ArticlePRiMER (Leawood, Kan.)2025
Methods for Studying Bias in Graduate Medical Education.
Article in PRiMER (Leawood, Kan.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- Implementation of Emotional Connection Training in Pediatric Primary Care: Mixed Methods Study.JMIR medical education · 2026Article
- Reframing the Kirkpatrick model for evaluating humanistic care training in nursing: a context-sensitive integrative perspective.Frontiers in public health · 2026Article
- Methods Matter: Introducing a Methodological Briefs Series inPRiMER (Leawood, Kan.) · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Consistent with patterns seen in the larger population, bias in medical settings has been well established and negatively impacts outcomes, quality of care, and patient-clinician interactions. The purpose of this article is to provide a brief and introductory review of research methods for studying bias in graduate medical education, including (a) specific designs to consider and (b) considerations for overcoming barriers to implementation. While there are a variety of ways in which bias and inequity can be studied in medical settings, the unique limitations of graduate medical education may pose numerous challenges that researchers may need to overcome. Limited research addresses bias and inequity in graduate medical settings; future research might explore these topics in ways that are tailored to this educational setting.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.