Use of a Night Float System to Comply With Resident Duty Hours Restrictions
Bibliographic record
Abstract
PURPOSE: Although some evidence suggests that resident duty hours reforms can lead to shift-worker mentality and loss of patient ownership, other evidence links long hours and fatigue to poor work performance and loss of empathy, suggesting the restrictions could positively affect professionalism. The authors explored perceived impacts of a 16-hour duty restriction, achieved using a night float (NF) system, on the workplace and professionalism. METHOD: In 2013, the authors conducted semistructured interviews with 18 residents, 9 staff physicians, and 3 residency program directors in the McGill University core internal medicine residency program regarding their perceptions of the program's 12-hour shift-based NF system. Interviews were transcribed and coded for common themes. The authors used a descriptive qualitative methodology. RESULTS: Participants viewed implementation of the NF system as leading to decreased physical and mental exhaustion, more consistent interaction with patients, and more stable team structure within shifts compared with the previous 24-hour call system. These workplace changes were felt to improve teamwork and patient ownership within shifts, quality of work performed, and empathy. Across shifts, however, more frequent sign-overs, stricter application of shift time boundaries, and loose integration between daytime and NF teams were perceived as leading to emergence of shift-worker mentality around sign-over. Perceptions of optimal patient ownership changed from the traditional single-physician-24/7 model to team-based shared ownership. CONCLUSIONS: Duty hours restrictions, as exemplified by an NF system, have both positive and negative impacts on professionalism. Interventions and training toward effective team-based care are needed to curb emergence of shift-worker mentality.
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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 | 0.003 | 0.013 |
| 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 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".