Is Canadian surgical residency training stressful?
Bibliographic record
Abstract
BACKGROUND: Surgical residency has the reputation of being arduous and stressful. We sought to determine the stress levels of surgical residents, the major causes of stress and the coping mechanisms used. METHODS: We developed and distributed a survey among surgical residents across Canada. RESULTS: A total of 169 participants responded: 97 (57%) male and 72 (43%) female graduates of Canadian (83%) or foreign (17%) medical schools. In all, 87% reported most of the past year of residency as somewhat stressful to extremely stressful, with time pressure (90%) being the most important stressor, followed by number of working hours (83%), residency program (73%), working conditions (70%), caring for patients (63%) and financial situation (55%). Insufficient sleep and frequent call was the component of residency programs that was most commonly rated as highly stressful (31%). Common coping mechanisms included staying optimistic (86%), engaging in enjoyable activities (83%), consulting others (75%) and exercising (69%). Mental or emotional problems during residency were reported more often by women (p = 0.006), who were also more likely than men to seek help (p = 0.026), but men reported greater financial stress (p = 0.036). Foreign graduates reported greater stress related to working conditions (p < 0.001), residency program (p = 0.002), caring for family members (p = 0.006), discrimination (p < 0.001) and personal and family safety (p < 0.001) than Canadian graduates. CONCLUSION: Time pressure and working hours were the most common stressors overall, and lack of sleep and call frequency were the most stressful components of the residency program. Female sex and graduating from a non-Canadian medical school increased the likelihood of reporting stress in certain areas of residency.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".