Barriers to Access among Indigenous Women Seeking Prenatal Care: A Literature Review
Bibliographic record
Abstract
Introduction: Indigenous women in Canada suffer disproportionately adverse prenatal outcomes due to access barriers in Canada's healthcare system. This paper aims to identify barriers Indigenous women face in accessing prenatal care in Canada. Methods: A literature search was conducted by all three authors using the following databases: PubMed, SCOPUS and CINAHL, and the keywords "Indigenous," "prenatal care," "access barriers," "maternal health," and "Canada." The search results yielded a total of 100 studies. Results: The studies included were written in English only, included Indigenous females between the age of 19–35, and excluded review articles. Twelve studies met the inclusion criteria and were included in the review. Participants in the studies examined did not have any severe underlying medical conditions for the duration of the study, and study designs included in the review are prospective cohort, cross-sectional, case report, and case-control studies. Five studies discussed the geographical distribution of facilities as the first major barrier to accessing prenatal care. Four studies identified distrust between patients and healthcare providers as the second major barrier, and six studies identified lack of culturally sensitive prenatal care as the third major access barrier. Discussion: The study found three main barriers Indigenous women face in accessing prenatal care in Canada; the geographical distribution of healthcare facilities, distrust between patients and healthcare professionals, and cultural sensitivity. Some changes in Canada's healthcare system to reduce access barriers to prenatal care include building more birthing and prenatal care facilities in rural areas for Indigenous women, educating healthcare professionals on culturally sensitive healthcare, and involving Indigenous people in decision-making to reduce distrust and power imbalances. Conclusion: The involvement of Indigenous women and community leaders is essential in making decisions regarding implementing effective healthcare and prenatal programs for Indigenous women. However, further research is required to understand the effectiveness of the solutions and the barriers that make prenatal care less accessible for Indigenous women in 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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.015 | 0.020 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".