A scoping review of Indigenous community-specific physical activity measures developed with and for Indigenous Peoples in Canada, Australia, and New Zealand
Bibliographic record
Abstract
Historical factors including colonization and ongoing socioeconomic inequities impact Indigenous Peoples’ ability to mitigate chronic disease risks such as achieving recommended physical activity (PA) levels. Reliably assessing, reflecting, and promoting PA participation among Indigenous Peoples may be impacted by a lack of culturally appropriate assessment methods and meaningful engagement with Indigenous communities throughout the research process. The objectives of this scoping review were to examine: (1) How PA research with Indigenous Peoples used community-specific PA measures developed with and/or for Indigenous Peoples in Canada, Australia, and New Zealand; and (2) How the studies utilized community-based participatory research (CBPR) principles to engage communities. A systematic search was conducted in four electronic databases (Web of Science, Medline, University of Saskatchewan Indigenous Portal, and ProQuest Dissertations and Theses Global). Thirty-one ( n = 31) articles were identified and data extracted for narrative synthesis. Studies using community-specific PA measures have been increasing over time. Adapting questionnaires to traditional Indigenous activities such as cultural dances, ceremonies, and food-gathering activities were the most frequent adjustments undertaken to use community-specific measures. There are, however, gaps in research partnering with communities with only 6% of studies including all eight CBPR principles. Practical ways researchers can engage Indigenous communities and build capacity such as training and employing community members were highlighted. More needs to be done to facilitate community self-determination and develop long-term sustainable initiatives. Using culturally appropriate and relevant methodologies including partnering with Indigenous communities may help identification and implementation of culturally relevant and sustainable health-promoting initiatives.
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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 | 0.033 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.026 | 0.037 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| 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".