Health promotion interventions supporting Indigenous healthy ageing: a scoping review
Bibliographic record
Abstract
Aging well is a priority in Canada and globally, particularly for older Indigenous adults experiencing an increased risk of chronic conditions. Little is known about health promotion interventions for older Indigenous adults and most literature is framed within Eurocentric paradigms that are not always relevant to Indigenous populations. This scoping review, guided by Arksey and O'Malley's framework and the PRISMA-ScR Checklist, explores the literature on Indigenous health promoting interventions across the lifespan, with specific attention to Indigenous worldview and the role of older Indigenous adults within these interventions. To ensure respectful and meaningful engagement of Indigenous peoples, articles were included in the Collaborate or Shared Leadership categories on the Continuum of Engagement. Fifteen articles used Indigenous theories and frameworks in the study design. Several articles highlighted engaging Elders as advisors in the design and/or delivery of programs however only five indicated Elders were active participants. In this scoping review, we suggest integrating a high level of community engagement and augmenting intergenerational approaches are essential to promoting health among Indigenous populations and communities. Indigenous older adults are keepers of essential knowledge and must be engaged (as advisors and participants) in intergenerational health promotion interventions to support the health of all generations.
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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 | 0.009 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".