A Systematic Literature Review of Physical Activity-Based Health Programs for Indigenous Women: Impacts on Physical Activity Levels, Obesity, and Community Building
Bibliographic record
Abstract
Indigenous women experience a disproportionate burden of chronic diseases and health challenges related to obesity. The need for culturally relevant programming to support and empower women to optimize health is well established. Participatory physical activity [PA]-focused programming responsive to the sociocultural realities of Indigenous women may hold promise. However, obesity and chronic disease literature for Indigenous women focusing on PA change predominantly discusses individual behaviors, leaving a knowledge gap around the social and environmental supports needed to realize improved outcomes. We searched PubMed, Ovid MEDLINE, CINAHL, Bibliography of Native North Americans, and the University of New Mexico’s Native Health Databases for English language peer-reviewed articles on PA-based programs addressing prevention or management of obesity with Indigenous women as a primary focus. Fifteen articles, representing 13 unique programs, were included in the review. Outcome measures included program attendance and factors influencing program acceptance, PA, biochemical markers and blood pressure, weight and waist circumference measurements, the development of social supports, and nutritional knowledge acquisition. Although some studies found improvements in PA level and other outcomes, the marked variability in study design makes it difficult to draw conclusions about best practices for PA-based wellness and weight management programs for Indigenous women. However, programming that acknowledges and provides accommodation for the complex factors that influence behavior, incorporates cultural and community elements, and integrates opportunities for supportive network development may improve outcomes.
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 | 0.007 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".