Indigenous maternal health and health services within Canada: a scoping review
Bibliographic record
Abstract
BACKGROUND: Globally, there are disparities in access to maternal health care services and equity in maternal health outcomes between Indigenous and non-Indigenous populations. While the literature is growing, it has not been systematically synthesized. This review addresses this gap by synthesizing the existing literature on the organizational structure of maternity care, accessibility and delivery of services, and clinical disparities impacting Indigenous maternal health within Canada. It also identifies current knowledge gaps in research on these topics. METHODS: A scoping review was completed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement guidelines and the extension for scoping reviews. The search for relevant papers was performed in PubMed, CINAHL, and SCOPUS electronic databases and included any empirical literature written in English and published during 2006 - 2021. The research team inductively coded 5 articles to develop a coding scheme, which was then applied to the remaining articles. RESULTS: A total of 89 articles were included in the review, of which 32 were qualitative papers, 40 quantitative, 8 were mixed-methods publications, and 9 were review papers. The analysis of the articles resulted in identifying a range of overarching themes pertaining to the maternal health of Indigenous women within Canada including provision of services, clinical issues, education, health disparities, organization, spatial context, and impact of informal support. The results suggest that physical, psychological, organizational, and systemic barriers inhibit the quality-of-care pregnant Indigenous women receive, and that maternal health services are not consistently provided in a culturally safe manner. Results also suggest that, compared to non-Indigenous pregnant women, Indigenous women are more likely to develop clinical complications during pregnancy, reflecting the structural impacts of colonization that continue to negatively influence Indigenous maternal health and well-being. CONCLUSIONS: There are many complex barriers that prevent Indigenous women from receiving high quality and culturally appropriate maternal care. Possible areas that could address the service gaps illuminated through this review include the implementation of cultural considerations across health care jurisdictions within Canada.
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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 | 0.020 | 0.071 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.033 | 0.052 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".