collective case study survey

• DOI: 10.4018/978-1-7998-8848-2.ch012
• Corpus ID: 244148121

Collective Case Study

• Sydnie Schoepf , Nicole Klimow
• Published in Conceptual Analyses of… 2022
• Education, Sociology
• Conceptual Analyses of Curriculum Inquiry Methodologies

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Collective Case Study: Making Qualitative Data More Impactful

To begin, the researcher must first understand case study design. Case study is defined as an examination of a confined or bounded system or unit, in context, involving both an in-depth examination and analysis in order to examine, reveal, or better understand a phenomenon, or a social or cultural issue (Creswell, 2013; Merriam & Tisdell, 2016; Putney, 2010; Stake, 1995; Yin, 2006). A case typically consists of an examination of one individual, organization, process, event, role, (sub)culture, encounter, period of time, or program (Miles, et al., 2020; Yin, 2006). Case studies can be either instrumental or intrinsic, and determining which type the researcher intends to use is an important step early on in the study design process. Instrumental cases are referred to when the case being examined is considered instrumental to comprehending not only that specific case, but something larger than itself (Putney, 2010; Stake, 1995). Intrinsic cases, in comparison, are used when there is an intrinsic interest in a particular case, not to learn about something that allows for generalization, but rather because of what the particular case has to offer in and of itself (Putney, 2010; Stake, 1995). Regardless of whether the case study is instrumental or intrinsic, the examination of a single case, bound in time and context, is the focus for this particular study design. There are significantly more elements to consider, in terms of design, when considering case study. For more information about case study design, the researcher may consult both Putney (2010) and Yin (2018).

Key Terms in this Chapter

Multiple Case Study : Explores a multiple bounded system involving multiple sources of information or relies on several instrumental, bounded cases to provide more extensive descriptions and explanations of a phenomenon or issue using varied data collection strategies to understand case similarities and differences to generalize conclusions over several units of analyses.

Case : A single bounded system or unit that is the investigational focus for a case study.

Data Management : The systematic organization of data into sets to assist meaning-making and prepare for analysis.

Data Collection : The process of gathering information in a systematic, organized, unbiased way.

Collective Case Study : Explores individual cases to provide detail and explanation regarding a situation, phenomenon, or experience where individual studies provides information into the “why” or “how,” and provides elaborative data through comparing cases cross-wise that allows for a more expansive understanding of the issue.

Case Study : An examination of a confined or bounded system or unit, in context, involving both an in-depth examination and analysis to examine, reveal, or better understand a phenomenon, or a social or cultural issue.

Results : The researcher’s systematic interpretation of the data in relation to the research question(s), making sense of the findings and providing contextual answers to the posited questions.

Findings : The identification of patterns and systematic recording of what the data sets display, prior to the researcher interpreting to determine results.

Data Analysis : The process of breaking down units into individual pieces for comparative and contrasting analysis, seeking intersection between pieces to identify patterns, and examining outliers to best understand how the pieces work in aggregate to explain the whole.

Complete Chapter List

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

Qualitative Research Designs

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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Doctoral Dissertations and Projects

A qualitative collective case study investigating the motivational factors of elementary-aged students in physical education class and leisurely physical activity.

Jesse Tanner Beam

School of Education

Doctor of Education (EdD)

Judy Sandlin

Childhood Obesity, Motivation, Physical Education, Positive Reinforcement

Disciplines

Education | Elementary Education and Teaching | Health and Physical Education

Recommended Citation

Beam, Jesse Tanner, "A Qualitative Collective Case Study Investigating the Motivational Factors of Elementary-Aged Students in Physical Education Class and Leisurely Physical Activity" (2015). Doctoral Dissertations and Projects . 1011. https://digitalcommons.liberty.edu/doctoral/1011

The purpose of this qualitative collective case study was to increase understanding of the influential motivating factors of elementary-aged students in physical education (PE) that foster positive reinforcement to manage student engagement. The study was conducted at three different elementary schools in a school district in the southeastern United States. To determine the factors that influence the students' motivation in PE and leisurely physical activity, a set of data collection sources was used. Student interviews, caregiver surveys, and teacher journal entries were utilized to collect purposeful data that identified the specific factors associated with participation. Data was then transcribed and coded to identify reoccurring themes across the cases. The study found multiple factors associated with PE engagement and leisurely physical activity involvement, which are: (a) incentives play a role in motivation; (b) organized and leisurely physical activity foster positive relationships among peers; (c) bullying negatively affects students' motivation; (d) leisurely family activities foster higher engagement levels in children; (e) access to parks, recreational facilities, and youth sports leagues play a role in leisurely physical activity levels; (f) caregivers' involvement in their child's education allows communication between teacher and caregiver to strengthen the PE program; (g) the effectiveness of the classroom management of the teacher ensures all students are provided with an education that is safe and fair; (h) the teacher's ability to use incentives appropriately increases the likelihood of the most desirable behaviors; and (i) consistent school-wide application of the PBIS model reinforces positive student outcomes.

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• Open access
• Published: 27 June 2011

The case study approach

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

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

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

Peer Review reports

Introduction

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

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

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

What is a case study?

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

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

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

What are case studies used for?

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

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

How are case studies conducted?

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

Defining the case

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

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

Selecting the case(s)

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

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

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

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

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

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

Collecting the data

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

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

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

Analysing, interpreting and reporting case studies

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

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

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

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

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

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

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

Conclusions

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

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Acknowledgements

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

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Sarah Crowe & Anthony Avery

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

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

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A Case Study Assessing the Cumulative Effects of Deepwater Horizon Restoration Projects on Barrier Island/Barrier Shoreline Ecosystem Resilience in the North-central Gulf of Mexico

USGS and partners will assess the potential cumulative effects of restoration projects on the resiliency of barrier islands and barrier shorelines in the north-central Gulf of Mexico.

The Science Issue and Relevance:   The Deepwater Horizon (DWH) mobile drilling unit explosion and associated oil spill in April 2010 substantially impacted northern Gulf of Mexico coastal ecosystems, exacerbating existing acute and chronic stressors. As part of the  Natural Resource Damage Assessment process, along with civil and criminal claims, and imposed fines and penalties, over $15 billion (USD) in funding was dedicated to addressing environmental and economic restoration. Since DWH, hundreds of projects have been planned and implemented across the coast with the overall goal of restoring ecosystem function and services. Given the unprecedented temporal, spatial, and funding scales associated with the DWH oil spill restoration effort, the need for robust monitoring was identified early on to help inform adaptive management and provide a means to assess restoration outcomes. Many restoration projects provide project-specific monitoring data (for example,  DIVER website ), which offer insight into project-specific outcomes. However, these data alone fall short of informing outcomes at the ecosystem or regional level that may incorporate cumulative, synergistic or antagonistic effects across a habitat type or geographic area. 

A recent  National Academies of Sciences Report focused on the need to develop approaches that specifically assess cumulative impacts of restoration across a geographic- or ecosystem-level scale. Such an approach requires understanding not just project-level outcomes, but also understanding the cumulative effects of multiple restoration projects on an ecosystem, and their interaction with impacts of on-going acute and chronic stressors (for example, sea-level rise). Over 85 restoration projects have been implemented across the north-central Gulf of Mexico coast as part of the DWH restoration response. These restoration activities provide an opportunity to examine cause and effect related to restoration actions, and more specifically, how on-going trends in the resilience and ecological changes in the barrier island/barrier shoreline (BI/BS) systems may differ from expected or predicted trends for this region.

Methodology for Addressing the Issue: The Louisiana State University, U.S. Fish and Wildlife Service, USGS, and the Water Institute of the Gulf are collaborating on a case study to assess the potential cumulative effects of DWH restoration projects on the resiliency of the BI/BS in the north-central Gulf of Mexico. The area of interest for this study will span from Dauphin Island in Alabama (Fig. 1) to Alligator Point in Florida (Point Bald State Park; Fig. 2). To achieve this objective, we will: 1) develop a conceptual model of BI/BS that identifies drivers, stressors, and outcome metrics to track BI/BS resiliency; 2) document changes in BI/BS resiliency indicators using available project and remotely sensed data; and 3) explore metrics to assess potential changes in these resiliency indicators in response to DWH restoration projects. 

Future Steps: The next steps include the assessment of potential cumulative effects of BI/BS and dissemination of results. This effort could be expanded via future updates with new or planned restoration activities and remote sensing data.

Electrical Resistivity Tomography study above inaccessible old mine workings for safe erection of high voltage electricity power transmission terrestrial towers: a case study 

• Original Paper
• Published: 13 September 2024
• Volume 83 , article number  398 , ( 2024 )

Cite this article

• Abhay Kumar Bharti 1 ,
• Amar Prakash 1 ,
• Sandip Oraon 1 ,
• Prerna Jaiswal 1 &
• Sujit Kumar Mandal 1  

Old and abandoned mine workings become inaccessible with time owing to safety issues thereby demanding insight review of strata overlying such areas. Electrical Resistivity Tomography (ERT) survey was carried out at locations within Kajora area of Eastern Coalfield Limited (ECL) in Raniganj coalfield, India to assess the present strata condition for the proposed high voltage electric transmission layout. Parallel 2D ERT profiles were carried out with 20 m offset covering the study area. Considering the sensitiveness in horizontal direction i.e., identification of vertical structures, the Dipole-Dipole array methodology was implemented. The acquired data sets were filtered and processed using Prosys-II software. L-curve criteria for misfit data was used for proper interpretation of subsurface features. Non-linear least-squares regularized optimization method and 3D ERT volumetric model were performed by combining 2D ERT parallel profiles data sets for better resolution of underground old mine working and accurately map the status of mine workings. High resistivity magnitude ranging between 200 Ωm to 1600 Ωm indicated intact bedrock and solid pillar. Depillared workings area (either dry-filling or air-filled) was identified through anomalous high resistivity magnitude of more than 1600 Ωm. The data generated were also validated with underground working plan and available borehole data. Combination of 2D ERT and 3D ERT techniques against each profile was found to be effective for detection of strata condition for safe installation of terrestrial high voltage electric transmission towers.

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The authors extend thanks to Director, CSIR-Central Institute of Mining and Fuel Research, Dhanbad, for providing relevant support, guidance in this study and permission for publication.

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Bharti, A.K., Prakash, A., Oraon, S. et al. Electrical Resistivity Tomography study above inaccessible old mine workings for safe erection of high voltage electricity power transmission terrestrial towers: a case study . Bull Eng Geol Environ 83 , 398 (2024). https://doi.org/10.1007/s10064-024-03893-6

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Promoting generalisation in qualitative nursing research using the multiple case narrative approach: a methodological overview

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Senior Lecturer, School of Nursing and Midwifery, La Trobe University, Melbourne, VIC, Australia

Background:

The ability to generalise research generated findings to different contexts is a significant, yet overlooked, feature in qualitative studies conducted in nursing, where evidence-based clinical practice is highly regarded. The multiple case narrative is a constructivist-narrative approach, claimed to not only have the potential for analytical and case-to-case generalisation but also sample-to-population generalisation.

This paper provides an overview of multiple case narrative by comparing it with similar methodologies, reviewing studies that have used this approach and critically evaluating its capacity for producing generalisable results.

The multiple case narrative approach addresses limitations of collective case study, case survey and meta-ethnography by employing greater sample sizes and more generalisable results. Most studies previously using this approach have been performed in the education field and with the purpose of overcoming sample size limitations in qualitative research. The approach offers a uniquely systematic approach to analysis by finding associations between categories generated from collective analysis of large number of cases and providing the potential for sample to population generalisation.

Conclusion:

Multiple case narrative, which to date has been underutilised, is a systematic approach with characteristics that make it an efficient research technique to provide valid qualitative evidence.

Introduction

The act of generalisation includes applying relevant outcomes from particular cases to other situations, which can often mean that inferences about what is not measurable are drawn based on what can be assessed ( Polit et al., 2010 ). Generalisation is crucial in nursing and other applied health research as they allow findings to be applied to people, places and timeframes other than those in a particular study. There would be no evidence-based practice without generalisation, and research evidence can only be applied if it has some relevance to settings and persons outside of the contexts investigated ( Carminati, 2018 ). Growing interest in evidence-based decision-making in medical care, as well as widespread adoption of systematic review methodology in scientific research, which began in the 1980s, have made generalisability of findings, a valued standard for decades, a critical criterion for assessing the quality of quantitative research ( Polit et al., 2010 ). Since then, arguments over the feasibility of generalisation have attracted considerable interest from qualitative researchers as well; however, the feasibility of generalising findings has largely been seen as an illusion for qualitative scholars ( Flyvbjerg, 2006 ).

In 2005 , Asher Shkedi developed the multiple case narrative approach that deals with broader sample sizes than those typically employed in qualitative research and with the potential for all three forms of generalisations namely, case-to-case, analytical and sample-to-population generalisation ( Shkedi, 2005 ). Shkedi questioned the validity, reliability and possibility of generalisation in qualitative studies, seeking to incorporate trustworthiness principles within the constructivist model in the multiple case narrative approach ( Shkedi, 2005 ). Multiple case narrative is a constructivist-narrative approach that borrows some elements from constructivist grounded theory, valuing the importance of contexts and placing significant emphasis on the contextual and structural sense that identified a phenomenon in all its complexity ( Shkedi, 2005 ).

Comparable research approaches to multiple case narrative

Comparable research approaches to multiple case narrative are instrumental and collective case study, case survey and meta-ethnography. A case study has been defined as an intensive, systematic assessment of a single person, group, community or other unit in which the researcher investigates in-depth data pertaining to multiple variables ( Heale et al., 2018 ). Stake (1995) defined case study into three types: intrinsic, instrumental and collective. The intrinsic case study is used to develop a better understanding of a specific instance, whilst the instrumental and collective case studies are utilised to develop theory. The collective case study involves examining multiple cases simultaneously or sequentially to gain a deeper understanding of a certain subject ( Bergen et al., 2000 ).

Multiple case narrative is most relevant to the instrumental form of case study when a general understanding and insight into a phenomenon is demanded ( Shkedi, 2005 ). Yin maintains a positivist approach to case study research that involves establishing variables before commencing a study and seeing whether they fit in with the findings, where the role of the researcher in influencing results is not recognised ( Yin, 1981 ). However, multiple case narrative does not attempt to discover correlations among previously established variables and acknowledges the role of the researcher and complexity of a phenomenon as a whole ( Shkedi, 2005 ).

Comparable to multiple case narrative is the collective case, which is an expanded form of instrumental case study containing multiple cases; two to ten in one study, instead of a single case ( Baxter et al., 2008 ). The number of cases in collective case studies is determined to ensure specific relevance to the areas of interest and the use of replication logic, where cases are selected to create predicted contrasting or comparable conclusion ( Harrison et al., 2017 ). Multiple or collective case studies entail the careful selection of a number of cases, with a boundary usually established for each case indicating the breadth of the research topic, population studied and length of the study ( Crowe et al., 2011 ). The multiple case narrative investigates a phenomenon from the perspective of the individuals who experience the phenomenon, organisation or process, with each case representing a unique individual. Cases are given without consideration to selection criteria and boundaries, and each is investigated within its own context ( Shkedi, 2005 ).

Collective case study and multiple case narrative vary in the order of the within-case analysis and between-case analysis. Multiple case narratives begin with within-case analysis to retain the uniqueness of each case, in contrast to collective case studies that begin with cross-case analysis by estimating the cross-case values for certain variables (Shkedi, 2005b; Yin, 2009 ). One of the primary characteristics of a collective case study is that, despite discussing multiple cases and presenting them collectively, each case narrative is depicted with its own unique qualities and context ( Stake, 1995 ). In contrast to collective case study, the multiple case narrative approach does not include a specific narrative of a case; instead, it discusses cross-cutting concepts that enable the researcher to see connections between cases ( Shkedi, 2005 ). This approach allows for identifying broad patterns across a variety of narratives and facilitates generalisations in the notions of constructivist approach ( Shkedi, 2005 ). Therefore, in addition to case-to-case and analytical generalisation as in single and collective case studies, the multiple case narrative approach provides the possibility for generalisation to other populations, which is generally only possible with positivistic-quantitative research approaches ( Shkedi, 2005 ).

Case survey, or case meta-analysis, is another equivalent research strategy to multiple case narrative, which synthesises existing case studies and aims to achieve generalisability of the survey as well as depth of the case study ( Shkedi, 2005 ). The case survey method proposes combining the advantages of two common research methods: case study and case survey ( Larsson, 1993 ). Based on existing case studies, it intends to harness the generalisability of survey and depth of case study. This approach was developed as a means of merging diverse case studies under a single conceptual framework to enable the accumulation of findings ( Larsson, 1993 ). The case survey focuses on certain components of previously published case studies while ignoring their specific contexts and integrating them using conventional statistics ( Berger, 1983 ). In general, the number of available cases pertinent to a particular subject of interest is limited. Moreover, case survey relies on reports of completed case studies and has no access to information beyond these reports ( Shkedi, 2005 ). It does not offer sufficient attention to specific context of the individual cases in case studies ( Yin, 1981 ). It is also impossible for case studies to provide results upon which theoretical or statistical generalisations can be developed, as the selection of particular case narratives is beyond the scope of the secondary researcher ( Berger, 1983 ; Yin, 1981 ).

Meta-ethnography addresses a number of limitations of the case study approach. Meta-ethnography utilises qualitative approaches to case studies to produce interpretive insights, whereas case survey primarily employs quantitative methods to synthesise case study findings ( Doyle, 2003 ). However, like case survey, in meta-ethnography, the interpretive nature of the original studies tends to be ignored ( Noblit et al., 1988 ). Furthermore, since the number of available studies is beyond the researcher’s control and original data are not accessible, generalisable results are unlikely to be produced ( Shkedi, 2005 ). Multiple case narrative seeks to address the limitations of case survey and meta-ethnography by including primary data from a large number of case narratives, as part of the same research, and providing more in-depth analysis of phenomena ( Shkedi, 2005 ).

Application of multiple case narrative

The analysis schema in the multiple case narrative consists of four steps, and each level of analysis builds on the level below including: (1) initial, (2) mapping, (3) focused and (4) theoretical. In multiple case narrative, analysis is accomplished when the primary categories are determined, their interrelationships are established and they are incorporated into a meaningful collective account ( Shkedi, 2005 ).

An example of the implementation of multiple case narrative as a qualitative research approach was employed in a study examining the registration experiences of internationally qualified midwives through the context of Australia’s evolving registration standards that have undergone significant changes over the time ( Safari et al., 2023 ). A total of 19 midwives from international countries, who applied for registration between 2000 and 2020, participated in the study. In-depth interviews were conducted with a purposeful sample of participants recruited nationally from Australia between November 2020 and September 2021. According to principles of the multiple case narrative, variation in study participants was established by selecting a purposive sample who represents a wide range of people and positions in the larger population under study ( Shkedi, 2005 ).

Initial stage

In this stage, researchers look for what they can discover and define from their data through close examination of each case narrative separately, without losing the whole picture of all data. All case narratives are considered from the same conceptual perspective ( Shkedi, 2005 ). The initial stage fragments the data and facilitates the identification of categories without requiring consistency and coherence and without the necessity to find an apparent relationship between categories; it only seeks to establish a broad orientation from the material. The process of grouping together components of data that pertain to the same phenomenon is referred to by Shkedi as categorisation. Categorisation is not only a process of classification, but also a way to expose and make meaning of data. It starts with a few broad categories to establish a general overview and then finding ways for progressively refining the data ( Shkedi, 2005 ). For categorisation, the researcher should employ in-vivo names; keywords used by the individuals being investigated. The use of specific terminology drawn directly from narratives anchors the analysis to the context of these data ( Shkedi, 2005 ). Once the data have been classified into broad categories, the second stage of analysis (mapping) can commence.

The initial stage of analysis was found to be comparable to ‘initial coding’ stage of analysis in grounded theory in which the researcher conducts initial coding by reading through the transcripts and selecting phrases until categories begin to emerge ( Glaser et al., 1968 ).

In our study exploring transition experiences of internationally qualified healthcare professionals, at initial stage, the data were segmented, allowing for the identification of categories without requiring consistency or a connection between categories to be apparent. Data-driven categories were formulated to take the text out of chronological narrative order and category names were assigned derived from experiences discussed by participants ( Safari et al., 2023 ).

Mapping stage

The mapping stage aims at providing a framework for establishing in-depth descriptions and explanations by identifying relationships between categories, which must be internally sound and empirically grounded ( Shkedi, 2005 ). This stage of analysis is the result of continuous discussion between the data, conceptual perspectives of the researcher and of the subject area. Unlike the initial stage, where each case narrative was categorised separately, at the mapping stage, all case narratives should be classified collectively. At this stage, similarities and differences between categories are compared, as well as the degree of meaning consistency among categories, and they are clustered into families ( Shkedi, 2005 ).

As multiple case narrative deals with several cases, it looks to find causal patterns based on associations between different categories after arriving at a tentative picture of the main categories. The nature of each pattern is determined by those common characteristics that are unique to a certain group of case narratives and distinguish them from other groups of cases; this strategy is known as the associational approach in multiple case narratives ( Shkedi, 2005 ). Diversity in appearance of categories is essential and inferences drawn from the scarcity of some categories are as significant as those formed from prominence of other categories ( Shkedi, 2005 ). The researcher must plot the characteristics of the categories on a continuum to assess their extreme possibilities. It is essential not to place as much emphasis on evidence by quantity as in positivistic-quantitative studies because in multiple case narratives like other qualitative studies, the context in which individual experiences are interpreted is more significant ( Shkedi, 2005 ).

Shkedi recommends organising the mapping array of categories in a textual document and distinguishing two types of categories in the tree ‘indication categories’ and ‘content categories’ ( Shkedi, 2005 ). Indication categories indicate a characteristic of the phenomenon and stipulate relationships between categories. Content categories, the lowest categories in the tree without subcategories, not only show characteristics of the categories but also have content elements (participants’ quotations). Multiple case narrative reports, like other qualitative methodologies, use direct quotations to convey informants’ experiences. The use of informants’ own words is congruent with the constructivist-narrative research approach and provides a genuine depiction of the investigated phenomenon ( Shkedi, 2005 ).

This stage of analysis in multiple case narrative was found to be distinctive and distinct from grounded theory and other qualitative research approaches in a number of ways, including the collective analysis of the categories generated from all the cases and the identification of patterns and causal relationships between them using a systematic mapping.

At the mapping stage of our study, we found similarities in the categories generated from the narratives of the participants who applied for registration in Australia through four different programmes between 2000 and 2020. Accordingly, they were divided into four cohorts based on the programme through which they applied for registration, including bridging programme, national adaptation programme, upgrading programme and outcomes-based programme. The study then identified distinct patterns in the prevalence of the main categories among these four groups, including language barriers, variation in the process, inadequate orientation and misdirection ( Figure 1 ).

Mapping stage of analysis.

Characteristics of the categories were placed on a continuum to see the possibilities of the category’s characteristics in four groups and results presented in percentages. As illustrated in diagram 1, variation in the process was only discussed by those who applied through the bridging programme for registration, inadequate orientation was the issue equally encountered by those who went through the bridging and upgrading programmes for registration. A majority of participants (86%) experiencing misdirection by the system were in the upgrading programme group. The common theme of language barriers was present in all groups, though to varying degrees, with the majority being in the upgrading programme ( n  = 6, 36%) and the least in the outcomes-based programme ( n  = 2, 12%). These findings were supported by direct quotations from participants ( Safari et al., 2023 ).

Focused stage

Focused categorisation, which can be the final stage of the study, occurs when the researcher centralises data into a cohesive account around the core categories and starts to formulate a better picture of study findings. The core category is the highest ‘indication’ category, to which many primary categories and subcategories are assigned. Therefore, the core category is the category that reflects the general identity of the entire set of categories ( Shkedi, 2005 ). What appears to be the key concern or issue of the informants and the essence of relevance represented in the data would determine which category has the most potential to become a core category ( Shkedi, 2005 ). The core category must be key to as many other categories and their features as possible, commonly present in the data, clearly relate to other categories and have clear implications for a more thorough explanation ( Shkedi, 2005 ).

The focused stage of analysis corresponds to the ‘core category’ step of analysis in grounded theory, with the similar objective of determining a meaningful and relevant pattern of behaviour for individuals involved ( Glaser et al., 1968 ).

In our example study, the focused stage of analysis saw the generation of the core category of systemic barriers in the registration experiences of internationally qualified midwives, which was easily related to other categories generated in the second stage of analysis and had clear implications for a broader explanation ( Safari et al., 2023 ).

Theoretical stage

In the first three steps of analysis, researchers seek categorisation of data, comparison of categories across cases and pattern identification. In the theoretical stage, the generated categories are sorted until they fit an appropriate theoretical story. The theoretical narrative is a description of the investigated phenomenon that has been elevated to a theoretical level and a conception of a coherent description of the central phenomenon ( Shkedi, 2005 ). First- and second-order analysis are distinguished as the key link between the data and their theoretical representation in multiple case narratives. First-order theoretical analysis involves direct translation of descriptive categories into theoretical concepts, but second-order theoretical analysis requires conversion of the existing system’s meaning to arrive at a new, abstract and more refined order of theoretical categorisation ( Shkedi, 2005 ). While the description and theoretical interpretations are directly connected in first-order theoretical analysis, the connection in second-order theoretical analysis is actually the interpretation of what is being discovered in relation to what is already known and has been published in the relevant literature ( Shkedi, 2005 ).

Similar to grounded theory, in multiple case narrative, once the researcher has introduced a unique set of categories, they can compare them to notions from the literature. To systematise and consolidate relationships, the researcher must utilise a combination of inductive and deductive reasoning, continually transitioning between posing questions, formulating hypotheses and drawing comparisons ( Shkedi, 2005 ). The researcher can begin to rearrange and reorganise the categories until they appear to match a proper theoretical narrative and yield analytical interpretations. The theory developed in multiple case narrative in contrast to grounded theory, in which theoretical concepts are more abstract and applicable, is a low-level theory that arose from the study of phenomenon situated in a particular context ( Shkedi, 2005 ).

Theory development was not the objective of our study; thus, the theoretical stage of analysis was excluded, which is a common practice in studies adopting multiple case narrative methodology, since according to the Shkedi the focused stage can be the final stage of analysis ( O’Malley, 2020 ; Phelps, 2016 ). This distinguishes the multiple case narrative from grounded theory, where theory generation based on data is the primary objective of the researcher ( Strauss et al., 1997 ).

Reporting of case narratives

In case-narrative research, there are two distinct types of results reporting. The first is a case-by-case narrative, which emphasises a specific case. The second type of narrative is the collective or multiple case narrative, which consists of multiple narratives around the phenomenon and requires both individual case narratives and cross-case analysis for reporting purposes ( Yin, 1981 ). The multiple case narrative approach does not strictly align with these two narrative reporting styles, considering that this study approach includes a variety of case narratives. Moreover, the main purpose of this approach is not to present the narrative of each case separately, but to clarify associated or distinguishing characteristics by making comparisons between them. Thus, cross-case issues are generally addressed in multiple case narrative studies instead of introducing specific case narratives ( Shkedi, 2005 ).

Multiple case narrative can make effective use of quantitative methods because of the inclusion of many case narratives, in contrast to some qualitative research that draws a sharp distinction between idiographic and nomothetic methods ( Shkedi, 2005 ). In multiple case narrative study, statistical analysis using frequency counts with percentage outcomes is appropriate ( Shkedi, 2005 ). Short quantitative descriptions are considered more focused and clearer in telling the story than long expressive descriptions. However, quantitative methods can only be used for those purposes consistent with the constructivist-narrative approach, the narrative nature of the research should be maintained, and actual verbal responses should be preserved ( Shkedi, 2005 ).

Generalisation of results

Shkedi (2005) claimed three types of generalisation from multiple case narrative, including: (1) case-to-case generalisation, (2) analytical generalisation and (3) generalisation from sample to population.

• Case-to-case generalisation. This concept requires the definition of generalisability to be modified to emphasise the degree to which the examined scenario is similar to other circumstances ( Yin, 2013 ). This definition of generalisation offers a more realistic perspective on the generalisability of constructivist-narrative research findings. It is more in line with Stake’s (2005) definition of ‘naturalistic generalisation’, which emphasises applying research findings to other situations that are similar in order to better understand those other situations. In multiple case narrative, single case narratives are not represented as independent entities in the final report; however, case-to-case generalisation does not inherently mean that all elements of case narrative should be transferable to other contexts and may be partly applicable. This capacity of case-to-case generalisation enables the final report of the multiple case narrative, which focuses on the conceptual analysis of case narratives, to be adapted for generalisation of this type ( Shkedi, 2005 ).
• Analytical generalisation: This occurs when findings replicate across similar theoretical contexts. In order to perform analytical generalisation, the researcher should refer to the conceptual theoretical context to demonstrate how concepts have driven the data collection and analysis to outline the theoretical parameters of the study ( Bergen et al., 2000 ). In the multiple case narrative as a constructivist-qualitative form of study, generalisation to theory is neither relevant to making assumptions, nor does it use the entire theory as a reference frame. The theories that emerge in multiple case narrative research are more of the grounded than the grand theory type ( Shkedi, 2005 ). In this technique, the process of theoretical analysis, that is, the formation of theoretical concepts and correlations, serves as the basis for analytical generalisation. Thus, specifying the study’s relevance to multiple theories would facilitate analytical generalisation ( Shkedi, 2005 ).
• Generalisation to population: The aim for a certain degree of generalisation from a sample to the wider population in the multiple case narrative approach was claimed by Shkedi (2005) . The ‘associational’ approach in multiple case narratives involves gathering information from various cases and allows for the ongoing comparison of data units. This process continues until the relationships of the categories are established and incorporated into a meaningful description ( Shkedi, 2005 ). By including moderate-to-large numbers of cases from a sufficiently diversified sample and emphasising broad cross-case patterns, the researcher can avoid the idiosyncrasy that may arise in single-case studies and enhance the potential of sample to population generalisation in multiple case narrative ( Shkedi, 2005 ). Treating case narratives as clusters of categories strengthens the potential of the study for sample-to-population generalisation by facilitating systematic comparisons between group of cases based on the pattern found in the emerged categories. If the researcher indicates that heterogeneity in the sample is comparable to that in other populations, then generalisation is more reliable ( Shkedi, 2005 ).

Literature review

Reviewing studies that have reported using Shkedi’s approach indicate that this methodology has mainly been applied in the education field as a qualitative analysis approach allowing for the study of large populations and performing systematic analysis ( Table 1 ). Multiple case study was reportedly also used as a qualitative methodology in two mixed methods studies ( Clouston et al., 2019 ; Minibas-Poussard, 2018 ).

Characteristics of studies employing multiple case narrative approach.

Examples of multiple case narrative demonstrate variance in sample size. Recent examples of multiple case narrative being used in an educational context include Minibas-Poussard (2018) who collected 19 case narratives to better understand unethical behaviour in higher education; Clouston et al. (2019) who studied 54 participants to explore occupational science in Europe and its link with occupational therapy and O’Malley (2020) who used multiple case narrative to understand the alignment between institutional brand promises and adult learner experience in an online master’s degree programme by including 17 participants in the United States. In addition to an educational context, health has been the other leading discipline to employ multiple case narrative in the past decade. Lim (2012) interviewed 43 nursing students to examine their experiences in becoming prescribers and compared these with those of other prescriber groups, whereas Nivedita (2015) sought to understand work trajectories of 19 people with mental illnesses as they developed in their larger life contexts.

With extensive narrative research experience in education, Shkedi looked to incorporate trustworthiness principles within the constructivist model in multiple case narrative approach. This methodology can facilitate the development of findings that are more broadly cross-sectional and generalisable than collective case studies. Regardless of whether single- or multiple-case studies are performed, the inability to generalise from case studies has been a major limitation of the method. Existing case study research literature, notably from Eisenhardt (1989) and Yin (2009) , has mostly emphasised the potential of multiple-case design for theoretical generalisation and claim that evidence from multiple cases is more convincing. However, selecting a case in a multiple-case study because it is expected to predict either (1) equivalent outcomes or (2) contrasting or opposite results based on established theoretical premises ( Miles & Huberman, 1994 ; Yin, 2009 ) suggested that the case does not characterise the population from which it was drawn, limiting generalisability. Contrary to the commonly held belief that it is unimportant to select cases that are representative of the population to which they belong, if the purpose of a study is to establish empirical generalisation, selecting representative cases over theoretical sampling makes more sense, as the two populations should share certain essential characteristics to justify the generalisation ( Mitchell, 1983 ). Larsson (1993) further emphasised that, while multiple case studies might achieve cross-case pattern analysis, small case sets may limit the method’s ability to profit from thorough cross-case analysis. The multiple case narrative technique protects researchers against biases that may occur in single or collective case studies by including a large number of case narratives and highlighting broad cross-case comparison ( Shkedi, 2005 ).

The multiple case narrative approach also gives more comprehensive process assessments of a phenomenon than questionnaire surveys and overcomes shortcomings in meta-ethnography using primary data from a wide range of case narratives as part of the same research. While Shkedi claimed the uniqueness of this approach, referring to categorisation, generating the core category and its sub-categories for analysis in the multiple case narrative approach, evident parallels can be drawn with constructivist grounded theory procedures, which provides a robust methodological foundation for this approach.

Several qualitative studies have utilised this methodology, since it allows for larger sample sizes compared to other approaches. It has also been used in mixed methods research, where a larger sample size significantly improves the quality of data collected due to increased complexity resulting from quantitative and qualitative components bringing their own issues of representation, legitimation, integration and politics into the setting ( Onwuegbuzie et al., 2007 ).

This approach attempts to integrate the study of the particular with the needs for comprehensive coverage of larger populations and a broader basis for formal generalisation. The concept of generalisability, the degree in which inferences from a study can be generalised to other populations, is often considered a criterion for evaluating quality and trustworthiness in qualitative health research ( Spencer et al., 2004 ). Sample adequacy, which pertains to appropriateness of sample composition and size in qualitative inquiry, is always considered in appraisal of generalisability ( Robinson, 2014 ). While most qualitative researchers would claim to be unconcerned with statistical inferences from qualitative findings, sample sizes in qualitative health research are commonly seen as small, resulting in tenuous foundations for validity of studies ( Carminati, 2018 ). Multiple case narrative allows for the study of larger samples compared to other qualitative approaches ensuring sufficient data for identifying patterns in generated categories ( Shkedi, 2005 ). The variety and diversity of participants are critical in qualitative research and multiple case narrative is especially accommodating to a diverse collection of participants ( Shkedi, 2005 ). By extending the variety and size of the sample across a range of cases with distinctive features, it is more likely that exceptions will cancel each other out, hence strengthening the sample’s representativeness and promoting generalisation ( Polit et al., 2010 ). Moreover, when heterogeneity in cases is comparable to that in other populations, then generalisation is more reliable ( McClintock et al., 1979 ).

Multiple case narrative collects information on case narratives and systematically finds causal relationships in generated categories among different groups of cases. Finding relationships between categories derived from a sufficient number of cases utilised to compare groups increases not only internal but also external validity ( Yin, 2013 ). Depending on how causality is viewed, qualitative studies can explore causal relationships. The positivistic-quantitative approach assumes there are real causes temporally prior to, or concurrent with, their effects, whereas the multiple case narrative approach assumes all entities are in a state of mutual simultaneous shaping, making it impossible to distinguish causes from effects ( Shkedi, 2005 ). According to Shkedi, multiple case narrative does not violate these presumptions; rather, it seeks to broaden their boundaries. Additionally, while positivistic-quantitative research begins with development of a foundational theory upon which all subsequent research phases are based ( Guba and Lincoln, 1994 ), the multiple case narrative approach does not arrive at causal explanation until conclusion of the research process, after data gathering and creation of informants’ descriptions ( Shkedi, 2005 ).

Since the associational approach employs a probabilistic way of thinking that is prevalent in quantitative analysis, it is common to neglect exceptions. Additionally, it is likely that cases lose their individual identities, as this approach de-emphasises individual cases and case narratives are not represented in final reports as distinct entities, in favour of illuminating cross-cutting themes ( Campbell, 1975 ; Firestone, 1993 ). Shkedi (2005) claimed that his approach overcame some limitations of the associational approach by attempting to partially avoid losing case identity and bringing along a large amount of information about each case through a matrix and illustrating strategies to see relationships among categories by generating a mapping tree. He encouraged starting analysis by examining individual cases, which encourages users to have a thorough understanding of case characteristics. Shkedi (2005) further emphasised that relationships formed between categories is supported by informant citations. In contrast, the positivist quantitative method eliminates all context-specific variables in order to apply conclusions to the greatest number of individuals and experiments possible ( Maykut et al., 1994 ). However, most qualitative researchers aim to provide rich, contextualised understandings of human experience through intensive study of specific cases, and they do not all agree on the importance or attainability of generalisability ( Carminati, 2018 ). Some believe that generalisation necessitates extrapolation that can never be fully justified because findings are always embedded in context and knowledge is idiographic, residing in particulars ( Erlandson et al., 1993 ). Conversely, some qualitative researchers believe that in-depth qualitative research is ideally suited for exposing concepts, and theories that are not unique to a particular participant or location ( Misco, 2007 ). The rich, exceedingly detailed and potentially informative quality of qualitative findings, according to this view, makes them perfect for generalisation.

Purposive sampling technique for use in multiple case narratives could lead to criticism of the generalisability of this approach. However, in the majority of quantitative research, the population to which generalisations are to be applied is typically poorly defined, and random sampling seldom yields random samples ( Polit et al., 2010 ). Additionally, purposive sampling in multiple case narratives, which focuses on defining typical cases and selecting units to obtain the widest possible variation for the sample from the population with the most knowledge, is comparable to probabilistic sampling in that it expands the potential for study findings to be replicated ( Gheondea-Eladi, 2014 ).

In our study exploring transition of international midwives in Australia, the application of the multiple case narrative approach was found to be beneficial in various ways, with certain limits. It promoted the inclusion of a larger sample size, as evidenced by other studies employing this methodology ( Clouston et al., 2019 ; Minibas-Poussard, 2018 ; O’Malley, 2020 ). Identifying relationships between categories based on their pattern of emergence in different cases was found to add special value and depth to the study’s findings by introducing a quantitative dimension to the analysis procedure, which distinguishes the multiple case narrative approach from other qualitative approaches. Inclusion of the relatively large sample size facilitated obtaining comprehensive understanding of the transition experiences of international midwives in Australia. On the other hand, it complicated management of the vast quantities of data collected. This issue was largely overcome by employing NVivo 12, which was not only utilised for coding data, grouping data and auditing data, but also, with its special characteristics, enabled us to perform a large cross-case comparison and identify relationships between the generated themes in different cases. Covering more variance with a large sample size was found to not only improve the generalisability of the study by incorporating diverse perspectives on the phenomenon, but also to strengthen the associational method by raising the likelihood of comparing more distinct groups. Thus, if this methodology is used, the availability of a large sample size, which is essential for multiple case narrative, should be guaranteed.

Due to the inclusion of a larger sample size in multiple case narrative, there is a risk that context-specific details may be lacking in the findings, complicating examination of the context for each narrative and sacrificing the depth and contextual nature of insights. In addition, uncommon themes will be overlooked when comparing the categories of the enormous data generated from a large sample size. Generally, however, the appropriate approach depends in part on what is already known. If the field is well-charted, an initial emphasis on constructs may be more appropriate. However, if pioneering studies are required in areas where little is known, multiple case narrative study may be more beneficial.

As evidence-based practice is increasingly adopted, the health sector relies on researchers’ findings to implement in real-world settings. Rather than denying the possibility for qualitative research to yield general truths, researchers can take steps to improve the readiness of their studies for logical and reasonable generalisation. Generalisable evidence is the ideal beginning for evaluating a scientific hypothesis in light of clinical expertise and patient preferences. The multiple case narrative, which to date has been underutilised, is a systematic approach with characteristics that make it an efficient research technique to provide valid and generalisable qualitative evidence, offers new possibilities for nursing and health research.

Key points for policy, practice and/or research

• The multiple case narrative is a systematic approach with characteristics that make it an efficient research technique to provide valid and generalisable qualitative evidence.
• The multiple case narrative allows for the study of larger samples compared to other qualitative approaches.
• This approach offers a uniquely systematic approach to analysis by finding associations between categories generated from collective analysis of large number of cases.
• The multiple case narrative, which is mainly used in the education field, offers new possibilities for nursing and health research.

Kolsoom Safari , RM, PhD, Research Fellow at the School of Nursing and Midwifery, La Trobe University, Bundoora, Victoria, Australia.

Lisa McKenna , RN, RM, PhD, Professor and Dean at the School of Nursing and Midwifery, La Trobe University, Bundoora, Victoria, Australia.

Jenny Davis , RN, RM, PhD, Senior Lecturer at the School of Nursing and Midwifery, La Trobe University, Bundoora, Victoria, Australia.

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

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

Ethical approval: Ethical approval was not required for this study as it solely focuses on providing a comprehensive analysis and synthesis of existing literature and does not involve any primary data collection from individuals. Therefore, no ethical considerations were applicable or necessary for this research.

Contributor Information

Kolsoom Safari, Research Fellow, School of Nursing and Midwifery, La Trobe University, Melbourne, VIC, Australia.

Lisa McKenna, Dean, School of Nursing and Midwifery, La Trobe University, Melbourne, VIC, Australia.

Jenny Davis, Senior Lecturer, School of Nursing and Midwifery, La Trobe University, Melbourne, VIC, Australia.

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