Preventing suicidal behaviours with a multilevel intervention: a cluster randomised controlled trial
Bibliographic record
Abstract
BACKGROUND: In the context of the recent surge in community based multilevel interventions for suicide prevention, all of which show promising results, we discuss the implications of the findings of such an intervention designed for and implemented in New Zealand. The multi-level intervention for suicide prevention in New Zealand (MISP-NZ) was a cluster randomised controlled community intervention trial involving eight hospital regions matched into four pairs and randomised to either the intervention or practice as usual (the control). Intervention regions received 25 months of interventions (01 June 2010 to 30 June 2012) including: 1) training in recognition of suicide risk factors; 2) workshops on mental health issues; 3) community based interventions (linking in with community events); and 4) distribution of print material and information on web-based resources. RESULTS: There was no significant difference between the change in rate of suicidal behaviours (ISH or self-inflicted deaths) in the intervention group compared with the control group (rate ratio = 1.07, 95% CI 0.82, 1.38). CONCLUSIONS: This study did not provide substantive evidence that the MISP-NZ intervention had an effect on suicidal behaviours raising important questions about the potential effectiveness of the multilevel intervention model for suicide prevention for all countries. Although a range of factors may account for this unanticipated finding, including inadequate study power, differences in design and intervention focus, and country-specific contextual factors, it is possible that the effectiveness of the multilevel intervention model for reducing suicidal behaviours may have been overstated. TRIAL REGISTRATION: This trial was retrospectively registered on 11 April 2013. ACTRN12613000399796 .
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".