Respectful maternity care and women's autonomy in decision making in Iceland: Application of scale instruments in a cross-sectional survey
Bibliographic record
Abstract
OBJECTIVE: To explore how maternal factors are associated with women's experiences of respect and autonomy in Icelandic maternity care. DESIGN: An online survey was developed including two measures assessing the quality of perinatal care: the Mothers on Respect Index and the Mothers' Autonomy in Decision Making Scale. Median and interquartile ranges were calculated for both scales. Logistic regression was used to calculate adjusted odds ratios and 95% confidence intervals to investigate the relationship between maternal factors and perceived low levels of respectful care and perceived low levels of autonomy in decision making. PARTICIPANTS AND SETTING: A total of 1,402 women participated. Requirements were: Age ≥ 18 years; antenatal care and childbirth in Iceland 2015-2021; and fluency in Icelandic, English or Polish. MEASUREMENTS AND FINDINGS: Perceived lower levels of respect were reported by migrant women [aOR 2.16 (1.55-3.00)], women with at least one social complication [aOR 2.52 (1.92-3.31)], primiparous women [aOR 1.72 (1.26-2.36)], women with at least one pregnancy complication [aOR 1.63 (1.22-2.18)] and those who gave birth by caesarean section [aOR 1.75 (1.25-2.45)]. Perceived lower levels of autonomy were reported by migrant women [aOR 1.42 (1.02-1.97)], women who had at least one social complication [aOR 2.12 (1.63-2.74)] and those who gave birth in a hospital setting [aOR 1.62 (1.03-2.55)]. KEY CONCLUSION: The results shed light on inequity in Icelandic maternity care and suggest that data from such surveys can provide valuable information on the changes that must be made in maternity health care services to ensure equity. IMPLICATIONS FOR PRACTICE: Action must be taken to increase provision of respectful, woman-centred maternity care with an emphasis on informed decision making. Strategies to improve services for groups that have been socially marginalized, such as migrant women and women affected by social determinants of health, should be implemented and monitored.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".