Burnout, job satisfaction, and intention to leave among midwives in Western Switzerland: The role of caseload and hospital-based practice models
Bibliographic record
Abstract
BACKGROUND: Burnout and job dissatisfaction among midwives compromise healthcare quality and workforce retention. Practice models, such as hospital-based versus caseload models, may influence midwives' well-being and warrant further exploration. AIM: To examine the association between midwifery practice models (caseload vs. hospital) and burnout, job satisfaction, and the intention to leave the profession among midwives in Western Switzerland. METHOD: A cross-sectional survey was conducted with 392 midwives, using the Copenhagen Burnout Inventory to assess personal, work-related, and patient-related burnout. Multivariable logistic regression explored associations between practice models and burnout levels, job satisfaction, as well as retention in the profession. MAIN RESULTS: Hospital midwives were over nine times more likely than caseload midwives to experience moderate to high work-related burnout (OR = 9.18, p < .001) and were 80 % less likely to report above average job satisfaction (OR = 0.21, p < .001), considering differences between socio-demographic and practice-related factors between the two groups of midwives. Nearly half of all hospital-based participants expressed an intention to leave compared to one in three caseload midwives. Higher burnout and lower job satisfaction were linked to intentions to leave the profession. DISCUSSION AND CONCLUSION: Caseload models may protect midwives' well-being and promote job satisfaction and retention. These findings highlight the critical need for practice model changes and structural reforms in hospital midwifery, incorporating caseload principles, to support sustainable maternal and child healthcare in Western Switzerland and retain a resilient midwifery workforce.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".