Workplace-Based Entrustment Scales for the Core EPAs: A Multisite Comparison of Validity Evidence for Two Proposed Instruments Using Structured Vignettes and Trained Raters
Bibliographic record
Abstract
PURPOSE: In undergraduate medical education (UME), competency-based medical education has been operationalized through the 13 Core Entrustable Professional Activities for Entering Residency (Core EPAs). Direct observation in the workplace using rigorous, valid, reliable measures is required to inform summative decisions about graduates' readiness for residency. The purpose of this study is to investigate the validity evidence of 2 proposed workplace-based entrustment scales. METHOD: The authors of this multisite, randomized, experimental study used structured vignettes and experienced raters to examine validity evidence of the Ottawa scale and the UME supervisory tool (Chen scale) in 2019. The authors used a series of 8 cases (6 developed de novo) depicting learners at preentrustable (less-developed) and entrustable (more-developed) skill levels across 5 Core EPAs. Participants from Core EPA pilot institutions rated learner performance using either the Ottawa or Chen scale. The authors used descriptive statistics and analysis of variance to examine data trends and compare ratings, conducted interrater reliability and generalizability studies to evaluate consistency among participants, and performed a content analysis of narrative comments. RESULTS: Fifty clinician-educators from 10 institutions participated, yielding 579 discrete EPA assessments. Both Ottawa and Chen scales differentiated between less- and more-developed skill levels (P < .001). The interclass correlation was good to excellent for all EPAs using Ottawa (range, 0.68-0.91) and fair to excellent using Chen (range, 0.54-0.83). Generalizability analysis revealed substantial variance in ratings attributable to the learner-EPA interaction (59.6% for Ottawa; 48.9% for Chen) suggesting variability for ratings was appropriately associated with performance on individual EPAs. CONCLUSIONS: In a structured setting, both the Ottawa and Chen scales distinguished between preentrustable and entrustable learners; however, the Ottawa scale demonstrated more desirable characteristics. These findings represent a critical step forward in developing valid, reliable instruments to measure learner progression toward entrustment for the Core EPAs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.061 | 0.176 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".