Exploring the Impact of Entrustable Professional Activities on Feedback Culture: A Qualitative Study of Anesthesiology Residents and Attendings
Bibliographic record
Abstract
PURPOSE: Entrustable professional activities (EPAs) were introduced as a potential way to optimize workplace-based assessments. Yet, recent studies suggest that EPAs have not yet overcome all of the challenges to implementing meaningful feedback. The aim of this study was to explore the extent to which the introduction of EPAs via mobile app impacts feedback culture as experienced by anesthesiology residents and attending physicians. METHOD: Using a constructivist grounded theory approach, the authors interviewed a purposive and theoretical sample of residents (n = 11) and attendings (n = 11) at the Institute of Anaesthesiology, University Hospital of Zurich, where EPAs had recently been implemented. Interviews took place between February and December 2021. Data collection and analysis were conducted iteratively. The authors used open, axial, and selective coding to gain knowledge and understanding on the interplay of EPAs and feedback culture. RESULTS: Participants reflected on a number of changes in their day-to-day experience of feedback culture with the implementation of EPAs. Three main mechanisms were instrumental in this process: lowering the feedback threshold, change in feedback focus, and gamification. Participants felt a lower threshold to feedback seeking and giving and that the frequency of feedback conversations increased and tended to be more focused on a specific topic and shorter, while feedback content tended to focus more on technical skills and more attention was given to average performances. Residents indicated that the app-based approach fostered a game-like motivation to "climb levels," while attendings did not perceive a game-like experience. CONCLUSIONS: EPAs may offer a solution to problems of infrequent occurrence of feedback and invite attention to average performances and technical competencies, but may come at the expense of feedback on nontechnical skills. This study suggests that feedback culture and feedback instruments have a mutually interacting influence on each other.
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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 | 0.013 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".