Suicide prevention interventions targeting Indigenous peoples in Australia, New Zealand, the United States and Canada: a rapid review: an evidence check review brokered by the Sax Institute for the NSW Ministry of Health
Bibliographic record
Abstract
This Evidence Check review examined suicide prevention interventions targeting Indigenous peoples, including educational, social and cultural activities, an empowerment program, community level alcohol restrictions and mental health service delivery. The authors recommend a multi-strategic approach, targeted to the local community, and well designed evaluation including the impact and economic costs of best-evidence programs.This report presents the results of a systematic search of the peer reviewed and grey literature, aimed at identifying studies that describe or evaluate suicide prevention interventions, including early intervention, prevention and postvention strategies, targeting Indigenous peoples in Australia, New Zealand (NZ), Canada or the United States (US), for the period 1981 to 2012 (May) (inclusive). It critiques the methodology of evaluations of suicide prevention interventions and describes their key characteristics. The likely causes of suicide among Aboriginal and Torres Strait Islander Australians most commonly articulated in the descriptive literature are also identified. The implications of overall findings for suicide prevention programs and policies targeting Aboriginal communities in NSW are discussed.
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 | 0.017 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.016 | 0.018 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".