Indigenous Youth Peer-Led Health Promotion in Canada, New Zealand, Australia, and the United States: A Systematic Review of the Approaches, Study Designs, and Effectiveness
Bibliographic record
Abstract
BACKGROUND: Youth peer-led interventions have become a popular way of sharing health information with young people and appear well suited to Indigenous community contexts. However, no systematic reviews focusing on Indigenous youth have been published. We conducted a systematic review to understand the range and characteristics of Indigenous youth-led health promotion projects implemented and their effectiveness. METHODS: A systematic search of Medline, Embase, and ProQuest Social Sciences databases was conducted, supplemented by gray literature searches. Included studies focused on interventions where young Indigenous people delivered health information to age-matched peers. RESULTS: Twenty-four studies were identified for inclusion, based on 20 interventions (9 Australian, 4 Canadian, and 7 from the United States of America). Only one intervention was evaluated using a randomized controlled study design. The majority of evaluations took the form of pre-post studies. Methodological limitations were identified in a majority of studies. Study outcomes included improved knowledge, attitude, and behaviors. CONCLUSION: Currently, there is limited high quality evidence for the effectiveness of peer-led health interventions with Indigenous young people, and the literature is dominated by Australian-based sexual health interventions. More systematic research investigating the effectiveness of peer-led inventions is required, specifically with Indigenous populations. To improve health outcomes for Indigenous youth, greater knowledge of the mechanisms and context under which peer-delivered health promotion is effective in comparison to other methods of health promotion is needed.
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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 | 0.034 | 0.081 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".