The Impact of Land-Based Physical Activity Interventions on Self-Reported Health and Well-Being of Indigenous Adults: A Systematic Review
Bibliographic record
Abstract
For many Indigenous communities, decreased participation in traditional land-based activities has led to higher rates of chronic disease and a decrease in well-being. This systematic review explores how traditional land-based activities impact self-reported health and well-being of Indigenous adults, using Indigenous and Western perspectives. A search of three electronic databases (PubMed, Scopus, and Web of Science) identified nine studies which explored the experiences and perspectives of Indigenous adults taking part in land-based subsistence and ceremonial activities. A thematic analysis of these studies identified many interconnected physical, spiritual, mental, emotional, and community benefits. Community engagement throughout all stages of the interventions was an important factor in effectively addressing challenges and barriers stemming from colonization, decreased knowledge transfer, and increased use of technology. Participants reported developing more effective stress management techniques, a greater awareness of modifiable risk factors along with increased engagement with Elders. Ultimately, land-based subsistence and ceremonial activities were identified as playing an influential role in the lives of Indigenous adults. The involvement of community members allowed for the development of more culturally relevant interventions. Future community-specific research is needed to increase engagement in traditional physical-activities, improve well-being and overall reduce the risk of chronic disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".