Home Field Advantage? Comparing the Quality of EPA Observations Completed On- vs Off-Service
Bibliographic record
Abstract
ABSTRACT Background Increasing evidence suggests that supervisors exhibit different assessment behaviors for residents from their own discipline compared to those completing a rotation from another discipline. As programs of assessment rely on collecting robust performance data to inform high-stakes decisions about progress and promotion, it is important to examine the quality of such inputs. Objective To compare the quality of workplace-based assessments (WBAs) of emergency medicine (EM) residents by EM and non-EM assessors. Methods This retrospective database study compared the quality of WBAs using the Quality of Assessment of Learning (QuAL) score (range 0-5), a previously published measure of WBA quality that has demonstrated strong psychometric characteristics. Five entrustable professional activities (EPAs), 3 procedural and 2 non-procedural, mapped to both EM and non-EM rotations, were selected for inclusion. Two hundred and fifty WBAs (50 WBAs per EPA; 25 EM and 25 non-EM), completed from July 2019 to June 2021, were rated by 3 blinded EM physician raters. QuAL scores were analysed using factorial ANOVA. Results Mean QuAL scores for WBAs completed during EM rotations were significantly higher compared to those completed during non-EM rotations (3.66±0.99 vs 3.02±0.99). Further, mean QuAL score for procedural EPAs was significantly higher than non-procedural EPAs (3.61±1.00 vs 3.16±1.03). Conclusions In this study, the quality of WBAs completed for EM residents during non-EM rotations was of lower quality compared to assessments on EM rotations.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".