BACKGROUND: Case study research (CSR) has gained popularity across disciplines due to its ability to provide detailed insights into specific phenomena.
OBJECTIVE: To explore the philosophy and methodology of CSR, drawing from notable authors who have contributed to its development.
CONCLUSIONS: This article discusses the characteristics of CSR in terms of design and method in both quantitative and qualitative approaches. It examines CSR\'s advantages and disadvantages as a research method. It draws on two example case studies to emphasise the use of CSR for exploring complex healthcare and social care settings.
CONCLUSIONS: CSR has proven valuable in nursing research for investigating complex clinical problems, patient-care scenarios, and organisational dynamics and phenomena.
CONCLUSIONS: CSR provides a methodological framework for nursing research that offers a unique lens for exploring multifaceted, complex issues. This ultimately improves patient care outcomes.

The determination of risk factors for disease incidence has been the subject of much epidemiologic research. With this goal a common study design entails the follow-up of an initially disease-free cohort, keeping track of the dates of disease incidence (onset) and ascertaining covariate (putative risk factor) information on the full cohort. However, the collection of certain covariate information on all study subjects may be prohibitively expensive and, therefore, the nested case-control study has commonly been used. The high cost of full covariate information on all subjects also arises when determining risk factors for \"failure,\" death say, \"following\" disease onset, in particular, in a prevalent cohort study with follow-up; in such a study a cohort of subjects with existing disease is followed. We here adapt nested case-control designs to the setting of a prevalent cohort study with follow-up, a topic previously not addressed in the literature. We provide the partial likelihood under risk set sampling and state the asymptotic properties of the estimated covariate effects and baseline cumulative hazard. We address the following design questions in the context of prevalent cohort studies with follow-up: How many subjects should be included in the sampled risk sets for efficient estimation? In what way is the proportion of censored subjects associated with the benefit of a nested case-control design? What proportion of overall variance is attributable to risk set sampling? This work is motivated by the anticipated analysis of data on survival with Parkinson\'s Disease, being collected as part of the ongoing Canadian Longitudinal Study on Aging.
La détermination des facteurs de risque pour l’incidence d’une maladie est le sujet de nombreuses études épidémiologiques. À cet effet, un plan d’expérience commun consiste à suivre une cohorte initialement en santé en prenant note de la date à laquelle la maladie se manifeste (début) et en évaluant les covariables (facteurs de risque présumés) pour la cohorte en entier. Lorsque la collecte de certaines covariables pour tous les individus s’avère trop onéreuse, une étude cas-témoins peut eˆtre considérée. Un problème similaire de couˆts élevés pour la collecte d’information sur tous les sujets peut également se présenter lorsque les facteurs de risque pour un « échec », disons le décès, doivent eˆtre déterminés après le début de la maladie. Une telle situation peut survenir dans une étude sur une cohorte prévalente avec suivi, mais la question n’a pas encore été traitée dans la littérature. Les auteurs développent la vraisemblance partielle pour un échantillonnage dans l’ensemble à risque et décrivent les propriétés asymptotiques des estimés de l’effet des covariables et de la fonction cumulative du risque de base. Ils répondent à certaines questions émergeant d’un plan d’expérience pour une cohorte prévalente avec suivi, notamment le nombre de sujets à inclure dans l’ensemble de risque pour obtenir une estimation efficace, les façons dont la proportion de sujets censurés est liée aux bénéfices d’un plan cas-témoin imbriqué, et la proportion de variance globale attribuable à l’échantillonnage dans l’ensemble à risque. Le développement de ces méthodes est motivé par l’analyse imminente de données de survie de patients atteints de la maladie de Parkinson dont la collecte est en cours dans le cadre de l’é tude longitudinale canadienne sur le vieillissement.

Prevotella copri is an abundant member of the human gastrointestinal microbiome, whose relative abundance has curiously been associated with positive and negative impacts on diseases, such as Parkinson\'s disease and rheumatoid arthritis. Yet, the verdict is still out on the definitive role of P. copri in human health, and on the effect of different diets on its relative abundance in the gut microbiome. The puzzling discrepancies among P. copri studies have only recently been attributed to the diversity of its strains, which substantially differ in their encoded metabolic patterns from the commonly used reference strain. However, such strain differences cannot be resolved by common 16S rRNA amplicon profiling methods. Here, we scrutinize P. copri, its versatile metabolic potential, and the hypotheses behind the conflicting observations on its association with diet and human health. We also provide suggestions for designing studies and bioinformatics pipelines to better research P. copri.

The rule of thumb that there is little gain in statistical power by obtaining more than 4 controls per case, is based on type-1 error α = 0.05. However, association studies that evaluate thousands or millions of associations use smaller α and may have access to plentiful controls. We investigate power gains, and reductions in p-values, when increasing well beyond 4 controls per case, for small α.
We calculate the power, the median expected p-value, and the minimum detectable odds-ratio (OR), as a function of the number of controls/case, as α decreases.
As α decreases, at each ratio of controls per case, the increase in power is larger than for α = 0.05. For α between 10-6 and 10-9 (typical for thousands or millions of associations), increasing from 4 controls per case to 10-50 controls per case increases power. For example, a study with power = 0.2 (α = 5 × 10-8) with 1 control/case has power = 0.65 with 4 controls/case, but with 10 controls/case has power = 0.78, and with 50 controls/case has power = 0.84. For situations where obtaining more than 4 controls per case provides small increases in power beyond 0.9 (at small α), the expected p-value can decrease by orders-of-magnitude below α. Increasing from 1 to 4 controls/case reduces the minimum detectable OR toward the null by 20.9%, and from 4 to 50 controls/case reduces by an additional 9.7%, a result which applies regardless of α and hence also applies to \"regular\" α = 0.05 epidemiology.
At small α, versus 4 controls/case, recruiting 10 or more controls/cases can increase power, reduce the expected p-value by 1-2 orders of magnitude, and meaningfully reduce the minimum detectable OR. These benefits of increasing the controls/case ratio increase as the number of cases increases, although the amount of benefit depends on exposure frequencies and true OR. Provided that controls are comparable to cases, our findings suggest greater sharing of comparable controls in large-scale association studies.

UNASSIGNED: We review the application and limitations of two implementations of the \"case-only design\" in injury epidemiology with example analyses of Fatality Analysis Reporting System data.
UNASSIGNED: The term \"case-only design\" covers a variety of epidemiologic designs; here, two implementations of the design are reviewed: (1) studies to uncover etiological heterogeneity and (2) studies to measure exposure effect modification. These two designs produce results that require different interpretations and rely upon different assumptions. The key assumption of case-only designs for exposure effect modification, the more commonly used of the two designs, does not commonly hold for injuries and so results from studies using this design cannot be interpreted. Case-only designs to identify etiological heterogeneity in injury risk are interpretable but only when the case-series is conceptualized as arising from an underlying cohort.
UNASSIGNED: The results of studies using case-only designs are commonly misinterpreted in the injury literature.

Genome-wide association studies (GWAS) have significantly advanced our understanding of the genetic underpinnings of diseases, but case and control cohort definitions for a given disease can vary between different published studies. For example, two GWAS for the same disease using the UK Biobank data set might use different data sources (i.e., self-reported questionnaires, hospital records, etc.) or different levels of granularity (i.e., specificity of inclusion criteria) to define cases and controls. The extent to which this variability in cohort definitions impacts the end-results of a GWAS study is unclear. In this study, we systematically evaluated the effect of the data sources used for case and control definitions on GWAS findings. Using the UK Biobank, we selected three diseases-glaucoma, migraine, and iron-deficiency anemia. For each disease, we designed 13 GWAS, each using different combinations of data sources to define cases and controls, and then calculated the pairwise genetic correlations between all GWAS for each disease. We found that the data sources used to define cases for a given disease can have a significant impact on GWAS end-results, but the extent of this depends heavily on the disease in question. This suggests the need for greater scrutiny on how case cohorts are defined for GWAS.

UNASSIGNED: Preeclampsia is a leading cause of maternal and perinatal mortality and morbidity. The management of preeclampsia has not changed much in more than two decades, and its aetiology is still not fully understood. Case reports and case series have traditionally been used to communicate new knowledge about existing conditions. Whether this is true for preeclampsia is not known.
UNASSIGNED: To determine whether recent case reports or case series have generated new knowledge and clinical discoveries about preeclampsia.
UNASSIGNED: A detailed search strategy was developed in consultation with a medical librarian. Two bibliographic databases were searched through Ovid: Embase and MEDLINE. We selected case reports or case series published between 2015 and 2020, comprising pregnant persons diagnosed with hypertensive disorders of pregnancy, including preeclampsia. Two reviewers independently screened all publications. One reviewer extracted data from included studies, while another conducted a quality check of extracted data. We developed a codebook to guide our data extraction and outcomes assessment. The quality of each report was determined based on Joanna Briggs Institute (JBI) critical appraisal checklist for case reports and case series.
UNASSIGNED: We included 104 case reports and three case series, together comprising 118 pregnancies. A severe presentation or complication of preeclampsia was reported in 81% of pregnancies, and 84% had a positive maternal outcome, free of death or persistent complications. Only 8% of the case reports were deemed to be of high quality, and 53.8% of moderate quality; none of the case series were of high quality. A total of 26 of the 107 publications (24.3%) included a novel clinical discovery as a central theme.
UNASSIGNED: Over two-thirds of recent case reports and case series about preeclampsia do not appear to present new knowledge or discoveries about preeclampsia, and most are of low quality.

Hybrid effectiveness-implementation studies allow researchers to combine study of a clinical intervention\'s effectiveness with study of its implementation with the aim of accelerating the translation of evidence into practice. However, there currently exists limited guidance on how to design and manage such hybrid studies. This is particularly true for studies that include a comparison/control arm that, by design, receives less implementation support than the intervention arm. Lack of such guidance can present a challenge for researchers both in setting up but also in effectively managing participating sites in such trials. This paper uses a narrative review of the literature (Phase 1 of the research) and comparative case study of three studies (Phase 2 of the research) to identify common themes related to study design and management. Based on these, we comment and reflect on: (1) the balance that needs to be struck between fidelity to the study design and tailoring to emerging requests from participating sites as part of the research process, and (2) the modifications to the implementation strategies being evaluated. Hybrid trial teams should carefully consider the impact of design selection, trial management decisions, and any modifications to implementation processes and/or support on the delivery of a controlled evaluation. The rationale for these choices should be systematically reported to fill the gap in the literature.

Collecting new data from cross-sectional/survey and cohort observational study designs can be expensive and time-consuming. Nested (hierarchically cocooned within an existing parent study) and/or Multipart (≥ 2 integrally interlinked projects) study designs can expand the scope of a prospective observational research program beyond what might otherwise be possible with available funding and personnel. The Brain, Bone, Heart (BBH) study provides an exemplary case to describe the real-world advantages, challenges, considerations, and insights from these complex designs. MAIN: BBH is a Nested, Multipart study conducted by the Specialized Center for Research Excellence (SCORE) on Sex Differences at Emory University. BBH is designed to examine whether estrogen insufficiency-induced inflammation compounds HIV-induced inflammation, leading to end-organ damage and aging-related co-morbidities affecting the neuro-hypothalamic-pituitary-adrenal axis (brain), musculoskeletal (bone), and cardiovascular (heart) organ systems. Using BBH as a real-world case study, we describe the advantages and challenges of Nested and Multipart prospective cohort study design in practice. While excessive dependence on its parent study can pose challenges in a Nested study, there are significant advantages to the study design as well. These include the ability to leverage a parent study\'s resources and personnel; more comprehensive data collection and data sharing options; a broadened community of researchers for collaboration; dedicated longitudinal research participants; and, access to historical data. Multipart, interlinked studies that share a common cohort of participants and pool of resources have the advantage of dedicated key personnel and the challenge of increased organizational complexity. Important considerations for each study design include the stability and administration of the parent study (Nested) and the cohesiveness of linkage elements and staff organizational capacity (Multipart).
Using the experience of BBH as an example, Nested and/or Multipart study designs have both distinct advantages and potential vulnerabilities that warrant consideration and require strong biostatistics and data management leadership to optimize programmatic success and impact.

The hallmark of case-control study design involves dividing groups based on outcome and looking back at exposures to determine associations. Case-control studies are ideal for scenarios when outcomes are rare, making them well suited to the infrequent events often found among neurosurgical diseases. It is also a favorable design for scenarios when it would be infeasible or unethical to assign treatment groups as is necessary for a randomized controlled trial. Case-control studies are powerful but often misapplied and mislabeled. This article provides an overview of case-control study design along with discussion of a real-world example of an effectively executed case-control study.