The Mothers on Respect (MOR) index: measuring quality, safety, and human rights in childbirth
Bibliographic record
Abstract
Background Abuse of human rights in childbirth are documented in low, middle and high resource countries. A systematic review across 34 countries by the WHO Research Group on the Treatment of Women During Childbirth concluded that there is no consensus at a global level on how disrespectful maternity care is measured. In British Columbia, a community-led participatory action research team developed a survey tool that assesses women's experiences with maternity care, including disrespect and discrimination. Methods A cross-sectional survey was completed by women of childbearing age from diverse communities across British Columbia. Several items (31/130) assessed characteristics of their communication with care providers. We assessed the psychometric properties of two versions of a scale (7 and 14 items), among women who described experiences with a single maternity provider ( n =2514 experiences among 1672 women). We also calculated the proportion and selected characteristics of women who scored in the bottom 10th percentile (those who experienced the least respectful care). Results To demonstrate replicability, we report psychometric results separately for three samples of women (S1 and S2) ( n =2271), (S3, n =1613). Analysis of item-to-total correlations and factor loadings indicated a single construct 14-item scale, which we named the Mothers on Respect index (MORi). Items in MORi assess the nature of respectful patient-provider interactions and their impact on a person's sense of comfort, behavior, and perceptions of racism or discrimination. The scale exhibited good internal consistency reliability. MORi- scores among these samples differed by socio-demographic profile, health status, experience with interventions and mode of birth, planned and actual place of birth, and type of provider. Conclusion The MOR index is a reliable, patient-informed quality and safety indicator that can be applied across jurisdictions to assess the nature of provider-patient relationships, and access to person-centered maternity care.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 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) | 0.002 | 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".