Residents' quality of life during an orthopedic trauma rotation: a multicentre prospective observational study.
Bibliographic record
Abstract
OBJECTIVE: Fewer orthopedic surgery trainees are choosing careers in trauma. The impact of stressors on health-related quality of life has not been evaluated among orthopedic surgical residents. The current study aimed to determine predictors of unsatisfactory resident quality of life during trauma rotations. METHOD: This was a prospective observational study in which we chose orthopedic trauma rotations within 2 training programs at 3 level 1 trauma centres. A sample of 15 orthopedic surgery residents participated in the study. The main outcome measure was the 36-Item Short-Form Health Survey taken at baseline, 2 and 6 months into the rotation. Residents ranked level of stress for 15 work-related and 13 individual problems on 5-point Likert scales. RESULTS: The residents ranged from training years 1 through 5, and their mean age was 31 (standard deviation [SD] 2.8) years. Fear of error decreased at 6 months, compared with baseline (p = 0.007). Lack of time for family decreased as a problem at 2 and 6 months, compared with baseline (p = 0.025). Baseline Physical Component Summary scores were above population norms (p = 0.007). At 2 months, scores for the concept role limitations (physical) decreased significantly (p = 0.019), compared with the baseline. Mean Physical Component Summary scores declined from 57.59 (SD 3.51) at baseline to 53.68 (SD 6.50) at 2 months (p = 0.015) and 53.94 (SD 3.52) at 6 months (p = 0.008). At 2 months, mean general health scores significantly decreased, compared with baseline (p = 0.022). Social functioning scores at 6 months were decreased from population norms (p = 0.02). More resident social time was spent with medical people exclusively at 6 months, compared with baseline (p < 0.02). CONCLUSION: Trauma rotations affect residents' emotional well-being. Training programs should equip residents with coping strategies to improve quality of life during trauma rotations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".