Midwifery and obstetrics: Factors influencing mothers’ satisfaction with the birth experience
Bibliographic record
Abstract
BACKGROUND: Satisfaction is a key component of the care experience and part of the health system "triple aim," along with improving population health and reducing per capita health care costs, the other two parts of the "triple aim." The objectives of the study were to examine birth-experience satisfaction among women in Ontario, Canada, who received care from midwives, family physicians, and obstetricians. METHODS: We used Statistics Canada's 2006 national Maternity Experiences Survey. The sample includes 1900 Ontario women and is, with appropriate weighting, representative of an estimated population of 29 700 women who gave birth in Ontario to a singleton baby during the study period. Information was collected on respondents' satisfaction with their health care providers, demographic characteristics, and a range of pregnancy, labor, birth, and postpartum experiences. We used logistic regression analysis to assess differences in patient/client satisfaction by type of health care provider. RESULTS: Women cared for by midwives were three times more likely to be satisfied with their care (OR 3.32 [95% CI 2.26-4.86]) when compared with obstetrician-led care. Depression symptoms, having to travel outside the respondents' community to give birth, and being born in an East Asian country were associated with lower levels of satisfaction. CONCLUSION: Given recent health system reforms emphasizing the importance of shifting from expensive acute hospital-based care to community-based care, our findings support empirically the importance of supporting women's access to midwifery services within their communities. Findings of ethnocultural differences in satisfaction with care can inform policy makers as health systems move to provide culturally appropriate care to increasingly diverse populations.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".