Evaluating the Quality of Written Feedback Within Entrustable Professional Activities in an Internal Medicine Cohort
Bibliographic record
Abstract
Background: Whether written comments in entrustable professional activities (EPAs) translate into high-quality feedback remains uncertain. Objective: We aimed to evaluate the quality of EPA feedback completed by faculty and senior residents. Methods: Using retrospective descriptive analysis, we assessed the quality of feedback from all EPAs for 34 first-year internal medicine residents from July 2019 to May 2020 at Western University in London, Ontario, Canada. We assessed feedback quality on 4 domains: timeliness, task orientation, actionability, and polarity. Four independent reviewers were blinded to names of evaluators and learners and were randomized to assess each EPA for the 4 domains. Statistical analyses were completed using R 3.6.3. Chi-square or Fisher's exact test and Cochran-Armitage test for trend were used to compare the quality of feedback provided by faculty versus student assessors, and to compare the effect of timely versus not timely feedback on task orientation, actionability, and polarity. Results: A total of 2471 EPAs were initiated by junior residents. Eighty percent (n=1981) of these were completed, of which 61% (n=1213) were completed by senior residents. Interrater reliability was almost perfect for timeliness (κ=0.99), moderate for task orientation (κ=0.74), strong for actionability (κ=0.81), and moderate for polarity (κ=0.62). Of completed EPAs, 47% (n=926) were timely, 85% (n=1697) were task oriented, 83% (n=1649) consisted of reinforcing feedback, 4% (n=79) contained mixed feedback, and 12% (n=240) had neutral feedback. Thirty percent (n=595) were semi- or very actionable. Conclusions: The written feedback in the EPAs was task oriented but was neither timely nor actionable. The majority of EPAs were completed by senior residents rather than faculty.
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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 | 0.030 | 0.143 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".