Wellness in Canadian paediatric residents and their program directors
Bibliographic record
Abstract
PURPOSE: This study aimed to explore the prevalence of and identify risk factors for depression and burnout in paediatric residents and paediatric program directors (PDs) in Canada. METHODS: Residents and PDs completed separate anonymous online surveys consisting of demographic questions, the Maslach Burnout Inventory and the Patient Health Questionnaire-2, which screens for risk of depression. RESULTS: A total of 166 paediatric residents completed the survey representing 14/17 Canadian paediatric residency programs. Participants were 74% female. Twenty-four (14%) were at risk of depression and 69 (42%) met criteria for burnout. Burnout was associated with year of residency (P=0.03), with third year residents at highest risk. Residents who reported unhelpful wellness curricula were at risk of burnout (81.3%) compared with those with no wellness curricula (51.1%) or curricula reported as helpful (29.1%, P=0.01). More than 79% of residents at risk of depression also met criteria for burnout (P=0.01). No associations were identified for risk of depression.Seventeen of 21 Canadian PDs completed the survey. No PDs were identified as at risk for depression. Five PDs (29%) met criteria for burnout. CONCLUSIONS: Paediatric PDs in Canada have relatively low rates of burnout and depression. In contrast, a large number of Canadian paediatric residents met criteria for burnout. Residents in programs with wellness curricula described as helpful are at lowest risk of burnout. Future research should include identifying features that define helpful wellness curricula and exploring interventions to help residents at risk of burnout and depression.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.003 | 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".