Canadian Indigenous Womens Perspectives of Maternal Health and Health Care Services: A Systematic Review
Bibliographic record
Abstract
Development of policies and interventions to address health disparities between Indigenous and non-Indigenous populations requires a comprehensive understanding of Indigenous people’s experiences and perspectives of healthcare services. We systematically reviewed the published literature on Canadian Indigenous women’s experiences and perspectives of maternal healthcare during pregnancy, childbirth, and the postpartum period. Major bibliographic databases (including PubMed, CINAHL, EMBASE, SCOPUS, and SSCI) were searched for published studies (1990–March 2015) in English. Reference lists of identified articles were searched to identify additional articles. 92 articles were retrieved for further review, of which 16 studies were included: 8 on maternal healthcare and/or medical evacuation; 3 on gestational diabetes mellitus; 3 on the impact of policies on maternal health; and 2 on maternal weight changes and/or breastfeeding. The included studies described 1043 participants: Indigenous peoples (n=918) and non-Indigenous peoples (n=125) who were mothers or pregnant women (n=814), healthcare providers or workers in a health-related field (n=132), and fathers, Elders, or other community members (n=97). Availability of healthcare resources, healthcare services’ consideration of socio-economic or lifestyle barriers to health, and the impact of colonization on interactions with healthcare providers were main factors that impacted Indigenous women’s maternal health experiences. Medical evacuation was often due to limited maternity care options available in remote communities, and was associated with emotional, physical, and financial stress. This review highlights the importance of consistent health policies and practices for maternal health in Canada and providing culturally safe and patient-centered maternity healthcare services within indigenous communities.
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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 | 0.010 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.022 | 0.034 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".