The Senior Medical Resident’s New Role in Assessment in Internal Medicine
Bibliographic record
Abstract
PURPOSE: With the introduction of competency-based medical education, senior residents have taken on a new, formalized role of completing assessments of their junior colleagues. However, no prior studies have explored the role of near-peer assessment within the context of entrustable professional activities (EPAs) and competency-based medical education. This study explored internal medicine residents' perceptions of near-peer feedback and assessment in the context of EPAs. METHOD: Semistructured interviews were conducted from September 2019 to March 2020 with 16 internal medicine residents (8 first-year residents and 8 second- and third-year residents) at the University of Toronto, Toronto, Ontario, Canada. Interviews were conducted and coded iteratively within a constructivist grounded theory approach until sufficiency was reached. RESULTS: Senior residents noted a tension in their dual roles of coach and assessor when completing EPAs. Senior residents managed the relationship with junior residents to not upset the learner and potentially harm the team dynamic, leading to the documentation of often inflated EPA ratings. Junior residents found senior residents to be credible providers of feedback; however, they were reticent to find senior residents credible as assessors. CONCLUSIONS: Although EPAs have formalized moments of feedback, senior residents struggled to include constructive feedback comments, all while knowing the assessment decisions may inform the overall summative decision of their peers. As a result, EPA ratings were often inflated. The utility of having senior residents serve as assessors needs to be reexamined because there is concern that this new role has taken away the benefits of having a senior resident act solely as a coach.
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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 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".