When Midwives Burn Out: Differences in the Experiences of Midwives in British Columbia and Alberta
Bibliographic record
Abstract
Background: Internationally, continuity of care has been identified as a possible strategy to prevent burnout. The majority of midwives in British Columbia and Alberta practice within a continuity-based model of care, but British Columbia midwives have significantly higher burnout scores. Methods: We compared data from midwives from Alberta and British Columbia who responded to the Canadian arm of the WHELM (Work, Health, and Emotional Lives of Midwives) survey through invitations via their professional organizations. The survey included demographic questions, items about work patterns, occupational stressors, burnout, and intentions and reasons to leave the profession. Results: Workload was the most commonly reported stressor in both British Columbia and Alberta. Midwives in British Columbia were more likely (54%) to have seriously considered leaving the profession in the last 12 months than midwives in Alberta (26%). One-third of British Columbia midwives and no Alberta midwives cited poor pay as a reason to leave the profession. In answers to open-ended questions, 47% of respondents from British Columbia, but none from Alberta, highlighted poor pay as something that would need to change in order for them to successfully manage workplace stress. Discussion and Conclusion: Our comparison of similar midwifery contexts in Western Canada suggests burnout and intention to leave the profession are associated with how the care is remunerated. Midwives in British Columbia and Alberta care for a similar volume of clients and are paid with a similar type of payment system, but midwives in British Columbia are paid significantly less per course of care. A revised payment system or a significant increase in pay per client may ensure that midwives in British Columbia can continue to provide high-quality relationship-based care while maintaining longevity in the profession. This article has been peer reviewed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".