Co-creation of a strengths-based approach to improve cardiometabolic health : a community-based and Indigenous led healthy lifestyle intervention
Bibliographic record
Abstract
Background: Finding culturally relevant and safe ways to co-create health and fitness programs that support traditional ways to be physically active are important areas of strengths-based research with Indigenous communities in Canada. Indigenous communities are returning to traditional ways of being active on the land, and colonial perceptions of health and fitness are culturally inappropriate for Indigenous communities. As such, research methodologies should focus on empowering Indigenous community leaders to be the key advocates of health behaviour change within their own communities. Objectives: This study examined the impact of a community-based and Indigenous led healthy lifestyle intervention designed specifically to improve health-related physical fitness and healthy lifestyle behaviours (reducing sedentary activity time and increasing physical activity levels) in adults (n = 15). Methodology: In collaboration and consultation with a rural and remote Indigenous community, we co-created a 13-week Indigenous led intervention incorporating individualized western exercise prescriptions and knowledge sharing circles in a group-based walking program. Measures of physical activity and sedentary behaviour (self-report and 7-day accelerometry), predicted maximal aerobic power (VO2max; 6-minute walk test), resting heart rate and blood pressure, and other health-related physical fitness measures (musculoskeletal fitness and body composition) were taken pre- and post-intervention. Results: Significant and clinically relevant improvements in aerobic fitness, resting blood pressure, and resting heart rate were observed. Accelerometry-measured moderate-to-vigorous intensity physical activity minutes were above international recommendations (~275 min/week), and sedentary activity time in bouts of >60 min reduced significantly post-intervention. No significant changes were observed in weight, body mass index, waist circumference, percentage body fat, grip strength, and flexibility. Conclusion: This work demonstrates how an Indigenous designed and led, community-based healthy lifestyle intervention can provide a culturally relevant strategy to increase health-related physical fitness, increase physical activity participation, and reduce sedentary behaviours.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| 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".