Effect of the ACGME Duty Hours Restrictions on Surgical Residents and Faculty: A Systematic Review
Bibliographic record
Abstract
PURPOSE: Educators in surgical training programs are concerned that the Accreditation Council for Graduate Medical Education (ACGME) duty hours limitations may adversely affect surgical residents' education, especially their operative experience, so the authors aimed to evaluate the impact of duty hours reductions on surgical residency. METHOD: The authors searched English- and French-language literature (2000-2008) for articles about the impact of duty hours restrictions on surgical residents' education and well-being and on faculty educators. They used the following databases: MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and ERIC. The authors included every report that examined the effects of duty hours limits on surgical training, excluding opinion papers and editorials. Two reviewers independently performed data extraction and quality assessment for all reports and resolved disagreements by consensus. RESULTS: The authors retrieved 1,146 reports and included 56 in the study. They compiled positive and negative outcomes on (1) residents' education, (2) resident lifestyle, and (3) surgical faculty. Overall, the effects of duty hours reductions on residents' education and lifestyle were positive or neutral, but the effects on surgical faculty were negative. The 16 articles with the highest-quality scores had 27 positive themes and 11 negative themes. CONCLUSIONS: This is the largest and most current review of the literature addressing the effect of the ACGME duty hours limitations on surgical training. Limitations had a positive effect on residents but a negative effect on surgical faculty. Importantly, duty hours limitations did not adversely affect surgical residents' operating-room experience.
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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 | 0.017 | 0.081 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".