Experiences of childbirth care among immigrant and non-immigrant women: a cross-sectional questionnaire study from a hospital in Norway
Bibliographic record
Abstract
BACKGROUND: Immigrant women have higher risks for poor pregnancy outcomes and unsatisfactory birth experiences than the general population. The mechanisms behind these associations remain largely unknown, but they may result from differential care provided to immigrant women or unsatisfactory interactions with health providers. This study aimed to investigate immigrant and non-immigrant women's experiences of health care during childbirth, particularly assessing two dimensions: perceived general quality of care and attainment of health care needs during childbirth. METHODS: This was a cross-sectional study carried out over 15 months in 2020 and 2021, and data were collected from a self-completed questionnaire. The labour and birth subscale from the Experience of Maternity Care questionnaire was used to assess the primary outcome of care experiences. A total of 680 women completed the questionnaire approximately within two days after birth (mean 2.1 days) at a hospital in Trondheim, in central Norway. The questionnaire was provided in eight languages. RESULTS: The 680 respondents were classified as immigrants (n = 153) and non-immigrants (n = 527). Most women rated their quality of care during childbirth as high (91.5%). However, one-quarter of the women (26.6%) reported unmet health care needs during childbirth. Multiparous immigrant women were more likely than multiparous non-immigrant women to report that their health care needs were unmet during childbirth (OR: 3.31, 95% CI: 1.91-5.72, p < 0.001, aOR: 2.83, 95% CI: 1.53-5.18, p = 0.001). No other significant differences between immigrant versus non-immigrant women were found in subjective ratings of childbirth care experiences. Having a Norwegian-born partner and a high level of Norwegian language skills did not influence the immigrant women's experience of childbirth care. CONCLUSIONS: Our findings indicate that many women feel they receive high-quality health care during childbirth, but a considerable number still report not having their health care needs met. Also, multiparous immigrant women report significantly more unmet health care needs than non-immigrants. Further research is required to assess immigrant women's childbirth experiences and for health care providers to give optimal care, which may need to be tailored to a woman's cultural background and individual expectations.
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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) | 0.000 | 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".