The effectiveness of middle and high school-based suicide prevention programmes for adolescents: a systematic review
Bibliographic record
Abstract
OBJECTIVE: To assess the effectiveness of middle and high school-based suicide prevention curricula. DATA SOURCES: The following were searched: Ovid MEDLINE(R) in-process and other non-indexed citations and Ovid MEDLINE(R), Ovid Healthstar, CINAHL, PsycINFO, all EBM reviews-Cochrane DSR, ACP Journal Club, DARE, CCTR, CMR, HTA, and NHSEED, and the ISI Web of Science, until October 2009; government web pages for statistics and other demographic data in countries where they were available; citation lists of relevant articles. REVIEW METHODS: Randomised controlled studies, interrupted time series analyses with a concurrent comparison group, studies with follow-up examinations (post-test questionnaires and monitoring suicide rates), and middle to high school-based curriculum studies, including both male and female participants, were included. RESULTS: 36 potentially relevant studies were identified, eight of which met the inclusion criteria. Overall, statistically significant improvements were noted in knowledge, attitude, and help-seeking behaviour. A decrease in self reported ideation was reported in two studies. None reported on suicide rates. CONCLUSION: Although evidence exists that school-based programmes to prevent suicide among adolescents improve knowledge, attitudes, and help-seeking behaviours, no evidence yet exists that these prevention programmes reduce suicide rates. Further well designed, controlled research is required before such programmes are instituted broadly to populations at risk.
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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 | 0.010 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".