Systematic Review of Physical Activity Interventions Implemented with American Indian and Alaska Native Populations in the United States and Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To describe physical activity (PA) interventions implemented in American Indian/Alaska Native (AI/AN) populations in the United States and Canada. DATA SOURCES: MEDLINE, PubMed, ERIC, and Sociological Abstracts were used to identify peer-reviewed journal articles. Dissertation abstracts, Web sites, and conference proceedings were searched to identify descriptions within the gray literature from 1986 to 2006. STUDY INCLUSION AND EXCLUSION CRITERIA: The target population had to be described as AI/ AN, aboriginal, native Hawaiian, and/or native U.S. Samoan. PA interventions among indigenous populations of Latin America were not included. DATA EXTRACTION: Descriptions of 64 different AI/AN PA interventions (28 peer-reviewed journal articles and 36 in the gray literature) were identified. DATA SYNTHESIS: Data were synthesized by geographic region, intervention strategy, target audience, activities, and sustainability. RESULTS: Most interventions were conducted in the southwest United States (35.4%), in reservation communities (72%), and among participants 18 years and younger (57.8%). Forty-one percent of the 27 interventions with evaluation components reported significant changes in health, behavior, or knowledge. CONCLUSIONS: Effective AI/AN PA interventions demonstrated impact on individual health and community resources. Program sustainability was linked to locally trained personnel, local leadership, and stable funding. Culturally acceptable and scientifically sound evaluation methods that can be implemented by local personnel are needed to assess the health and social impact of many long-running AI/AN PA interventions.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it