ArticleBMC medical education2024
Measuring and correcting staff variability in large-scale OSCEs.
Article in BMC medical education, 2024. 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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Agreement Between Reasoning-Oriented Generative AI Models and Clinical Educators in Evaluating Japanese Objective Structured Clinical Examination Transcripts: Preliminary Comparative Study.JMIR formative research · 2026Article
- Applying generalized theory to optimize the quality of high-stakes objective structured clinical examinations for undergraduate medical students: experience from the French medical school.BMC medical education · 2025Article
- Teaching Interprofessional Communication in Midwifery Students Using the SBAR Tool.Journal of medical education and curricular developmentArticle
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
contextObjective Structured Clinical Examinations (OSCEs) are an increasingly popular evaluation modality for medical students. While the face-to-face interaction allows for more in-depth assessment, it may cause standardization problems. Methods to quantify, limit or adjust for examiner effects are needed.
methodsData originated from 3 OSCEs undergone by 900-student classes of 5
resultsFrom the four sessions, a total of 16,910 station scores were collected from 2615 student sessions, with two of the sessions undergone by the same students, and 36, 36, 35 and 20 distinct staff teams in each station for each session. Scores had staff-related heterogeneity (p<10
conclusionStaff variability impacts OSCE scores as much as student variability, and the former can be reduced with dual assessment or adjusted for with mixed models. Both are small compared to unmeasured sources of variability, making them difficult to capture consistently.
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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.