Immigrant women’s and families’ views and experiences of routine postnatal care: findings from a qualitative evidence synthesis
Bibliographic record
Abstract
BACKGROUND: Uptake of postnatal care (PNC) is low and inequitable in many countries, and immigrant women may experience additional challenges to access and effective use. As part of a larger study examining the views of women, partners, and families on routine PNC, we analysed a subset of data on the specific experiences of immigrant women and families. METHODS: This is a subanalysis of a larger qualitative evidence synthesis. We searched MEDLINE, PUBMED, CINAHL, EMBASE, EBM-Reviews and grey literature for studies published until December 2019 with extractable qualitative data with no language restrictions. For this analysis, we focused on papers related to immigrant women and families. Two reviewers screened each study independently; inclusion was agreed by consensus. Data abstraction and quality assessment were carried out using a study-specific extraction form and established quality assessment tools. Study findings were identified using thematic analysis. Findings are presented by confidence in the finding, applying the GRADE-CERQual approach. FINDINGS: We included 44 papers, out of 602 full-texts, representing 11 countries where women and families sought PNC after immigrating. All but one included immigrants to high-income countries. Four themes were identified: resources and access, differences from home country, support needs, and experiences of care. High confidence study findings included: language and communication challenges; uncertainty about navigating system supports including transportation; high mental health, emotional, and informational needs; the impact of personal resources and social support; and the quality of interaction with healthcare providers. These findings highlight the importance of care experiences beyond clinical care. More research is also needed on the experiences of families migrating between low-income countries. CONCLUSIONS: Immigrant families experience many challenges in getting routine PNC, especially related to language, culture, and communication. Some challenges may be mitigated by improving comprehensive and accessible information on available services, as well as holistic social support. TRIAL REGISTRATION NUMBER: CRD42019139183.
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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 | 0.090 | 0.119 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.011 | 0.016 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".