A Systematic Review of Evaluated Suicide Prevention Programs Targeting Indigenous Youth
Bibliographic record
Abstract
BACKGROUND: Indigenous young people have significantly higher suicide rates than their non-indigenous counterparts. There is a need for culturally appropriate and effective suicide prevention programs for this demographic. AIMS: This review assesses suicide prevention programs that have been evaluated for indigenous youth in Australia, Canada, New Zealand, and the United States. METHOD: The databases MEDLINE and PsycINFO were searched for publications on suicide prevention programs targeting indigenous youth that include reports on evaluations and outcomes. Program content, indigenous involvement, evaluation design, program implementation, and outcomes were assessed for each article. RESULTS: The search yielded 229 articles; 90 abstracts were assessed, and 11 articles describing nine programs were reviewed. Two Australian programs and seven American programs were included. Programs were culturally tailored, flexible, and incorporated multiple-levels of prevention. No randomized controlled trials were found, and many programs employed ad hoc evaluations, poor program description, and no process evaluation. CONCLUSION: Despite culturally appropriate content, the results of the review indicate that more controlled study designs using planned evaluations and valid outcome measures are needed in research on indigenous youth suicide prevention. Such changes may positively influence the future of research on indigenous youth suicide prevention as the outcomes and efficacy will be more reliable.
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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 | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".