Rater Training in Medical Education: A Scoping Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There is an increasing focus in medical education on trainee evaluation. Often, reliability and other psychometric properties of evaluations fall below expected standards. Rater training, a process whereby raters undergo instruction on how to consistently evaluate trainees and produce reliable and accurate scores, has been suggested to improve rater performance within behavioral sciences. A scoping literature review was undertaken to examine the effect of rater training in medical education and address the question: "Does rater training improve performance attending physician evaluations of medical trainees?" Two independent reviewers searched PubMed®, MEDLINE®, EMBASE™, the Cochrane Library, CINAHL®, ERIC™, and PsycInfo® databases and identified all prospective studies examining the effect of rater training on physician evaluations of medical trainees. Consolidated Standards of Reporting Trials (CONSORT) and Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklists were used to assess quality. Fourteen prospective studies met the inclusion criteria. All had heterogeneity in design, type of rater training, and measured outcomes. Pooled analysis was not performed. Four studies examined rater training used to assess technical skills; none identified a positive effect. Ten studies assessed its use to evaluate non-technical skills: six demonstrated no effect, while four showed a positive effect. The overall quality of studies was poor to moderate. Rater training in medical education literature is heterogeneous, limited, and describes minimal improvement on the psychometric properties of trainee evaluations when implemented. Further research is required to assess rater training's efficacy in medical education.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.121 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it