Factors Affecting Medical Residents’ Decisions to Work After Call
Bibliographic record
Abstract
BACKGROUND: Accreditation Council for Graduate Medical Education (ACGME) work-hour restrictions (WHRs) are intended to improve patient safety by reducing resident fatigue. Compliance with ACGME WHRs is not universal. PURPOSE: The purpose of this study was to identify factors that influence residents' decisions to take a postcall day (PCD) off according to ACGME WHRs. METHODS: Residents (N = 433) at one university were emailed a link to a survey in 2019. The survey included demographic details and a Discrete Choice Experiment examining influences on resident decisions to take a PCD off. RESULTS: One hundred seventy-five residents (40.4%) responded to the survey; 113 residents (26%) completed the survey. Positive feedback from attending physicians about taking PCDs off in the past had the greatest impact on respondents' decisions to take a PCD off, increasing the probability by 27.3%, followed by chief resident comments about the resident looking tired (16.6% increase), and having never heard their attendings comment about PCDs off as either positive or negative (13.9% increase). Factors that had the largest effect on decreasing the probability of taking a PCD were negative feedback about taking PCDs off (14.3% decrease), continuity of care concerns (10.8% decrease), and whether the resident was looking forward to an assignment (7.9% decrease). CONCLUSIONS: The most important influencer of residents' decisions to take a PCD off was related to feedback from their attending physicians, suggesting that compliance with WHRs can be improved by focusing on the residency program's safety culture.
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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 | 0.002 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".