Patient-led decision making: Measuring autonomy and respect in Canadian maternity care
Bibliographic record
Abstract
OBJECTIVE: The Changing Childbirth in British Columbia study explored women's preferences and experiences of maternity care, including women's role in decision-making. METHODS: Following content validation by community members, we administered a cross-sectional online survey exploring novel topics, including drivers for interventions, and experiences of autonomy, respect, or mistreatment during maternity care. Using the Mothers Autonomy in Decision-Making (MADM) scale as an outcome measure in a mixed-effects analysis, we examined differential experiences by socio-demographic and prenatal risk profile, type of care provider, interventions received, and nature of communication with care providers. RESULTS: A geographically representative sample of Canadian women (n = 2051) reported on 3400 pregnancies. Most women (95.2%) preferred to be the lead decision-maker during care. Patients of physicians had significantly lower autonomy (MADM) scores than midwifery clients as did women who felt pressured to accept interventions. Women who had a difference in opinion with their provider, and those who felt their provider seemed rushed reported the lowest MADM scores. CONCLUSION: Women's autonomy is significantly altered by model of maternity care, the nature of interactions with care providers, and women's ability for self-determination. PRACTICE IMPLICATIONS: If health professionals acquire skills in person-centred decision-making experience of autonomy among pregnant women may improve.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".