Understanding the Multidimensional Effects of Resident Duty Hours Restrictions: A Thematic Analysis of Published Viewpoints in Surgery
Bibliographic record
Abstract
PURPOSE: Individuals representing various surgical disciplines have expressed concerns with the impact of resident duty hours (RDH) restrictions on resident education and patient outcomes. This thematic review of published viewpoints aimed to describe the effects of these restrictions in surgery. METHOD: The authors conducted a qualitative systematic review of non-research-based literature published between 2003 and 2015. Articles were included if they focused on the RDH restrictions in surgery and resident wellness, health promotion, resident safety, resident education and/or training, patient safety, medical errors, and/or heterogeneity regarding training or disciplines. A thematic analysis approach guided data extraction. Contextual data were abstracted from the included articles to aid in framing the identified themes. RESULTS: Of 1,482 identified articles, 214 were included in the review. Most were from authors in the United States (144; 67%) and focused on the 80-hour workweek (164; 77%). The emerging themes were organized into three overarching categories: (1) impact of the RDH restrictions, (2) surgery has its own unique culture, and (3) strategies going forward. Published opinions suggested that RDH restrictions alone are insufficient to achieve the desired outcomes and that careful consideration of the surgical training model is needed to maintain the integrity of educational outcomes. CONCLUSIONS: Opinions from the surgical community highlight the complexity of issues surrounding the RDH restrictions and suggest that recent changes are not achieving all the desired outcomes and have resulted in unintended outcomes. From the perceptions of the various stakeholders in surgical education studied, areas for new policies were identified.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.086 | 0.168 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.019 | 0.022 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 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".