research methodology case study method

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• Published: 27 June 2011

The case study approach

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

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

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

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Introduction

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

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

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

What is a case study?

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

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

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

What are case studies used for?

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

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

How are case studies conducted?

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

Defining the case

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

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

Selecting the case(s)

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

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

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

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

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

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

Collecting the data

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

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

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

Analysing, interpreting and reporting case studies

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

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

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

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

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

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

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

Conclusions

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

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

Google Scholar  

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

Article   CAS   PubMed   PubMed Central   Google Scholar  

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

Article   Google Scholar  

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

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

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

Article   PubMed   Google Scholar  

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

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

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

PubMed   PubMed Central   Google Scholar  

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

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

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

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

Article   PubMed Central   Google Scholar  

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

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

CAS   PubMed   PubMed Central   Google Scholar  

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

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

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

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

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

Mason J: Qualitative researching. 2002, London: Sage

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

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

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

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

Article   PubMed   PubMed Central   Google Scholar  

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

Article   CAS   PubMed   Google Scholar  

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

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

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

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

Book   Google Scholar  

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

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

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

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

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Acknowledgements

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

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

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A Case Study is a research method involving a detailed examination and in-depth description of a particular empirical case. This can be done in many different ways, and the unit of analysis can vary (a person, an institution, a country, etc.). Case Studies can include both quantitative and qualitative evidence (Stake, 1995) and typically rely on bringing together many different articles of evidence from various sources to illuminate the case as a whole.

Case Studies benefit from having a developed theoretical framework before data collection begins (Yin, 2003). At the same time, the Case Study approach allows flexibility and can be used in exploratory contexts. This can be attractive to the researcher because it allows data collection to begin immediately (though there remains a need to impose a theoretical structure in the analysis phase). Consequently, Case Studies can be conducted at different levels of formality and replicability (Hetherington, 2013).

The case study research design can be used to test whether theories and models work in real contexts of application (Shuttleworth, 2008) and, conversely, to generate hypotheses and theories.

Case Study: GO-GN Insights

Sarah Hutton used a hermeneutic phenomenological case study to illuminate a direct connection between undergraduate student participation in courses with a participatory OER authorship or open access publishing of student artefacts model, to the development of internal goals and deepened engagement:

“Participatory OER development and an open pedagogical model provide the potential for students to have autonomous control over the development of course content, fostering greater intrinsic motivation, and therefore more successful and transferable learning outcomes. The resulting analysis creates a compelling case for the adoption of OER materials beyond the affordability argument, further advocating for the engagement of students in open scholarship at the undergraduate level.”

Viviane Vladimirschi explored evidence-based guidelines in the context of Teacher Professional Development (TPD) for Brazilian fundamental education public school teachers by undertaking an intervention in one school. The main goal of the OER Development Program was to raise awareness and build teachers’ knowledge regarding OER adoption and use:

“The case study methodology used in this research is a very common approach within Educational Studies. It is also a fairly easy method to use and the analysis of multiple sources of data have the potential to not only generate new insights throughout the case study but also generate new theory. Theory-building is very well-suited to new research areas, which was the case of this research. However, there are some disadvantages to using this methodology. First, it is not possible to generalize the findings from a single case study. Second, achieving the balance between producing an overly complex theory or a narrow idiosyncratic theory is quite challenging. Theory generated by case studies must be testable, replicable and coherent. The TPD guidelines generated by this research are testable, replicable and pretty straightforward so I am confident I managed to achieve this balance. The Design Thinking for Educators approach (please note that it is not a method) that I used in this research for the face-to-face workshops I highly recommend to any researcher who wishes to undertake an intervention, especially in the K-12 sector. This approach not only enables researchers to gain more insight into potential solutions for introducing new professional practices, but also affords teachers multiple opportunities to participate in the process of determining how innovation may be best implemented. Its only potential disadvantage is that it requires a longer period of time of application during each of its distinct phases to obtain bottom-up buy-in to an innovation.”

Useful references for Case Studies: Hetherington (2013); Shuttleworth (2008); Stake (1995); Yin (2003)

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On This Page:

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

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

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

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

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

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

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

 Famous Case Studies

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

Clinical Case Studies

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

Child Psychology Case Studies

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

Types of Case Studies

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

Where Do You Find Data for a Case Study?

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

1. Primary sources

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

2. Secondary sources

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

3. Archival records

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

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

4. Organizational records

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

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

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

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

How do I Write a Case Study in Psychology?

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

1. Introduction

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

2. Case Presentation

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

3. Management and Outcome

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

4. Discussion

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

5. Additional Items

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

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

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

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

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

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

Limitations

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Further Information

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

Case Study Research: Methods and Designs

Case study research is a type of qualitative research design. It’s often used in the social sciences because it involves…

Case study research is a type of qualitative research design. It’s often used in the social sciences because it involves observing subjects, or cases, in their natural setting, with minimal interference from the researcher.

In the case study method , researchers pose a specific question about an individual or group to test their theories or hypothesis. This can be done by gathering data from interviews with key informants.

Here’s what you need to know about case study research design .

What Is The Case Study Method?

Main approaches to data collection, case study research methods, how case studies are used, case study model.

Case study research is a great way to understand the nuances of a matter that can get lost in quantitative research methods. A case study is distinct from other qualitative studies in the following ways:

• It’s interested in the effect of a set of circumstances on an individual or group.
• It begins with a specific question about one or more cases.
• It focuses on individual accounts and experiences.

Here are the primary features of case study research:

• Case study research methods typically involve the researcher asking a few questions of one person or a small number of people—known as respondents—to test one hypothesis.
• Case study in research methodology may apply triangulation to collect data, in which the researcher uses several sources, including documents and field data. This is then analyzed and interpreted to form a hypothesis that can be tested through further research or validated by other researchers.
• The case study method requires clear concepts and theories to guide its methods. A well-defined research question is crucial when conducting a case study because the results of the study depend on it. The best approach to answering a research question is to challenge the existing theories, hypotheses or assumptions.
• Concepts are defined using objective language with no reference to preconceived notions that individuals might have about them. The researcher sets out to discover by asking specific questions on how people think or perceive things in their given situation.

They commonly use the case study method in business, management, psychology, sociology, political science and other related fields.

A fundamental requirement of qualitative research is recording observations that provide an understanding of reality. When it comes to the case study method, there are two major approaches that can be used to collect data: document review and fieldwork.

A case study in research methodology also includes literature review, the process by which the researcher collects all data available through historical documents. These might include books, newspapers, journals, videos, photographs and other written material. The researcher may also record information using video cameras to capture events as they occur. The researcher can also go through materials produced by people involved in the case study to gain an insight into their lives and experiences.

Field research involves participating in interviews and observations directly. Observation can be done during telephone interviews, events or public meetings, visits to homes or workplaces, or by shadowing someone for a period of time. The researcher can conduct one-on-one interviews with individuals or group interviews where several people are interviewed at once.

Let’s look now at case study methodology.

The case study method can be divided into three stages: formulation of objectives; collection of data; and analysis and interpretation. The researcher first makes a judgment about what should be studied based on their knowledge. Next, they gather data through observations and interviews. Here are some of the common case study research methods:

One of the most basic methods is the survey. Respondents are asked to complete a questionnaire with open-ended and predetermined questions. It usually takes place through face-to-face interviews, mailed questionnaires or telephone interviews. It can even be done by an online survey.

2. Semi-structured Interview

For case study research a more complex method is the semi-structured interview. This involves the researcher learning about the topic by listening to what others have to say. This usually occurs through one-on-one interviews with the sample. Semi-structured interviews allow for greater flexibility and can obtain information that structured questionnaires can’t.

3. Focus Group Interview

Another method is the focus group interview, where the researcher asks a few people to take part in an open-ended discussion on certain themes or topics. The typical group size is 5–15 people. This method allows researchers to delve deeper into people’s opinions, views and experiences.

4. Participant Observation

Participant observation is another method that involves the researcher gaining insight into an experience by joining in and taking part in normal events. The people involved don’t always know they’re being studied, but the researcher observes and records what happens through field notes.

Case study research design can use one or several of these methods depending on the context.

Case studies are widely used in the social sciences. To understand the impact of socio-economic forces, interpersonal dynamics and other human conditions, sometimes there’s no other way than to study one case at a time and look for patterns and data afterward.

It’s for the same reasons that case studies are used in business. Here are a few uses:

• Case studies can be used as tools to educate and give examples of situations and problems that might occur and how they were resolved. They can also be used for strategy development and implementation.
• Case studies can evaluate the success of a program or project. They can help teams improve their collaboration by identifying areas that need improvements, such as team dynamics, communication, roles and responsibilities and leadership styles.
• Case studies can explore how people’s experiences affect the working environment. Because the study involves observing and analyzing concrete details of life, they can inform theories on how an individual or group interacts with their environment.
• Case studies can evaluate the sustainability of businesses. They’re useful for social, environmental and economic impact studies because they look at all aspects of a business or organization. This gives researchers a holistic view of the dynamics within an organization.
• We can use case studies to identify problems in organizations or businesses. They can help spot problems that are invisible to customers, investors, managers and employees.
• Case studies are used in education to show students how real-world issues or events can be sorted out. This enables students to identify and deal with similar situations in their lives.

And that’s not all. Case studies are incredibly versatile, which is why they’re used so widely.

Human beings are complex and they interact with each other in their everyday life in various ways. The researcher observes a case and tries to find out how the patterns of behavior are created, including their causal relations. Case studies help understand one or more specific events that have been observed. Here are some common methods:

1. Illustrative case study

This is where the researcher observes a group of people doing something. Studying an event or phenomenon this way can show cause-and-effect relationships between various variables.

2. Cumulative case study

A cumulative case study is one that involves observing the same set of phenomena over a period. Cumulative case studies can be very helpful in understanding processes, which are things that happen over time. For example, if there are behavioral changes in people who move from one place to another, the researcher might want to know why these changes occurred.

3. Exploratory case study

An exploratory case study collects information that will answer a question. It can help researchers better understand social, economic, political or other social phenomena.

There are several other ways to categorize case studies. They may be chronological case studies, where a researcher observes events over time. In the comparative case study, the researcher compares one or more groups of people, places, or things to draw conclusions about them. In an intervention case study, the researcher intervenes to change the behavior of the subjects. The study method depends on the needs of the research team.

Deciding how to analyze the information at our disposal is an important part of effective management. An understanding of the case study model can help. With Harappa’s Thinking Critically course, managers and young professionals receive input and training on how to level up their analytic skills. Knowledge of frameworks, reading real-life examples and lived wisdom of faculty come together to create a dynamic and exciting course that helps teams leap to the next level.

Explore Harappa Diaries to learn more about topics such as Objectives Of Research , What are Qualitative Research Methods , How To Make A Problem Statement and How To Improve your Cognitive Skills to upgrade your knowledge and skills.

Case Studies

Case studies are a popular research method in business area. Case studies aim to analyze specific issues within the boundaries of a specific environment, situation or organization.

According to its design, case studies in business research can be divided into three categories: explanatory, descriptive and exploratory.

Explanatory case studies aim to answer ‘how’ or ’why’ questions with little control on behalf of researcher over occurrence of events. This type of case studies focus on phenomena within the contexts of real-life situations. Example: “An investigation into the reasons of the global financial and economic crisis of 2008 – 2010.”

Descriptive case studies aim to analyze the sequence of interpersonal events after a certain amount of time has passed. Studies in business research belonging to this category usually describe culture or sub-culture, and they attempt to discover the key phenomena. Example: “Impact of increasing levels of multiculturalism on marketing practices: A case study of McDonald’s Indonesia.”

Exploratory case studies aim to find answers to the questions of ‘what’ or ‘who’. Exploratory case study data collection method is often accompanied by additional data collection method(s) such as interviews, questionnaires, experiments etc. Example: “A study into differences of leadership practices between private and public sector organizations in Atlanta, USA.”

Advantages of case study method include data collection and analysis within the context of phenomenon, integration of qualitative and quantitative data in data analysis, and the ability to capture complexities of real-life situations so that the phenomenon can be studied in greater levels of depth. Case studies do have certain disadvantages that may include lack of rigor, challenges associated with data analysis and very little basis for generalizations of findings and conclusions.

John Dudovskiy

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• Case Study | Definition, Examples & Methods

Case Study | Definition, Examples & Methods

Published on 5 May 2022 by Shona McCombes . Revised on 30 January 2023.

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

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

Table of contents

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

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

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

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

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

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

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

If you find yourself aiming to simultaneously investigate and solve an issue, consider conducting action research . As its name suggests, action research conducts research and takes action at the same time, and is highly iterative and flexible. 

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

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

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

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

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

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

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

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

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

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

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Home » Research Methodology – Types, Examples and writing Guide

Research Methodology – Types, Examples and writing Guide

Table of Contents

Research Methodology

Definition:

Research Methodology refers to the systematic and scientific approach used to conduct research, investigate problems, and gather data and information for a specific purpose. It involves the techniques and procedures used to identify, collect , analyze , and interpret data to answer research questions or solve research problems . Moreover, They are philosophical and theoretical frameworks that guide the research process.

Structure of Research Methodology

Research methodology formats can vary depending on the specific requirements of the research project, but the following is a basic example of a structure for a research methodology section:

I. Introduction

• Provide an overview of the research problem and the need for a research methodology section
• Outline the main research questions and objectives

II. Research Design

• Explain the research design chosen and why it is appropriate for the research question(s) and objectives
• Discuss any alternative research designs considered and why they were not chosen
• Describe the research setting and participants (if applicable)

III. Data Collection Methods

• Describe the methods used to collect data (e.g., surveys, interviews, observations)
• Explain how the data collection methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or instruments used for data collection

IV. Data Analysis Methods

• Describe the methods used to analyze the data (e.g., statistical analysis, content analysis )
• Explain how the data analysis methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or software used for data analysis

V. Ethical Considerations

• Discuss any ethical issues that may arise from the research and how they were addressed
• Explain how informed consent was obtained (if applicable)
• Detail any measures taken to ensure confidentiality and anonymity

VI. Limitations

• Identify any potential limitations of the research methodology and how they may impact the results and conclusions

VII. Conclusion

• Summarize the key aspects of the research methodology section
• Explain how the research methodology addresses the research question(s) and objectives

Research Methodology Types

Types of Research Methodology are as follows:

Quantitative Research Methodology

This is a research methodology that involves the collection and analysis of numerical data using statistical methods. This type of research is often used to study cause-and-effect relationships and to make predictions.

Qualitative Research Methodology

This is a research methodology that involves the collection and analysis of non-numerical data such as words, images, and observations. This type of research is often used to explore complex phenomena, to gain an in-depth understanding of a particular topic, and to generate hypotheses.

Mixed-Methods Research Methodology

This is a research methodology that combines elements of both quantitative and qualitative research. This approach can be particularly useful for studies that aim to explore complex phenomena and to provide a more comprehensive understanding of a particular topic.

Case Study Research Methodology

This is a research methodology that involves in-depth examination of a single case or a small number of cases. Case studies are often used in psychology, sociology, and anthropology to gain a detailed understanding of a particular individual or group.

Action Research Methodology

This is a research methodology that involves a collaborative process between researchers and practitioners to identify and solve real-world problems. Action research is often used in education, healthcare, and social work.

Experimental Research Methodology

This is a research methodology that involves the manipulation of one or more independent variables to observe their effects on a dependent variable. Experimental research is often used to study cause-and-effect relationships and to make predictions.

Survey Research Methodology

This is a research methodology that involves the collection of data from a sample of individuals using questionnaires or interviews. Survey research is often used to study attitudes, opinions, and behaviors.

Grounded Theory Research Methodology

This is a research methodology that involves the development of theories based on the data collected during the research process. Grounded theory is often used in sociology and anthropology to generate theories about social phenomena.

Research Methodology Example

An Example of Research Methodology could be the following:

Research Methodology for Investigating the Effectiveness of Cognitive Behavioral Therapy in Reducing Symptoms of Depression in Adults

Introduction:

The aim of this research is to investigate the effectiveness of cognitive-behavioral therapy (CBT) in reducing symptoms of depression in adults. To achieve this objective, a randomized controlled trial (RCT) will be conducted using a mixed-methods approach.

Research Design:

The study will follow a pre-test and post-test design with two groups: an experimental group receiving CBT and a control group receiving no intervention. The study will also include a qualitative component, in which semi-structured interviews will be conducted with a subset of participants to explore their experiences of receiving CBT.

Participants:

Participants will be recruited from community mental health clinics in the local area. The sample will consist of 100 adults aged 18-65 years old who meet the diagnostic criteria for major depressive disorder. Participants will be randomly assigned to either the experimental group or the control group.

Intervention :

The experimental group will receive 12 weekly sessions of CBT, each lasting 60 minutes. The intervention will be delivered by licensed mental health professionals who have been trained in CBT. The control group will receive no intervention during the study period.

Data Collection:

Quantitative data will be collected through the use of standardized measures such as the Beck Depression Inventory-II (BDI-II) and the Generalized Anxiety Disorder-7 (GAD-7). Data will be collected at baseline, immediately after the intervention, and at a 3-month follow-up. Qualitative data will be collected through semi-structured interviews with a subset of participants from the experimental group. The interviews will be conducted at the end of the intervention period, and will explore participants’ experiences of receiving CBT.

Data Analysis:

Quantitative data will be analyzed using descriptive statistics, t-tests, and mixed-model analyses of variance (ANOVA) to assess the effectiveness of the intervention. Qualitative data will be analyzed using thematic analysis to identify common themes and patterns in participants’ experiences of receiving CBT.

Ethical Considerations:

This study will comply with ethical guidelines for research involving human subjects. Participants will provide informed consent before participating in the study, and their privacy and confidentiality will be protected throughout the study. Any adverse events or reactions will be reported and managed appropriately.

Data Management:

All data collected will be kept confidential and stored securely using password-protected databases. Identifying information will be removed from qualitative data transcripts to ensure participants’ anonymity.

Limitations:

One potential limitation of this study is that it only focuses on one type of psychotherapy, CBT, and may not generalize to other types of therapy or interventions. Another limitation is that the study will only include participants from community mental health clinics, which may not be representative of the general population.

Conclusion:

This research aims to investigate the effectiveness of CBT in reducing symptoms of depression in adults. By using a randomized controlled trial and a mixed-methods approach, the study will provide valuable insights into the mechanisms underlying the relationship between CBT and depression. The results of this study will have important implications for the development of effective treatments for depression in clinical settings.

How to Write Research Methodology

Writing a research methodology involves explaining the methods and techniques you used to conduct research, collect data, and analyze results. It’s an essential section of any research paper or thesis, as it helps readers understand the validity and reliability of your findings. Here are the steps to write a research methodology:

• Start by explaining your research question: Begin the methodology section by restating your research question and explaining why it’s important. This helps readers understand the purpose of your research and the rationale behind your methods.
• Describe your research design: Explain the overall approach you used to conduct research. This could be a qualitative or quantitative research design, experimental or non-experimental, case study or survey, etc. Discuss the advantages and limitations of the chosen design.
• Discuss your sample: Describe the participants or subjects you included in your study. Include details such as their demographics, sampling method, sample size, and any exclusion criteria used.
• Describe your data collection methods : Explain how you collected data from your participants. This could include surveys, interviews, observations, questionnaires, or experiments. Include details on how you obtained informed consent, how you administered the tools, and how you minimized the risk of bias.
• Explain your data analysis techniques: Describe the methods you used to analyze the data you collected. This could include statistical analysis, content analysis, thematic analysis, or discourse analysis. Explain how you dealt with missing data, outliers, and any other issues that arose during the analysis.
• Discuss the validity and reliability of your research : Explain how you ensured the validity and reliability of your study. This could include measures such as triangulation, member checking, peer review, or inter-coder reliability.
• Acknowledge any limitations of your research: Discuss any limitations of your study, including any potential threats to validity or generalizability. This helps readers understand the scope of your findings and how they might apply to other contexts.
• Provide a summary: End the methodology section by summarizing the methods and techniques you used to conduct your research. This provides a clear overview of your research methodology and helps readers understand the process you followed to arrive at your findings.

When to Write Research Methodology

Research methodology is typically written after the research proposal has been approved and before the actual research is conducted. It should be written prior to data collection and analysis, as it provides a clear roadmap for the research project.

The research methodology is an important section of any research paper or thesis, as it describes the methods and procedures that will be used to conduct the research. It should include details about the research design, data collection methods, data analysis techniques, and any ethical considerations.

The methodology should be written in a clear and concise manner, and it should be based on established research practices and standards. It is important to provide enough detail so that the reader can understand how the research was conducted and evaluate the validity of the results.

Applications of Research Methodology

Here are some of the applications of research methodology:

• To identify the research problem: Research methodology is used to identify the research problem, which is the first step in conducting any research.
• To design the research: Research methodology helps in designing the research by selecting the appropriate research method, research design, and sampling technique.
• To collect data: Research methodology provides a systematic approach to collect data from primary and secondary sources.
• To analyze data: Research methodology helps in analyzing the collected data using various statistical and non-statistical techniques.
• To test hypotheses: Research methodology provides a framework for testing hypotheses and drawing conclusions based on the analysis of data.
• To generalize findings: Research methodology helps in generalizing the findings of the research to the target population.
• To develop theories : Research methodology is used to develop new theories and modify existing theories based on the findings of the research.
• To evaluate programs and policies : Research methodology is used to evaluate the effectiveness of programs and policies by collecting data and analyzing it.
• To improve decision-making: Research methodology helps in making informed decisions by providing reliable and valid data.

Purpose of Research Methodology

Research methodology serves several important purposes, including:

• To guide the research process: Research methodology provides a systematic framework for conducting research. It helps researchers to plan their research, define their research questions, and select appropriate methods and techniques for collecting and analyzing data.
• To ensure research quality: Research methodology helps researchers to ensure that their research is rigorous, reliable, and valid. It provides guidelines for minimizing bias and error in data collection and analysis, and for ensuring that research findings are accurate and trustworthy.
• To replicate research: Research methodology provides a clear and detailed account of the research process, making it possible for other researchers to replicate the study and verify its findings.
• To advance knowledge: Research methodology enables researchers to generate new knowledge and to contribute to the body of knowledge in their field. It provides a means for testing hypotheses, exploring new ideas, and discovering new insights.
• To inform decision-making: Research methodology provides evidence-based information that can inform policy and decision-making in a variety of fields, including medicine, public health, education, and business.

Advantages of Research Methodology

Research methodology has several advantages that make it a valuable tool for conducting research in various fields. Here are some of the key advantages of research methodology:

• Systematic and structured approach : Research methodology provides a systematic and structured approach to conducting research, which ensures that the research is conducted in a rigorous and comprehensive manner.
• Objectivity : Research methodology aims to ensure objectivity in the research process, which means that the research findings are based on evidence and not influenced by personal bias or subjective opinions.
• Replicability : Research methodology ensures that research can be replicated by other researchers, which is essential for validating research findings and ensuring their accuracy.
• Reliability : Research methodology aims to ensure that the research findings are reliable, which means that they are consistent and can be depended upon.
• Validity : Research methodology ensures that the research findings are valid, which means that they accurately reflect the research question or hypothesis being tested.
• Efficiency : Research methodology provides a structured and efficient way of conducting research, which helps to save time and resources.
• Flexibility : Research methodology allows researchers to choose the most appropriate research methods and techniques based on the research question, data availability, and other relevant factors.
• Scope for innovation: Research methodology provides scope for innovation and creativity in designing research studies and developing new research techniques.

Research Methodology Vs Research Methods

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Prospective physics teachers must have research skills because they will later utilize and transfer these skills throughout their teaching careers. However, research shows that students' research skills, including in Indonesia, are still low. In addition to equipping students with theoretical research knowledge, an emphasis is needed on the practical stage for prospective teachers in obtaining research skills. Using a reflective case study approach with qualitative methods, this research observes and describes the implementation of research-based learning for prospective physics teachers. The research-based learning was implemented through an experiment on resistance utilizing alternative tools and materials. Data was collected through participant observation from four participants, with the researcher as the main instrument. This study shows that the implementation of research-based learning provides an opportunity for prospective physics teachers to practice research skills and apply the scientific method to solve problems. More studies are needed regarding implementing research-based learning, especially in higher education.

DeHaan, R. (2009) Teaching creativity and inventive problem solving in science. CBE—Life Sciences Education, 8(3), 172 – 181.

Diggle, P. J., Chetwynd, A., & Chetwynd, A. G. (2011). Statistics and scientific method: an introduction for students and researchers. Oxford University Press.

Dörnyei, Z. (2007). Research methods in applied linguistics. New York: Oxford University Press.

Given, L. M. (Ed.). (2008). The Sage encyclopedia of qualitative research methods. Sage publications.

Hamilton, L., & Corbett-Whittier, C. (2012). Using case study in education research. Sage.

Huy, D. T. N., & Thuy, N. T. (2021). Education for students to enhance research skills and meet demand from workplace-case in vietnam. Ilkogretim Online, 20(4).

Inyeo, C., & Wattanakasiwich, P. (2021). Pencil on paper as low cost alternative resistors. J. Phys.: Conf. Ser., 4(1).

Kapon, S. (2016). Doing research in school: Physics inquiry in the zone of proximal development. J. Res. Sci. Teach, 53(8), 1172–1197.

Laidlaw, A., Aiton, J., Struthers, J., & Guild, S. (2012). Developing research skills in medical students: AMEE Guide No. 69. Medical teacher, 34(9), 754-771.

Mcgloin, S. (2008). The trustworthiness of case study methodology. Nurse Researcher, 16(1), 45-55. doi: 10.7748/nr2008.10.16.1.45.c6752

Meerah, T. S. M., Osman, K., Zakaria, E., Ikhsan, Z. H., Krish, P., Lian, D. K. C., & Mahmod, D. (2012a). Developing an instrument to measure research skills. Procedia-Social and Behavioral Sciences, 60, 630-636.

Meerah, T. S. M., Osman, K., Zakaria, E., Ikhsan, Z. H., Krish, P., Lian, D. K. C., & Mahmod, D. (2012b). Measuring graduate students research skills. Procedia-Social and Behavioral Sciences, 60, 626-629.

Mitchell, M. (2009). Complexity: A Guided Tour. Oxford: Oxford University Press.

Murdoch-Eaton, D., Drewery, S., Elton, S., Emmerson, C., Marshall, M., Smith, J. A., ... & Whittle, S. (2010). What do medical students understand by research and research skills? Identifying research opportunities within undergraduate projects. Medical teacher, 32(3), e152-e160.

Murtonen, M., Olkinuora, E., Tynjälä, P., & Lehtinen, E. (2008). “Do I need research skills in working life?”: University students’ motivation and difficulties in quantitative methods courses. Higher Education, 56, 599-612.

Musante, K., & DeWalt, B. R. (2010). Participant observation: A guide for fieldworkers. Rowman Altamira.

Nurlaelah, I., Widodo, A., Redjeki, S., & Rahman, T. (2020, March). Student’s research skills in middle school of Kuningan district. In Journal of Physics: Conference Series (Vol. 1521, No. 4, p. 042105). IOP Publishing.

Nurzaman, I., Trimayanti, E., Zainuddin, E. S., & Khotimah, S. N. (2018). Rangkaian Listrik Menggunakan Isi Pensil. Prosiding SNIPS, 8–12.

Quintão, C., Andrade, P., & Almeida, F. (2020). How to Improve the Validity and Reliability of a Case Study Approach?. Journal of Interdisciplinary Studies in Education, 9(2), 264-275.

Riege, A. (2003). Validity and reliability tests in case study research: a literature review with “hands‐on” applications for each research phase. Qualitative Market Research, 6(2), 75-86. doi: 10.1108/13522750310470055

Roito, E., Solihat, R., & Wulan, A. R. (2019). Pencapaian Keterampilan Meneliti Abad Ke-21 Peserta Didik SMA pada Pembelajaran Ekosistem melalui Step-By-Step Model Experiment. Assimilation: Indonesian Journal of Biology Education, 2(1), 14-18.

Sears, F. W., Zemansky, M. W., Young, H. D., & Freedman, R. A. (2001). Fisika Universitas Edisi Kesepuluh Jilid 2. Erlangga: Jakarta.

Solihat, R., Rustaman, N., Widodo, A., & Saefudin, S. (2015). Keterampilan Riset Mahasiswa Biologi dan Pendidikan Biologi; Analisis Berdasarkan Refleksi Personal. Metodik Didaktik: Jurnal Pendidikan Ke-SD-an, 9(2).

Street, C. T., & Ward, K. W. (2012). Improving validity and reliability in longitudinal case study timelines. European Journal of Information Systems, 21(2), 160-175. doi: 10.1057/ejis.2011.53

Şahan, H. H., & Tarhan, R. (2015). Scientific research competencies of prospective teachers and their attitudes toward scientific resea. International Journal of Psychology and Educational Studies, 2(3), 20-31.

Taşdemir, A. (2013). The nature of science and scientific process skills. In M. Demirbaş (Eds.), The Nature of Science and its Teaching. Ankara: Pegem Academy.

Turiman, P., Omar, J., Daud, A. M., & Osman, K. (2012). Fostering the 21st century skills through scientific literacy and science process skills. Procedia-Social and Behavioral Sciences, 59, 110-116.

Walkington, H., Griffin, A. L., Keys-Mathews, L., Metoyer, S. K., Miller, W. E., Baker, R., & France, D. (2011). Embedding research-based learning early in the undergraduate geography curriculum. Journal of Geography in Higher Education, 35(3), 315-330.

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Assessment of Tunable Resistive Pulse Sensing (TRPS) Technology for Particle Size Distribution in Vaccine Formulations – A Comparative Study with Dynamic Light Scattering

• Original Research Article
• Published: 22 April 2024

Cite this article

• Rahul Misra   ORCID: orcid.org/0000-0002-9573-2778 1   na1 ,
• Ginny Fung 1   na1 ,
• Siddhant Sharma 1   na1 ,
• Jian Hu 1   na1 &
• Marina Kirkitadze 1   na1  

A comparative assessment was performed to evaluate the potential of particle sizing by an ensemble based conventional dynamic light scattering (DLS) technique and an emerging technology based on tunable resistive pulse sensing (TRPS) using particle by particle approach by evaluating three different types of vaccine formulations representing three case studies and showing the limitation of each technique, instrument variability, sensitivity, and the resolution in mixed population.

Three types of in-house vaccine formulations- a protein antigen, an outer membrane vesicle and viral particles were simultaneously evaluated by TRPS based Exoid and two DLS instruments-Zetatrac and Zetasizer for particle size distribution, aggregates, and resolution of polydisperse species.

The data from first case study show the risk of possible size overestimation and size averaging in polydisperse samples in DLS measurements which can be addressed by the TRPS analysis. It also shows how TRPS may be utilized only to large size antigens due to its limited size range. The second case study highlights the difference in the sensitivities of two DLS instruments working on the same principle. The third case study show that how TRPS can better resolve the large aggregate species compare to DLS in polydisperse samples.

This analysis shows that TRPS can be used as an orthogonal technique in addition to conventional DLS based methods for more precise and in-depth characterization. Both techniques are efficient in size characterization and produce comparable results, however the choice will depend on the type of formulation and size range to be evaluated.

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Oyewumi MO, Kumar A, Cui Z. Nano-microparticles as immune adjuvants: correlating particle sizes and the resultant immune responses. Expert Rev Vaccines. 2010;9(9):1095–107.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Rech J, Fradkin A, Krueger A, Kraft C, Paskiet D. Evaluation of Particle Techniques for the Characterization of Subvisible Particles From Elastomeric Closure Components. J Pharm Sci. 2020;109(5):1725–35.

Article   CAS   PubMed   Google Scholar  

Moussa EM, Kotarek J, Blum JS, Marszal E, Topp EM. Physical Characterization and Innate Immunogenicity of Aggregated Intravenous Immunoglobulin (IGIV) in an In Vitro Cell-Based Model. Pharm Res. 2016;33(7):1736–51.

Shomali M, Freitag A, Engert J, Siedler M, Kaymakcalan Z, Winter G, et al . Antibody responses in mice to particles formed from adsorption of a murine monoclonal antibody onto glass microparticles. J Pharm Sci. 2014;103(1):78–89.

Kotarek J, Stuart C, De Paoli SH, Simak J, Lin TL, Gao Y, et al . Subvisible Particle Content, Formulation, and Dose of an Erythropoietin Peptide Mimetic Product Are Associated With Severe Adverse Postmarketing Events. J Pharm Sci. 2016;105(3):1023–7.

Hassett KJ, Higgins J, Woods A, Levy B, Xia Y, Hsiao CJ, et al . Impact of lipid nanoparticle size on mRNA vaccine immunogenicity. J Control Release. 2021;335:237–46.

Bachmann MF, Jennings GT. Vaccine delivery: a matter of size, geometry, kinetics and molecular patterns. Nat Rev Immunol. 2010;10(11):787–96.

Benne N, van Duijn J, Kuiper J, Jiskoot W, Slutter B. Orchestrating immune responses: How size, shape and rigidity affect the immunogenicity of particulate vaccines. J Control Release. 2016;234:124–34.

Hong X, Zhong X, Du G, Hou Y, Zhang Y, Zhang Z, et al . The pore size of mesoporous silica nanoparticles regulates their antigen delivery efficiency. Sci Adv. 2020;6(25):eaaz4462.

Wang X, Li X, Ito A, Sogo Y, Ohno T. Particle-size-dependent toxicity and immunogenic activity of mesoporous silica-based adjuvants for tumor immunotherapy. Acta Biomater. 2013;9(7):7480–9.

Wang W, Roberts CJ. Protein aggregation - Mechanisms, detection, and control. Int J Pharm. 2018;550(1–2):251–68.

Gross-Rother J, Blech M, Preis E, Bakowsky U, Garidel P. Particle detection and characterization for biopharmaceutical applications: Current principles of established and alternative techniques. Pharmaceutics. 2020;12(11).  https://doi.org/10.3390/pharmaceutics12111112 .

Mukesh Kumar Singh, Annika Singh. Chapter 15 - Particle size analysis, Characterization of Polymers and Fibres, Sep19, 2021. Elsevier Publishing; 2022.

Markova N, Cairns S, Jankevics-Jones H, Kaszuba M, Caputo F, Parot J. Biophysical characterization of viral and lipid-based vectors for vaccines and therapeutics with light scattering and calorimetric techniques. Vaccines (Basel). 2021;10(1):49.  https://doi.org/10.3390/vaccines10010049 .

Justino IA, Marincek A, Ferreira IRS, Amaral RLF, Fontanezi BB, Aldana-Mejia JA, et al . Brazilian red propolis extract free and encapsulated into polymeric nanoparticles against ovarian cancer: formulation, characterisation and biological assays in 2D and 3D models. J Pharm Pharmacol. 2023;75(6):806–18.

Article   PubMed   Google Scholar  

Zheng T, Bott S, Huo Q. Techniques for Accurate Sizing of Gold Nanoparticles Using Dynamic Light Scattering with Particular Application to Chemical and Biological Sensing Based on Aggregate Formation. ACS Appl Mater Interfaces. 2016;8(33):21585–94.

Kalbfleisch K, Deshmukh S, Mei C, Ore M, Williams W, Durowoju I, et al . Identity, Structure and Compositional Analysis of Aluminum Phosphate Adsorbed Pediatric Quadrivalent and Pentavalent Vaccines. Comput Struct Biotechnol J. 2019;17:14–20.

Gerzon G, Sheng Y, Kirkitadze M. Process Analytical Technologies - Advances in bioprocess integration and future perspectives. J Pharm Biomed Anal. 2022;207:114379.

Kirkitadze M, Remi E, Bhandal K, Carpick B. Visible and subvisible particles in the BCG immunotherapeutic product Immucyst(R). Comput Struct Biotechnol J. 2016;14:154–60.

Pan R, Hu K, Jia R, Rotenberg SA, Jiang D, Mirkin MV. Resistive-Pulse Sensing Inside Single Living Cells. J Am Chem Soc. 2020;142(12):5778–84.

Garboczi EJ. The influence of particle shape on the results of the electrical sensing zone method as explained by the particle intrinsic conductivity. Powder Technolog. 2017;322:32–40.

Article   CAS   Google Scholar  

Stelzl A, Grabarek A, Schneid S, Jiskoot W, Menzen T, Winter G. Comparison of Submicron Particle Counting Methods with a Heat Stressed Monoclonal Antibody: Effect of Electrolytes and Implications on Sample Preparation. J Pharm Sci. 2022;111(7):1992–9.

Kozak D, Anderson W, Vogel R, Trau M. Advances in Resistive Pulse Sensors: Devices bridging the void between molecular and microscopic detection. Nano Today. 2011;6(5):531–45.

Emma LCJ, Blundell LJM, Billinge ER, Platt M. Emergence of tunable resistive pulse sensing as a biosensor. Anal Methods. 2015;7:7055–66.

Article   Google Scholar  

Weatherall E, Willmott GR. Applications of tunable resistive pulse sensing. Analyst. 2015;140(10):3318–34.

van der Pol E, Coumans FA, Grootemaat AE, Gardiner C, Sargent IL, Harrison P, et al . Particle size distribution of exosomes and microvesicles determined by transmission electron microscopy, flow cytometry, nanoparticle tracking analysis, and resistive pulse sensing. J Thromb Haemost. 2014;12(7):1182–92.

Pal AK, Aalaei I, Gadde S, Gaines P, Schmidt D, Demokritou P, et al . High resolution characterization of engineered nanomaterial dispersions in complex media using tunable resistive pulse sensing technology. ACS Nano. 2014;8(9):9003–15.

Farkas K, Pang L, Lin S, Williamson W, Easingwood R, Fredericks R, et al. A gel filtration-based method for the purification of infectious rotavirus particles for environmental research applications. Food Environ Virol. 2013;5:231–5. https://doi.org/10.1007/s12560-013-9122-4 .

Chung MC, Dean S, Marakasova ES, Nwabueze AO, van Hoek ML. Chitinases are negative regulators of Francisella novicida biofilms. PLoS ONE. 2014;9(3):e93119.

Article   PubMed   PubMed Central   Google Scholar  

Balhuizen MD, Veldhuizen EJA, Haagsman HP. Outer Membrane Vesicle Induction and Isolation for Vaccine Development. Front Microbiol. 2021;12:629090.

Colby AH, Colson YL, Grinstaff MW. Microscopy and tunable resistive pulse sensing characterization of the swelling of pH-responsive, polymeric expansile nanoparticles. Nanoscale. 2013;5(8):3496–504.

Nooraei S, Bahrulolum H, Hoseini ZS, Katalani C, Hajizade A, Easton AJ, et al . Virus-like particles: preparation, immunogenicity and their roles as nanovaccines and drug nanocarriers. J Nanobiotechnol. 2021;19(1):59.

United States Pharmacopeia (2023). General Chapter, 〈729〉 Globule Size Distribution in Lipid Injectable Emulsions. USP-NF. Rockville, MD: United States Pharmacopeia. The United States Pharmacopeial Convention. 2023.

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Acknowledgements

Authors would like to thank Jean-Sébastien Bolduc (Sanofi) for providing the proofreading and editorial support.

This study was funded by Sanofi.

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Rahul Misra, Ginny Fung, Siddhant Sharma, Jian Hu, Marina Kirkitadze are authors have equal contribution.

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Vaccine CMC Development and Supply, Analytical Sciences, Sanofi, Toronto, Ontario, M2R 3T4, Canada

Rahul Misra, Ginny Fung, Siddhant Sharma, Jian Hu & Marina Kirkitadze

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All authors substantially contributed to the conception or design of the work, or the acquisition, analysis, or interpretation of data for the work, and provide final approval of the version to be published. R.M., G.F., S.S., J.H. and M.K. contributed to drafting the work and revising it critically for important intellectual content.

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Correspondence to Rahul Misra .

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Rahul Misra, Jian Hu, Ginny Fung, Siddhant Sharma and Marina Kirkitadze are Sanofi employees and may hold shares and/or stock options in the company. The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript.

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Misra, R., Fung, G., Sharma, S. et al. Assessment of Tunable Resistive Pulse Sensing (TRPS) Technology for Particle Size Distribution in Vaccine Formulations – A Comparative Study with Dynamic Light Scattering. Pharm Res (2024). https://doi.org/10.1007/s11095-024-03698-y

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Published : 22 April 2024

DOI : https://doi.org/10.1007/s11095-024-03698-y

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• Survey Methods

Can machines compete with humans in transcribing audio? A case study using sermons from U.S. religious services

A 2019 Pew Research Center study and follow-up study in 2020 involved the complicated task of transcribing more than 60,000 audio and video files of sermons delivered during religious services at churches around the United States. The primary goal of this research was to evaluate relatively broad topics discussed in the sermons to determine if there were any notable patterns or denominational differences in their length and subject matter.

The huge number of audio and video files meant that it would have been too time-consuming and expensive to ask humans to transcribe all the sermons. Instead, we used Amazon Transcribe , a speech recognition service offered by Amazon Web Services (AWS). We hoped to identify the key themes in the sermons we collected, even if the machine transcriptions were not perfect or at times lacked elements like punctuation that would often come with a traditional human transcription service.

Overall, the machine transcriptions were legible. But we did run into a few challenges. The Amazon service did not always get specific religious terminology or names right. (A few examples included “punches pilot” instead of “Pontius Pilate” and “do Toronto me” in lieu of “Deuteronomy.”) There were also some recordings for which the machine transcription was simply of low quality across the board.

A notable body of research has found that machine transcription sometimes struggles with certain accents or dialects , like regional Southern accents and African American English (AAE). This led us to wonder if the errors we were seeing in the machine transcripts of sermons was coincidental, or if we were encountering performance biases that could be making some transcriptions more reliable than others in a way that might affect the conclusions of our research.

Since we downloaded our sermon files directly as audio or audio/video, we lacked an original written transcript to compare against the machine-transcribed text. Instead, as a test, we asked a third-party human transcription service to tackle portions of some of the sermons that Amazon Transcribe had already transcribed and then compared the results between the two.

What we did

For this experiment, we were interested in using sermons that included a variety of regional accents and dialects among the speakers. One obvious challenge, however, was that we didn’t know much about the speakers themselves. We knew the location of the church where the sermon was delivered, as well as its religious tradition, but these were not necessarily sufficient to assign an accent or a dialect to the person speaking in a recording. We could only use these features as approximations.

With that caveat in mind, we focused the analysis on audio files from the four main religious traditions for which we had a reportable sample size: mainline Protestant, evangelical Protestant, historically Black Protestant and Catholic. We also examined three large geographic regions: the Midwest, the South and a combined region that merges the Northeast and the West (again to account small sample sizes in those two regions).

We took a stratified random sample of 200 sermons from churches for each combination of religious tradition and region, proportional to the number of sermons each church had in the dataset. From this sample of full audio files, we took one random snippet of audio with a duration of 30 to 210 seconds from each file and sent those audio snippets to our external human transcription service. This service was a standard online provider that claimed to have native language speakers, a multistep quality check process and experience transcribing religious content, including sermons specifically. At the end of this process, we had a total sample size of 2,387 texts with both machine and human transcriptions.

How we compared transcriptions

There are a variety of computational methods to measure the similarity or difference between two sets of text. In this analysis, we used a metric known as Levenshtein distance to compare our machine and human transcriptions.

Levenshtein distance counts the number of discrete edits – insertions, deletions and substitutions – at the character level necessary to transform one text string into another. For example, if the word “COVID” is transcribed as “cove in,” there is a Levenshtein distance of three, as the transformation requires three edits: one edit to add a space between the “v” and the “i,” one edit to add an “e” after the “v,” and one edit to substitute the “d” for an “n.”

Levenshtein distance is useful as a comparison metric because it can be normalized and used to compare texts of different lengths. It also allows for nuance by focusing on character-level edits rather than entire words, providing more granularity than something like simple word error rate by scoring how incorrect a mistranscription is.

As a final bit of housekeeping, we standardized both our machine and human transcriptions to make sure that they matched one another stylistically. We transformed all the text into lower case, spelled out numbers and symbols when appropriate, and removed punctuation, filler words and words associated with vocalizations (such as “uh” or “ooh”). We also removed the “[UNINTELLIGIBLE]” annotations that the human transcription service included at our request to flag cases in which someone was speaking but their words couldn’t be clearly understood.

Across all the audio files we evaluated, the average difference between machine transcriptions and human transcriptions was around 11 characters per 100. That is, for every 100 characters in a transcription text, approximately 11 differed from one transcription method to the other.

We were also interested in looking at the difference across religious traditions and geographical regions. To do so, we used pairwise t-tests to test for differences in means across all religious traditions and all regions. (We did not calculate comparisons between each religious tradition and region combination after determining the interaction of the two variables was not statistically significant.)

The analysis found a small but statistically significant difference in Levenshtein distances between machine and human transcriptions for several religious traditions. Text taken from Catholic sermons, for example, had more inconsistency between transcripts than was true of those taken from evangelical Protestant sermons. And sermons from historically Black Protestant churches had significantly more inconsistency in transcriptions when compared with the other religious traditions.

While these differences were statistically significant, their magnitude was relatively small. Even for historically Black Protestant sermons – the tradition with the largest mismatch between machines and humans – the differences worked out to around just 15 characters per 100, or four more than the overall average. It’s also important to remember that we cannot assume the speaker is speaking AAE simply because the sermon was given in a historically Black Protestant church.

One expectation we had going into this experiment is that machine transcription would perform worst with Southern accents. However, we found that transcriptions of sermons from churches in the Midwest had significantly more inconsistency between machine and human transcriptions than those in other regions. Anecdotally, it appears this discrepancy may be because human transcribers had more difficulty than machines in understanding speakers in the Midwest: Sermon texts from the Midwest that were transcribed by humans included a greater number of “[UNINTELLIGIBLE]” annotations than those from other regions. There may also be other factors affecting transcription quality that we cannot account for, such as the possibility that sermons from the Midwest had systematically worse audio quality than those from other regions.

Again, although these differences were statistically significant, their magnitude was relatively small. Midwestern sermons, despite having the greatest inconsistency across regions, had only two more character differences per 100 characters than the overall average.

Conclusions and suggestions

In social science research, automated transcription services have become a popular alternative to human transcription because of the costs and labor involved in the latter. All in all, we found that the machine transcriptions and the human transcriptions used in this experiment were comparable enough to justify our decision to use an automated service in our research on U.S. sermons.

However, our experience does suggest a few ideas that researchers should keep in mind should they find themselves in a similar situation.

First, issues with transcription quality can be tied to the quality of the audio being transcribed – which presents challenges for humans and computers alike. By the same token, machine transcription may perform worse or better on certain accents or dialects – but that’s also true for human transcribers.  When working with audio that has specialized vocabulary (in our case, religious terms), human transcribers sometimes made errors where machines did not. This is likely because a robust machine transcription service will have a larger dictionary of familiar terms than the average person. Similarly, we found that humans are more likely to make typos, something one will not run into with machine transcription.

More generally, reliability is usually an advantage of machine transcription. Human transcription can vary in quality based on the service used, and possibly from one transcript to another if there are multiple human transcribers. But the reliability of machine transcription can sometimes backfire. When presented with a segment of tricky audio, for example, humans can determine that the text is “unintelligible.” A machine, on the other hand, will try to match the sounds it hears as closely as possible to a word it knows with little to no regard for grammar or intelligibility. While this might produce a phonetically similar transcription, it may deviate far from what the speaker truly said.

Ultimately, both machine and human transcription services can be viable options. Beyond the obvious questions of budget and timeline that are often primary considerations, we would suggest evaluating the nature of the audio files that are being analyzed before transcription begins. Audio of mixed quality, or which features competing sound from an audience, can be tricky for humans and machines alike.

Researchers should also determine how important it is to have formatting and punctuation in the text they hope to analyze. Our researchers found that the lack of these elements can be a key barrier to understanding the meaning of a particular piece of text quickly. In our case, it wasn’t an insurmountable barrier, but it certainly added a significant cognitive burden to tasks like labeling training data. And it might have posed an even bigger problem had our analysis relied more heavily on unguided methods for identifying our topics of interest.

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The case study approach

Sarah crowe.

1 Division of Primary Care, The University of Nottingham, Nottingham, UK

Kathrin Cresswell

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

Ann Robertson

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

Anthony Avery

Aziz sheikh.

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.

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 ​ Tables1, 1 , ​ ,2, 2 , ​ ,3 3 and ​ and4) 4 ) and those of others to illustrate our discussion[ 3 - 7 ].

Example of a case study investigating the reasons for differences in recruitment rates of minority ethnic people in asthma research[ 3 ]

Example of a case study investigating the process of planning and implementing a service in Primary Care Organisations[ 4 ]

Example of a case study investigating the introduction of the electronic health records[ 5 ]

Example of a case study investigating the formal and informal ways students learn about patient safety[ 6 ]

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 ​ (Table5), 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.

Definitions of a case study

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 ​ (Table1), 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 ​ Tables2, 2 , ​ ,3 3 and ​ and4) 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 ​ (Table2) 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 ​ Tables2 2 and ​ and3, 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 ​ (Table4 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 ​ (Table6). 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 ].

Example of epistemological approaches that may be used in case study research

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 ​ Table7 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 ].

Example of a checklist for rating a case study proposal[ 8 ]

For example, in our evaluation of the introduction of electronic health records in English hospitals (Table ​ (Table3), 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 ​ (Table1) 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 ​ Table3) 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 ​ (Table2 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 ​ (Table1 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 ​ (Table3 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 ​ (Table4 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 ​ Table3, 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 ​ (Table4), 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 ​ Table8 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 ​ (Table9 9 )[ 8 ].

Potential pitfalls and mitigating actions when undertaking case study research

Stake's checklist for assessing the quality of a case study report[ 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.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

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.

Pre-publication history

The pre-publication history for this paper can be accessed here:

http://www.biomedcentral.com/1471-2288/11/100/prepub

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.

• Yin RK. Case study research, design and method. 4. London: Sage Publications Ltd.; 2009. [ Google Scholar ]
• Keen J, Packwood T. Qualitative research; case study evaluation. BMJ. 1995; 311 :444–446. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Sheikh A, Halani L, Bhopal R, Netuveli G, Partridge M, Car J. et al. Facilitating the Recruitment of Minority Ethnic People into Research: Qualitative Case Study of South Asians and Asthma. PLoS Med. 2009; 6 (10):1–11. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Pinnock H, Huby G, Powell A, Kielmann T, Price D, Williams S, The process of planning, development and implementation of a General Practitioner with a Special Interest service in Primary Care Organisations in England and Wales: a comparative prospective case study. Report for the National Co-ordinating Centre for NHS Service Delivery and Organisation R&D (NCCSDO) 2008. http://www.sdo.nihr.ac.uk/files/project/99-final-report.pdf
• Robertson A, Cresswell K, Takian A, Petrakaki D, Crowe S, Cornford T. et al. Prospective evaluation of the implementation and adoption of NHS Connecting for Health's national electronic health record in secondary care in England: interim findings. BMJ. 2010; 41 :c4564. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Pearson P, Steven A, Howe A, Sheikh A, Ashcroft D, Smith P. the Patient Safety Education Study Group. Learning about patient safety: organisational context and culture in the education of healthcare professionals. J Health Serv Res Policy. 2010; 15 :4–10. doi: 10.1258/jhsrp.2009.009052. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• van Harten WH, Casparie TF, Fisscher OA. The evaluation of the introduction of a quality management system: a process-oriented case study in a large rehabilitation hospital. Health Policy. 2002; 60 (1):17–37. doi: 10.1016/S0168-8510(01)00187-7. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Stake RE. The art of case study research. London: Sage Publications Ltd.; 1995. [ Google Scholar ]
• Sheikh A, Smeeth L, Ashcroft R. Randomised controlled trials in primary care: scope and application. Br J Gen Pract. 2002; 52 (482):746–51. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• King G, Keohane R, Verba S. Designing Social Inquiry. Princeton: Princeton University Press; 1996. [ Google Scholar ]
• Doolin B. Information technology as disciplinary technology: being critical in interpretative research on information systems. Journal of Information Technology. 1998; 13 :301–311. doi: 10.1057/jit.1998.8. [ CrossRef ] [ Google Scholar ]
• George AL, Bennett A. Case studies and theory development in the social sciences. Cambridge, MA: MIT Press; 2005. [ Google Scholar ]
• Eccles M. the Improved Clinical Effectiveness through Behavioural Research Group (ICEBeRG) Designing theoretically-informed implementation interventions. Implementation Science. 2006; 1 :1–8. doi: 10.1186/1748-5908-1-1. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Netuveli G, Hurwitz B, Levy M, Fletcher M, Barnes G, Durham SR, Sheikh A. Ethnic variations in UK asthma frequency, morbidity, and health-service use: a systematic review and meta-analysis. Lancet. 2005; 365 (9456):312–7. [ PubMed ] [ Google Scholar ]
• Sheikh A, Panesar SS, Lasserson T, Netuveli G. Recruitment of ethnic minorities to asthma studies. Thorax. 2004; 59 (7):634. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Hellström I, Nolan M, Lundh U. 'We do things together': A case study of 'couplehood' in dementia. Dementia. 2005; 4 :7–22. doi: 10.1177/1471301205049188. [ CrossRef ] [ Google Scholar ]
• Som CV. Nothing seems to have changed, nothing seems to be changing and perhaps nothing will change in the NHS: doctors' response to clinical governance. International Journal of Public Sector Management. 2005; 18 :463–477. doi: 10.1108/09513550510608903. [ CrossRef ] [ Google Scholar ]
• Lincoln Y, Guba E. Naturalistic inquiry. Newbury Park: Sage Publications; 1985. [ Google Scholar ]
• Barbour RS. Checklists for improving rigour in qualitative research: a case of the tail wagging the dog? BMJ. 2001; 322 :1115–1117. doi: 10.1136/bmj.322.7294.1115. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Mays N, Pope C. Qualitative research in health care: Assessing quality in qualitative research. BMJ. 2000; 320 :50–52. doi: 10.1136/bmj.320.7226.50. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Mason J. Qualitative researching. London: Sage; 2002. [ Google Scholar ]
• Brazier A, Cooke K, Moravan V. Using Mixed Methods for Evaluating an Integrative Approach to Cancer Care: A Case Study. Integr Cancer Ther. 2008; 7 :5–17. doi: 10.1177/1534735407313395. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Miles MB, Huberman M. Qualitative data analysis: an expanded sourcebook. 2. CA: Sage Publications Inc.; 1994. [ Google Scholar ]
• Pope C, Ziebland S, Mays N. Analysing qualitative data. Qualitative research in health care. BMJ. 2000; 320 :114–116. doi: 10.1136/bmj.320.7227.114. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Cresswell KM, Worth A, Sheikh A. Actor-Network Theory and its role in understanding the implementation of information technology developments in healthcare. BMC Med Inform Decis Mak. 2010; 10 (1):67. doi: 10.1186/1472-6947-10-67. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Malterud K. Qualitative research: standards, challenges, and guidelines. Lancet. 2001; 358 :483–488. doi: 10.1016/S0140-6736(01)05627-6. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Yin R. Case study research: design and methods. 2. Thousand Oaks, CA: Sage Publishing; 1994. [ Google Scholar ]
• Yin R. Enhancing the quality of case studies in health services research. Health Serv Res. 1999; 34 :1209–1224. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Green J, Thorogood N. Qualitative methods for health research. 2. Los Angeles: Sage; 2009. [ Google Scholar ]
• Howcroft D, Trauth E. Handbook of Critical Information Systems Research, Theory and Application. Cheltenham, UK: Northampton, MA, USA: Edward Elgar; 2005. [ Google Scholar ]
• Blakie N. Approaches to Social Enquiry. Cambridge: Polity Press; 1993. [ Google Scholar ]
• Doolin B. Power and resistance in the implementation of a medical management information system. Info Systems J. 2004; 14 :343–362. doi: 10.1111/j.1365-2575.2004.00176.x. [ CrossRef ] [ Google Scholar ]
• Bloomfield BP, Best A. Management consultants: systems development, power and the translation of problems. Sociological Review. 1992; 40 :533–560. [ Google Scholar ]
• Shanks G, Parr A. Proceedings of the European Conference on Information Systems. Naples; 2003. Positivist, single case study research in information systems: A critical analysis. [ Google Scholar ]

ORIGINAL RESEARCH article

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Rewilding in Practice

Developing guidelines and a theory of change framework for rewilding application based on an empirical study of rewilding practice Provisionally Accepted

• 1 University of Cumbria, United Kingdom
• 2 University of Leeds, United Kingdom

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There remain a number of debates and conflicts about the concept of rewilding which can be barriers to its application. Some of these conflicts stem from the variety of contextual interpretations of rewilding, leading to conflict between rewilding theories and approaches.Conclusions have also been drawn about rewilding based on limited case studies, so that emergent rewilding theories aren't applicable to all rewilding projects, limiting their support in the field. Past theories have distinguished different types of rewilding, encouraging debate over the proposed methods, although in practice these approaches often share similar goals and use similar interventions. One barrier to achieving consensus in the practice of rewilding is that there are no clear guidelines for rewilding, and there are limited broad-scale studies focusing on how rewilding is practiced. This paper addresses this by offering the first broad study of rewilding guidelines and interventions, using data sourced from rewilding organisations, case studies, and research. Drawing from these data, the paper offers three tools to guide rewilding practitioners: (1) an overview of guidelines for rewilding practice, (2) a list of interventions used in rewilding, considering them against rewilding goals, (3) a theory of change framework to guide rewilding application. The tools presented here will inform work towards IUCN rewilding guidelines and suggests several areas that require further consideration. We hope that this initial study of application can improve agreement and collaboration among the rewilding community.

Keywords: rewilding, Adaptive co.management, Theory of change (ToC), Transformative conservation, Rewilding and Restoring

Received: 09 Feb 2024; Accepted: 23 Apr 2024.

Copyright: © 2024 Hawkins, Convery and Carver. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Sally Hawkins, University of Cumbria, City of Carlisle, United Kingdom

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