Examining respect, autonomy, and mistreatment in childbirth in the US: do provider type and place of birth matter?
Bibliographic record
Abstract
BACKGROUND: Analyses of factors that determine quality of perinatal care consistently rely on clinical markers, while failing to assess experiential outcomes. Understanding how model of care and birth setting influence experiences of respect, autonomy, and decision making, is essential for comprehensive assessment of quality. METHODS: We examined responses (n = 1771) to an online cross-sectional national survey capturing experiences of perinatal care in the United States. We used validated patient-oriented measures and scales to assess four domains of experience: (1) decision-making, (2) respect, (3) mistreatment, and (4) time spent during visits. We categorized the provider type and birth setting into three groups: midwife at community birth, midwife at hospital-birth, and physician at hospital-birth. For each group, we used multivariate logistic regression, adjusted for demographic and clinical characteristics, to estimate the odds of experiential outcomes in all the four domains. RESULTS: Compared to those cared for by physicians in hospitals, individuals cared for by midwives in community settings had more than five times the odds of experiencing higher autonomy (aOR: 5.22, 95% CI: 3.65-7.45), higher respect (aOR: 5.39, 95% CI: 3.72-7.82) and lower odds of mistreatment (aOR: 0.16, 95% CI: 0.10-0.26). We found significant differences across birth settings: participants cared for by midwives in the community settings had significantly better experiential outcomes than those in the hospital settings: high- autonomy (aOR: 2.97, 95% CI: 2.66-4.27), respect (aOR: 4.15, 95% CI: 2.81-6.14), mistreatment (aOR: 0.20, 95% CI: 0.11-0.34), time spent (aOR: 8.06, 95% CI: 4.26-15.28). CONCLUSION: Participants reported better experiential outcomes when cared for by midwives than by physicians. And for those receiving midwifery care, the quality of experiential outcomes was significantly higher in community settings than in hospital settings. Care settings matter and structures of hospital-based care may impair implementation of the person-centered midwifery care model.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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 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".