clinical 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.

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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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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

Understanding Case Study Method in Research: A Comprehensive Guide

Table of Contents

Have you ever wondered how researchers uncover the nuanced layers of individual experiences or the intricate workings of a particular event? One of the keys to unlocking these mysteries lies in the qualitative research focusing on a single subject in its real-life context.">case study method , a research strategy that might seem straightforward at first glance but is rich with complexity and insightful potential. Let’s dive into the world of case studies and discover why they are such a valuable tool in the arsenal of research methods.

What is a Case Study Method?

At its core, the case study method is a form of qualitative research that involves an in-depth, detailed examination of a single subject, such as an individual, group, organization, event, or phenomenon. It’s a method favored when the boundaries between phenomenon and context are not clearly evident, and where multiple sources of data are used to illuminate the case from various perspectives. This method’s strength lies in its ability to provide a comprehensive understanding of the case in its real-life context.

Historical Context and Evolution of Case Studies

Case studies have been around for centuries, with their roots in medical and psychological research. Over time, their application has spread to disciplines like sociology, anthropology, business, and education. The evolution of this method has been marked by a growing appreciation for qualitative data and the rich, contextual insights it can provide, which quantitative methods may overlook.

Characteristics of Case Study Research

What sets the case study method apart are its distinct characteristics:

• Intensive Examination: It provides a deep understanding of the case in question, considering the complexity and uniqueness of each case.
• Contextual Analysis: The researcher studies the case within its real-life context, recognizing that the context can significantly influence the phenomenon.
• Multiple Data Sources: Case studies often utilize various data sources like interviews, observations, documents, and reports, which provide multiple perspectives on the subject.
• Participant’s Perspective: This method often focuses on the perspectives of the participants within the case, giving voice to those directly involved.

Types of Case Studies

There are different types of case studies, each suited for specific research objectives:

• Exploratory: These are conducted before large-scale research projects to help identify questions, select measurement constructs, and develop hypotheses.
• Descriptive: These involve a detailed, in-depth description of the case, without attempting to determine cause and effect.
• Explanatory: These are used to investigate cause-and-effect relationships and understand underlying principles of certain phenomena.
• Intrinsic: This type is focused on the case itself because the case presents an unusual or unique issue.
• Instrumental: Here, the case is secondary to understanding a broader issue or phenomenon.
• Collective: These involve studying a group of cases collectively or comparably to understand a phenomenon, population, or general condition.

The Process of Conducting a Case Study

Conducting a case study involves several well-defined steps:

• Defining Your Case: What or who will you study? Define the case and ensure it aligns with your research objectives.
• Selecting Participants: If studying people, careful selection is crucial to ensure they fit the case criteria and can provide the necessary insights.
• Data Collection: Gather information through various methods like interviews, observations, and reviewing documents.
• Data Analysis: Analyze the collected data to identify patterns, themes, and insights related to your research question.
• Reporting Findings: Present your findings in a way that communicates the complexity and richness of the case study, often through narrative.

Case Studies in Practice: Real-world Examples

Case studies are not just academic exercises; they have practical applications in every field. For instance, in business, they can explore consumer behavior or organizational strategies. In psychology, they can provide detailed insight into individual behaviors or conditions. Education often uses case studies to explore teaching methods or learning difficulties.

Advantages of Case Study Research

While the case study method has its critics, it offers several undeniable advantages:

• Rich, Detailed Data: It captures data too complex for quantitative methods.
• Contextual Insights: It provides a better understanding of the phenomena in its natural setting.
• Contribution to Theory: It can generate and refine theory, offering a foundation for further research.

Limitations and Criticism

However, it’s important to acknowledge the limitations and criticisms:

• Generalizability : Findings from case studies may not be widely generalizable due to the focus on a single case.
• Subjectivity: The researcher’s perspective may influence the study, which requires careful reflection and transparency.
• Time-Consuming: They require a significant amount of time to conduct and analyze properly.

Concluding Thoughts on the Case Study Method

The case study method is a powerful tool that allows researchers to delve into the intricacies of a subject in its real-world environment. While not without its challenges, when executed correctly, the insights garnered can be incredibly valuable, offering depth and context that other methods may miss. Robert K\. Yin ’s advocacy for this method underscores its potential to illuminate and explain contemporary phenomena, making it an indispensable part of the researcher’s toolkit.

Reflecting on the case study method, how do you think its application could change with the advancements in technology and data analytics? Could such a traditional method be enhanced or even replaced in the future?

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Research Methods in Psychology

1 Introduction to Psychological Research – Objectives and Goals, Problems, Hypothesis and Variables

• Nature of Psychological Research
• The Context of Discovery
• Context of Justification
• Characteristics of Psychological Research
• Goals and Objectives of Psychological Research

2 Introduction to Psychological Experiments and Tests

• Independent and Dependent Variables
• Extraneous Variables
• Experimental and Control Groups
• Introduction of Test
• Types of Psychological Test
• Uses of Psychological Tests

3 Steps in Research

• Research Process
• Identification of the Problem
• Review of Literature
• Formulating a Hypothesis
• Identifying Manipulating and Controlling Variables
• Formulating a Research Design
• Constructing Devices for Observation and Measurement
• Sample Selection and Data Collection
• Data Analysis and Interpretation
• Hypothesis Testing
• Drawing Conclusion

4 Types of Research and Methods of Research

• Historical Research
• Descriptive Research
• Correlational Research
• Qualitative Research
• Ex-Post Facto Research
• True Experimental Research
• Quasi-Experimental Research

5 Definition and Description Research Design, Quality of Research Design

• Research Design
• Purpose of Research Design
• Design Selection
• Criteria of Research Design
• Qualities of Research Design

6 Experimental Design (Control Group Design and Two Factor Design)

• Experimental Design
• Control Group Design
• Two Factor Design

7 Survey Design

• Survey Research Designs
• Steps in Survey Design
• Structuring and Designing the Questionnaire
• Interviewing Methodology
• Data Analysis
• Final Report

8 Single Subject Design

• Single Subject Design: Definition and Meaning
• Phases Within Single Subject Design
• Requirements of Single Subject Design
• Characteristics of Single Subject Design
• Types of Single Subject Design
• Advantages of Single Subject Design
• Disadvantages of Single Subject Design

9 Observation Method

• Definition and Meaning of Observation
• Characteristics of Observation
• Types of Observation
• Advantages and Disadvantages of Observation
• Guides for Observation Method

10 Interview and Interviewing

• Definition of Interview
• Types of Interview
• Aspects of Qualitative Research Interviews
• Interview Questions
• Convergent Interviewing as Action Research
• Research Team

11 Questionnaire Method

• Definition and Description of Questionnaires
• Types of Questionnaires
• Purpose of Questionnaire Studies
• Designing Research Questionnaires
• The Methods to Make a Questionnaire Efficient
• The Types of Questionnaire to be Included in the Questionnaire
• Advantages and Disadvantages of Questionnaire
• When to Use a Questionnaire?

12 Case Study

• Definition and Description of Case Study Method
• Historical Account of Case Study Method
• Designing Case Study
• Requirements for Case Studies
• Guideline to Follow in Case Study Method
• Other Important Measures in Case Study Method
• Case Reports

13 Report Writing

• Purpose of a Report
• Writing Style of the Report
• Report Writing – the Do’s and the Don’ts
• Format for Report in Psychology Area
• Major Sections in a Report

14 Review of Literature

• Purposes of Review of Literature
• Sources of Review of Literature
• Types of Literature
• Writing Process of the Review of Literature
• Preparation of Index Card for Reviewing and Abstracting

15 Methodology

• Definition and Purpose of Methodology
• Participants (Sample)
• Apparatus and Materials

16 Result, Analysis and Discussion of the Data

• Definition and Description of Results
• Statistical Presentation
• Tables and Figures

17 Summary and Conclusion

• Summary Definition and Description
• Guidelines for Writing a Summary
• Writing the Summary and Choosing Words
• A Process for Paraphrasing and Summarising
• Summary of a Report
• Writing Conclusions

18 References in Research Report

• Reference List (the Format)
• References (Process of Writing)
• Reference List and Print Sources
• Electronic Sources
• Book on CD Tape and Movie
• Reference Specifications
• General Guidelines to Write References

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• Volume 21, Issue 1
• What is a case study?
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• Roberta Heale 1 ,
• Alison Twycross 2
• 1 School of Nursing , Laurentian University , Sudbury , Ontario , Canada
• 2 School of Health and Social Care , London South Bank University , London , UK
• Correspondence to Dr Roberta Heale, School of Nursing, Laurentian University, Sudbury, ON P3E2C6, Canada; rheale{at}laurentian.ca

https://doi.org/10.1136/eb-2017-102845

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What is it?

Case study is a research methodology, typically seen in social and life sciences. There is no one definition of case study research. 1 However, very simply… ‘a case study can be defined as an intensive study about a person, a group of people or a unit, which is aimed to generalize over several units’. 1 A case study has also been described as an intensive, systematic investigation of a single individual, group, community or some other unit in which the researcher examines in-depth data relating to several variables. 2

Often there are several similar cases to consider such as educational or social service programmes that are delivered from a number of locations. Although similar, they are complex and have unique features. In these circumstances, the evaluation of several, similar cases will provide a better answer to a research question than if only one case is examined, hence the multiple-case study. Stake asserts that the cases are grouped and viewed as one entity, called the quintain . 6  ‘We study what is similar and different about the cases to understand the quintain better’. 6

The steps when using case study methodology are the same as for other types of research. 6 The first step is defining the single case or identifying a group of similar cases that can then be incorporated into a multiple-case study. A search to determine what is known about the case(s) is typically conducted. This may include a review of the literature, grey literature, media, reports and more, which serves to establish a basic understanding of the cases and informs the development of research questions. Data in case studies are often, but not exclusively, qualitative in nature. In multiple-case studies, analysis within cases and across cases is conducted. Themes arise from the analyses and assertions about the cases as a whole, or the quintain, emerge. 6

Benefits and limitations of case studies

If a researcher wants to study a specific phenomenon arising from a particular entity, then a single-case study is warranted and will allow for a in-depth understanding of the single phenomenon and, as discussed above, would involve collecting several different types of data. This is illustrated in example 1 below.

Using a multiple-case research study allows for a more in-depth understanding of the cases as a unit, through comparison of similarities and differences of the individual cases embedded within the quintain. Evidence arising from multiple-case studies is often stronger and more reliable than from single-case research. Multiple-case studies allow for more comprehensive exploration of research questions and theory development. 6

Despite the advantages of case studies, there are limitations. The sheer volume of data is difficult to organise and data analysis and integration strategies need to be carefully thought through. There is also sometimes a temptation to veer away from the research focus. 2 Reporting of findings from multiple-case research studies is also challenging at times, 1 particularly in relation to the word limits for some journal papers.

Examples of case studies

Example 1: nurses’ paediatric pain management practices.

One of the authors of this paper (AT) has used a case study approach to explore nurses’ paediatric pain management practices. This involved collecting several datasets:

Observational data to gain a picture about actual pain management practices.

Questionnaire data about nurses’ knowledge about paediatric pain management practices and how well they felt they managed pain in children.

Questionnaire data about how critical nurses perceived pain management tasks to be.

These datasets were analysed separately and then compared 7–9 and demonstrated that nurses’ level of theoretical did not impact on the quality of their pain management practices. 7 Nor did individual nurse’s perceptions of how critical a task was effect the likelihood of them carrying out this task in practice. 8 There was also a difference in self-reported and observed practices 9 ; actual (observed) practices did not confirm to best practice guidelines, whereas self-reported practices tended to.

Example 2: quality of care for complex patients at Nurse Practitioner-Led Clinics (NPLCs)

The other author of this paper (RH) has conducted a multiple-case study to determine the quality of care for patients with complex clinical presentations in NPLCs in Ontario, Canada. 10 Five NPLCs served as individual cases that, together, represented the quatrain. Three types of data were collected including:

Review of documentation related to the NPLC model (media, annual reports, research articles, grey literature and regulatory legislation).

Interviews with nurse practitioners (NPs) practising at the five NPLCs to determine their perceptions of the impact of the NPLC model on the quality of care provided to patients with multimorbidity.

Chart audits conducted at the five NPLCs to determine the extent to which evidence-based guidelines were followed for patients with diabetes and at least one other chronic condition.

The three sources of data collected from the five NPLCs were analysed and themes arose related to the quality of care for complex patients at NPLCs. The multiple-case study confirmed that nurse practitioners are the primary care providers at the NPLCs, and this positively impacts the quality of care for patients with multimorbidity. Healthcare policy, such as lack of an increase in salary for NPs for 10 years, has resulted in issues in recruitment and retention of NPs at NPLCs. This, along with insufficient resources in the communities where NPLCs are located and high patient vulnerability at NPLCs, have a negative impact on the quality of care. 10

These examples illustrate how collecting data about a single case or multiple cases helps us to better understand the phenomenon in question. Case study methodology serves to provide a framework for evaluation and analysis of complex issues. It shines a light on the holistic nature of nursing practice and offers a perspective that informs improved patient care.

• Gustafsson J
• Calanzaro M
• Sandelowski M

Competing interests None declared.

Provenance and peer review Commissioned; internally peer reviewed.

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Writing a case report in 10 steps

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• Victoria Stokes , foundation year 2 doctor, trauma and orthopaedics, Basildon Hospital ,
• Caroline Fertleman , paediatrics consultant, The Whittington Hospital NHS Trust
• victoria.stokes1{at}nhs.net

Victoria Stokes and Caroline Fertleman explain how to turn an interesting case or unusual presentation into an educational report

It is common practice in medicine that when we come across an interesting case with an unusual presentation or a surprise twist, we must tell the rest of the medical world. This is how we continue our lifelong learning and aid faster diagnosis and treatment for patients.

It usually falls to the junior to write up the case, so here are a few simple tips to get you started.

First steps

Begin by sitting down with your medical team to discuss the interesting aspects of the case and the learning points to highlight. Ideally, a registrar or middle grade will mentor you and give you guidance. Another junior doctor or medical student may also be keen to be involved. Allocate jobs to split the workload, set a deadline and work timeframe, and discuss the order in which the authors will be listed. All listed authors should contribute substantially, with the person doing most of the work put first and the guarantor (usually the most senior team member) at the end.

Getting consent

Gain permission and written consent to write up the case from the patient or parents, if your patient is a child, and keep a copy because you will need it later for submission to journals.

Information gathering

Gather all the information from the medical notes and the hospital’s electronic systems, including copies of blood results and imaging, as medical notes often disappear when the patient is discharged and are notoriously difficult to find again. Remember to anonymise the data according to your local hospital policy.

Write up the case emphasising the interesting points of the presentation, investigations leading to diagnosis, and management of the disease/pathology. Get input on the case from all members of the team, highlighting their involvement. Also include the prognosis of the patient, if known, as the reader will want to know the outcome.

Coming up with a title

Discuss a title with your supervisor and other members of the team, as this provides the focus for your article. The title should be concise and interesting but should also enable people to find it in medical literature search engines. Also think about how you will present your case study—for example, a poster presentation or scientific paper—and consider potential journals or conferences, as you may need to write in a particular style or format.

Background research

Research the disease/pathology that is the focus of your article and write a background paragraph or two, highlighting the relevance of your case report in relation to this. If you are struggling, seek the opinion of a specialist who may know of relevant articles or texts. Another good resource is your hospital library, where staff are often more than happy to help with literature searches.

How your case is different

Move on to explore how the case presented differently to the admitting team. Alternatively, if your report is focused on management, explore the difficulties the team came across and alternative options for treatment.

Finish by explaining why your case report adds to the medical literature and highlight any learning points.

Writing an abstract

The abstract should be no longer than 100-200 words and should highlight all your key points concisely. This can be harder than writing the full article and needs special care as it will be used to judge whether your case is accepted for presentation or publication.

Discuss with your supervisor or team about options for presenting or publishing your case report. At the very least, you should present your article locally within a departmental or team meeting or at a hospital grand round. Well done!

Competing interests: We have read and understood BMJ’s policy on declaration of interests and declare that we have no competing interests.

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What Is a Case Study?

Weighing the pros and cons of this method of research

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Cara Lustik is a fact-checker and copywriter.

Verywell / Colleen Tighe

• Pros and Cons

What Types of Case Studies Are Out There?

Where do you find data for a case study, how do i write a psychology case study.

A case study is an in-depth study of one person, group, or event. In a case study, nearly every aspect of the subject's life and history is analyzed to seek patterns and causes of behavior. Case studies can be used in many different fields, including psychology, medicine, education, anthropology, political science, and social work.

The point of a case study is to learn as much as possible about an individual or group so that the information can be generalized to many others. Unfortunately, case studies tend to be highly subjective, and it is sometimes difficult to generalize results to a larger population.

While case studies focus on a single individual or group, they follow a format similar to other types of psychology writing. If you are writing a case study, we got you—here are some rules of APA format to reference.  

At a Glance

A case study, or an in-depth study of a person, group, or event, can be a useful research tool when used wisely. In many cases, case studies are best used in situations where it would be difficult or impossible for you to conduct an experiment. They are helpful for looking at unique situations and allow researchers to gather a lot of˜ information about a specific individual or group of people. However, it's important to be cautious of any bias we draw from them as they are highly subjective.

What Are the Benefits and Limitations of Case Studies?

A case study can have its strengths and weaknesses. Researchers must consider these pros and cons before deciding if this type of study is appropriate for their needs.

One of the greatest advantages of a case study is that it allows researchers to investigate things that are often difficult or impossible to replicate in a lab. Some other benefits of a case study:

• Allows researchers to capture information on the 'how,' 'what,' and 'why,' of something that's implemented
• Gives researchers the chance to collect information on why one strategy might be chosen over another
• Permits researchers to develop hypotheses that can be explored in experimental research

On the other hand, a case study can have some drawbacks:

• It cannot necessarily be generalized to the larger population
• Cannot demonstrate cause and effect
• It may not be scientifically rigorous
• It can lead to bias

Researchers may choose to perform a case study if they want to explore a unique or recently discovered phenomenon. Through their insights, researchers develop additional ideas and study questions that might be explored in future studies.

It's important to remember that the insights from case studies cannot be used to determine cause-and-effect relationships between variables. However, case studies may be used to develop hypotheses that can then be addressed in experimental research.

Case Study Examples

There have been a number of notable case studies in the history of psychology. Much of  Freud's work and theories were developed through individual case studies. Some great examples of case studies in psychology include:

• Anna O : Anna O. was a pseudonym of a woman named Bertha Pappenheim, a patient of a physician named Josef Breuer. While she was never a patient of Freud's, Freud and Breuer discussed her case extensively. The woman was experiencing symptoms of a condition that was then known as hysteria and found that talking about her problems helped relieve her symptoms. Her case played an important part in the development of talk therapy as an approach to mental health treatment.
• Phineas Gage : Phineas Gage was a railroad employee who experienced a terrible accident in which an explosion sent a metal rod through his skull, damaging important portions of his brain. Gage recovered from his accident but was left with serious changes in both personality and behavior.
• Genie : Genie was a young girl subjected to horrific abuse and isolation. The case study of Genie allowed researchers to study whether language learning was possible, even after missing critical periods for language development. Her case also served as an example of how scientific research may interfere with treatment and lead to further abuse of vulnerable individuals.

Such cases demonstrate how case research can be used to study things that researchers could not replicate in experimental settings. In Genie's case, her horrific abuse denied her the opportunity to learn a language at critical points in her development.

This is clearly not something researchers could ethically replicate, but conducting a case study on Genie allowed researchers to study phenomena that are otherwise impossible to reproduce.

There are a few different types of case studies that psychologists and other researchers might use:

• Collective case studies : These involve studying a group of individuals. Researchers might study a group of people in a certain setting or look at an entire community. For example, psychologists might explore how access to resources in a community has affected the collective mental well-being of those who live there.
• Descriptive case studies : These involve starting with a descriptive theory. The subjects are then observed, and the information gathered is compared to the pre-existing theory.
• Explanatory case studies : These   are often used to do causal investigations. In other words, researchers are interested in looking at factors that may have caused certain things to occur.
• Exploratory case studies : These are sometimes used as a prelude to further, more in-depth research. This allows researchers to gather more information before developing their research questions and hypotheses .
• Instrumental case studies : These occur when the individual or group allows researchers to understand more than what is initially obvious to observers.
• Intrinsic case studies : This type of case study is when the researcher has a personal interest in the case. Jean Piaget's observations of his own children are good examples of how an intrinsic case study can contribute to the development of a psychological theory.

The three main case study types often used are intrinsic, instrumental, and collective. Intrinsic case studies are useful for learning about unique cases. Instrumental case studies help look at an individual to learn more about a broader issue. A collective case study can be useful for looking at several cases simultaneously.

The type of case study that psychology researchers use depends on the unique characteristics of the situation and the case itself.

There are a number of different sources and methods that researchers can use to gather information about an individual or group. Six major sources that have been identified by researchers are:

• Archival records : Census records, survey records, and name lists are examples of archival records.
• Direct observation : This strategy involves observing the subject, often in a natural setting . While an individual observer is sometimes used, it is more common to utilize a group of observers.
• Documents : Letters, newspaper articles, administrative records, etc., are the types of documents often used as sources.
• Interviews : Interviews are one of the most important methods for gathering information in case studies. An interview can involve structured survey questions or more open-ended questions.
• Participant observation : When the researcher serves as a participant in events and observes the actions and outcomes, it is called participant observation.
• Physical artifacts : Tools, objects, instruments, and other artifacts are often observed during a direct observation of the subject.

If you have been directed to write a case study for a psychology course, be sure to check with your instructor for any specific guidelines you need to follow. If you are writing your case study for a professional publication, check with the publisher for their specific guidelines for submitting a case study.

Here is a general outline of what should be included in a case study.

Section 1: A Case History

This section will have the following structure and content:

Background information : The first section of your paper will present your client's background. Include factors such as age, gender, work, health status, family mental health history, family and social relationships, drug and alcohol history, life difficulties, goals, and coping skills and weaknesses.

Description of the presenting problem : In the next section of your case study, you will describe the problem or symptoms that the client presented with.

Describe any physical, emotional, or sensory symptoms reported by the client. Thoughts, feelings, and perceptions related to the symptoms should also be noted. Any screening or diagnostic assessments that are used should also be described in detail and all scores reported.

Your diagnosis : Provide your diagnosis and give the appropriate Diagnostic and Statistical Manual code. Explain how you reached your diagnosis, how the client's symptoms fit the diagnostic criteria for the disorder(s), or any possible difficulties in reaching a diagnosis.

Section 2: Treatment Plan

This portion of the paper will address the chosen treatment for the condition. This might also include the theoretical basis for the chosen treatment or any other evidence that might exist to support why this approach was chosen.

• Cognitive behavioral approach : Explain how a cognitive behavioral therapist would approach treatment. Offer background information on cognitive behavioral therapy and describe the treatment sessions, client response, and outcome of this type of treatment. Make note of any difficulties or successes encountered by your client during treatment.
• Humanistic approach : Describe a humanistic approach that could be used to treat your client, such as client-centered therapy . Provide information on the type of treatment you chose, the client's reaction to the treatment, and the end result of this approach. Explain why the treatment was successful or unsuccessful.
• Psychoanalytic approach : Describe how a psychoanalytic therapist would view the client's problem. Provide some background on the psychoanalytic approach and cite relevant references. Explain how psychoanalytic therapy would be used to treat the client, how the client would respond to therapy, and the effectiveness of this treatment approach.
• Pharmacological approach : If treatment primarily involves the use of medications, explain which medications were used and why. Provide background on the effectiveness of these medications and how monotherapy may compare with an approach that combines medications with therapy or other treatments.

This section of a case study should also include information about the treatment goals, process, and outcomes.

When you are writing a case study, you should also include a section where you discuss the case study itself, including the strengths and limitiations of the study. You should note how the findings of your case study might support previous research. 

In your discussion section, you should also describe some of the implications of your case study. What ideas or findings might require further exploration? How might researchers go about exploring some of these questions in additional studies?

Need More Tips?

Here are a few additional pointers to keep in mind when formatting your case study:

• Never refer to the subject of your case study as "the client." Instead, use their name or a pseudonym.
• Read examples of case studies to gain an idea about the style and format.
• Remember to use APA format when citing references .

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach .  BMC Med Res Methodol . 2011;11:100.

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach . BMC Med Res Methodol . 2011 Jun 27;11:100. doi:10.1186/1471-2288-11-100

Gagnon, Yves-Chantal.  The Case Study as Research Method: A Practical Handbook . Canada, Chicago Review Press Incorporated DBA Independent Pub Group, 2010.

Yin, Robert K. Case Study Research and Applications: Design and Methods . United States, SAGE Publications, 2017.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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A Case for the Case Study: How and Why They Matter

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• Volume 45 , pages 189–200, ( 2017 )

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• Jeffrey Longhofer 1 ,
• Jerry Floersch 1 &
• Eric Hartmann 2  

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In this special issue we have asked the contributors to make a case for the case study. The guest editors, Jeffrey Longhofer, Jerry Floersch and Eric Hartmann, intergrate ideas from across the disciplines to explore the complexties of case study methods and theory. In education, Gary Thomas explores the importance of ethnographic case studies in understanding the relationships among schools, teachers, and students. Lance Dodes and Josh Dodes use the case study to articulate a psychoanalytic approach to addiction. In policy and generalist practice, Nancy Cartwright and Jeremy Hardie elaborate a model for a case-by-case approach to prediction and the swampy ground prediction serves up to practitioners. Christian Salas and Oliver Turnbull persuasively write about the role of the case study in neuro-psychoanalysis and illustrate it with a case vignette. In political science, Sanford Schram argues for a bottom up and ethnographic approach to studying policy implementation by describing a case of a home ownership program in Philadelphia. Eric Hartman queers the case study by articulating its role in deconstructing normative explanations of sexuality. In applied psychology, Daniel Fishman describes a comprehensive applied psychology perspective on the paradigmatic case study. Richard Miller and Miriam Jaffe offer us important ways of thinking about writing the case study and the use of multi-media. Each contributor brings a unique perspective to the use of the case study in their field, yet they share practical and philosophical assumptions.

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Jeffrey Longhofer & Jerry Floersch

DSW Program, Rutgers School of Social Work, New Brunswick, USA

Eric Hartmann

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Longhofer, J., Floersch, J. & Hartmann, E. A Case for the Case Study: How and Why They Matter. Clin Soc Work J 45 , 189–200 (2017). https://doi.org/10.1007/s10615-017-0631-8

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DOI : https://doi.org/10.1007/s10615-017-0631-8

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Teaching with Case Studies to Develop Clinical Reasoning

By Ann Horigan 

• Owen, M.I. (2017). A case study scavenger hunt for senior nursing students. Journal of Nursing Education, 56(3), 191. doi: 10.3928/01484834-20170222-13.  Describes the use of a case study and simulation used with a group of senior nursing students in a synthesis seminar. The purpose of the exercise in this course was to provide students with a standardized method of analyzing and synthesizing content from previous courses to help prepare them for the RN licensure exam.  Good example of using a case study with low fidelity simulation and demonstrates that students benefit from this type of exercise. However, this was done in a sim lab setting in small groups of students and does not delve into issues of using case studies in a didactic setting to establish and further clinical reasoning.
• Peery, A. (2015). Use of the unfolding case study in teaching nurse educator master of science in nursing students. Journal of Nursing Education, 54(3), 180. doi: 10.3928/01484834-20150217-11 . Course for nurse educator MSN students done in an online format which uses an unfolding case study to work through challenging issues that a nurse educator is likely to encounter. Unfolding cases promote inquiry among students and should be believable and relevant to the class. Four steps to developing an unfolding case study are discussed. Students found the exercise useful and made them aware of situations they otherwise may not have been aware of in education. It is a dynamic and engaging method for teaching and preparing for real-life scenarios. This article is helpful as it notes the steps in devising an unfolding case study and the benefits of using this type of exercise. It would be more helpful if this had been set up as a formal inquiry with specific measures of application and synthesis pre and post. As it is, it describes an experience and innovative method which is helpful.
• Kaylor, S. and Strickland, H. (2015). Unfolding case studies as a formative teaching methodology for novice nursing students.  Journal of Nursing Education, 54(2), 106-110. doi:10.3928/01484834-20150120-06. Describes a way in which unfolding case studies can be used to teach undergraduate nursing, novice students evidence based practice information rather than the case study acting as a summative evaluation of knowledge. Unfolding case studies develop over time and are unpredictable to the learner. If well done, promotes experiential education and imagination. Students picture themselves as part of the scenario. Enables students to practice making decisions and evaluating the effects of those decisions in a non-threatening environment. When this is done in small groups, students are developing decision making, communication, clinical judgment and problem solving. Helps students connect dots between theory and practice. Authors recommend that this is not the only method of active learning used throughout the semester and should be used several times but not exhaustively.  Excellent article that presents a unique active learning method with benefits, barriers, lessons learned. Would be interesting to see what students thought of it as a learning method.
• Dudas, K. (2012). Podcast and unfolding case study to promote active learning. Journal of Nursing Education, 51(8), 476. DOI:10.3928/01484834-20120719-02. Describes the use of a pre-class podcast used to give information for an unfolding case study on a patient with a neuromuscular disorder completed in class. Information from the podcast was reviewed at the beginning of class and then students were given the unfolding case study. Class reconvened and answers to the case study reviewed. Students reported feeling actively involved in learning and that clinical decision making skills improved. Students wanted these more frequently in the course. Authors state that while unfolding case studies are time consuming to prepare, the benefits from active learning outweigh the time needed.
• Utterback, V., Davenport, D. Gallegos, B. & Boyd, E. (2012). The critical difference assignment: An innovative instructional method. Journal of Nursing Education, 51(1), 42-45. DOI:10.3928/01484834-20111116-03. Describes an assignment called the Critical Difference assignment where two case studies are given to students who must use reasoning to differentiate between the 2 cases. The cases have similar patient presentations but have differing and unknown underlying pathophysiologies. Students must compare and contrast symptoms, lab results, diagnostic studies to come to an understanding of the critical difference between the 2 cases and then develop a plan of care for each case based on the similarities and differences in the cases. These studies are called companion case studies and are purposely constructed so that students must discriminate between 2 similarly presenting patient problems. The outcomes from this type of learning are that the learner can learn by themselves, learn with others, share information, and make decisions. This mirrors the ability to work with others in the clinical setting. Excellent example of how to move students thinking to the next level. Again, would be interesting to see what students thought of experience as well as any objective measures of how this has helped initiate clinical judgment or improve abilities in clinical judgment.
• Priddy, K. & Crow, M. (2011). Clinical imagination: Dynamic cast studies using an attribute listing matrix. Journal of Nursing Education, 50(10), 591-594. DOI:10.3928/01484834-20110630-03. Describes how to develop and use a matrix for choosing elements of a case study so that they are randomly generated and students have differing elements with different outcomes. It allows for more opportunities to role model and richer discussion. The number of choices on the matrix can be based on the context and the problem at hand. This can be done based on developmental level of students and where they are in the nursing curriculum. It describes the steps of how to implement this in class in detail which is very helpful. The variety of options possible gives opportunity for great discussion and generation of nursing knowledge. Great example of what can be done in smaller groups as formative or summative evaluation. Would be difficult to do in a large lecture course. Again, no objective measures of how this has pushed students to think and engage.
• Bennett, C., Kennedy, S. & Donato, A. (2011). Preparing NP’s for primary care: Unraveling complexity with unfolding cases. Journal of Nursing Education, 50(6), 328-331. doi:10.3928/01484834-20110228-05. Describes the use of Backward Design (identifying desired results, identifying evidence of learning and developing teaching methods) to design a course for nurse practitioners in a behavioral health therapeutics course. Faculty developed cases that included an initial patient encounter and follow up encounter which were video taped with actors and complications of treatment or new problems were added at follow up visits. In the final step of Backward Design, creating teaching methods, the authors used Zull’s model of learning as brain change, which encourage innovative strategies to teach in context. There is an emphasis on reflection and iterative knowledge development. The authors found that students’ iterative thought processes advanced as they were able to practice as independent clinicians in a safe and collaborative environment. Course evaluations were done based on university requirements and therefore did not evaluate this method specifically, but they state that written feedback was overwhelmingly positive. Would be nice to see objective measures of advancement of clinical thinking, maybe samples of how grades improved over the semester or how pass rates on certification exams improved.
• Beyer, D. (2011). Reverse case study: To think like a nurse. Journal of Nursing Education, 50(1), 48-50.  doi:10.3928/01484834-20101029-06. Describes combining two active learning strategies, case studies and concept mapping into a reverse case study to promote critical thinking and problem solving. The article outlines a process for creating a reverse case study to be used in small groups. They are given a blank concept map with elements of the nursing process and patient history on it, but with no specific information other than a list of medications. Students work backward from that point to devise a list of anticipated medical problems the patient probably experiences and the care for these problems. The complexity of the cases can be manipulated by the number and type of medications. Groups then present their cases and priorities. This is a unique twist on the traditional case study. It could be done at every level of nursing education and development. A lab or discussion course would probably be best, not a class of 100+ students.
• Tanner, C. (2009). The case for cases: A pedagogy for developing habits of thought. Journal of Nursing Education, 48(6), 299-300.  An editorial that argues that the use of case based learning as a method that supports experiential thinking, clinical judgment and encourages students to “think like a nurse”. No information on actual work done in classroom.
• Sandstom, S. (2006). Use of case studies to teach diabetes and other chronic illnesses to nursing students. Journal of Nursing Education, 45(6), 229-232. Case studies increase learning by “placing” them in a situation where they must use or apply knowledge learned in the classroom. They are in a real world situation with decisions to make. The use of the example case study is done in the laboratory setting about diabetes as students are learning to draw up insulin and monitor blood glucose. Discusses 2 other assignments related to diabetes content that students are assigned. The article lacks depth about how the case studies are developed and why. No objective findings of student evaluation or learning other than the author’s recitation of what has been said in lab.
• Schlenker, E. & Kerber, C. (2006). The CARE case study method for teaching community health nursing. Journal of Nursing Education, 45(4), 144. Stands for Case study, Application, Research, Evaluation. Goal of this method is to facilitate understanding of theoretical content, foster interaction between faculty and students and knowledge sharing, give opportunities to apply knowledge in the classroom. Case studies are developed based on current topics in community health nursing and introduced during class time. Students work in small groups to answer clinical questions. The authors state that this has been well received by students who are motivated and excited to come to class and have done the prep work. There is no description of how the case studies are generated other than by choosing current topics in community health nursing, there is also no further discussion of how this method is used but a generic description. More detail would be helpful.
• Loving, G. & Siow, P. (2005). Use of an online case study template in nursing education. Journal of Nursing Education, 44(8), 387-388. The authors created a template to be used in online nursing courses that was based on interactivity and feedback for faculty to use in the design of case studies. It is a set of online forms that allows faculty to enter information. Students also work through this case study and click on multiple choice answers where feedback is given. This isn’t particularly helpful information. It doesn’t inform how the body of the case should be created, the elements, whether they should unfold and how or how the students interface with the case study in detail. 
• Tarcinale, M. (1987). The case study as a vicarious learning technique. Journal of Nursing Education, 26(8), 340-341. Discusses vicarious learning or learning through imagination, which I think now 30 years later would be experiential, or situational learning. The learner will use information from previous experiences to help solve current situational problems. Components of a case study are discussed (very helpful and one of only a few articles that do this). The placement of the case study in class depends on what it would be used for. Helpful information, but I think that the case study method has evolved quite a bit over time to include the reverse and unfolding case studies. However this is a good summary of how a basic case study can be used to bring abstract concepts to more concrete understanding.
• Page, J., Kowlowitz, V. & Alden, K. (2010). Development of a scripted unfolding case study focusing on delirium in older adults. The Journal of Continuing Education in Nursing, 41(5), 225-230. DOI:10.3928/00220124-20100423-05. The article begins by talking about how simulation is an important piece of practice based learning and that continuing education for nurses should incorporate more of it. The article then goes on to describe how to develop an unfolding case study. (might be splitting hairs, but case studies and simulation are not the same, many times simulation will use a case study, but sometimes it doesn’t. And not all uses of case studies are simulation. They don’t do a good job of connecting the two in the article) The steps for developing a case study for use are outlined as well as how to review it before implementing it. The authors present data on evaluation of the case by nurses who were involved in the continuing education. This is good information, detailed in the description of how the case can be developed, presented and evaluated.
• Jones, D. & Sheridan, M., (1999). A case study approach: Developing critical thinking skills in novice pediatric nurses. The Journal of Continuing Education in Nursing, 30(2), 75-78. Key component of nursing is problem solving, but not all nurses are good at it. The use of case studies promotes problem solving and critical thinking. They can be done with real or hypothetical situations. Provides an opportunity to enact in decision making when a real clinical situation isn’t available. In novice pediatric nurses, case studies reinforce what was learned in school but also introduce them to unique situations in family focused nursing. The article goes on to describe that case studies should include certain elements and gives and example. The article does not present data on how case studies have improved novice nurses comfort level or competence in working with families and children or if novice nurses found them useful during an orientation period.
• Smallheer, B. (2016). Reverse case study: A new perspective on an existing teaching strategy. Nurse Educator, 41(1), 7-8. DOI: 10.1097/NNE.0000000000000186. Traditional case studies can be limited to utilizing the lower portion of Blooms taxonomy, remembering, understanding, applying.  The reverse case study can engage students in higher parts of taxonomy: analyzing evaluating and creating. Students actually develop the scenario which means they must analyze and evaluate material in creating the materials and data for the case study. The article gives an example of a graded reverse case study done in a nursing pharmacology class. During the session, faculty observed collaboration, team work, prioritization and critical thinking. This type of case study refocuses students from being task oriented to being thinkers and planners. Would be an excellent process for lab or seminar group, clinical post conference group. May be difficult to do in a large class without splitting into groups. Again, wonder if there are any objective measures regarding student outcomes.
• Porter-Wenzlaff, L. (2013). Unfolding multicourse case study: Developing students administrative competencies. Nurse Educator, 38(6), 241-245. DOI: 10.1097/01.NNE.0000435263.15495.9f. The articles describes an unfolding case study that is done over 2 semesters in 2 courses. This is done in 2 graduate level nurse executive courses that are leveled. Students work in teams as the nurse executive of a fictional facility and must work through administrative complexities such as physician relations, resource allocation etc. Students are to do individual pieces of projects and come together and use the work in the larger objective. The projects progress across semesters and ideally students teams are the same as semesters change. The author recognized that students felt over whelmed and unprepared for this learning (and probably would have no matter the format) but found ways to help them work through by validating their concerns, having help available and that learning is an ongoing process. This paper does a great job of reporting anecdotal feedback from students, although it acknowledges there were no formal pre and post measures of implementation of this case study format.
• Harrison, E., (2012). How to develop well written case studies: The essential elements. Nurse Educator, 37(2), 67-70. DOI: 10.1097/NNE.0b013e3182461ba2. Briefly discusses the history of the use of case studies as educational tool in nursing. Suggests that case studies, much like narratives, should have a setting, characters, plot and elements of style that come together to create a mystery, a puzzle to be solved by the information given and knowing what additional information is needed. Students identify important data from that data that may be superfluous or not essential to the case. This is a unique way to describe a case study and how to create elements that nurses may forget, or not emphasize in their creation of case studies. Would be helpful to know if this paradigm has been used by others and if they found it effective.
• Henning, J.E., Nielsen, L.E. & Hauschildt, J.A. (2006). Implementing case study methodology in critical care nursing: a discourse analysis. Nurse Educator, 31(4):153-8. Describes a change in content delivery technique based on student feedback that lectures were boring and they wanted to experience more patient scenarios. Case study approach was adopted to increase interaction between teacher and students. Used method by Stepien et al. to analyze the case.  A model for discussion was then used with the case method which uses 3 types of discussion, 1. Frame the discussion where interest is generated and background information is given. 2. Conceptual discussion – teacher guides students in grasping concept 3. Application discussions where students discuss newly acquired knowledge is discussed as applied to scenarios. Using this method required that the teacher learn a new way to talk with or to students; had to learn how to elicit information from students and respond to them.  Student participation increased significantly with each addition of the next level of discussion where the teacher adjusted their questioning/cuing of students to elicit more response. They found that students spoke 2x as much as professor and both students and teacher seemed to become more comfortable with their new role as discussions went on. Very helpful in describing a way in which a classroom discussion can take place, one that elicits student participation and lets students guide the learning and morphs into a review discussion where the teacher makes sure that students understand the material accurately and use their discussion to apply newly acquired material.
• Ciesielka, D. (2003). Clues for clinicians: a case study approach to educating the renaissance nurse. Nurse Educator, 28(1), 3-4. Describes a way to integrate the humanities into a rigorous graduate curriculum already packed with science in order to prepare nurses to be able to work with patients of all cultures and social status. Developed Clues for Clinicians and used in the first clinical reasoning/clinical judgment course in nurse practitioner program. Instead of deriving cases from standard everyday clinical practice, cases were developed based on historical accounts. Faculty guided students in problem solving and students found themselves discussing the medical issue while also investigating a part of medical history.. Feedback was unanimously positive. I’m not convinced that this infuses humanities to the extent that the authors think it does, but it does keep interest and encourages student participation and reasoning as well as gives students something memorable to hang the information on. 
• Dowd, S.B. & Davidhizar, R. (1999). Using case studies to teach clinical problem-solving. Nurse Educator, 24(5), 42-6. Discusses advantages of using case studies to as well as preparation for faculty. Lists ways to prepare the case studies and how case studies can be solved.  Case studies connect theory to practice. They require preparation on the part of faculty and flexibility in allowing students to solve the case.
• Summary of findings: Most studies lack any data regarding student performance in clinical reasoning or judgment pre/post implementation of this method. While there is evidence that students find this method useful and engaging, no study presents findings that demonstrate that the case study method does what it’s purported to do. Studies discuss the preparation that must go into the case study development, that there are different ways of using the case study method (traditional, unfolding, reverse) and that students find them beneficial as well as how thinking is transformed to reach higher levels of Blooms Taxonomy. Almost all studies discuss case studies used in small groups or large classes broken into groups. None discuss how to lead a large class through a case and if/how this can engage students as well as improve their clinical reasoning. Only one articles discusses the use of an ongoing case that continues to the next semester, and this is for graduate students who are at a very different level of processing information than undergraduate students.

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• Published: 13 May 2024

Multiple paths to rumination within a network analytical framework

• Gerly Tamm 1 ,
• Ernst H. W. Koster 1 &
• Kristof Hoorelbeke 1  

Scientific Reports volume  14 , Article number:  10874 ( 2024 ) Cite this article

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Theories of rumination have proposed different psychological factors to place one at risk for repetitive negative thinking. A comprehensive empirical test that captures the most relevant contributors to rumination is lacking. Building on influential self-regulatory and metacognitive frameworks, we modeled how key constructs in this context relate to ruminative thinking. 498 participants completed online questionnaires including indicators of rumination, metacognition, promotion goal orientation, effortful control, and depression. We estimated regularized partial correlation networks to investigate unique associations between the different constructs and followed these analyses up with directed acyclic graphs to identify potential pathways towards rumination. Results demonstrated that: (1) both self-regulatory and metacognitive factors were directly linked to rumination, amongst these were (2) positive beliefs, negative beliefs about uncontrollability and harm, cognitive self-consciousness, depression, effortful control, perfectionism, and (lack of) cognitive confidence, and (3) we identified multiple directed pathways, suggesting three direct contributors to rumination while controlling for the influence of all other variables: diminished effortful control, positive beliefs, and cognitive self-consciousness. This study is the first to comprehensively assess metacognitive and self-regulatory frameworks of rumination in a data-driven manner. Our findings suggest that there are multiple pathways towards rumination, which should be incorporated in clinical case conceptualization of rumination and related disorders.

Introduction

Rumination is a form of repetitive negative thinking with a focus on negative past experiences and feelings. It is a process that is characterized by perseverative thinking that induces negative feelings and is considered a transdiagnostic risk factor for affective disorders 1 , 2 . There indeed is substantial empirical evidence showing that rumination is directly linked to clinical depression 3 , 4 , and suicide ideation 5 , 6 , 7 . In addition to predicting depression, rumination is also a key feature of many other mental health disorders, and serves as a transdiagnostic predictor for general psychological health 8 , 9 .

The current literature includes a multitude of reviews and research papers that have sought to explain the persistence of repetitive negative thinking. These theories have proposed a wide range of different key mechanisms that capture unique aspects of rumination. The Ruminative Response Style Theory (RRST) 4 is one of the most influential frameworks for rumination in the context of depression. The RRST conceptualizes depressive rumination as a trait-like passive and unhelpful response style to negative mood, and its potential causes and consequences. Other major theories include the Habit-Goal Framework of Depressive Rumination 10 , the Self-Regulatory Executive Function model (S-REF) 11 , the Impaired Disengagement Hypothesis 12 , the Goal Progress Theory 13 , the Control Theory 14 , and the Self-Regulation Risk Phenotype hypothesis 15 . These theories capture different focal points within the cognitive architecture behind rumination, such as the emphasis on metacognitive factors (e.g. 16 , 17 , 18 ), and the extent to which rumination is conceptualized as a type of self-regulation (e.g. 19 , 20 , 21 ). Interestingly, each of these theories have garnered extensive empirical support for their claims.

Considering that each of these different frameworks of rumination are supported by a multitude of prospective and experimental studies, it is likely that there are multiple etiological pathways towards rumination. This indicates the need for an integrative framework to best capture the mechanisms behind rumination. Building on the existing literature, a few papers have tried to integrate different aspects of rumination into a comprehensive framework. For instance, one of the more recent theoretical models is the H-EX-A-GO-N model 22 , which is supported by substantial evidence for each of the different components. The model proposes multiple loops between key variables that cause state and trait rumination and contribute to its maintenance. These include habit development, executive control, abstract processing, goal discrepancies, and negative bias (H-EX-A-GO-N).

Such integrative models have some challenges still to be overcome. Comprehensive empirical testing is needed to examine the influence and interplay between different psychological processes. Moreover, there is a considerable overlap between different theoretical constructs (e.g., effortful control as part of metacognition, rumination as a form of self-regulation etc.) which can complicate testing differential predictions from each theoretical model. As to date, comprehensive empirical tests of the relative importance of different processes in rumination are mostly lacking. As a result, unique associations (while controlling for overlap) between the key variables proposed in different theoretical frameworks of rumination remain to be explored. There is a need for a comprehensive examination of these associations on a broader level, to capture the main components of different theories. In the next sections, we will elaborate on central constructs in self-regulatory and metacognitive theories of rumination, and propose a data-driven approach to model and empirically test the interplay and directionality between these key aspects.

From self-regulation to rumination

Self-regulation is a cognitive ability that is concerned with controlling one’s actions, thoughts, and emotions (e.g. 23 , 24 ), which relies on prefrontal top-down executive processing that regulates the allocation of attention resources to enhance goal-directed behavior 25 , 26 . These resources are used when people need to modify their behaviors, thoughts, and emotions with an aim to reach personal goals. Effortful control 26 represents one form of self-regulation 27 which includes a voluntary recruitment of processes (attentional control, cognitive, and behavioral inhibition) that are most appropriate considering a given situation 28 .

From a self-regulatory perspective, rumination has been conceptualized as an emotion regulation strategy: it is an effortful, controlled, and conscious process that aims to reduce negative feelings but can actually have detrimental effects 21 . This assumes that when people ruminate they allocate their attentional resources towards an internal discrepancy (between ideal and the present state) with an aim to resolve this. However, when self-regulation fails (e.g., when the problem cannot be solved), then the ongoing unresolved discrepancy between goals and the current state continues to trigger and maintain ruminative processes, resulting in sustained negative affect. In this context, the theory of regulatory focus 29 suggests that there are two types of goals that people may pursue in their everyday lives: prevention (avoidance, safety focused) and promotion (approach, aspiration focused) related goals. Importantly, Jones et al. 30 concluded that a failure to reach promotion goals predicted rumination and this effect was further amplified by negative mood state. Moreover, rumination is known to increase the detrimental impact of promotion goal failure on depressive symptomatology 31 , 32 .

Setting extremely high goals is an indicator of perfectionism. Thus, individuals with extremely high expectations for themselves could be at risk for continuous goal discrepancy, and related to this, rumination and depression. Indeed, Olson and Kwon 33 showed that high levels of perfectionism in combination with brooding and stress lead to depressive symptoms over time. These studies point to the need to consider a specific type of goal failure (i.e., promotion goal failure) in combination with perfectionism as potential key contributors to rumination.

From rumination to self-regulation

When approached from the other end of the self-regulatory perspective, rumination can further amplify a variety of cognitive symptoms that can be seen in depression, such as impaired problem-solving, diminished cognitive performance, and persistent negative affect (as in RRST 4 ). This suggests a direct link between rumination and effortful control (also see 34 , 35 ). For instance, rumination is known to negatively impact performance on behavioral measures of attention 36 . However, not all studies suggest a direct link from rumination to effortful control. Instead, alternative patterns of directionality have been proposed by many researchers (e.g. 37 , 38 ), suggesting that rumination-related cognitive impairments may further increase susceptibility to ruminative responses 39 . In line with this, recent studies suggest beneficial effects of experimental manipulation of cognitive control on rumination, further impacting depression severity (e.g. 40 ; for a meta-analysis, see Vander Zwalmen et al. 41 ).

The role of metacognition

From a metacognitive perspective, rumination is conceptualized as a strategy that some people use to cope with distress 42 . The most prominent metacognitive theory, the Self-regulatory Executive Function framework (S-REF 11 ), proposes that rumination stems from positive metacognitive beliefs about rumination. Based on these beliefs, rumination is used as a tool for coping and self-regulation. These beliefs can be positive (e.g., “ruminating about the past helps me to prevent future mistakes and failures” 43 ), or negative (e.g., “ruminating is uncontrollable and harmful” 44 ). A recent meta-analysis showed that both positive and negative beliefs significantly predicted rumination and depression 45 . The S-REF model proposes that these beliefs guide the controlled processing system which relies on execution of voluntary attention, linking it back to self-regulatory views of rumination.

In addition to specific beliefs regarding the usefulness and effects of repetitive negative thinking, other metacognitive aspects have been considered relevant in the context of vulnerability for internalizing disorders. These include the need to control thoughts which refers to the beliefs that one needs to be in control of their thoughts at all times, cognitive confidence which is concerned with beliefs about one’s memory performance, and cognitive self-consciousness which refers to the ability to monitor one’s thoughts 46 . Amongst others, these dysfunctional metacognitive beliefs have been related to reduced effortful control 47 . In addition, Spada et al. 48 showed that these metacognitive aspects are particularly relevant in predicting depression but not anxiety. Therefore, these aspects should be considered when aiming to comprehensively examine the key processes related to rumination.

Current study

By using a data-driven exploratory approach, this study aims to examine predictions from the major theories of rumination, each of which place different emphasis on how metacognitive and self-regulatory processes contribute to rumination. For this purpose, we will rely on network analysis and directed acyclic graphs to model complex interrelations and identify potential directed pathways of the variables of interest and rumination.

First, we aimed to model centrality of and unique associations between effortful control, indices of promotion goal focus, metacognition, rumination, and depression. Network analytical approaches are increasingly used in psychopathology research 49 and are particularly suitable for exploration of interconnections between multiple variables. The network theory of psychiatric disorders assumes that psychiatric symptoms causally interact with each other 49 . The data driven approach is the key element here to test whether the theories of rumination hold up in relation to the empirical data while considered within the network analytical framework. The major advantage of this approach is that it considers a set of key variables as a complex system 49 in which all possible associations can be included and the most relevant links can be detected by applying a data-driven approach (via pre-defined and rigorously tested algorithms). As such, we will rely on undirected regularized partial correlation network models to clarify the complex interplay between self-regulatory and metacognitive aspects of rumination.

Although providing important insights into the structure of the model and centrality of specific variables, a disadvantage of undirected models is that they describe the general structure of associations while ignoring the potential direction of effects. In this context, several mathematical optimization techniques and machine learning approaches have been developed that allow to explore directionality in data obtained from cross-sectional studies. Applying such methods to explore the network structure and (potential) directionality willprovide the most comprehensive overview of unique associations between the variables of interest and rumination. As such, to test the potential directionality of these associations, we will—as a second step—apply Bayesian network analysis 50 , 51 .

This approach was developed and further tested by Pearl and colleagues 52 , 53 , and has been applied to study psychopathological processes by several researchers 51 , 54 . Bayesian networks rely on the mathematical principles of causal reasoning 50 which unifies the three theories of causation: the probabilistic 55 , counterfactual 56 , and the manipulationist approach 57 . As a result, they are represented as directed acyclic graphs (DAGs) which allow to identify potential directed associations in a data-driven way and provide a future basis for testing specific hypotheses about causality between the key variables. The DAGs can provide an approximation and hypotheses about how different concepts from different theories are positioned in relation to each other within the cognitive architecture of rumination.

Participants

A total of 504 participants between ages 18 and 85 were recruited via Academic Prolific ( www.prolific.co ) from the United Kingdom (UK). In addition to the 504 participants who completed the study, 23 decided not to submit their data, and 7 participants were timed out. Out of the 504, 6 participants (5 women, 1 man) were excluded due to incorrect responses to at least one of the check items out of three. Thus, a total of 498 were included into the final sample. All participants were fluent in English. The sample’s sex, age, and ethnicity distributions were representative of the UK’s population based on most recent census data (cf. Supplementary Materials, Table S6 ).

Ethics declaration

All participants gave an informed consent, agreed to participate voluntarily, and their time spent was compensated for data was anonymized. The study was approved by the local ethics committee of the Faculty of Psychology and Educational Science of Ghent University. All research was performed in accordance with regulations (incl. Declaration of Helsinki).

Self-report questionnaires and key variables

The following questionnaires were used to measure the 12 key variables included in the network model. All questionnaires used have gone through a rigorous validation and have demonstrated adequate reliability. Table S1 in Supplementary Materials includes a more detailed discussion of each of the key variables.

Rumination and depression

We measured rumination with the Ruminative Response Scale (RRS) 58 , 59 . The full version of the 22-item scale included all three factors (brooding, reflection, and depression). Higher scores indicate more frequent rumination. Each item is rated on a four-point Likert scale from 1 (almost never) to 4 (almost always). The RRS has good internal consistency, validity, and high reliability 60 . In our data, the overall Cronbach’s α was 0.95. We used the summary compound of rumination by adding the scores for the 22 items (as in 61 ) to capture all aspects of rumination.

We measured depression with the Depression, Anxiety, Stress Scales (DASS-21 62 ). The DASS is a 21-item questionnaire that includes three factors: depression, anxiety, and stress. Each item is rated on a four-point Likert scale from 0 (did not apply to me at all) to 3 (applied to me very much, or most of the time). Higher scores indicate more frequent symptomatology. Given the focus of the study, we only included the depression subscale (7 items) into the analysis. DASS-21 has acceptable validity and reliability 63 . In our data, the Cronbach’s α for the depression subscale was very high (α = 0.94). In line with the original instructions, we calculated the depression subscale by adding the scores of all depression items and multiplying this by 2 62 .

Promotion focus, promotion goal failure, and perfectionism

We measured promotion focus with the Regulatory Focus Questionnaire (RFQ 64 ). The RFQ is an 11-item questionnaire that captures two factors: promotion and prevention focus. We included the promotion focus subscale consisting of 6 items into the analysis. Each of the items is rated on a Likert scale from 1 (never or seldom) to 5 (very often). RFQ has acceptable validity and reliability 64 . In our data, the Cronbach’s α for the promotion focus subscale was acceptable (α = 0.70). Higher scores refer to more frequent promotion focus. We obtained the summary score for the promotion focus subscale by calculating the average score of the 6 items 64 .

We measured promotion goal failure with the Computerized Selves Task (CS 31 ) that includes ratings for six adjectives (personal ideals/goals) reported by the participant. Each item is rated on how far away the person was at that time from their ideals on a 7-point Likert scale ranging from 1 (not at all) to 7 (extremely). We calculated the scores based on the original instructions: average score of the six items. Higher scores indicate a greater discrepancy between ideals and the present self. This task has been used in multiple prior studies to measure discrepancy between the ideal and present self as a proxy for promotion goal failure 65 . In our data, the overall Cronbach’s α was 0.89.

We measured perfectionism with the Frost Multidimensional Perfectionism Scale—Brief 66 . This 8-item measure has two factors (strivings and evaluative concerns). It has good reliability and validity 66 . In our data, the overall Cronbach’s α was 0.85. We calculated the compound score for perfectionism by adding all items as suggested by Burgess et al. 66 .

Metacognitive beliefs

We measured positive metacognitive beliefs about rumination with the Positive Beliefs about Rumination Scale which has good validity and reliability (PBRS 43 ). In our data, Cronbach’s α was 0.93. The scale includes 9 items, each item is rated on a four-point Likert scale from 1 (do not agree) to 4 (agree very much). We calculated the overall score based on the original instructions as the sum of all items.

We measured two types of negative beliefs about rumination with the Negative Beliefs about Rumination Scale (NBRS 44 ). The NBRS (13 items) includes two factors: (1) negative beliefs about uncontrollability and harmfulness of rumination , and (2) negative beliefs about negative social and interpersonal consequences . Each item is rated on a four-point Likert scale from 1 (do not agree) to 4 (agree very much). The NBRS has good psychometric properties 60 . In our data, the Cronbach’s α for each of the factors were 0.88 and 0.85, respectively. The score of this scale was based on the sum of all items per factor.

Additionally, we measured metacognitive beliefs about the need to control thoughts, cognitive self-consciousness , and (lack of) cognitive confidence with the Metacognitions Questionnaire (MCQ-30 67 ). The MCQ-30 has 30 items that are distributed between five factors ( the need to control thoughts, cognitive self-consciousness , (lack of)  cognitive confidence, negative beliefs about uncontrollability and harm, and positive beliefs ). We only used three factors ( need to control thoughts, cognitive self-consciousness , and (lack of)   cognitive confidence ) in the analysis, since other scales captured the other two factors better (i.e., in the MCQ, positive and negative beliefs about one’s thinking are mainly focused on measuring worry rather than rumination, in contrast to the PBRS and NBRS). Each item is rated on a four-point Likert scale ranging from 1 (do not agree) to 4 (agree very much). The MCQ-30 has acceptable validity and reliability 46 . In our data, the Cronbach’s α for each of the factors were 0.75, 0.85, and 0.90, accordingly. We followed the original instructions for calculations and summed all items for each factor 67 .

Effortful control

We measured effortful control with the effortful control subscale (EC) from the short version of the Adult Temperament Questionnaire (ATQ-EC 28 ). The EC subscale has 19 items that are distributed between three factors: inhibitory control, activation control and attentional control. Each item is rated on a Likert scale from 1 (extremely untrue) to 7 (extremely true). EC is often used separately from the ATQ full version to measure effortful control. Higher scores indicate better effortful control. Its validity and reliability are acceptable 28 . In our data, Cronbach’s α was 0.84. Scores were calculated according to the instructions provided by Evans and Rothbart 28 .

This study was carried out online using Limesurvey and Academic Prolific. Data was collected in November 2022. Participants who registered in Academic Prolific and who fit the criteria (based on UK census data) were automatically invited to the study. Participants could fill in the questionnaires using their laptops, computers, tablets or smartphones.

All participants had to log in to their Academic Prolific account and follow the Limesurvey link to the study. First, they completed the sociodemographic questionnaire which was followed by a fully randomized block of all nine questionnaires. After completing the randomized block, participants completed an additional block of questionnaires with a main focus on trauma (not reported here). The sequence of the two blocks was fixed. In addition to the questionnaires, three attention check questions were used to check for careless responding. Median study completion time was 27 min. After completion of both blocks, participants were reimbursed via Academic Prolific platform.

Data analysis

All data analyses were carried out in RStudio (2023.03.0 Build 386) with R version 4.2.3. Descriptive statistical analysis included arithmetic mean, standard deviation, and visual inspection of the data (histograms and scatter plots). Summarized data and R code are available here: https://osf.io/6zqmd/ .

Data checks

There were no missing data. After visual and statistical inspection of data distributions we noted that all variables deviated somewhat from the Normal distribution. In order to improve normality and to ease the assumption for Gaussian networks 68 , we used the nonparanormal transformation, as suggested by Epskamp et al. 69 , by applying huge.npn() from huge package 70 .

We used the goldbricker() function from networktools package 71 to check for collinearity between the different variables. We relied on the method proposed by Hittner et al. 72 to identify highly correlated node pairs ( r  ≥ 0.5) showing similar correlation patterns (≤ 25% unique associations, α  = 0.05), suggesting that these might measure the same underlying construct based upon which they could be revised. In our dataset, based on tests for collinearity, no reductions to the selected node set were needed.

Undirected networks

First, we estimated a Gaussian Graphical Model (GGM), also known as regularized partial correlation networks or Markov Random Fields 49 , 73 , to explore the interconnections (i.e., edges) between the variables of interest (i.e., nodes; for an overview of included variables, see Table S1 in Supplementary Materials). Partial correlations between nodes (i.e., variables) provide an estimate of unique variation captured by every node while considering all variation (all other nodes) within the network. We included 12 nodes (see Table S1 in Supplementary Materials): rumination (RUM), effortful control (EC), cognitive confidence (CC), positive beliefs about rumination (PB), cognitive self-consciousness (M-SC), need for control of thoughts (M-NC), beliefs about uncontrollability and harmfulness of rumination (NB-U), beliefs about negative social and interpersonal consequences of rumination (NB-S), promotion focus (PRO), perfectionism (PER), promotion goal failure (PGF), and depression (DEP).

Network estimation and visualization

The partial correlation matrix was calculated with cor_auto() from qgraph (based on Lavaan function lavCor 74 ) and was used as input for network estimation. We estimated the undirected networks with qgraph() from the qgraph package 75 . To remove spurious edges (i.e., false positives) from the network, it is recommended to use statistical regularization methods. For that purpose, we used Least Absolute Shrinkage and Selection Operator regularization (gLASSO 76 ) from glasso package 77 , which is a modified and faster version of the regular LASSO 78 . Often, combined with Extended Bayesian Information Criterion (EBIC 79 ), it is used to identify the optimal model, particularly in moderately large samples 69 .

In an exploratory context of many nodes and hundreds of potential edges, gLASSO limits the number of edges by setting potentially spurious (smaller) edges equal to zero. This results in more realistic, and sparser models. gLASSO uses a tuning parameter lambda (λ) which controls the level of sparsity. We used the default settings for λ in qgraph package 80 . We used additional thresholding (before EBIC) as implemented in qgraph which removed all elements in the inverse variance–covariance matrix that were below a theoretical threshold 81 to ensure high specificity. Also, we set additional limits to the EBIC model selection procedure by setting the hyperparameter gamma (γ) to 0.5. Gamma is typically set between 0 and 0.5 82 while 0.5 has been recommended as it reflects a more conservative approach 73 , 82 .

Undirected networks are visualized using circles (nodes, representing variables) and lines (edges, representing unique associations) to connect the circles. Red/dashed lines refer to negative edges (negative association between the two variables), and blue/full lines refer to positive associations. Line thickness corresponds with the relative weight of the edge (i.e., regularized partial correlation) between the two nodes while considering all other nodes in the model. The Fruchterman-Reingold algorithm 83 was used, which aims to position more influential nodes in the center of the model.

Centrality and predictability

Centrality indices are used to describe how well nodes are connected to other nodes in the network. Strength centrality (i.e., the sum of absolute edge weights of edges connected to that node) was used to identify the most well-connected nodes in the model as an indicator of relative importance. Strength centrality has shown to be one of the most reliable centrality indices 84 . In addition, node predictability is relevant when considering the practical prediction value of the model 85 . Nodewise predictability quantifies how well each node was predicted by all other nodes in the model: how much variance of a node can be explained by the edges connected to that node. It is also a marker for potential influence within that network. High predictability of nodes suggests that the model includes relevant factors. Predictability was estimated with the qgraph package (version 1.9.8), and plotted using circular pie-charts around the nodes. The colored areas (here, we used black) indicate the percentage of variance explained by the edges that are connected to that particular node.

Accuracy and stability

Estimating accuracy and stability of the network models is crucial to demonstrate the robustness of findings 73 . We tested the accuracy of edge weights, and stability of node strengths with the three steps outlined by Epskamp et al. 69 : (1) First, we calculated bootstrapped confidence intervals for edge weights using a non-parametric bootstrap. We used the bootnet() function from bootnet package 86 with nBoots set to 1000 and plot function to model sampling variability in edge weights; (2) Next, we investigated the stability of the obtained order of node strengths using the case-dropping subset bootstrap procedure 69 . This allows to investigate to what extent the order of nodes in terms of strength centrality remains stable when re-estimating the network model in subsets of the sample. In particular, correlation stability refers to the maximum percentage of cases that can be dropped so that the correlation between the original and the bootstrapped networks is above 0.7 for 95% of the cases (as recommended by Epskamp et al. 69 ; (3) Finally, the procedure included bootstrapped difference tests between all paired edges, and between all nodes.

Directed acyclic graphs

In the second part of the data analysis, we aimed to explore the potential directed relationships between all nodes that have been included in the undirected network model (see Table S1 in Supplementary Materials). For this purpose we used Bayesian networks (also known as directed acyclic graphs , DAGs) 51 , 87 . Gaussian DAGs have parametric assumptions such as linear Gaussian distribution with the normal-Wishart prior 68 . To satisfy this assumption, we relied on the transformed data (section Data Imputation, and Transformation).

We estimated the structure of a DAG with a constraint-based modern version of the Parent–Child algorithm: PC stable 88 . We used the pc.stable() function from the bnlearn package 89 . PC stable is developed from the inductive causation 90 , 91 , and it is concerned with finding best matches for each potential directed pair of nodes: i.e., a parent (“from”) and child (“to”) pair. PC stable learns the directed structure from the data as follows 51 : (1) it estimates a network model including pairwise connections between all nodes; (2) then removes edges between conditionally independent pairs of nodes, and; (3) assigns directions ( arcs —i.e., directed edges in DAGs 51 ) to all edges by starting from colliders (also known as v-structures, where two disconnected nodes cause the third node); (4) To ensure the robustness of the DAG, we then continued with bootstrapping procedures to exclude unstable edges. For this purpose, we applied the PC stable algorithm to the data 1000 times, and used 0.85 as a threshold for edge strength and 0.5 as a threshold for minimum direction (the percentage of networks having the same directions for that particular edge) to trim down the number of potential connections between nodes 51 .

We considered the directed model with thresholding as the final model and based our conclusions on the results of this final step. We plotted the directed network with and without thresholding. In these plots, circles represent nodes, and arrows represent potential directed relationships between the nodes. In the plot that includes all potential directions, edge thickness represents the percentage of times the edge was present in this particular direction in the set of 1000 bootstrapped solutions. To understand the meaning of the predicted directed associations between each pair of nodes, we conducted pair-wise regression analyses to test how nodes were connected. That is, we checked whether there was a positive or negative beta value.

Sample size characteristics and descriptive statistics of all variables included into the network analysis are described in Table 1 . Further details about each of the variables can be found in Table S1 in Supplementary Materials. Pearson correlations between all variables are described in Supplementary Materials, Table S2 .

First, we estimated the GGM (Fig.  1 A). The centrality index (strength) is visualized in Fig.  1 B. Additional accuracy and stability checks show that the obtained network model was relatively accurate and stable (Supplementary Materials, Figs. S1 – S3 ; strength correlation stability = 0.67). The edge weight matrix for the GGM can be found in Supplementary Materials, Table S3 .

GGM. ( A ) Undirected network model. Blue/full lines indicate unique positive associations and red/dashed lines indicate negative associations between the variables (nodes). Black circles around the nodes indicate node predictability. ( B ) Centrality of the nodes: Strength. Higher strength indicates relative importance of that node in the network model.

As expected, rumination was ranked first in terms of Strength centrality (Fig.  1 B), given the selection of nodes based on theoretical frameworks of rumination. This suggested that rumination was among the most influential variables in this network. When considering all potential associations between the nodes, the model showed that rumination (RUM) was directly and positively associated with depression (DEP), positive beliefs about rumination (PBR), negative beliefs about uncontrollability and harmfulness of rumination (M-BU), cognitive self-consciousness (M-SC), (lack of) cognitive confidence (CC), and perfectionism (PER); furthermore, rumination (RUM) was directly negatively associated with effortful control (EC).

There was a strong direct connection between depression and promotion focus (negative association), which was also related to effortful control (positive association) and perfectionism (positive association). In addition, negative beliefs about social consequences also showed relatively strong connections with  negative beliefs about uncontrollability and harm (positive association) and the need for control of thoughts (positive association), the latter also being connected with cognitive self-consciousness (positive association) and (lack of) cognitive confidence (positive association). The least central node in this model was promotion goal failure, which was directly associated with effortful control only (more feelings of failure were associated with lower effortful control).

We estimated predictability (R 2 ) of the nodes from the GGM model. Rumination had the highest predictability, and promotion goal failure had the lowest predictability. Mean node predictability of the conservative model that included additional thresholding was 0.29, which means that on average 29% of variance in nodes was explained by surrounding nodes. Predictability of rumination was 52% (with additional thresholding).

In sum, these findings indicate tha—while controlling for the influence of all other variables in the model—multiple constructs from metacognitive and self-regulatory theories share a direct association with rumination. Together, these variables predict a significant amount of variability (52%) in rumination within the sample.

Next, we estimated DAGs with the constraint based PC stable algorithm to identify potential directed pathways. Figure  2 A illustrates the averaged DAG after bootstrapping, and applying the threshold (0.85) for edges. The obtained model suggests several potential pathways towards rumination. First, the obtained pathways suggest that lower cognitive confidence (i.e., more "lack of cognitive confidence") may lead to reduced effortful control, increasing the likelihood of rumination (for corresponding regression coefficients, see Supplementary Materials, Table S4 ).

DAG. ( A ) Averaged Directed Acyclic Graph. Arrows indicate potential causal associations between the variables (nodes). ( B ) Bootstrapping Results. The graph illustrates all associations that were present in the data before applying the threshold to trim down the most likely and most relevant associations which are presented on panel ( A ). PGF promotion goal failure, EC effortful control, CC (lack of) cognitive confidence, PB positive beliefs about rumination, M-SC cognitive self-consciousness, M-NC need for control, NB-U negative beliefs about uncontrollability and harm, NB-SC negative beliefs about social consequences, PRO promotion focus, RUM rumination, DEP depression, PER perfectionism.

In parallel to that, the results suggest that stronger promotion focus results in higher levels of effortful control, reflecting a potential protective effect, and lower depressive symptomatology. Positive beliefs about rumination increase the likelihood of ruminating both directly as well as indirectly via increased cognitive self-consciousness. Rumination is related to further activation of negative beliefs about uncontrollability and harm, which feeds into depression and negative beliefs about social consequences. Through need for control of thoughts, activation of cognitive self-consciousness also feeds into negative beliefs about social consequences of rumination. Perfectionism and promotion goal failure were unconnected in the model.

Figure  2 B contains the unthresholded DAG including all estimated directions with edge/arc probabilities after 1000 bootstraps (see Supplementary Materials, Table S5 for bootstrap results), which allows evaluation of the robustness of the obtained edge directions. Although the PC stable algorithm identified several edges/arcs that were relatively stable, in some cases it was difficult for the algorithm to determine the directionality between node pairs. For instance, an edge from rumination to depression was present in 46% of the 1000 bootstrapped samples, and from depression to rumination in 54% of the bootstrapped samples. In the final averaged DAG, no direct connection between rumination and depression was included. This may imply that the algorithm could not determine directionality based on this data due to the bidirectional nature of these relations in combination with the conservative threshold (0.85) for strength.

In sum, the averaged DAG suggests effortful control, positive beliefs about rumination and cognitive self-consciousness to contribute to rumination directly, further spiraling into activation of negative metacognitions regarding rumination, and related to this, depressive symptomatology. Promotion goal focus indirectly impacted rumination via effortful control.

This study aimed to explore the interplay between rumination and related factors proposed in major theories of rumination. We applied a data-driven network analytical approach to examine unique associations as well as potential directed pathways between rumination, metacognitive beliefs and abilities, effortful control, depression, perfectionism, promotion focus, and promotion goal failure. The network models suggested that there were multiple paths to rumination. These results are the first to show that the major theories of rumination that put different emphasis on metacognitive and self-regulatory aspects of rumination complement each other as demonstrated by a comprehensive data-driven model. The main results that emerged from the data driven analysis are in line with more recent theories of rumination, such as the S-REF 16 as well as with the H-EX-A-GO-N model 22 , and provide empirical background for the therapeutic interventions that are built upon those theories (e.g., metacognitive therapy). We will elaborate on the main findings, clinical implications, limitations, and future directions below.

Undirected network

First, the undirected network model included a set of variables based on major theories of rumination, which had not yet been incorporated and modelled in a single study. To investigate patterns of unique association between these different constructs, we estimated a GGM.

The undirected network model (Fig.  1 A) indicated that seven key variables were directly linked to rumination: (1) depression; (2) negative beliefs about rumination (uncontrollability and harm); (3) positive beliefs about rumination; (4) cognitive self-consciousness; (5) effortful control; (6) perfectionism, and; (7) cognitive confidence. Some of these associations were weaker than others. For example, perfectionism had a significantly weaker direct association with rumination than most other variables mentioned above (Supplementary Materials, Fig. S3 A). Moreover, effortful control was negatively associated with rumination, whereas the other aspects were positively associated with rumination. Together, these variables explained 52% of observed variance in rumination in the thresholded model, suggesting that our model contained most central constructs in this context.

Overall, our findings bring together and support self-regulatory (e.g. 12 , 13 , 14 , 19 , as well as metacognitive perspectives on rumination 17 . Moreover, our results are in line with recent empirical findings that suggest that positive metacognitive beliefs and diminished attentional control both independently contribute to rumination 92 . Importantly, our results expand this notion by adding that there are multiple roads to rumination: several metacognitive aspects, as well as negative and positive beliefs about rumination, and perfectionism share unique and direct associations with rumination.

In addition to the direct links with rumination mentioned above, we observed several indirect links within the network. Promotion goal failure, promotion focus, need for control of thoughts, and negative beliefs about social consequences were part of the rumination network but these processes were not directly linked to higher levels of rumination. Instead they contributed to rumination in an indirect manner. For instance, promotion focus was only connected to rumination through other nodes, among which depression and effortful control. This suggests that people who are focused on their ideals and goals (promotion focused), may report less depressive symptoms, and vice versa. Similarly, promotion focus was related to increased effortful control, in turn linking promotion focus to reduced rumination, and vice versa. These findings are in accordance with Jones et al. 30 who showed that experimental manipulation of promotion focus (participants were prompted to think about past promotion goal failures) was associated with rumination and negative affect.

Interestingly, effortful control was the only variable linking promotion goal failure with rumination and other constructs, including promotion focus, in the model. Our result suggests that people who experience a stronger discrepancy between their ideal and present self, report less effortful control, which correlates with rumination. This is partially in accordance with the framework outlined in the H-EX-A-GO-N model 22 which refers to a direct link from goal discrepancy to rumination but also notes that executive functions can influence both rumination and perception of goal discrepancy. One interpretation of this finding is that in order to process discrepancies between the ideal and the present self, one needs to effortfully direct attention to the problem with an aim to solve this. From a self-regulatory perspective, it is generally accepted that promotion goal failure triggers rumination 14 , 22 , and it is supported by experimental findings showing that cueing unresolved goals results in more rumination than cueing a resolved goal, especially in habitual ruminators 93 . However, our model adds the potential role of effortful control in linking both constructs. As such, when a person is trying to resolve the discrepancy between the ideal and the present self by applying effortful control, then attention directed at trying to find a solution or an explanation to the discrepancy may reduce the ability to focus and work towards a solution. Although undirected, these results suggest that effortful control may play a crucial role in maintaining rumination.

The undirected network model included other variables that were indirectly linked to rumination. Interestingly, metacognitive beliefs about the need for control of thoughts, and negative social consequences were strongly connected but differentially linked to rumination. Rumination and need for control were connected through cognitive self-consciousness, suggesting that people who believe that one needs to be in control of their thoughts are likely to report being more self-conscious, which is linked to more rumination, and vice versa. However, our model suggests that people who believe that rumination has negative social consequences are also more likely to believe that rumination is uncontrollable, which correlates with more rumination (and vice versa). These multiple links to rumination further demonstrate the heterogeneous and complex etiology of rumination.

Causal inference

After obtaining the network structure, our second goal was to identify potential directed pathways between the variables of interest by applying Bayesian network analysis to the data. Causal inference methods have been used for decades, but they are relatively new in psychopathology research 94 . DAGs are useful and low-cost tools to generate hypotheses about directed effects which can later be tested with experiments.

First, by visual inspection we noticed that the averaged DAG resulted in two interconnected sets of variables. One included several metacognitive variables, and the other one included the main variables from self-regulatory theories, in addition to cognitive confidence (Fig.  2 A). Second, the model depicted three potentially directed pathways to rumination: One potential directed pathway suggests a central role for effortful control, where lower cognitive confidence may lead to reduced effortful control, increasing the likelihood of rumination (for corresponding regression coefficients, see Supplementary Materials, Table S4 ). This finding is consistent with the metacognitive approach, which implies that changes in rumination can be induced by modifying top-down metacognitive processes and beliefs, and by strengthening attentional control (away from self-focused attention) 16 , 17 . Furthermore, the model suggested that effortful control also receives input from promotion focus, potentially resulting in less rumination. The second directed pathway involves positive beliefs about rumination directly leading to more rumination. The third pathway involves positive beliefs about rumination leading to higher cognitive self-consciousness which leads to more rumination. This suggests that these three aspects are relevant in triggering or maintaining ruminative thinking. Importantly, our model also contained a pathway indicating that rumination may further result in activation of negative beliefs about repetitive negative thinking, and subsequent depressive symptomatology.

We estimated the averaged DAG using the widely implemented PC stable algorithm 88 , and relied on bootstrapping and thresholding procedures to obtain an accurate and stable model. In addition, we applied an alternative model estimation algorithm to test the robustness of the model (the hybrid Min–Max Hill Climbing algorithm, MMHC 95 ; Supplementary Materials, Fig. S4 ). These different algorithms capture different aspects of the data 96 . In general, the obtained DAG model (Fig. S4 ) was highly comparable in terms of observed associations linking the key variables of interest with rumination, with the exception of one additional direct link from rumination to depression. This is also in line with the findings obtained from the undirected network model (Fig.  1 A). The directions, however, were variable when comparing the two DAGs. This difference could be attributed to the potential reciprocal relationships between the variables of interest, which is also consistent with the findings from the bootstrapping procedure (Fig.  2 B). In the context of proximal risk factors for repetitive negative thinking, many of the observed associations can, indeed, be bidirectional in nature as also suggested, for example, by the H-EX-A-GO-N model 22 as well as outlined in the metacognitive models 16 , 18 . Moreover, the multi-node-loop hypothesis is further supported by empirical findings from another network study which focused on describing the associations between state rumination, self-criticism and behavioral executive control 97 . This is in accordance with the metacognitive models that suggest that the vicious cycles between beliefs about rumination, depression, metacognitive efficiency and confidence may be the underlying cause for persistence of depression 16 , 42 . Systematic feedback loops have also been proposed by other theories, including a broader system’s dynamic framework that includes biological, cognitive, as well as societal and environmental factors that can reinforce rumination and depression 98 . It is important to note that these theories do not exclude the role of causal factors in triggering rumination and depression. Instead, they emphasize the need to explore the causal pathways and entry points that lead into the vicious feedback loop of rumination and depression. This can be achieved via exploring the data with Bayesian networks, followed up by experimental and simulation studies.

Clinical implications

These data-driven results bring together and affirm several predictions from prior major theories of rumination and depression, and potential clinical implications. The results confirm the proposition from the metacognitive theory for depression 44 which predicts that positive beliefs about rumination can directly initiate rumination. This suggests that in clinical case conceptualization, individual metacognitive abilities and beliefs need to be considered. Indeed, belief modification has proven to benefit many but not all patients who experience depressive rumination. Self-regulatory theories (e.g. 13 , 14 ) emphasize the ideal-actual self-discrepancy as the core trigger and maintaining factor for rumination, and suggest that the ability to shift attention away from the negative thoughts is the key intervention point. In the current study, the direct association between effortful control and rumination suggested that modifying attentional control by training attentional disengagement from ideals/goals, or from the negative thought content could result in diminished rumination, as supported by some experiments (e.g. 93 ). The S-REF model 17 provides a more comprehensive framework and emphasizes that the specific complex pattern of thinking called the “Cognitive Attentional Syndrome” causes and maintains psychopathology; the syndrome includes self-focused attention, attentional biases, worry, and rumination. It assumes that multiple cognitive processes simultaneously contribute to psychopathology. Our model indeed shows that attentional processing, beliefs about rumination, and other metacognitive aspects all contribute to rumination. Our results do not provide a direct empirical proof for the effectiveness of any psychological intervention but the model outlines a set of key variables, and associations to rumination, to be considered in case conceptualization. The results emphasize the relevance to explore alternative pathways to rumination in clinical case conceptualization.

Limitations and future directions

This study is the first to provide a data-driven test of unique associations between key constructs from self-regulatory and metacognitive frameworks of rumination, as well as to explore potential directed pathways between these constructs. Similar to other network analyses in rumination research 97 , we acknowledge that network analysis is a correlational method that has some interpretational limits. For instance, while LASSO regularization helps to avoid false positive results, it increases the chances for missing potential associations that could be relevant in explaining the underlying mechanisms. Importantly, in the current study, the variables included into the model with additional thresholding explained up to 52% of the variation in rumination, which suggests that the model captured a large proportion of the mechanism behind rumination. Moreover, we used a moderately large population representative sample which reaffirms the stability of the obtained results.

To identify potential directed pathways, we relied on DAGs. Although often used in psychopathology research, DAGs assume acyclicity of the underlying mechanism. However, many psychological mechanisms include cycles in which the outcome variable can affect the input (e.g., A causes B, B causes C, C causes A). Importantly, it has been demonstrated that even if the assumption for acyclicity is not met, the retrieved set of directions between variables is the most likely set of causal effects 99 . Thus, the main value of DAGs in psychopathology research is that they provide a data-driven view on potential directed effects. However, this approach should be considered as strictly exploratory and hypothesis generating. The results should be interpreted with caution. These potential directed pathways need to be confirmed through prospective (e.g., studies relying on experience sampling methodology) or experimental research.

The current study relied on a representative sample for the adult UK population, which is informative for the process of rumination and related factors in the general population. However, we cannot exclude that other mechanisms may be involved in clinical or specific at-risk populations. As such, for future research, it would be interesting to extend the investigation of the role of self-regulatory and metacognitive factors in rumination, and how this adds to mental health complaints, to (sub)clinical samples (e.g., individuals suffering from major depression).

In addition, differential pathways may be observed when focusing on other types of repetitive negative thinking and related factors (e.g., worry in the context of anxiety). Here, we did not include all aspects from prior theories for technical reasons, such as multicollinearity, and for theoretical consideration because we aimed to focus on depression related variables rather than anxiety. One important aspect that should be considered in the future studies is the habitual aspect of rumination. The H-EX-A-GO-N model suggests that habitual rumination is relevant in the maintenance of psychopathology. Here, within this cross-sectional study we did not aim to separate this particular aspect from the global measure of rumination (RRS) but in future studies it could be advisable to explore how rumination develops and persist in daily life by using suitable prospective and experimental designs to capture the habitual component. Other important aspects that could be explored further include abstract thinking, subtypes of rumination (brooding and reflection), and personality characteristics that associate with perfectionism (e.g., neuroticism) which could further elucidate the complex system behind rumination.

Conclusions

This study explored the complex interrelations between rumination and central constructs from related self-regulatory and metacognitive frameworks in a large adult population sample. The data-driven approach revealed that metacognitive and self-regulatory aspects complement one another by adding unique variance to explain rumination. We estimated undirected and directed network models, which suggested that there are multiple paths to rumination. The three main potential causes for rumination included: positive beliefs about rumination, effortful control, and cognitive self-consciousness. While these findings provide considerable support for the therapeutic approaches that combine the metacognitive belief modification, and attention control training in treatment of depression, the causality of these processes needs further investigation. These results specify hypotheses about the potential causal mechanisms for rumination to be tested in prospective or experimental studies. Finally, these results have the potential to help develop novel therapeutic approaches where, based on the current results, it would seem wise to target multiple factors driving rumination 1 .

Data availability

Summarized data and R code are available here: https://osf.io/6zqmd/ .

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This work was supported by a fellowship of the Research Foundation Flanders (FWO), awarded to KH (12J9722N).

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Does a perceptual gap lead to actions against digital misinformation? A third-person effect study among medical students

• Zongya Li   ORCID: orcid.org/0000-0002-4479-5971 1 &
• Jun Yan   ORCID: orcid.org/0000-0002-9539-8466 1  

BMC Public Health volume  24 , Article number:  1291 ( 2024 ) Cite this article

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We are making progress in the fight against health-related misinformation, but mass participation and active engagement are far from adequate. Focusing on pre-professional medical students with above-average medical knowledge, our study examined whether and how third-person perceptions (TPP), which hypothesize that people tend to perceive media messages as having a greater effect on others than on themselves, would motivate their actions against misinformation.

We collected the cross-sectional data through a self-administered paper-and-pencil survey of 1,500 medical students in China during April 2022.

Structural equation modeling (SEM) analysis, showed that TPP was negatively associated with medical students’ actions against digital misinformation, including rebuttal of misinformation and promotion of corrective information. However, self-efficacy and collectivism served as positive predictors of both actions. Additionally, we found professional identification failed to play a significant role in influencing TPP, while digital misinformation self-efficacy was found to broaden the third-person perceptual gap and collectivism tended to reduce the perceptual bias significantly.

Conclusions

Our study contributes both to theory and practice. It extends the third-person effect theory by moving beyond the examination of restrictive actions and toward the exploration of corrective and promotional actions in the context of misinformation., It also lends a new perspective to the current efforts to counter digital misinformation; involving pre-professionals (in this case, medical students) in the fight.

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Introduction

The widespread persistence of misinformation in the social media environment calls for effective strategies to mitigate the threat to our society [ 1 ]. Misinformation has received substantial scholarly attention in recent years [ 2 ], and solution-oriented explorations have long been a focus but the subject remains underexplored [ 3 ].

Health professionals, particularly physicians and nurses, are highly expected to play a role in the fight against misinformation as they serve as the most trusted information sources regarding medical topics [ 4 ]. However, some barriers, such as limitations regarding time and digital skills, greatly hinder their efforts to tackle misinformation on social media [ 5 ].

Medical students (i.e., college students majoring in health/medical science), in contrast to medical faculty, have a greater potential to become the major force in dealing with digital misinformation as they are not only equipped with basic medical knowledge but generally possess greater social media skills than the former generation [ 6 ]. Few studies, to our knowledge, have tried to explore the potential of these pre-professionals in tackling misinformation. Our research thus fills the gap by specifically exploring how these pre-professionals can be motivated to fight against digital health-related misinformation.

The third-person perception (TPP), which states that people tend to perceive media messages as having a greater effect on others than on themselves [ 7 ], has been found to play an important role in influencing individuals’ coping strategies related to misinformation. But empirical exploration from this line of studies has yielded contradictory results. Some studies revealed that individuals who perceived a greater negative influence of misinformation on others than on themselves were more likely to take corrective actions to debunk misinformation [ 8 ]. In contrast, some research found that stronger TPP reduced individuals’ willingness to engage in misinformation correction [ 9 , 10 ]. Such conflicting findings impel us to examine the association between the third-person perception and medical students’ corrective actions in response to misinformation, thus attempting to unveil the underlying mechanisms that promote or inhibit these pre-professionals’ engagement with misinformation.

Researchers have also identified several perceptual factors that motivate individuals’ actions against misinformation, especially efficacy-related concepts (e.g., self-efficacy and health literacy) and normative variables (e.g., subjective norms and perceived responsibility) [ 3 , 8 , 9 ]. However, most studies devote attention to the general population; little is known about whether and how these factors affect medical students’ intentions to deal with misinformation. We recruited Chinese medical students in order to study a social group that is mutually influenced by cultural norms (collectivism in Chinese society) and professional norms. Meanwhile, systematic education and training equip medical students with abundant clinical knowledge and good levels of eHealth literacy [ 5 ], which enable them to have potential efficacy in tackling misinformation. Our study thus aims to examine how medical students’ self-efficacy, cultural norms (i.e., collectivism) and professional norms (i.e., professional identification) impact their actions against misinformation.

Previous research has found self-efficacy to be a reliable moderator of optimistic bias, the tendency for individuals to consider themselves as less likely to experience negative events but more likely to experience positive events as compared to others [ 11 , 12 , 13 ]. As TPP is thought to be a product of optimistic bias, accordingly, self-efficacy should have the potential to influence the magnitude of third-person perception [ 14 , 15 ]. Meanwhile, scholars also suggest that the magnitude of TPP is influenced by social distance corollary [ 16 , 17 ]. Simply put, individuals tend to perceive those who are more socially distant from them to be more susceptible to the influence of undesirable media than those who are socially proximal [ 18 , 19 , 20 ]. From a social identity perspective, collectivism and professional identification might moderate the relative distance between oneself and others while the directions of such effects differ [ 21 , 22 ]. For example, collectivists tend to perceive a smaller social distance between self and others as “they are less likely to view themselves as distinct or unique from others” [ 23 ]. In contrast, individuals who are highly identified with their professional community (i.e., medical community) are more likely to perceive a larger social distance between in-group members (including themselves) and out-group members [ 24 ]. In this way, collectivism and professional identification might exert different effects on TPP. On this basis, this study aims to examine whether and how medical students’ perceptions of professional identity, self-efficacy and collectivism influence the magnitude of TPP and in turn influence their actions against misinformation.

Our study builds a model that reflects the theoretical linkages among self-efficacy, collectivism, professional identity, TPP, and actions against misinformation. The model, which clarifies the key antecedents of TPP and examines the mediating role of TPP, contribute to the third-person effect literature and offer practical contributions to countering digital misinformation.

Context of the study

As pre-professionals equipped with specialized knowledge and skills, medical students have been involved in efforts in health communication and promotion during the pandemic. For instance, thousands of medical students have participated in various volunteering activities in the fight against COVID-19, such as case data visualization [ 25 ], psychological counseling [ 26 ], and providing online consultations [ 27 ]. Due to the shortage of medical personnel and the burden of work, some medical schools also encouraged their students to participate in health care assistance in hospitals during the pandemic [ 28 , 29 ].

The flood of COVID-19 related misinformation has posed an additional threat to and burden on public health. We have an opportunity to address this issue and respond to the general public’s call for guidance from the medical community about COVID-19 by engaging medical students as a main force in the fight against coronavirus related misinformation.

Literature review

The third-person effect in the misinformation context.

Originally proposed by Davison [ 7 ], the third-person effect hypothesizes that people tend to perceive a greater effect of mass media on others than on themselves. Specifically, the TPE consists of two key components: the perceptual and the behavioral [ 16 ]. The perceptual component centers on the perceptual gap where individuals tend to perceive that others are more influenced by media messages than themselves. The behavioral component refers to the behavioral outcomes of the self-other perceptual gap in which people act in accordance with such perceptual asymmetry.

According to Perloff [ 30 ], the TPE is contingent upon situations. For instance, one general finding suggests that when media messages are considered socially undesirable, nonbeneficial, or involving risks, the TPE will get amplified [ 16 ]. Misinformation characterized as inaccurate, misleading, and even false, is regarded as undesirable in nature [ 31 ]. Based on this line of reasoning, we anticipate that people will tend to perceive that others would be more influenced by misinformation than themselves.

Recent studies also provide empirical evidence of the TPE in the context of misinformation [ 32 ]. For instance, an online survey of 511 Chinese respondents conducted by Liu and Huang [ 33 ] revealed that individuals would perceive others to be more vulnerable to the negative influence of COVID-19 digital disinformation. An examination of the TPE within a pre-professional group – the medical students–will allow our study to examine the TPE scholarship in a particular population in the context of tackling misinformation.

Why TPE occurs among medical students: a social identity perspective

Of the works that have provided explanations for the TPE, the well-known ones include self-enhancement [ 34 ], attributional bias [ 35 ], self-categorization theory [ 36 ], and the exposure hypothesis [ 19 ]. In this study, we argue for a social identity perspective as being an important explanation for third-person effects of misinformation among medical students [ 36 , 37 ].

The social identity explanation suggests that people define themselves in terms of their group memberships and seek to maintain a positive self-image through favoring the members of their own groups over members of an outgroup, which is also known as downward comparison [ 38 , 39 ]. In intergroup settings, the tendency to evaluate their ingroups more positively than the outgroups will lead to an ingroup bias [ 40 ]. Such an ingroup bias is typically described as a trigger for the third-person effect as individuals consider themselves and their group members superior and less vulnerable to undesirable media messages than are others and outgroup members [ 20 ].

In the context of our study, medical students highly identified with the medical community tend to maintain a positive social identity through an intergroup comparison that favors the ingroup and derogates the outgroup (i.e., the general public). It is likely that medical students consider themselves belonging to the medical community and thus are more knowledgeable and smarter than the general public in health-related topics, leading them to perceive the general public as more vulnerable to health-related misinformation than themselves. Accordingly, we propose the following hypothesis:

H1: As medical students’ identification with the medical community increases, the TPP concerning digital misinformation will become larger.

What influences the magnitude of TPP

Previous studies have demonstrated that the magnitude of the third-person perception is influenced by a host of factors including efficacy beliefs [ 3 ] and cultural differences in self-construal [ 22 , 23 ]. Self-construal is defined as “a constellation of thoughts, feelings, and actions concerning the relationship of the self to others, and the self as distinct from others” [ 41 ]. Markus and Kitayama (1991) identified two dimensions of self-construal: Independent and interdependent. Generally, collectivists hold an interdependent view of the self that emphasizes harmony, relatedness, and places importance on belonging, whereas individualists tend to have an independent view of the self and thus view themselves as distinct and unique from others [ 42 ]. Accordingly, cultural values such as collectivism-individualism should also play a role in shaping third-person perception due to the adjustment that people make of the self-other social identity distance [ 22 ].

Set in a Chinese context aiming to explore the potential of individual-level approaches to deal with misinformation, this study examines whether collectivism (the prevailing cultural value in China) and self-efficacy (an important determinant of ones’ behavioral intentions) would affect the magnitude of TPP concerning misinformation and how such impact in turn would influence their actions against misinformation.

The impact of self-efficacy on TPP

Bandura [ 43 ] refers to self-efficacy as one’s perceived capability to perform a desired action required to overcome barriers or manage challenging situations. He also suggests understanding self-efficacy as “a differentiated set of self-beliefs linked to distinct realms of functioning” [ 44 ]. That is to say, self-efficacy should be specifically conceptualized and operationalized in accordance with specific contexts, activities, and tasks [ 45 ]. In the context of digital misinformation, this study defines self-efficacy as one’s belief in his/her abilities to identify and verify misinformation within an affordance-bounded social media environment [ 3 ].

Previous studies have found self-efficacy to be a reliable moderator of biased optimism, which indicates that the more efficacious individuals consider themselves, the greater biased optimism will be invoked [ 12 , 23 , 46 ]. Even if self-efficacy deals only with one’s assessment of self in performing a task, it can still create the other-self perceptual gap; individuals who perceive a higher self-efficacy tend to believe that they are more capable of controlling a stressful or challenging situation [ 12 , 14 ]. As such, they are likely to consider themselves less vulnerable to negative events than are others [ 23 ]. That is, individuals with higher levels of self-efficacy tend to underestimate the impact of harmful messages on themselves, thereby widening the other-self perceptual gap.

In the context of fake news, which is closely related to misinformation, scholars have confirmed that fake news efficacy (i.e., a belief in one’s capability to evaluate fake news [ 3 ]) may lead to a larger third-person perception. Based upon previous research evidence, we thus propose the following hypothesis:

H2: As medical students’ digital misinformation self-efficacy increases, the TPP concerning digital misinformation will become larger.

The influence of collectivism on TPP

Originally conceptualized as a societal-level construct [ 47 ], collectivism reflects a culture that highlights the importance of collective goals over individual goals, defines the self in relation to the group, and places great emphasis on conformity, harmony and interdependence [ 48 ]. Some scholars propose to also examine cultural values at the individual level as culture is embedded within every individual and could vary significantly among individuals, further exerting effects on their perceptions, attitudes, and behaviors [ 49 ]. Corresponding to the construct at the macro-cultural level, micro-psychometric collectivism which reflects personality tendencies is characterized by an interdependent view of the self, a strong sense of other-orientation, and a great concern for the public good [ 50 ].

A few prior studies have indicated that collectivism might influence the magnitude of TPP. For instance, Lee and Tamborini [ 23 ] found that collectivism had a significant negative effect on the magnitude of TPP concerning Internet pornography. Such an impact can be understood in terms of biased optimism and social distance. Collectivists tend to view themselves as an integral part of a greater social whole and consider themselves less differentiated from others [ 51 ]. Collectivism thus would mitigate the third-person perception due to a smaller perceived social distance between individuals and other social members and a lower level of comparative optimism [ 22 , 23 ]. Based on this line of reasoning, we thus propose the following hypothesis:

H3: As medical students’ collectivism increases, the TPP concerning digital misinformation will become smaller.

Behavioral consequences of TPE in the misinformation context

The behavioral consequences trigged by TPE have been classified into three categories: restrictive actions refer to support for censorship or regulation of socially undesirable content such as pornography or violence on television [ 52 ]; corrective action is a specific type of behavior where people seek to voice their own opinions and correct the perceived harmful or ambiguous messages [ 53 ]; promotional actions target at media content with desirable influence, such as advocating for public service announcements [ 24 ]. In a word, restriction, correction and promotion are potential behavioral outcomes of TPE concerning messages with varying valence of social desirability [ 16 ].

Restrictive action as an outcome of third-person perceptual bias (i.e., the perceptual component of TPE positing that people tend to perceive media messages to have a greater impact on others than on themselves) has received substantial scholarly attention in past decades; scholars thus suggest that TPE scholarship to go beyond this tradition and move toward the exploration of corrective and promotional behaviors [ 16 , 24 ]. Moreover, individual-level corrective and promotional actions deserve more investigation specifically in the context of countering misinformation, as efforts from networked citizens have been documented as an important supplement beyond institutional regulations (e.g., drafting policy initiatives to counter misinformation) and platform-based measures (e.g., improving platform algorithms for detecting misinformation) [ 8 ].

In this study, corrective action specifically refers to individuals’ reactive behaviors that seek to rectify misinformation; these include such actions as debunking online misinformation by commenting, flagging, or reporting it [ 3 , 54 ]. Promotional action involves advancing correct information online, including in response to misinformation that has already been disseminated to the public [ 55 ].

The impact of TPP on corrective and promotional actions

Either paternalism theory [ 56 ] or the protective motivation theory [ 57 ] can act as an explanatory framework for behavioral outcomes triggered by third-person perception. According to these theories, people act upon TPP as they think themselves to know better and feel obligated to protect those who are more vulnerable to negative media influence [ 58 ]. That is, corrective and promotional actions as behavioral consequences of TPP might be driven by a protective concern for others and a positive sense of themselves.

To date, several empirical studies across contexts have examined the link between TPP and corrective actions. Koo et al. [ 8 ], for instance, found TPP was not only positively related to respondents’ willingness to correct misinformation propagated by others, but also was positively associated with their self-correction. Other studies suggest that TPP motivates individuals to engage in both online and offline corrective political participation [ 59 ], give a thumbs down to a biased story [ 60 ], and implement corrective behaviors concerning “problematic” TV reality shows [ 16 ]. Based on previous research evidence, we thus propose the following hypothesis:

H4: Medical students with higher degrees of TPP will report greater intentions to correct digital misinformation.

Compared to correction, promotional behavior has received less attention in the TPE research. Promotion commonly occurs in a situation where harmful messages have already been disseminated to the public and others appear to have been influenced by these messages, and it serves as a remedial action to amplify messages with positive influence which may in turn mitigate the detrimental effects of harmful messages [ 16 ].

Within this line of studies, however, empirical studies provide mixed findings. Wei and Golan [ 24 ] found a positive association between TPP of desirable political ads and promotional social media activism such as posting or linking the ad on their social media accounts. Sun et al. [ 16 ] found a negative association between TPP regarding clarity and community-connection public service announcements (PSAs) and promotion behaviors such as advocating for airing more PSAs in TV shows.

As promotional action is still underexplored in the TPE research, and existing evidence for the link between TPP and promotion is indeed mixed, we thus propose an exploratory research question:

RQ1: What is the relationship between TPP and medical students’ intentions to promote corrective information?

The impact of self-efficacy and collectivism on actions against misinformation

According to social cognitive theory, people with higher levels of self-efficacy tend to believe they are competent and capable and are more likely to execute specific actions [ 43 ]. Within the context of digital misinformation, individuals might become more willing to engage in misinformation correction if they have enough knowledge and confidence to evaluate information, and possess sufficient skills to verify information through digital tools and services [ 61 ].

Accordingly, we assumed medical students with higher levels of digital misinformation self-efficacy would be likely to become more active in the fight against misinformation.

H5: Medical students with higher levels of digital misinformation self-efficacy will report greater intentions to (a) correct misinformation and (b) promote corrective information on social media.

Social actions of collectivists are strongly guided by prevailing social norms, collective responsibilities, and common interest, goals, and obligations [ 48 ]. Hence, highly collectivistic individuals are more likely to self-sacrifice for group interests and are more oriented toward pro-social behaviors, such as adopting pro-environmental behaviors [ 62 ], sharing knowledge [ 23 ], and providing help for people in need [ 63 ].

Fighting against misinformation is also considered to comprise altruism, especially self-engaged corrective and promotional actions, as such actions are costly to the actor (i.e., taking up time and energy) but could benefit the general public [ 61 ]. Accordingly, we assume collectivism might play a role in prompting people to engage in reactive behaviors against misinformation.

It is also noted that collectivist values are deeply rooted in Chinese society and were especially strongly advocated during the outbreak of COVID-19 with an attempt to motivate prosocial behaviors [ 63 ]. Accordingly, we expected that the more the medical students were oriented toward collectivist values, the more likely they would feel personally obliged and normatively motivated to engage in misinformation correction. However, as empirical evidence was quite limited, we proposed exploratory research questions:

RQ2: Will medical students with higher levels of collectivism report greater intentions to (a) correct misinformation and (b) promote corrective information on social media?

The theoretical model

To integrate both the antecedents and consequences of TPP, we proposed a theoretical model (as shown in Fig. 1 ) to examine how professional identification, self-efficacy and collectivism would influence the magnitude of TPP, and how such impact would in turn influence medical students’ intentions to correct digital misinformation and promote corrective information. Thus, RQ3 was proposed:

RQ3: Will the TPP mediate the impact of self-efficacy and collectivism on medical students’ intentions to (a) correct misinformation, and (b) promote corrective information on social media? Fig. 1 The proposed theoretical model. DMSE = Digital Misinformation Self-efficacy; PIMC = Professional Identification with Medical Community; ICDM = Intention to Correct Digital Misinformation; IPCI = Intention to Promote Corrective Information Full size image

To examine the proposed hypotheses, this study utilized cross-sectional survey data from medical students in Tongji Medical College (TJMC) of China. TJMC is one of the birthplaces of Chinese modern medical education and among the first universities and colleges that offer eight-year curricula on clinical medicine. Further, TJMC is located in Wuhan, the epicenter of the initial COVID-19 outbreaks, thus its students might find the pandemic especially relevant – and threatening – to them.

The survey instrument was pilot tested using a convenience sample of 58 respondents, leading to minor refinements to a few items. Upon approval from the university’s Institutional Research Board (IRB), the formal investigation was launched in TJMC during April 2022. Given the challenges of reaching the whole target population and acquiring an appropriate sampling frame, this study employed purposive and convenience sampling.

We first contacted four school counselors as survey administrators through email with a letter explaining the objective of the study and requesting cooperation. All survey administrators were trained by the principal investigator to help with the data collection in four majors (i.e., basic medicine, clinical medicine, nursing, and public health). Paper-and-pencil questionnaires were distributed to students on regular weekly departmental meetings of each major as students in all grades (including undergraduates, master students, and doctoral students) were required to attend the meeting. The projected time of completion of the survey was approximately 10–15 min. The survey administrators indicated to students that participation was voluntary, their responses would remain confidential and secure, and the data would be used only for academic purposes. Though a total of 1,500 participants took the survey, 17 responses were excluded from the analysis as they failed the attention filters. Ultimately, a total of 1,483 surveys were deemed valid for analysis.

Of the 1,483 respondents, 624 (42.10%) were men and 855 (57.70%) were women, and four did not identify gender. The average age of the sample was 22.00 ( SD  = 2.54, ranging from 17 to 40). Regarding the distribution of respondents’ majors, 387 (26.10%) were in basic medicine, 390 (26.30%) in clinical medicine, 307 (20.70%) in nursing, and 399 (26.90%) in public health. In terms of university class, 1,041 (70.40%) were undergraduates, 291 (19.70%) were working on their master degrees, 146 (9.90%) were doctoral students, and five did not identify their class data.

Measurement of key variables

Perceived effects of digital misinformation on oneself and on others.

Three modified items adapted from previous research [ 33 , 64 ] were employed to measure perceived effects of digital misinformation on oneself. Respondents were asked to indicate to what extent they agreed with the following: (1) I am frequently concerned that the information about COVID-19 I read on social media might be false; (2) Misinformation on social media might misguide my understanding of the coronavirus; (3) Misinformation on social media might influence my decisions regarding COVID-19. The response categories used a 7-point scale, where 1 meant “strongly disagree” and 7 meant “strongly agree.” The measure of perceived effects of digital misinformation on others consisted of four parallel items with the same statement except replacing “I” and “my” with “the general others” and “their”. The three “self” items were averaged to create a measure of “perceived effects on oneself” ( M  = 3.98, SD  = 1.49, α  = 0.87). The three “others” items were also added and averaged to form an index of “perceived effects on others” ( M  = 4.62, SD  = 1.32, α  = 0.87).

The perceived self-other disparity (TPP)

TPP was derived by subtracting perceived effects on oneself from perceived effects on others.

Professional identification with medical community

Professional identification was measured using a three item, 7-point Likert-type scale (1 =  strongly disagree , 7 =  strongly agree ) adapted from previous studies [ 65 , 66 ] by asking respondents to indicate to what extent they agreed with the following statements: (1) I would be proud to be a medical staff member in the future; (2) I am committed to my major; and (3) I will be in an occupation that matches my current major. The three items were thus averaged to create a composite measure of professional identification ( M  = 5.34, SD  = 1.37, α  = 0.88).

Digital misinformation self-efficacy

Modified from previous studies [ 3 ], self-efficacy was measured with three items. Respondents were asked to indicate on a 7-point Linkert scale from 1 (strongly disagree) to 7 (strongly agree) their agreement with the following: (1) I think I can identify misinformation relating to COVID-19 on social media by myself; (2) I know how to verify misinformation regarding COVID-19 by using digital tools such as Tencent Jiaozhen Footnote 1 and Piyao.org.cn Footnote 2 ; (3) I am confident in my ability to identify digital misinformation relating to COVID-19. A composite measure of self-efficacy was constructed by averaging the three items ( M  = 4.38, SD  = 1.14, α  = 0.77).

• Collectivism

Collectivism was measured using four items adapted from previous research [ 67 ], in which respondents were asked to indicate their agreement with the following statements on a 7-point scale, from 1 (strongly disagree) to 7 (strongly agree): (1) Individuals should sacrifice self-interest for the group; (2) Group welfare is more important than individual rewards; (3) Group success is more important than individual success; and (4) Group loyalty should be encouraged even if individual goals suffer. Therefore, the average of the four items was used to create a composite index of collectivism ( M  = 4.47, SD  = 1.30, α  = 0.89).

Intention to correct digital misinformation

We used three items adapted from past research [ 68 ] to measure respondents’ intention to correct misinformation on social media. All items were scored on a 7-point scale from 1 (very unlikely) to 7 (very likely): (1) I will post a comment saying that the information is wrong; (2) I will message the person who posts the misinformation to tell him/her the post is wrong; (3) I will track the progress of social media platforms in dealing with the wrong post (i.e., whether it’s deleted or corrected). A composite measure of “intention to correct digital misinformation” was constructed by adding the three items and dividing by three ( M  = 3.39, SD  = 1.43, α  = 0.81).

Intention to promote corrective information

On a 7-point scale ranging from 1 (very unlikely) to 7 (very likely), respondents were asked to indicate their intentions to (1) Retweet the corrective information about coronavirus on my social media account; (2) Share the corrective information about coronavirus with others through Social Networking Services. The two items were averaged to create a composite measure of “intention to promote corrective information” ( M  = 4.60, SD  = 1.68, r  = 0.77).

Control variables

We included gender, age, class (1 = undergraduate degree; 2 = master degree; 3 = doctoral degree), and clinical internship (0 = none; 1 = less than 0.5 year; 2 = 0.5 to 1.5 years; 3 = 1.5 to 3 years; 4 = more than 3 years) as control variables in the analyses. Additionally, coronavirus-related information exposure (i.e., how frequently they were exposed to information about COVID-19 on Weibo, WeChat, and QQ) and misinformation exposure on social media (i.e., how frequently they were exposed to misinformation about COVID-19 on Weibo, WeChat, and QQ) were also assessed as control variables because previous studies [ 69 , 70 ] had found them relevant to misinformation-related behaviors. Descriptive statistics and bivariate correlations between main variables were shown in Table 1 .

Statistical analysis

We ran confirmatory factor analysis (CFA) in Mplus (version 7.4, Muthén & Muthén, 1998) to ensure the construct validity of the scales. To examine the associations between variables and tested our hypotheses, we performed structural equation modeling (SEM). Mplus was chosen over other SEM statistical package mainly because the current data set included some missing data, and the Mplus has its strength in handling missing data using full-information maximum likelihood imputation, which enabled us to include all available data [ 71 , 72 ]. Meanwhile, Mplus also shows great flexibility in modelling when simultaneously handling continuous, categorical, observed, and latent variables in a variety of models. Further, Mplus provides a variety of useful information in a concise manner [ 73 ].

Table 2 shows the model fit information for the measurement and structural models. Five latent variables were specified in the measurement model. To test the measurement model, we examined the values of Cronbach’s alpha, composite reliability (CR), and average variance extracted (AVE) (Table 1 ). Cronbach’s alpha values ranged from 0.77 to 0.89. The CRs, which ranged from 0.78 to 0.91, exceeded the level of 0.70 recommended by Fornell (1982) and thus confirmed the internal consistency. The AVE estimates, which ranged from 0.54 to 0.78, exceeded the 0.50 lower limit recommended by Fornell and Larcker (1981), and thus supported convergent validity. All the square roots of AVE were greater than the off-diagonal correlations in the corresponding rows and columns [ 74 ]. Therefore, discriminant validity was assured. In a word, our measurement model showed sufficient convergence and discriminant validity.

Five model fit indices–the relative chi-square ratio (χ 2 / df ), the comparative fit index (CFI), the Tucker–Lewis index (TLI), the root mean square error of approximation (RMSEA), and the standardized root-mean-square residual (SRMR) were used to assess the model. Specifically, the normed chi-square between 1 and 5 is acceptable [ 75 ]. TLI and CFI over 0.95 are considered acceptable, SRMR value less than 0.08 and RMSEA value less than 0.06 indicate good fit [ 76 ]. Based on these criteria, the model was found to have an acceptable fit to the data.

Figure 2 presents the results of our hypothesized model. H1 was rejected as professional identification failed to predict TPP ( β  = 0.06, p  > 0.05). Self-efficacy was positively associated with TPP ( β  = 0.14, p  < 0.001) while collectivism was negatively related to TPP ( β  = -0.10, p  < 0.01), lending support to H2 and H3.

Note. N  = 1,483. The coefficients of relationships between latent variables are standardized beta coefficients. Significant paths are indicated by solid line; non-significant paths are indicated by dotted lines. * p  < .05, ** p  < .01; *** p  < .001. DMSE = Digital Misinformation Self-efficacy; PIMC = Professional Identification with Medical Community; ICDM = Intention to Correct Digital Misinformation; IPCI = Intention to Promote Corrective Information

H4 posited that medical students with higher degrees of TPP would report greater intentions to correct digital misinformation. However, we found a negative association between TPP and intentions to correct misinformation ( β  = -0.12, p  < 0.001). H4 was thus rejected. Regarding RQ1, results revealed that TPP was negatively associated with intentions to promote corrective information ( β  = -0.08, p  < 0.05).

Further, our results supported H5 as we found that self-efficacy had a significant positive relationship with corrective intentions ( β  = 0.18, p  < 0.001) and promotional intentions ( β  = 0.32, p  < 0.001). Collectivism was also positively associated with intentions to correct misinformation ( β  = 0.14, p  < 0.001) and promote corrective information ( β  = 0.20, p  < 0.001), which answered RQ2.

Regarding RQ3 (see Table 3 ), TPP significantly mediated the relationship between self-efficacy and intentions to correct misinformation ( β  = -0.016), as well as the relationship between self-efficacy and intentions to promote corrective information ( β  = -0.011). However, TPP failed to mediate either the association between collectivism and corrective intentions ( β  = 0.011, ns ) or the association between collectivism and promotional intentions ( β  = 0.007, ns ).

Recent research has highlighted the role of health professionals and scientists in the fight against misinformation as they are considered knowledgeable, ethical, and reliable [ 5 , 77 ]. This study moved a step further by exploring the great potential of pre-professional medical students to tackle digital misinformation. Drawing on TPE theory, we investigated how medical students perceived the impact of digital misinformation, the influence of professional identification, self-efficacy and collectivism on these perceptions, and how these perceptions would in turn affect their actions against digital misinformation.

In line with prior studies [ 3 , 63 ], this research revealed that self-efficacy and collectivism played a significant role in influencing the magnitude of third-person perception, while professional identification had no significant impact on TPP. As shown in Table 1 , professional identification was positively associated with perceived effects of misinformation on oneself ( r  = 0.14, p  < 0.001) and on others ( r  = 0.20, p  < 0.001) simultaneously, which might result in a diminished TPP. What explains a shared or joint influence of professional identification on self and others? A potential explanation is that even medical staff had poor knowledge about the novel coronavirus during the initial outbreak [ 78 ]. Accordingly, identification with the medical community was insufficient to create an optimistic bias concerning identifying misinformation about COVID-19.

Our findings indicated that TPP was negatively associated with medical students’ intentions to correct misinformation and promote corrective information, which contradicted our hypotheses but was consistent with some previous TPP research conducted in the context of perceived risk [ 10 , 79 , 80 , 81 ]. For instance, Stavrositu and Kim (2014) found that increased TPP regarding cancer risk was negatively associated with behavioral intentions to engage in further cancer information search/exchange, as well as to adopt preventive lifestyle changes. Similarly, Wei et al. (2008) found concerning avian flu news that TPP negatively predicted the likelihood of engaging in actions such as seeking relevant information and getting vaccinated. In contrast, the perceived effects of avian flu news on oneself emerged as a positive predictor of intentions to take protective behavior.

Our study shows a similar pattern as perceived effects of misinformation on oneself were positively associated with intentions to correct misinformation ( r  = 0.06, p  < 0.05) and promote corrective information ( r  = 0.10, p  < 0.001, See Table 1 ). While the reasons for the behavioral patterns are rather elusive, such findings are indicative of human nature. When people perceive misinformation-related risk to be highly personally relevant, they do not take chances. However, when they perceive others to be more vulnerable than themselves, a set of sociopsychological dynamics such as self-defense mechanism, positive illusion, optimistic bias, and social comparison provide a restraint on people’s intention to engage in corrective and promotional actions against misinformation [ 81 ].

In addition to the indirect effects via TPP, our study also revealed that self-efficacy and collectivism serve as direct and powerful drivers of corrective and promotive actions. Consistent with previous literature [ 61 , 68 ], individuals will be more willing to engage in social corrections of misinformation if they possess enough knowledge, skills, abilities, and resources to identify misinformation, as correcting misinformation is difficult and their effort would not necessarily yield positive outcomes. Collectivists are also more likely to engage in misinformation correction as they are concerned for the public good and social benefits, aiming to protect vulnerable people from being misguided by misinformation [ 82 ].

This study offers some theoretical advancements. First, our study extends the TPE theory by moving beyond the examination of restrictive actions and toward the exploration of corrective and promotional actions in the context of misinformation. This exploratory investigation suggests that self-other asymmetry biased perception concerning misinformation did influence individuals’ actions against misinformation, but in an unexpected direction. The results also suggest that using TPP alone to predict behavioral outcomes was deficient as it only “focuses on differences between ‘self’ and ‘other’ while ignoring situations in which the ‘self’ and ‘other’ are jointly influenced” [ 83 ]. Future research, therefore, could provide a more sophisticated understanding of third-person effects on behavior by comparing the difference of perceived effects on oneself, perceived effects on others, and the third-person perception in the pattern and strength of the effects on behavioral outcomes.

Moreover, institutionalized corrective solutions such as government and platform regulation are non-exhaustive [ 84 , 85 ]; it thus becomes critical to tap the great potential of the crowd to engage in the fight against misinformation [ 8 ] while so far, research on the motivations underlying users’ active countering of misinformation has been scarce. The current paper helps bridge this gap by exploring the role of self-efficacy and collectivism in predicting medical students’ intentions to correct misinformation and promote corrective information. We found a parallel impact of the self-ability-related factor and the collective-responsibility-related factor on intentions to correct misinformation and promote corrective information. That is, in a collectivist society like China, cultivating a sense of collective responsibility and obligation in tackling misinformation (i.e., a persuasive story told with an emphasis on collective interests of social corrections of misinformation), in parallel with systematic medical education and digital literacy training (particularly, handling various fact-checking tools, acquiring Internet skills for information seeking and verification) would be effective methods to encourage medical students to engage in active countering behaviors against misinformation. Moreover, such an effective means of encouraging social corrections of misinformation might also be applied to the general public.

In practical terms, this study lends new perspectives to the current efforts in dealing with digital misinformation by involving pre-professionals (in this case, medical students) into the fight against misinformation. As digital natives, medical students usually spend more time online, have developed sophisticated digital competencies and are equipped with basic medical knowledge, thus possessing great potential in tackling digital misinformation. This study further sheds light on how to motivate medical students to become active in thwarting digital misinformation, which can help guide strategies to enlist pre-professionals to reduce the spread and threat of misinformation. For example, collectivism education in parallel with digital literacy training would help increase medical students’ sense of responsibility for and confidence in tackling misinformation, thus encouraging them to engage in active countering behaviors.

This study also has its limitations. First, the cross-sectional survey study did not allow us to justify causal claims. Granted, the proposed direction of causality in this study is in line with extant theorizing, but there is still a possibility of reverse causal relationships. To establish causality, experimental research or longitudinal studies would be more appropriate. Our second limitation lies in the generalizability of our findings. With the focus set on medical students in Chinese society, one should be cautious in generalizing the findings to other populations and cultures. For example, the effects of collectivism on actions against misinformation might differ in Eastern and Western cultures. Further studies would benefit from replication in diverse contexts and with diverse populations to increase the overall generalizability of our findings.

Drawing on TPE theory, our study revealed that TPP failed to motivate medical students to correct misinformation and promote corrective information. However, self-efficacy and collectivism were found to serve as direct and powerful drivers of corrective and promotive actions. Accordingly, in a collectivist society such as China’s, cultivating a sense of collective responsibility in tackling misinformation, in parallel with efficient personal efficacy interventions, would be effective methods to encourage medical students, even the general public, to actively engage in countering behaviors against misinformation.

Availability of data and materials

The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request.

Tencent Jiaozhen Fact-Checking Platform which comprises the Tencent information verification tool allow users to check information authenticity through keyword searching. The tool is updated on a daily basis and adopts a human-machine collaboration approach to discovering, verifying, and refuting rumors and false information. For refuting rumors, Tencent Jiaozhen publishes verified content on the homepage of Tencent's rumor-refuting platform, and uses algorithms to accurately push this content to users exposed to the relevant rumors through the WeChat dispelling assistant.

Piyao.org.cn is hosted by the Internet Illegal Information Reporting Center under the Office of the Central Cyberspace Affairs Commission and operated by Xinhuanet.com. The platform is a website that collects statements from Twitter-like services, news portals and China's biggest search engine, Baidu, to refute online rumors and expose the scams of phishing websites. It has integrated over 40 local rumor-refuting platforms and uses artificial intelligence to identify rumors.

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Acknowledgements

We thank all participants and staff working for the project.

This work was supported by Humanities and Social Sciences Youth Foundation of the Ministry of Education of China (Grant No. 21YJC860012).

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Li, Z., Yan, J. Does a perceptual gap lead to actions against digital misinformation? A third-person effect study among medical students. BMC Public Health 24 , 1291 (2024). https://doi.org/10.1186/s12889-024-18763-9

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The learning curve for minimally invasive Achilles repair using the “lumbar puncture needle and oval forceps” technique

• Yanrui Zhao 1   na1 ,
• Hanzhou Wang 1   na1 ,
• Binzhi Zhao 1   na1 ,
• Shuo Diao 1 ,
• Yuling Gao 1 ,
• Junlin Zhou 1 &
• Yang Liu 1  

BMC Musculoskeletal Disorders volume  25 , Article number:  373 ( 2024 ) Cite this article

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Introduction

An acute Achilles tendon rupture represents a common tendon injury, and its operative methods have been developed over the years. This study aimed to quantify the learning curve for the minimally invasive acute Achilles tendon rupture repair.

From May 2020 to June 2022, sixty-seven patient cases who received minimally invasive tendon repair were reviewed. Baseline data and operative details were collected. The cumulative summation (CUSUM) control chart was used for the learning curve analyses. Achilles tendon rupture score (ATRS), American Orthopedic Foot and Ankle Society (AOFAS) ankle/hindfoot score, and visual analog scale (VAS) at 3/6/9/12 months were calculated to assess the clinical outcomes.

Thirty-six cases underwent at least a year of follow up and were enrolled in this study. The gender ratio and average age were 80.5% and 32.5 years. The linear equation fitted well (R 2  = 0.95), and CUSUM for operative time peaked in the 12th case, which was divided into the learning phase (n = 12) and master phase (n = 24). No significant difference was detected between the two groups in clinical variables, except for the operative time (71.1 ± 13.2 min vs 45.8 ± 7.2 min, p = 0.004). Moreover, we detected one case with a suture reaction and treated it properly.

Minimally invasive Achilles repair provides an opportunity for early rehabilitation. Notably, the learning curve showed that the “lumbar puncture needle and oval forceps” technique was accessible to surgeons.

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The Achilles tendon is the strongest and largest tendon in the human body, and its rupture is a common sports-related injury [ 1 , 2 ]. The incidence of acute Achilles tendon rupture keeps rising, and it has been reported to reach 18 per 100,000 people per year due to improper strength explosions in the ankle or the weakening of elasticity during frequent and high-intensity physical exercise [ 3 , 4 , 5 ]. Most acute Achilles tendon ruptures are observed in middle-aged men, predominantly during sports activities that require abrupt initiation and cessation of movement, including tennis, basketball, soccer, and badminton [ 6 ]. Notably, between 81 and 89% of rupture cases are attributed to the physical demands of athletic activities as the primary cause of injury [ 7 , 8 , 9 ]. Acute Achilles tendon rupture usually requires operative intervention. Otherwise, passive therapy may cause continuous pain and limited motion of the overall ankle joint and even leave a lifelong disability due to the extremity atrophy of the injured side.

Notably, this operative procedure has varied over the years. As such, the open repair requires a 10—15 cm incision to broadly separate the subcutaneous fascia and tendon sheath to search the broken ends for tendon anastomosis. This method was performed under direct supervision and could effectively protect the sural nerve, which was reported to significantly improve clinical outcomes compared with nonoperative options [ 10 ]. In 1977, Prof Ma and Griffith introduced the mini-open technique for acute Achilles tendon ruptures. They reported that this advanced attempt has many advantages, including a rapid recovery, a short hospitalization period, and a cosmetic appearance at the surgical site [ 11 ]. Recent literature also reported a series of surgical methods for minimally invasive approaches and described their clinical effects to minimize adverse events [ 12 , 13 , 14 ]. An Achilles tendon rupture guideline indicates that acute Achilles tendon rupture is a suitable indication for minimally invasive techniques, with clinical recovery rates of at least 85% [ 15 ]. Nevertheless, many institutions lack professional facilities to perform this surgery, and the importation of some equipment is limited for financial and administrative reasons.

In recent years, we have referred to previous reports that used the “lumbar puncture needle and oval forceps” technique to repair the ruptured Achilles tendon [ 16 , 17 , 18 ]. Generally, the surgical proficiency of orthopedic surgeons could be assessed using statistical analysis of surgical details, radiographic parameters, and postoperative clinical outcomes. However, this traditional evaluation has shown limited accuracy in demonstrating a surgeon’s ability. As such, the learning curve can be used to measure competency and proficiency in various surgical procedures [ 19 , 20 ]. Notably, this progressive method has been widely used to estimate foot and ankle surgery [ 21 , 22 ].

Based on this, our study used the cumulative sum (CUSUM) methodology to present the learning process of this minimally invasive operation in treating acute Achilles tendon rupture.

Study design

With the approval of the institutional review committee, a retrospective study was performed on patients who underwent operative treatments for acute Achilles tendon ruptures in 36 from May 2020 to June 2022.

Inclusion criteria were as follows: (1) patients over 18 years old, (2) within two weeks after injury, (3) the definitive diagnosis of the Achilles tendon rupture confirmed by preoperative ultrasound and MRI, (4) positive results of Thompson test and the palpable gap at the rupture sites of Achilles tendon, (5) the Achilles tendon rupture occurring at 2–8 cm proximal to insertion (non-insertional type), (6) receiving a minimally invasive treatment of “lumbar puncture needle and oval forceps,” (7) follow-up more than twelve months. Exclusion criteria: (1) patients under 18 years old, (2) chronic injury (> 2 weeks), (3) open injury of Achilles tendons, (4) incomplete clinical data or follow-up of less than a year.

Two clinical investigators were responsible for individual data collection. Demographic data (gender and age), injury mechanism, and injury side were obtained from medical records. In addition, surgical details, including surgical time and postoperative length of stays (post-LOS), were also reviewed.

Operative technique

Minimally invasive repair (lumbar puncture needle and oval forceps) [ 16 , 18 ].

The patient was under spinal anesthesia or general anesthesia, in a prone position with a pad under the ankle. (Fig.  1 ).

The surgeon palpated the tendon’s gap and observed the positive sign (“finger sign”). Then, a 2–3 cm longitudinal incision was immediately made over the ruptured Achilles tendon site.

An Allis clamp was used to retrieve the proximal/distal broken end. An oval forceps was also inserted to penetrate both sides of the ruptured tendon. A lumber puncture needle (BD Medical System, NJ, USA) created a subcutaneous tunnel through the skin, subcutaneous fat, fascia, paratenon, tendon, and two eyelet rings of the oval forceps. Particularly in confirming whether the needle involved the ruptured tendon, the surgeon should attempt to withdraw the oval forceps.

Then, a No. 0 polydioxanone (PDS) (Ethicon, Somerville, NJ, USA) was passed through the needle. After the needle and oval forceps were retrieved, the suture tails were concomitantly detached from the incision. Sutures were carefully separated and marked. The above procedure was repeated three times at the proximal/ distal site, and the needle pitch was about 0.8 cm. A No. 2 polyester suture (Ethicon, Somerville, NJ, USA) was used in each middle suture.

Ruptured tendon strength was tested by gentle retraction of the sutures, which could minimize the risk of entrapping the sural nerve. The operated ankle was located at 30° of plantar flexion during repair. The most proximal suture from the proximal segment was tied to the most proximal from the distal, and so on. The loops were concealed severally beneath the paratenon.

The paratenon/subcutaneous tissue and skin were closed using 2/0 Vicryl (Ethicon, Somerville, NJ, USA) and 3/0 nonabsorbable suture (Ethicon, Somerville, NJ, USA), respectively.A sterile dressing and a plaster splint were applied to the ankle with 30 degrees of plantar flexion.

A series of interoperative photos illustrating the minimally invasive Achilles repair. A A pre-operative MRI showing a definite rupture of the Achilles tendon. B A 2-cm transverse incision was made over the central part of the Achilles tendon defect. C: An Allis clamp exposed and retracted the rupture site. D After the subcutaneous tunnel was built, the oval forceps was inserted and the Achilles tendon defect was grasped. Then, a lumbar puncture needle was passed through the tendon and the eyelet ring of the oval forceps. E Sutures went into the needle. The red circle denoted the nonabsorbable sutures. F It should be noted that the stitches were separated to avoid the concentration of suture knots. G The wound was sewed up in plantar flexion. H Postoperative radiographic data presented that the tendon healed well

Postoperative management

Stage 1: For the first two weeks postoperatively, patients were instructed to apply over-the-knee full casts with 30-degree knee flexion and 30-degree plantar flexion. Additionally, they were allowed to sustain 1/6 to 1/3 of the total weight. Heel cushions were available to adjust the plantar flexion angle and enhance the ankle proprioception.

Stage 2: A below-knee cast and walking brace were used for the next two weeks, and the goal was to gradually reach a full weight bearing. A full range of ankle motion attempts and concentric loading was instituted under the guidance of a physical therapist. Subsequent eccentric loading is gradually carried out according to the patient's recovery.

Stage 3: The walking braces were removed at 5 weeks postoperative, and they could walk with normal shoes. Plyometric exercises were permitted, and patients were encouraged to participate in athletic activities if they felt comfortable during the ninth week.

• Clinical outcomes

To evaluate the operative outcome, we used the Achilles tendon rupture score (ATRS), the American Orthopedic Foot and Ankle Society (AOFAS) ankle/hindfoot score, and the visual analog scale (VAS). The ATRS scoring system is a validated Achilles tendon rupture instrument [ 23 , 24 ]. The ATRS is a Patient-Reported Outcome Measure (PROM) presenting the difficulty level of various physical activities due to symptoms. The AOFAS scoring systems, including self-assessment and objective scoring, are broadly used to evaluate the ankle joint's clinical function, range of motion, and tolerance [ 25 ]. During the follow-up, we also recorded the time to return to work, full weight bearing, and return to previous activities. Furthermore, we collected patient complications during follow-up, including re-rupture, suture reaction, wound dehiscence, and deep infection.

Re-rupture was defined as a definite rupture after surgical repair. Suture reaction and wound dehiscence were counted when the redness/swelling of the incision and superficial wound breakdown, respectively [ 26 ]. Deep infection was referred to the previous definition of fracture-related infection, regarding as a postoperative infection presented a year after surgery and met at least one of the pathologic conditions: (1) clinical signs of a fistula, sinus, wound necrosis, or purulent exudation, (2) confirmed microorganisms by laboratory evidence from at least two separate deep tissues or implants during paracentesis or re-operation [ 27 ].

CUSUM analysis

Consecutive cases were enrolled in chronological order. The CUSUM method was applied to analyze the learning curve, focusing on surgical duration [ 28 ]. We also used the following formula for the CUSUM calculation: \(CUSUM={\sum }_{i=1}^{n}(Xi-U)\) . 'Xi' was the operation time per case, 'U' was the average operation time across all cases, and 'n' was the consecutive numbering of each case. Python (version 3.9.6) was used for analysis and scatter plot generation was used to obtain the function formula through curve fitting. The efficacy of the curve fitting was assessed using the correlation coefficient R 2 , with values approaching 1 indicating more precise fitting. The first order of the curve was chosen and the curve apex was based on the slope. Notably, this apex contributed to segregating the patients into individual groups of learning and mastery, establishing a cut-off value representing the minimum number of cases in which a surgeon was required to obtain a certain level of proficiency [ 29 ].

Statistical analysis

According to the normal distribution results, continuous variables were analyzed using the independent samples t-test or Mann–Whitney u-test. The enumeration variables were analyzed using the chi-square or Fisher exact tests where appropriate. Descriptive data were presented as mean ± standard deviation (SD), median (interquartile range, IQR), and frequency (percentage) for normally and non-normally distributed continuous data and enumeration data. All statistical analyses were performed using SPSS software (IBM SPSS Statistics, Version 26.0). A p -value of < 0.05 was considered statistically significant in this study.

Baseline data and learning curve quantification

In general, a consecutive cohort of sixty-seven cases who received a “lumbar puncture needle and oval forceps” in treating acute Achilles rupture in our institution were reviewed. Finally, thirty-six patients were enrolled in this study (Fig.  2 ).

Flowchart of the study design

Since these results of surgical performance demonstrated that the learning curve peaked at the 12th case, we divided the cases into 2 groups: the learning phase ( n  = 12, case 1–12) and master phase ( n  = 24, case 13–36) (Fig.  3 ). The best-fit linear equation was: CUSUM = 1.68 × 10 −2 n 3 —1.30 × 10 0 n 2  + 2.42 × 10 1 n + 4.14 × 10 1 (R 2  = 0.95), where n represented the individual case.

The cumulative sum curve for surgical time: peak at the twelfth case

The learning phase and master phase were statistically similar in gender ratio (the learning phase 83.3%, the master phase 79.2%, p  = 0.766) and age (the learning phase 32.8 ± 6.8 years, the master phase 32.3 ± 5.2 years, p  = 0.785) (Fig.  4 ). Other clinical data also demonstrated no statistical difference between these groups in injury mechanism, injury side, post-LOS, and blood loss ( p  > 0.05). However, the learning phase was significantly longer than the master phase for surgical time (71.1 ± 13.2 vs. 45.8 ± 7.2 min, p  = 0.004).

The forest graph illustrating the comparisons of baseline data and surgical details between the learning and master phases

Postoperative assessments

The clinical outcome evaluation was assessed using the ATRS and AOFAS. The VAS scoring system determined the pain. We found no statistical correlation between these ATRS, AOFAS, and VAS groups in 3/6/9/12 months (Table  1 , Figs.  5  and  6 ). Similarly, neither time to return to work/ full-weight bearing/ previous activities showed a significant difference ( p  > 0.05).

Boxplots of the clinical scoring systems between the two groups. The horizontal lines, the boxes and the whiskers represent the median scores, the interquartile range and the minimum/ maximum, respectively

Proportion bar charts of VAS in these groups at 3/6/9/12 months

Regarding the complication within a year, one patient (case 4) was detected with a suture reaction, which presented in the fourth month postoperatively. After removing the nonabsorbable sutures, the redness and swelling of his injured Achilles tendon gradually improved in the following seven days. Major complications, including re-rupture, wound dehiscence, and deep infection, were not found in these thirty-six patients.

Achilles tendon rupture is a common injury in daily life, accounting for 35% of the rate of human tendon damage. This injury always occurs during motor activity, of which men aged 30 – 50 are the most susceptible [ 30 , 31 ]. A clinical study found that the male proportion and the mean age of the entire study were 88.9% and 36.9 years, consistent with our research [ 32 ]. We also detected that patients were keen on exercise and usually in good physical condition before the tendon got hurt. For such patients, they were enthusiastic about rehabilitation.

Despite it usually suddenly occurring, however, there is still a fair amount of chronic Achilles tendon rupture that is ascribed to misdiagnosis or disregarding this injury. Chronic Achilles tendon rupture mainly presents with cicatricial tissues irregularly buttressing the rupture gap and causing broken ends retraction, gastrocnemius atrophy, and gait incoordination [ 33 , 34 ]. Consequently, these uncertainties and diversity produce different therapeutic regimens compared to acute injuries. Therefore, we excluded patients with chronic Achilles tendon rupture from this study.

Many different techniques have been introduced for operative interventions. Previous research pointed out that open surgery had a deficiency in wound healing and deep infection [ 35 , 36 , 37 ]. Although the percutaneous method minimized the wound complications, it increased the risk of the sural nerve injury and re-rupture [ 38 ]. A cadaveric study also observed that a minimally invasive method could be safe for sural nerves if the technique were used correctly [ 11 , 39 ]. Campillo-Recio et al. disagreed that the percutaneous method was superior to the conservative treatment because the latter allowed the earlier weight-bearing and controlled rehabilitation protocol at a young age [ 40 ]. Furthermore, Attia et al. reported that the incidence of deep infection for open surgery was over 20% [ 41 ]. However, our results did not detect deep infection, possibly due to the small number of patients we included and the short follow-up period.

In 2014, a technique was described that included a mini-open surgery combined with a knotless percutaneous instrument (the Achilles Midsubstance SpeedBridge) to repair the injured site [ 42 ]. Hoskins et al. also reported that patients treated by an Arthrex PARS Achilles Jig System and their postoperative AOFAS and ATRS reached 90.3 and 88.0 points [ 9 ]. Concerning complications, they observed cases of re-rupture (1.2%) and suture irritation (1.2%). Notably, these follow-up data were similar to ours. Thus, patients could obtain a full weight bearing in the ninth week after surgery, conforming to the principle of rehabilitation.

For economic reasons, our institution did not import these instruments. Therefore, we referred to previous studies and used the simplified instrument, “the oral forceps and lumbar puncture needles.” This method was first reported by Ngai et al. and significantly reduced the surgery cost, which was widely used worldwide [ 18 ]. Liu et al. inserted an additional two anchors into the calcaneus from this previous study. However, we thought this also caused unnecessary waste [ 16 ]. Thus, our study used only three sutures and ensured these knots were staggered to avoid tissue cutting and centralization. Follow-up results also showed a relatively clinical outcome. Biz et al. used Tenolig technology to repair the Achilles tendon rupture, which cost nearly 1,000 euros [ 43 ].

In this study, the average operative time was 45.8 min after reaching mastery. Attia et al. included ten randomized controlled studies on open versus minimal invasive acute Achilles tendon rupture repair. The results showed that the average time was 51.0 and 29.7 min [ 41 ]. We took a longer surgical time for each procedure, which might be attributed to different calculations, defined as the time interval from surgical area disinfection to wound closing in our institution.

We recognize that there are several limitations to this study. Firstly, the relatively small series size, including its retrospective design, limits the reliability of our research. A power analysis was not conducted, and our results must be interpreted cautiously. Secondly, this minimally invasion surgery was performed by an individual surgeon. Discrepancies in the learning curves exist among surgeons, so its generalization remains unknown. For all this, our study has proved surgeons could be proficient with this technique over time. However, additional studies are needed to support these findings.

Conclusions

Our learning curve analysis demonstrated that the surgical competence in treating an acute Achilles tendon rupture with the “lumbar puncture needle and oval forceps” was obtained after the primary learning period of 12 cases. Furthermore, this technique benefited early rehabilitation and rapid return to normal life.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

We appreciate all co-authors for their contributions to this study and the writing of this manuscript. The authors thank AiMi Academic Services ( www.aimieditor.com ) for English language editing and review services.

This work is Supported by National Natural Science Foundation of China (82272469) and Beijing Key Clinical Specialty Project.

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Yanrui Zhao, Hanzhou Wang and Binzhi Zhao contributed equally to this work and co-first authors.

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Department of Orthopedic Surgery, Beijing Chaoyang Hospital, Capital Medical University, 8 Gongren Tiyuchang Nanlu, Chaoyang District, 100020, Beijing, P.R. China

Yanrui Zhao, Hanzhou Wang, Binzhi Zhao, Shuo Diao, Yuling Gao, Junlin Zhou & Yang Liu

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All authors contributed to the conception and design of the study. Material preparation, data collection, and analysis were performed by ZYR, WHZ, and ZBZ. WHZ and ZBZ wrote the first draft of the manuscript. SD and YLG were responsible for the production of the study illustrations. Throughout the process, YL and JLZ provided guidance and insight. All authors have read and approved the final manuscript for submission.

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Correspondence to Junlin Zhou or Yang Liu .

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Zhao, Y., Wang, H., Zhao, B. et al. The learning curve for minimally invasive Achilles repair using the “lumbar puncture needle and oval forceps” technique. BMC Musculoskelet Disord 25 , 373 (2024). https://doi.org/10.1186/s12891-024-07489-9

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Received : 03 January 2024

Accepted : 03 May 2024

Published : 11 May 2024

DOI : https://doi.org/10.1186/s12891-024-07489-9

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