Childbirth Experience, Mistreatment, and Migrant Status: A Retrospective Cross‐Sectional Study
Bibliographic record
Abstract
INTRODUCTION: Childbirth experience can affect women's long-term health and well-being. However, there is limited knowledge on whether migrant status affects woman's experience during childbirth. We aimed to answer the following research questions: (1) Is there a difference in childbirth experience between migrant and native-born women in Iceland; and (2) Are migrant women more likely to experience mistreatment in childbirth compared to native-born women in Iceland? METHODS: An online survey was developed including the Childbirth Experience Questionnaire 2 to assess overall childbirth experience, and descriptive analysis and linear regression were conducted to determine differences between migrant and native-born women in Iceland. The mistreatment by care providers in childbirth indicators were used to evaluate mistreatment in childbirth, and frequencies and logistic regression were conducted. Both regression models were adjusted for sociodemographic and obstetric factors. RESULTS: A total of 1365 women participated. Migrant women reported statistically significantly lower scores for birth experience compared to native-born women (F [12, 1352] = 23.97, p < 0.001). There was no statistical difference between groups regarding mistreatment in childbirth. One in four of all women reported at least one form of mistreatment. CONCLUSION: This study suggests that there are areas in maternity care that can be improved upon, particularly in providing care for migrant women and addressing mistreatment in childbirth for all. Our results suggest further research in this area as well as evaluation of maternity systems, training in cultural competency and effective communication.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".