complex Phenomena

Within any given situation involving risk, there are many variables of interest, including the processes at work within the dynamic of the situation; the changes that occur due to the introduction of particular risk messages; relations between various stakeholders during the pre-crisis, crisis, or post-crisis situations; and the learning that results following the response to a crisis situation. These variables involving individuals, groups, organizations, or social entities represent the multidimensionality of the phenomena involved in risk communication.

In addition, the varied nature of questions posed by researchers and practitioners pertaining to risk situations further demonstrates how the complexity of a case can be studied using this approach. Case studies seeking to know what happened in a particular context rely on “what” questions. What happened in a particular situation causing a response? When researchers seek answers to “how” questions, they want descriptions. How did an entity communicate risk messages? Researchers seeking explanations regarding the particular motivations of communicators in a situation rely on “why” questions. Why were company spokespeople compelled to communicate particular messages to the public about a risk situation? In contrast to quantitative and qualitative methodologies where researchers tend to focus on one dimension or variable, the case study approach enables the researcher to use all of these questions. Questions like these are used throughout the cases to reveal the multidimensionality of the risk and crisis events.

Establishing a Framework for Case Studies

Identifying a framework for case studies is essential if comparisons are to be made. Stake ( 2000 ) suggests the following items as essential in the creation of a case study:

The nature of the case; the case's historical background; the physical setting; other contexts (e.g., economic, political, legal, and aesthetic); other cases through which this case is recognized; and those informants through whom the case can be known. (pp. 438– 439)

Thus, to provide clarity, we determined that each case study should be written to include common elements providing comparable information for the reader to consider. In the following case studies, we provide:

An introduction and overview of the case.

Evidence and application of the best practices for risk communication within the case.

Lessons learned and implications drawn from the use of best practices for risk communication.

From a research perspective, with these elements as constants, individual authors were able to gather data appropriate to each case and uniformly present their findings. In addition, similar textual materials were used in each of the studies, providing the reader with comparable information to consider.

Five Cases of Risk Communication

Stake ( 2000 ) argues that, “perhaps the most unique aspect of the case study is the selection of cases to study” (p. 446). With this in mind, we selected crisis situations where the presence or absence of best practices for risk communication could be identified, providing the readers with insight into how risk communication may or could have been used to affect the behavior of various stakeholders prior to the onset of a crisis situation. Each case study is unique in the risks posed, as well as how the communication agent sought to affect compliant behavior from the various stakeholders receiving the risk messages.

In the case of the Cryptosporidium crisis, the risks associated with water quality in a major metropolitan area and a community's response to a water quality crisis are examined. The risks associated with inadequate planning and the events related to the Hurricane Katrina disaster reveal how different levels of the government responded to a natural disaster. A government's use of interacting arguments revealed a paradox between appearing to accept the risk of foot and mouth disease and dismissing its likelihood on a New Zealand island. The Odwalla case study focuses on the risks associated with their trademark apple juice and how it struggled to renew itself within the health food industry. Finally, the ConAgra Foods Salmonella case study features the complexities of addressing multiple audiences during a major recall event involving pot pies.

“ Cryptosporidium: Unanticipated Risk Factors ,” provides the example of a community organization that experienced a crisis because it did not respond in time to government warnings calling for stronger guidelines for guarding municipal water against Cryptosporidium invasions. At the time of the crisis, Milwaukee had no water monitoring systems in place and the outbreak served as a wake-up call by exposing weaknesses in the public health system and pointing out the bioterrorism risks. Throughout the crisis, community leaders failed to be open, honest, and timely with the information they provided to the public. They failed to be mindful of public concerns expressed prior to the cryptosporidium outbreak. In addition, they did not collaborate or coordinate across agencies, exacerbating the crisis. Milwaukee was unprepared but learned from the event, established a plan should such a crisis occur in the future, and now has one of the safest water treatment systems in the country.

“Hurricane Katrina: Risk Communication in Response to a Natural Disaster,” examines how local leaders failed to create an adequate crisis plan, despite having knowledge of the damage that would occur if a hurricane of Katrina's magnitude struck New Orleans. While local crisis managers had a plan, its usefulness was mitigated by the length and format of the document. Once the hurricane struck, New Orleans crisis managers faced the difficult challenge of collaborating and coordinating resource distribution to affected residents. Another difficulty was getting information to the stakeholders. In the pre-crisis and crisis stages, the media were often ahead of local officials in presenting information to residents. This compromised the local officials' credibility and accountability. Clearly, lack of pre-event planning, the absence of collaboration and coordination, and the need for honest, candid, open, and accountable communication are key reasons why local crisis managers were unable to plan for, manage, and move past what was a devastating event for New Orleans and the surrounding region.

“New Zealand Beef Industry: Risk Communication in Response to a Terrorist Hoax” expands knowledge of risk communication by introducing how hoaxes and terrorist threats complicate our understanding of risk situations. In New Zealand, after receiving a threat claiming a deliberate release of the foot and mouth disease virus on Waiheke Island, the government had to provide intersecting messages demonstrating their capacity to manage the crisis situation. In essence, they claimed to be treating the situation as a potential crisis, while at the same time indicating their belief that the threat was a hoax. Managing crisis uncertainty became the focus for local leaders as they presented messages minimizing the risk as a hoax while acknowledging their treatment of the message as a viable threat to the security of the cattle and the New Zealand economy. The pre-crisis partnerships established between crisis managers and the various stakeholders proved valuable as the agencies worked together to disseminate information and communicate with the local citizens, as well as New Zealand's international partners. While a crisis plan was in place, and had been tested, there were some initial concerns raised by the local public that were ultimately mitigated due to open communication, as well as an attitude of compassion and empathy demonstrated by crisis spokespeople. While the hoax never developed into a crisis, providing messages of self-efficacy about checking for symptoms became an effective way to garner public confidence.

How a company managed to survive the challenge of an E. coli outbreak associated with one of its juice products is the subject of the chapter, “Odwalla: The Long Term Implications of Risk Communication.” Despite the potential risks associated with the continued consumption product, the public stood by Odwalla and its actions during and after the crisis. Odwalla met the needs of the media and remained accessible by holding press conferences, continually updating a website, instituting a hotline, and maintaining open communication with consumers and the press. The company delivered messages of self-efficacy and offered multiple ways for consumers to remain safe. In addition, company leaders apologized publicly, acknowledged the tragedy of the situation, paid medical bills for victims, and acknowledged the impact of the crisis on the image of the company. Following the crisis, Odwalla created an advisory council that ultimately recommended a new pasteurization process, breaking new ground in the industry. The use of some of the best practices enabled Odwalla to embrace a crisis, use it as an opportunity to become an industry leader, initiate industry wide change, and to encourage organizational renewal.

“ConAgra: Audience Complexity in Risk Communication” focuses on the need for organizations to consider multiple audiences when issuing risk messages. In the process of what appeared to be a demonstration of more concerned about their bottom line than with the safety of their customers, ConAgra initially shifted the blame for the outbreak to consumers for not cooking the pot pies properly. In addition, ConAgra made overly-assuring statements to the public about which products were affected by Salmonella (chicken and turkey), and which were not (beef). The assumptions made by ConAgra Foods about the literacy levels, economic status, access to media, proximity to outbreak, and cultural group identities of those receiving the risk messages also complicated their communication with stakeholders. In this case, once Salmonella was linked to ConAgra Foods' pot pies, the company issued a recall of all brands associated with their product. While additional information about the ConAgra Foods recall has yet to emerge, the case points to the need for greater attention by company spokespeople to the best practices of risk communication in order to preserve a positive reputation with the public.

This chapter introduced the case study method as a viable way to study risk communication in crisis situations. Our reasons for choosing the case study approach include its utility for exploring situations from multiple points of view, its usefulness when investigating contemporary events, and its ability to provide enhanced knowledge about complex phenomena. The best practices of risk communication, based on the best practices of crisis communication (Seeger, 2006 ), provide the theoretical framework for the case studies included in this book.

The framework we used for the case studies includes an introduction and overview to the case, a timeline of events, evidence and application of the best practices, and lessons learned. Five cases were introduced: the Milwaukee Cryp-tosporidium crisis, the Hurricane Katrina crisis, the New Zealand foot and mouth disease hoax crisis, the Odwalla juice crisis, and the ConAgra Foods Salmonella crisis. In each case, the best practices of risk communication provide insight into what occurred, or failed to occur, and the implications that followed in each crisis situation.

The five case studies provide insight into the best practices of risk communication. In all of the cases, risk communicators should have acknowledged competing arguments in the construction of risk messages. For example, the Cryptosporid-ium case demonstrates the need to infuse risk communication into policy making. By accepting that current practices would take care of the problem, local leaders allowed the crisis to develop. In the Hurricane Katrina case, the dynamic state of affairs required communicators to continuously review the situation and be proactive in communicating strategies of self-efficacy. Regarding the New Zealand potential foot and mouth disease case, a clear argument exists for why risk communicators must acknowledge and reinforce the unknown when framing messages for the public. Similarly, the collaboration and coordination among agencies with credible information sources helped the New Zealand crisis leaders build support among the various stakeholders affected by the potential contamination. As for Odwalla, the company was forced to acknowledge diverse levels of risk tolerance as the complexity of the situation unfolded. Similarly, a recognition of the need for a culture-centered approach would have enhanced the communication of ConAgra Foods with consumers and demonstrated a commitment to safety over profit. The following five chapters serve as examples of case studies involving risk communication.

Patton, M. Q. (2002). Qualitative research and evaluation methods (3rd ed.). Thousand Oaks, CA: Sage.

Google Scholar  

Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York, NY: Free Press.

Seeger, M. W. (2006). Best practices in crisis communication: An expert panel process. Journal of Applied Communication Research 34 (3), 232–244.

Article   Google Scholar  

Seeger, M. W., Sellnow, T. L., & Ulmer, R. R. (Eds.). (2008). Crisis communication and the public health . Cresskill, NJ: Hampton Press, Inc.

Sellnow, T. L., & Littlefield, R. S. (Eds.). (2005). Lessons learned about protecting America's food supply: Case studies in crisis communication . Fargo, ND: Institute for Regional Studies.

Stake, R. E. (2000). Case studies. In N. K. Denzin & Y. S. Lincoln (Eds.) Handbook of qualitative research (2nd ed.), (pp. 435–454). Thousand Oaks, CA: Sage.

Tuschman, M. L., & Anderson, P. (1997). Managing strategic innovation and change: A collection of readings . New York: Oxford University Press.

Ulmer, R. R., Sellnow, T. L., & Seeger, M. W. (2007). Effective crisis communication: Moving from crisis to opportunity . Thousand Oaks, CA: Sage.

Yin, R. K. (2003). Case study research: Design and methods (3rd ed.). Applied Social Research Methods Series, Vol. 5. Thousand Oaks, CA: Sage.

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(2009). The Case Study Approach. In: Effective Risk Communication. Food Microbiology and Food Safety. Springer, New York, NY. https://doi.org/10.1007/978-0-387-79727-4_4

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FHFA Statistics Measuring Price Effects from Disasters Using Public Data: A Case Study of Hurricane Ian

​​What happens to home values after a disaster? In a  recent working paper , we address this question with a combination of readily available public data sources that track insurance claims and house prices. Focusing on a specific storm, Hurricane Ian, we use leading statistical estimation approaches, difference-in-differences (DiD) and synthetic control methods (SCM), to provide some insights. A key finding is that data limitations create problems for identifying precise price effects. This blogpost discusses the data, methodological choices, and basic findings.

As a preview, we find positive price effects for homes affected by the hurricane. However, our results should not be interpreted as causal, but more correlational. Several factors, including COVID-19 and measurement error, could have confounding influences which make it difficult to measure the effects of Ian’s damage on home prices. Still, the exercise is useful because it demonstrates how one might use public information and why it is useful to continue improving such data releases to support policy analyses.

Defining Damages from Hurricane Ian to Estimate Price Effects

Hurricane Ian struck southwest Florida on September 23, 2022, damaging homes across the state. According to the National Hurricane Center Tropical Cyclone Report, Hurricane Ian “was responsible for over 150 direct and indirect deaths and over $112 billion in damage, making it the costliest hurricane in Florida’s history and the third costliest in the United States history”. 1  Figure 1 shows that path of Ian through Florida. Real estate listings are shown with yellow dots (larger circles indicating counties with more properties for sale) and darker blue shading indicates places that had more claims filed for damages. The figure shows a large concentration of insurance claims in southwest Florida, which also has a large number of real estate listings. We focus on Lee County, which has the darkest shading and is located on the Gulf Coast side of the state where the storm first landed.

Figure 1: Hurricane Ian’s path through Florida in 2022

​We estimate price effects by combining publicly available damages data with real estate listings data for southwest Florida between March 2015 and June 2023. The Federal Emergency Management Agency (FEMA) determines real property damage to properties for claims with limited or no insurance as part of the Individuals and Households Program (IHP). This information is combined with real estate market activity from Multiple Listing Service (MLS) data sourced by CoreLogic.

The key challenge we face is that many damage-related reports rely on publicly available disaster data, which for privacy reasons typically only include coarse descriptions of location. As a result, individual properties must be assigned damages from an aggregate level (e.g., county or ZIP code), thus introducing measurement error. This is a problem because previous research has shown mismeasured “treatment” variables like damages to a home can create problems for estimating causal price effects. 2

After merging IHP and MLS data, treated areas are classified at the county or ZIP code levels and with each home in an area assigned the same treatment status. This occurs regardless of whether the home was damaged. We consider multiple ways to assign treatment at the county and ZIP code levels. While the full set of aggregate treatment definitions are shown in the paper, this blogpost only presents a preferred specification at the county level (with damages aggregated for all homes therein) where treatment indicates county damages exceed the median for other counties.

Preliminary Evidence

Real estate market measures are illustrated in two panels within Figure 2. While not shown here, the trends are similar between Lee County (the focus area) and the entire state of Florida. The left panel presents median list (solid navy line) and close prices (solid maroon line) for each month during our sample. Both price trends are noisy and lack a sharp change when the storm hit, which is denoted by the dashed vertical black line. The right panel shows a reduction in the number of new listings, suggesting that prices could have been propped up by a decrease in home supply. Alternatively, homes that sold after the storm could be disproportionately better quality and command a premium. We are agnostic about the correct channel at work here: more careful analysis is needed to identify the mechanism(s) operating to affect prices. Finally, a potential COVID-19 effect starts after 2020 with prices increasing more quickly in the left panel and greater listing volatility in the right panel.

The lack of a clear and sustained impact on home prices suggests a more rigorous empirical analysis is needed for prices. We emphasize that we do not claim to establish a causal relationship nor that a price adjustment mechanism is identified correctly. We simply aim to estimate any aggregate price effect while using public data and documenting the challenges even when using leading statistical approaches.

Figure 2:​ Real estate market activity in Lee County, Florida

Difference-in-Differences Method for Price Effects

The most common approach used in the disaster literature for estimating price effects is a difference-in-differences (DiD) or event study approach. 3  In generalized terms, this means comparing price trends in affected (“treated”) areas with price trends in unaffected (“control”) areas.

Figure 3: Dynamic DiD for Lee County where Hurricane Ian made landfall

Figure 3 conveys the DiD results for a dynamic treatment (“event study”). The horizontal axis represents time relative to Ian, with the vertical dashed line indicating Ian’s landfall. The vertical axis shows an estimated parameter that is the difference in price trends between affected and unaffected areas at each time, with the shaded area representing the 95% confidence interval of the parameter. Higher prices are correlated with damages post-Ian. Where is this shown? By the price trend increasing above the zero line after the dashed vertical line.

However, the key assumption underlying DiD is the parallel trends assumption, which says that absent Hurricane Ian the areas affected and not affected would have had similar price trends. To test whether this assumption holds, researchers commonly conduct “pre-trends” tests, checking whether before Ian affected and not affected areas had similar price trends. In Figure 3, this corresponds to the difference in price trends being close to zero prior to the dashed line. As the figure shows, there is evidence that parallel trends does appear to be violated about 20 to 25 months prior to Ian’s arrival. What happened at that time? That was the early period of COVID. This is problematic statistically because the homes that saw prices increase during the early stages of the pandemic were the same homes that were damaged by Ian, making identification of the true Ian price effects challenging.

Synthetic Control Method for Price Effects

Another approach one can take is to construct a suitable control using the synthetic control method (SCM) at the aggregated level. The SCM determines an optimal weighted average of untreated counties (i.e. its synthetic control) to match the pre-Ian price trends of Lee County. Figure 4 below illustrates Lee County and its synthetic control. The figure suggests a time-varying price premium of at least five percent that peaks in the low double digits a few months after Ian, similar to the DiD finding. However, despite the apparent good fit in the figure with the blue and red lines appearing to be on top of each other until the dashed vertical line, more sensitive goodness of fit tests indicate these estimates lack statistical significance.

Figure 4: Synthetic control for Lee County

In summary, using publicly available data it may be difficult to estimate price effects even when employing leading empirical techniques. While we record some evidence for positive price effects for Ian, it is possible that declines across many markets but less so in the target county. Either way, these results should be viewed with some skepticism because of an inability to establishing actual property-level damages when using public data. Given the local nature of damages, when one is unable to precisely identify which units are treated or not, finding a suitable control group is extremely difficult. For those interested in working with such data, we offer several suggestions in the paper and encourage you to read further.

1  See  https://www.nhc.noaa.gov/data/tcr/AL092022_Ian.pdf .

2  For recent academic research on this type of problem in a difference-in-differences setting, see Denteh Kedagni (2022) and Negi Negi (2022), for example. The problem is the mismeasurement of the treatment variable, often called a “misclassification” problem.

3  See another one of FHFA’s working papers, for a recent review of the applied disaster literature: Justin Contat, Carrie Hopkins, Luis Mejia, Matthew Suandi. 2024. “When Climate Meets Real Estate: A Survey of the Literature." Real Estate Economics.  https://doi.org/10.1111/1540-6229.12489 .

By:Justin Contat

Senior Economist

Division of Research and Statistics

By:Will Doerner

Supervisory Economist

By:Robert Renner

Senior Geographer

By:Malcolm Rogers

Tagged: FHFA Stats Blog; Source: FHFA; Natural Disasters; Natural Disaster Price Effects; hurricane; real estate valuation

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Purposive sampling: complex or simple? Research case examples

Steve campbell.

Professor of Clinical Redesign, Nursing, Associate Head Research, School of Nursing, University of Tasmania, College of Health and Medicine, Australia

Melanie Greenwood

Associate Professor, Director Post Graduate Courses, School of Nursing, University of Tasmania, College of Health and Medicine, Australia

Sarah Prior

Lecturer, Tasmanian School of Medicine, University of Tasmania, College of Health and Medicine, Australia

Toniele Shearer

Lecturer, PhD Candidate, School of Nursing, University of Tasmania, College of Health and Medicine, Australia

Kerrie Walkem

Sarah young.

Professor of Health Care Improvement, School of Nursing, University of Tasmania, College of Health and Medicine, School of Health Science, Australia

Danielle Bywaters

PhD Candidate, School of Nursing, University of Tasmania, College of Health and Medicine, Australia

Purposive sampling has a long developmental history and there are as many views that it is simple and straightforward as there are about its complexity. The reason for purposive sampling is the better matching of the sample to the aims and objectives of the research, thus improving the rigour of the study and trustworthiness of the data and results. Four aspects to this concept have previously been described: credibility, transferability, dependability and confirmability.

The aim of this paper is to outline the nature and intent of purposive sampling, presenting three different case studies as examples of its application in different contexts.

Presenting individual case studies has highlighted how purposive sampling can be integrated into varying contexts dependent on study design. The sampling strategies clearly situate each study in terms of trustworthiness for data collection and analysis. The selected approach to purposive sampling used in each case aligns to the research methodology, aims and objectives, thus addressing each of the aspects of rigour.

Conclusions

Making explicit the approach used for participant sampling provides improved methodological rigour as judged by the four aspects of trustworthiness. The cases presented provide a guide for novice researchers of how rigour may be addressed in qualitative research.

Introduction

Novice nurse researchers tend to see purposive sampling as either simple or too difficult ( Tuckett, 2004 ) and may therefore default to using a convenience sample for the wrong reasons. Attempting to ensure that nursing research has the right sample is crucial to good processes. This paper came out of the ongoing work of a research group, made up largely of nurses, at the University of Tasmania. The group ranged in experience from PhD students and early career researchers to experienced full professors and the research ranged similarly from PhD studies to funded research. A number of the group were using purposive sampling techniques under different circumstances and with different challenges. The lessons learnt by the individuals and by the group as a whole are interweaved into this paper and the case studies using purposive sampling are used to exemplify the different uses of purposive sampling, and the way in which each context has been handled.

Purposive sampling

In terms of sampling, the strategy for participant selection should be integrated into the overall logic of any study ( Punch, 2004 ) and the rationale for sample selection needs to be aligned from an ontological, epistemological and axiological perspective with the overarching aims of the study. In a qualitative study, a relatively small and purposively selected sample may be employed ( Miles and Huberman, 1994 ), with the aim of increasing the depth (as opposed to breadth) of understanding ( Palinkas et al., 2015 ). Purposive sampling is ‘used to select respondents that are most likely to yield appropriate and useful information’ ( Kelly, 2010 : 317) and is a way of identifying and selecting cases that will use limited research resources effectively ( Palinkas et al., 2015 ).

Purposive sampling strategies move away from any random form of sampling and are strategies to make sure that specific kinds of cases of those that could possibly be included are part of the final sample in the research study. The reasons for adopting a purposive strategy are based on the assumption that, given the aims and objectives of the study, specific kinds of people may hold different and important views about the ideas and issues at question and therefore need to be included in the sample ( Mason, 2002 ; Robinson, 2014 ; Trost, 1986 ).

With respect to research involving multiple cases, the most popular forms of purposive sampling are stratified, cell, quota and theoretical sampling. The different nature of these approaches is described in brief below.

Stratified sampling selects specific kinds or groups of participants that need to be part of the final sample. The sample is then stratified by the characteristic of the participant or group, with a specific number allocated to each stratification. (The number allocated to each category is also clearly important, particularly when allocation to separate groups is different.) Categories might be age, size of family, IQ, etc. However, and importantly, there needs to be a clear reason linked to the aims and objectives of the study to show why each group is different. Moreover, in terms of interviews, they must have something to add to the study.

Cell sampling is similar to stratified sampling but differs in that the categories for stratification are discrete, and in cell sampling they can overlap like a Venn diagram ( Miles and Huberman, 1994 ). For example, in a study of children with chronic disease, one cell might be obese children and the other might be children with diabetes and the overlap will be obese children with diabetes.

In quota sampling, there is greater flexibility – rather than fixed numbers of cases being required with particular criteria, quota sampling specifies categories and the minimum number needed for each one ( Mason, 2002 ). As the study proceeds, numbers in each area are monitored for fulfilment of the quota. For example, in a study, again of children with chronic illness, there might be quota for kinds of chronic illness and for kinds of family. The research team would specify a minimum for each of the quota. (A minimum of five children each with diabetes, leukaemia, arthritis, etc., and for the kind of family, 10 from a nuclear family, 15 from a reconstituted family, etc.) The use of minimum quota makes sure that key participants are part of the final sample. It is argued that this approach is also more flexible in shaping the final sample and easier, in recruitment terms, compared with stratified and cell sampling ( Robinson, 2014 ).

Theoretical sampling is different by being part of the collection and analysis of the data, following provisional sampling and analysis of some data ( Coyne, 1997 ; Robinson, 2014 ; Strauss, 1987 ). Theoretical sampling originally came from Grounded Theory but is applied to other methods as well ( Mason, 2002 ). The process involves either identifying cases from new groups, which might amount to being a comparison or a contrast with other groups, or reshaping the sample into a new set of criteria as a result of the analysis, and in so doing replacing the original sampling strategy chosen a-priori ( Draucker et al., 2007 ; Robinson, 2014 ).

This paper now introduces three different research studies in which the processes and challenges of purposive sampling are taken up in each instance.

Research study 1: Co-led redesign of stroke services in North West Tasmania

This example relates to the redesign of stroke services and is reported at the point when all patient interviews have been collected. Co-led redesign initiatives in healthcare service provision rely on experience-based feedback from patients and their families as well as sourcing information from healthcare staff and data collected specifically for the purpose of a service redesign (Prior and Campbell, 2018). The stroke service co-led redesign project utilised a purposive sampling method developed by Reed et al. (1996) based on stakeholder sampling ( Ovretveit, 1998 ), termed the Matrix sampling method. Matrix sampling empowers the stakeholders, allowing them to select categories of participants who they determine to be representative of the service users, essentially creating a trustworthy sample. For example, the stroke patient interviews consisted of 50% of patients over age 65 and 50% of those aged 65 or under. The stakeholder group identified that these two groups of patients require differing types of acute and rehabilitative stroke care in some instances and placed a high level of importance on being able to achieve the levels of care required for different age groups. The stakeholders included senior medical and nursing management, medical consultants, nursing unit managers, the director of allied health and the research team. The research team is then able to perform the interviews with selected patients on behalf of the stakeholders and report the findings to the group via thematic analysis.

Matrix sampling strengthens qualitative research by providing a structured and purposive method for nominating participants. It creates maximum variability based on stakeholder knowledge of the population and the intended research outcomes. Previously utilised in healthcare redesign research in the United Kingdom ( Campbell et al., 2004 ) as part of a patient journey approach, Matrix sampling is a cost-effective and time-efficient method allowing the stakeholders a level of control over the selected sample. This method of sampling was selected to capture a relevant participant group, representing stroke patients in North West Tasmania. A number of clinical and demographic variables were considered when determining the appropriate stroke patient participants, influenced by the local population and a quantitative data analysis determining the numbers and types of stroke patients admitted. Exclusion criteria were set prior to the sampling process; these included mini strokes (transient ischaemic attacks), patients who were living in a nursing home at the time of their stroke and deceased patients. As with other purposive sampling methods, Matrix sampling utilises the specific characteristic of stroke to provide a potential pool of participants. Other characteristics of importance noted during the participant selection phase for this project included the number of risk factors associated with each stroke patient, mode of arrival to the hospital, whether the patient was transferred into or out of a specific hospital and the type of stroke for which the patient was admitted (haemorrhagic or ischaemic). These specific criteria, determined by the stakeholders, allowed the research team to find candidates for the interviews to represent the patient group who could provide the most appropriate input into stroke service redesign for this particular population area.

Although this sampling method fulfils the needs of the stakeholders by allowing them to make the decisions over the sample population, there are also some weaknesses or disadvantages to the Matrix sampling method. If it is not possible to recruit participants to a selected criterion, gaps appear in the data. In the project it was noted that one particular criterion, patients who were transferred between hospitals, was more difficult to ‘fill’ due to smaller numbers of admitted patients fitting this description, purely due to the population being sampled. The dependability of the data, then, can be difficult to control; however, to overcome this issue, discussions with the stakeholder group suggested other recruitment methods, such as clinicians identifying patients and requesting consent. If these patients were unable to be identified, the group was satisfied that all was done to ensure the stakeholder view was utilised to the best abilities of the research team and the results delivered still reflected a representative population.

The Matrix sampling method is an easily transferable approach for qualitative research, which allows the input of the stakeholder(s) to determine the output of the research through the provision of local information and knowledge. Matrix sampling is a form of stratified sampling, but it is also quota driven. It is a form of stakeholder sampling where the views of the stakeholders are paramount, as they have to be reassured of the adequacy of the sampling so they regard the evidence as adequate and credible.

Research study 2: Child and family health nurses and safety and wellbeing of young children

This example is from a PhD study (Young, 2020 [unpublished thesis]) focusing on the response of child and family health (CFH) nurses to concerns around the safety and wellbeing of young children aged from birth to 5 years within the family, using Interpretive Description (ID) as the methodological approach. The setting in which the study is situated is that of a CFH nursing service provided by an Australian state-wide health department.

ID methodology, developed by Thorne et al. (1997) , is a way of generating increased understanding of clinical phenomena that are complex and experiential. ID studies generate an ID of the themes and patterns captured within subjective perceptions around a phenomena of clinical interest ( Thorne et al., 2004 ) and produce practice-relevant knowledge that can be immediately applied in the clinical context ( Thorne, 2016 ; Hunt, 2009 ). When using ID methodology, researchers identify who should be included in the study, so the eventual findings allow better understanding of the phenomenon of interest ( Hunt, 2009 ; Thorne, 2016 ). Purposive sampling is an accepted and often used initial sampling strategy in ID methodology as it allows settings and people to be recruited based on their expected contribution to the study ( Schensul, 2011 ) and by virtue of some angle of the phenomenon that they might help us better understand ( Hunt, 2009 ; Thorne, 2016 ). Participants are those who are most likely to have in-depth knowledge and experience of the phenomenon being studied. With this in mind, the inclusion criteria developed for this study were that participants must be nurses currently employed as CFH nurses with a minimum of 2 years recent (within the last 5 years) experience working in this specialist area of nursing. This was to help to ensure the opinions obtained were those of experienced CFH nurses with exposure to relevant practice experiences in a range of situations. Excluded from the study were those nurses who did not have at least 2 years recent post-graduate experience as a CFH nurse.

In developing the sample subset, an awareness was maintained of how this might either privilege or silence particular angles or perspectives and thus impact the eventual findings of the study and its credibility ( Thorne, 2016 ). To enhance credibility, care was taken to clearly, transparently and explicitly describe the logic used in selecting the sample subset ( Robinson, 2014 ; Thorne, 2016 ). Furthermore, a critical awareness of the nature of the selected sample and how this might impact on any findings generated was maintained throughout the study to help ensure claims beyond the sample subset were not made ( Robinson, 2014 ; Thorne, 2016 ).

Transferability was enhanced by the way in which study participants were clearly identified in terms of inclusion and exclusion criteria and demographic information. This helps others to determine whether the findings are applicable to other situations and population groups ( Shenton, 2004 ; Amankwaa, 2016 ). A sample that is fully contextualised helps prevent unwarranted generalisation ( Robinson, 2014 ). Dependability was enhanced by the description of participants using clear inclusion and exclusion criteria ( Shenton, 2014 ). In addition, a well-accepted sampling strategy appropriate to an ID study was used ( Thorne, 2016 ). Confirmability was enhanced by the provision of a rationale for the choice of inclusion and exclusion criteria, so that the integrity of the process could be determined by others ( Shenton, 2014 ).

Research study 3: How can mental wellbeing for new mothers be achieved?

This example is from a PhD study (Young, 2020 [unpublished thesis]) about women's experiences after childbirth, where recruitment is about to commence. This research aims to determine what influences mothers’ mental wellbeing in the year after the birth of a first baby and asks, ‘how can mental wellbeing for new mothers be achieved?’ Narrative inquiry involving three or four in-depth interviews with ∼10 women will be used to answer this question. The interviews will be conducted longitudinally over a period of 9–12 months and will aim to capture a rich, deep picture of the first year after childbirth. It is hoped that the major influences impacting mental wellbeing will be identified.

To determine which women to include in this study, purposive sampling will be employed. Specific inclusion and exclusion criteria will be indicated, making the inclusion of participants in this study non-probabilistic, and indeed purposive, in nature. Women will be recruited for involvement from the antenatal clinic at the local public hospital by way of response to a posted flyer. Although there is an element of convenience sampling involved in this process, the very specific nature of the criteria for involvement make this design purposive. Inclusion criteria will include considerations such as first-time mothers only, singleton pregnancy, maternal age over 18 years and gestational due date within a specified timeframe to facilitate the longitudinal interview schedule. Exclusion criteria will include anyone who has had a previous mental health issue or a pregnancy-related health complication (e.g., gestational diabetes, placenta praevia, known foetal issues, etc.).

The trustworthiness and rigour of the data will be enhanced by the purposive sampling design. In terms of credibility, this method of sampling supports the likelihood that ‘member checking’ may occur, which will increase the credibility of the findings ( Guba, 1981 ). Because women will self-select for participation in the study, this degree of interest and investment increases the likelihood of their willingness to remain involved for the duration of the research.

Both the transferability and dependability of the data will be enhanced by the specific nature of the inclusion and exclusion criteria laid out for this research. Transferability will be affected because these detailed criteria will allow readers to develop a clear picture of participants involved. Guba notes the importance of ‘full description of all the contextual factors impinging on the inquiry’ (1981: 70) and the participants themselves can be considered a ‘contextual factor’ in the research. In a similar vein, the detailed nature of the criteria will form part of the audit trail that contributes to dependability in a study ( Baillie, 2015 ; Guba, 1981 ). A risk to trustworthiness in interview-based research is the role of the interviewer themselves and the influence of their own beliefs and perspectives ( Haga et al., 2012 ; Shenton, 2004 ).

When determining the sample size for a study of this nature, several factors are considered. Morse notes that the scope of the study, the nature of the topic, the quality of the data, the study design and the use of shadowed data all require consideration (2000). Relatedly, Morse (2000 : 4) emphasises that ‘the quality of data and the number of interviews per participant determine the amount of useable data obtained. There is an inverse relationship between the amount of useable data obtained from each participant and the number of participants’. This is an important consideration with a longitudinal study where, for example, four interviews with 10 participants would amass data very quickly. With these considerations in mind, a sample size of 10 participants will be the aim.

Implications for research in nursing and health

The sample, particularly for qualitative research, is often not analysed by the nursing reader of practice papers ( Gelling et al., 2014 ). The sample itself, the context and the process are all important issues to consider when reading a paper and considering its impact, particularly when making potential policy changes. Therefore, novice nursing researchers need to ensure the sampling process fits the needs of the study and be clear about the actual process that ensued. For instance: does the sample in the nursing research strategy match the patients who are being considered? The context of sampling in nursing research, as in all research, is a key issue.

Each of these research studies has considered purposive sampling in very different contexts. However, all of them, although purposive, have a convenience element to them given the voluntary nature of all consent processes, where the researcher is at the mercy of the pool of potential participants. However, the voluntary nature of the participation means the researchers can characterise them as fitting not only the inclusion criteria of the study, but also being interested in the topic and motivated to take part out of this interest and their potential to contribute to development of knowledge in this arena.

The Co-Led Stroke Redesign sampling process was about interviewing a representative sample that was persuasive enough to inform change of practice in the stakeholders. The CFH nurse study is the simplest of the designs cited in this paper and has power in this simplicity. However, the analysis of the data is already showing important differences in the nature of the sample. The identification of the right mothers to gain their views of motherhood shows the lengths researchers can go to when considering complex forms of purposive sampling, only to discard them for a simpler process. However, this process of considering options is important in developing high-quality research designs rather than settling for standard approaches.

A continued narrative for all of the research studies that have been exemplified in this paper was whether being purposive in some more complex manner was actually necessary. The only clarity was that all studies were purposive with the intent of recruiting participants who could inform the researchers' aims and objectives. The argument was that the reader of the research would be able to make the judgements about the relevance of the research, if the nature of the sample was transparent. This is another example of the context of research being all important in qualitative research. In combination, the case studies highlight important elements researchers should consider when using purposive sampling techniques to address the four elements of trustworthiness for the research design.

Key points for policy, practice and/or research

• Novice nurse researchers need to ensure purposive sampling is used where appropriate and not default to a convenience sample.
• The context of the data collection is an important consideration in purposive sampling for trustworthiness of data in nursing research.
• Nurse researchers adopt theoretical positions that are reflected in purposive sampling techniques and assist policy makers to understand the relevance of the research.
• The voluntary nature of nursing research supports the purposive sampling approach, it does not mitigate against it.

Acknowledgements

The authors thank the Patient Involvement Group, School of Health Sciences, University of Tasmania.

Steve Campbell joined the University of Tasmania in January 2013 as the Head of Nursing and Midwifery and then Head of the School of Health Sciences until 2016. With the reestablishment of the School of Nursing in 2019, Steve is now the Research Director/Associate Head of Research for the school and Professor of Clinical Redesign, Nursing.

Melanie Greenwood is an Associate Professor within the School of Nursing at the University of Tasmania and leads the school’s extensive postgraduate framework. She has over 20 years’ critical care nursing expertise in researching into recognition and response to deteriorating patients with a quality and safety in healthcare focus.

Sarah Prior is an academic with the School of Medicine, coordinating the postgraduate, workplace integrated healthcare quality and safety courses. Sarah’s research interests include patient involvement, co-design, rural health service delivery and health service improvement.

Toniele Shearer has worked as a critical care nurse in Australia for around 17 years in the Intensive Care/Coronary Care setting. Toniele teaches in both postgraduate and undergraduate programs offered in the School of Nursing at the University of Tasmania. She is also a PhD candidate.

Kerrie Walkem is a lecturer in the School of Nursing. She coordinates and teaches the postgraduate child and family health nursing stream, as well as other related nursing units across the postgraduate and undergraduate areas. She is also a PhD candidate.

Sarah Young is a PhD candidate with the University of Tasmania’s School of Nursing. Her PhD thesis aims to contribute to the development of a picture of women's experiences after having their first baby.

Danielle Bywaters is a nursing lecturer in the School of Nursing and a photographer who is currently a PhD Candidate. Her PhD study is interdisciplinary and uses a visual method to explore communication in nursing.

Kim Walker is a nurse and a former Professor of Healthcare Improvement, a position he held between the University of Tasmania (nursing discipline) and St Vincent’s Private hospital in Sydney.

Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article..

Ethical approval: This paper is a methodological paper, therefore ethics approval was not needed.

Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs: Steve Campbell https://orcid.org/0000-0003-4830-8488 Melanie Greenwood https://orcid.org/0000-0001-5840-0750 Sarah Prior

• Amankwaa L. (2016) Creating protocols for trustworthiness in qualitative research . Journal of Cultural Diversity 23 ( 3 ): 121–125. [ PubMed ] [ Google Scholar ]
• Baillie L. (2015) Promoting and evaluating scientific rigour in qualitative research . Nursing Standard 29 ( 46 ): 36–42. [ PubMed ] [ Google Scholar ]
• Campbell S, Watson B, Gibson A, et al. (2004) Comprehensive service and practice development: City Hospitals Sunderland's experience of patient journeys . Practice Development in Health Care 3 ( 1 ): 15–26. [ Google Scholar ]
• Coyne IT. (1997) Sampling in qualitative research. purposeful and theoretical sampling; merging or clear boundaries? . Journal of Advanced Nursing 26 ( 3 ): 623–630. [ PubMed ] [ Google Scholar ]
• Draucker CB, Martsolf DS, Ross R, et al. (2007) Theoretical sampling and category development in Grounded Theory . Qualitative Health Research 17 ( 8 ): 1137–1148. [ PubMed ] [ Google Scholar ]
• Gelling L. (2014) Qualitative research . Nursing Standard 29 ( 30 ): 43–47. [ PubMed ] [ Google Scholar ]
• Guba EG. (1981) Criteria for assessing the trustworthiness of naturalistic inquiries . Educational Technology Research and Development 29 ( 2 ): 75–91. [ Google Scholar ]
• Haga S, Lynne A, Slinning K, et al. (2012) A qualitative study of depressive symptoms and well-being among first-time mothers . Scandinavian Journal of Caring Sciences 26 ( 3 ): 458–466. [ PubMed ] [ Google Scholar ]
• Hunt M. (2009) Strengths and challenges in the use of interpretive description: Reflections arising from a study of the moral experience of health professionals in humanitarian work . Qualitative Health Research 19 ( 9 ): 1284–1292. [ PubMed ] [ Google Scholar ]
• Kelly S. (2010) Qualitative interviewing techniques and styles . In: Bourgeault I, Dingwall R, de Vries R. (eds) The Sage Handbook of Qualitative Methods in Health Research , Thousand Oaks: Sage Publications. [ Google Scholar ]
• Miles M, Huberman A. (1994) An expanded sourcebook: Qualitative data analysis , 2nd ed. Thousand Oaks: Sage Publications. [ Google Scholar ]
• Mason J. (2002) Qualitative researching , 2nd ed. London: Sage. [ Google Scholar ]
• Morse J. (2000) Editorial: Determining sample size . Qualitative Health Research 10 ( 1 ): 3–5. [ Google Scholar ]
• Ovretveit J. (1998) Evaluating Health Interventions , Buckingham: Open University. [ Google Scholar ]
• Palinkas LA, Horwitz SM, Green CA, et al. (2015) Purposeful sampling for qualitative data collection and analysis in mixed method implementation research . Administration and Policy in Mental Health and Mental Health Services Research 42 ( 5 ): 533–544. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Prior SJ and Campbell S (2018) Patient and family involvement: a discussion of co-led redesign of healthcare services. Journal of Participatory Medicine 10(1): e5. [ PMC free article ] [ PubMed ]
• Punch K. (2004) Developing Effective Research Proposals , London: Sage Publications. [ Google Scholar ]
• Reed J, Procter S, Murray S. (1996) A sampling strategy for qualitative research . Nursing Research 3 ( 4 ): 52–68. [ PubMed ] [ Google Scholar ]
• Robinson OC. (2014) Sampling in interview-based qualitative research: A theoretical and practical guide . Qualitative Research in Psychology 11 ( 1 ): 25–41. [ Google Scholar ]
• Schensul J (2011) Methodology, methods and tools in qualitative research in Lapan S, Quartaroli M and Riemer F (eds) Qualitative Research. Hoboken: Wiley, 69–103.
• Shenton A (2004) Strategies for ensuring trustworthiness in qualitative research projects. Education for Information, no. 22, pp. 63–75.
• Strauss AL. (1987) Qualitative analysis for social scientists , New York: Cambridge University Press. [ Google Scholar ]
• Thorne S. (2016) Interpretive description , 2nd ed. Walnut Creek: Left Coast Press. [ Google Scholar ]
• Thorne S, Kirkham SR, O'Flynn-Magee K. (2004) The analytic challenge in interpretive description . International Journal of Qualitative Methods 3 ( 1 ): 1–11. [ Google Scholar ]
• Thorne S, Reimer Kirkha S, MacDonald-Emes J. (1997) Interpretive Description: A noncategorical qualitative alternative for developing nursing knowledge . Research in Nursing and Health 20 ( 2 ): 167–177. [ PubMed ] [ Google Scholar ]
• Trost JA. (1986) Statistically non-representative stratified sampling: A sampling technique for qualitative studies . Qualitative Sociology 9 ( 1 ): 54–57. [ Google Scholar ]
• Tuckett A. (2004) Qualitative research sampling: The very real complexities . Nurse Researcher 12 ( 1 ): 47–61. [ PubMed ] [ Google Scholar ]
• Young SM (2020) An examination of the influences affecting maternal mental wellbeing after first-time childbirth in Tasmania. Unpublished Doctoral Thesis. University of Tasmania.

What executives are saying about the future of hybrid work

In the postpandemic future of work, nine out of ten organizations will be combining remote and on-site working, according to a new McKinsey survey of 100 executives across industries and geographies. 1 From December 2020 through January 2021, McKinsey surveyed and analyzed responses from 100 respondents at the C-suite, vice-president, and director level, evenly split among organizations based in Asia, Europe, Latin America, and the United States, and among a variety of industries. Company revenues ranged, on average, from $5.1 billion to $11.0 billion per year. The survey confirms that productivity and customer satisfaction have increased during the pandemic.

About the authors

A McKinsey Live event on ‘Getting hybrid work right: What employees are saying’

The following charts, drawn from our survey, offer insights for executives who are sorting out the particulars of the hybrid approach. A notable finding is that organizations with the biggest productivity increases during the pandemic have supported and encouraged “small moments of engagement” among their employees, moments in which coaching, mentorship, idea sharing, and coworking take place. These organizations are preparing for hybrid working by training managers for remote leadership, by reimagining processes, and by rethinking how to help employees thrive in their roles.

The future will be more hybrid. Prior to the COVID-19 crisis, the majority of organizations required employees to spend most of their time on-site. But as the pandemic eases, executives say that the hybrid model—in which employees work both remotely and in the office—will become far more common. The majority of executives expect that (for all roles that aren’t essential to perform on-site) employees will be on-site between 21 and 80 percent of the time, or one to four days per week.

Future vision. Although nine out of ten executives envision a hybrid model going forward, most have at best a high-level plan for how to carry it out—and nearly a third of them say that their organizations lack alignment on a high-level vision among the top team. Although another third of organizations have a more detailed vision in place, only one in ten organizations have begun communicating and piloting that vision.

Productive nonetheless. The survey also confirms that during the pandemic most organizations have seen rises in individual and team productivity and employee engagement, and, perhaps as a result of this increased focus and energy, a rise in the satisfaction of their customers as well.

But not every organization has experienced the same improvement. Take individual productivity. Some 58 percent of executives report improvements in individual productivity, but an additional third say that productivity has not changed. Lagging companies, which make up 10 percent of respondents, relate that individual productivity has declined during the pandemic. It’s important to note the high correlation between individual and team productivity: C-suite executives who say that individual productivity has improved are five times more likely to report that team productivity has risen too.

Making the small connections count. Why have some companies enjoyed higher productivity during the pandemic? According to our survey, they’re the ones supporting small connections between colleagues—opportunities to discuss projects, share ideas, network, mentor, and coach, for example. Two-thirds of productivity leaders report that these kinds of “microtransactions” have increased, compared with just 9 percent of productivity laggards. As executives look to sustain pandemic-style productivity gains with a hybrid model, they will need to design and develop the right spaces for these small interactions to take place.

Managing differently. Supporting small moments of connection requires subtle shifts in how managers work. Nearly all executives surveyed recognize that managing remotely differs from when all employees are on-site, but other subtleties may not be as apparent. Nuances can be seen in the more than half of productivity leaders that have trained their managers on how to lead teams more effectively. Only a third of productivity laggards have done the same. The emphasis on small connections suggests that organizations could better support managers  by, among other things, educating them about the positive and negative impact they have on the people who report to them, and by training managers on soft skills , such as providing and receiving feedback. Organizations can also explore novel ways to address the loss of empathy  that often accompanies gains in authority.

Experiment and iterate. Across organizations, executives already recognize the need to redesign processes to better support a remote workforce—with the majority having at least identified the processes that will require rethinking. But productivity leaders are more likely to continually iterate and tweak their processes as the context shifts. As organizations look to codify the hybrid model, there is evidence that the test-and-learn approach to process redesign will be an important enabler.

Reimagine hiring. Hiring is among the most crucial processes to reconsider in the hybrid world. Should organizations continue to hire within specific geographies, or should they open up their talent aperture beyond traditional recruiting locations, for instance? Should they conduct more remote interviews? During the pandemic, nearly two-thirds of organizations have moved in-person recruiting events and activities to remote settings, but only one in three have reimagined hiring from the ground up. Forty percent of productivity leaders, by contrast, have holistically redesigned their entire hiring process.

Rethink talent allocation. During the pandemic, nearly two-thirds of organizations have reassessed the number of people in each role and in each function in the company. But productivity leaders are more likely than middle performers and laggards to fall into this category. A select few leading companies have taken it even further and have gone beyond reassessing to actually implementing changes. As organizations redesign their hybrid future, matching the workforce with the right priorities could help spur productivity improvements.

Andrea Alexander is an associate partner in McKinsey’s Houston office, where Mihir Mysore is a partner; Rich Cracknell is a solution leader in the Silicon Valley office; Aaron De Smet is a senior partner in the New Jersey office; and Meredith Langstaff is an associate partner in the Washington, DC, office, where Dan Ravid is a research and knowledge fellow.

This article was edited by Lang Davison, an executive editor in the Seattle office.

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