Burnout and resilience among Canadian palliative care physicians
Bibliographic record
Abstract
BACKGROUND: Physicians experience high rates of burnout, which may negatively impact patient care. Palliative care is an emotionally demanding specialty with high burnout rates reported in previous studies from other countries. We aimed to estimate the prevalence of burnout and degree of resilience among Canadian palliative care physicians and examine their associations with demographic and workplace factors in a national survey. METHODS: Physician members of the Canadian Society of Palliative Care Physicians and Société Québécoise des Médecins de Soins Palliatifs were invited to participate in an electronic survey about their demographic and practice arrangements and complete the Maslach Burnout Inventory for Medical Professionals (MBI-HSS (MP)), and Connor-Davidson Resilience Scale (CD-RISC). The association of categorical demographic and practice variables was examined in relation to burnout status, as defined by MBI-HSS (MP) score. In addition to bivariable analyses, a multivariable logistic regression analysis, reporting odds ratios (OR), was conducted. Mean CD-RISC score differences were examined in multivariable linear regression analysis. RESULTS: One hundred sixty five members (29%) completed the survey. On the MBI-HSS (MP), 36.4% of respondents reported high emotional exhaustion (EE), 15.1% reported high depersonalization (DP), and 7.9% reported low personal accomplishment (PA). Overall, 38.2% of respondents reported a high degree of burnout, based on having high EE or high DP. Median CD-RISC resilience score was 74, which falls in the 25th percentile of normative population. Age over 60 (OR = 0.05; CI, 0.01-0.38), compared to age ≤ 40, was independently associated with lower burnout. Mean CD-RISC resilience scores were lower in association with the presence of high burnout than when burnout was low (67.5 ± 11.8 vs 77.4 ± 11.2, respectively, p < 0.0001). Increased mean CD-RISC score differences (higher resilience) of 7.77 (95% CI, 1.97-13.57), 5.54 (CI, 0.81-10.28), and 8.26 (CI, 1.96-14.57) occurred in association with age > 60 as compared to ≤40, a predominantly palliative care focussed practice, and > 60 h worked per week as compared to ≤40 h worked, respectively. CONCLUSIONS: One in three Canadian palliative care physicians demonstrate a high degree of burnout. Burnout prevention may benefit from increasing resilience skills on an individual level while also implementing systematic workplace interventions across organizational levels.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".