Assessing Health Care Access and Use among Indigenous Peoples in Alberta: a Systematic Review
Bibliographic record
Abstract
Alberta's Indigenous population is growing, yet health care access may be limited. This paper presents a comprehensive review on health care access among Indigenous populations in Alberta with a focus on the health care services use and barriers to health care access. Scientific databases (PubMed, EMBASE, CINAHL, and PsycINFO) and online search engines were systematically searched for studies and grey literature published in English between 2000 and 2013 examining health care services access, use and barriers to access among Indigenous populations in Alberta. Information on health care services use and barriers to use or access was synthesized based on the MOOSE guidelines. Overall, compared to non-Indigenous populations, health care use rates for hospital/emergency room services were higher and health care services use of outpatient specialists was lower among Indigenous peoples. Inadequate numbers of Indigenous health care professionals; a lack of cross-cultural training; fear of foreign environments; and distance from family and friends were barriers to health care use and access. Inequity in social determinants of health among Indigenous peoples and inadequate "health services with prevention approaches," may contribute to present health disparities between Indigenous and non-Indigenous populations in the province.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.011 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".