This article summarizes the major types of research designs used in healthcare research, including experimental, quasi-experimental, and observational studies. Observational studies are divided into survey studies (descriptive and correlational studies), case-studies and analytic studies, the last of which are commonly used in epidemiology: case-control, retrospective cohort, and prospective cohort studies. Similarities and differences among the research designs are described and the relative strength of evidence they provide is discussed. Emphasis is placed on five criteria for drawing causal inferences that are derived from the writings of the philosopher John Stuart Mill, especially his methods or canons. The application of the criteria to experimentation is explained. Particular attention is given to the degree to which different designs meet the five criteria for making causal inferences. Examples of specific studies that have used various designs in chaplaincy research are provided.
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http://dx.doi.org/10.1080/08854726.2014.871909 | DOI Listing |
Proc Natl Acad Sci U S A
January 2025
Department of Primate Behavioral Ecology, Institute of Biology, Leipzig University, Leipzig 04103, Germany.
Biological relatedness is a key consideration in studies of behavior, population structure, and trait evolution. Except for parent-offspring dyads, pedigrees capture relatedness imperfectly. The number and length of identical-by-descent DNA segments (IBD) yield the most precise relatedness estimates.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Department of Economics, University of Oregon, Eugene, OR 97403.
The advent of herbicide-tolerant genetically modified (GM) crops spurred rapid and widespread use of the herbicide glyphosate throughout US agriculture. In the two decades following GM-seeds' introduction, the volume of glyphosate applied in the United States increased by more than 750%. Despite this breadth and scale, science and policy remain unresolved regarding the effects of glyphosate on human health.
View Article and Find Full Text PDFBrief Bioinform
November 2024
School of Artificial Intelligence, Jilin University, 3003 Qianjin Street, 130012 Changchun, China.
Accurate identification of causal genes for cancer prognosis is critical for estimating disease progression and guiding treatment interventions. In this study, we propose CPCG (Cancer Prognosis's Causal Gene), a two-stage framework identifying gene sets causally associated with patient prognosis across diverse cancer types using transcriptomic data. Initially, an ensemble approach models gene expression's impact on survival with parametric and semiparametric hazard models.
View Article and Find Full Text PDFClin Pharmacol Ther
January 2025
Center for Observational Research, Amgen Inc., Thousand Oaks, California, USA.
A compilation of factors over the past decade-including the availability of increasingly large and rich healthcare datasets, advanced technologies to extract unstructured information from health records and digital sources, advancement of principled study design and analytic methods to emulate clinical trials, and frameworks to support transparent study conduct-has ushered in a new era of real-world evidence (RWE). This review article describes the evolution of the RWE era, including pharmacoepidemiologic methods designed to support causal inferences regarding treatment effects, the role of regulators and other health authorities in establishing distributed real-world data networks enabling analytics at scale, and the many global guidance documents on principled methods of producing RWE. This article also highlights the growing opportunity for RWE to support decision making by regulators, health technology assessment groups, clinicians, patients, and other stakeholders and provides examples of influential RWE studies.
View Article and Find Full Text PDFHLA
January 2025
IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, Italy.
COVID-19 remains a significant global health problem with uncertain long-term consequences for convalescents. We investigated the relationships between anti-N protein antibody levels, severe acute respiratory syndrome (SARS)-CoV-2-associated TCR repertoire parameters, HLA type and epidemiological information from three cohorts of 524 SARS-CoV-2-infected subjects subgrouped in acute phase, seronegative and seropositive convalescents from the Emilia Romagna region. Epidemiological information and anti-N antibody index were associated with TCR repertoire data.
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