P.192 Resident wellness and burnout in the University of Alberta Neurosurgery Residency Program – a quality improvement study
Bibliographic record
Abstract
Background: Residency training is well-known to be an arduous life event - especially in neurosurgery. The Maslach Burnout Index (MBI) is the gold standard for assessing burnout while the Perceived Stress Scale (PSS) identifies the relative importance of stressors. The purpose of this study is to quantify resident wellness using two validated instruments (MBI and PSS). Methods: The MBI and PSS were anonymously administered to all residents. Scores were compiled and analyzed. Freeform data was collected to identify areas for intervention. Results: Completion rate was 8/9 residents. Baseline scores showed 71% had at least moderately low personal accomplishment, 86% at least moderate emotional exhaustion, and 71% at least moderate depersonalization. 86% had above average perceived stress. Areas for improvement included call room conditions, increased social events, and study resource funding. Conclusions: Most residents are objectively experiencing low personal accomplishment, above average emotional exhaustion and depersonalization, and above average perceived stress. Assessments will characterize temporal trends, identify avenues for wellness improvement, and be correlated with interventions.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".