Systematic Review and Individual Participant Data Meta-Analysis: Reducing Self-Harm in Adolescents: Pooled Treatment Effects, Study, Treatment, and Participant Moderators
Bibliographic record
Abstract
OBJECTIVE: Self-harm is common in adolescents and a major public health concern. Evidence for effective interventions that stop repetition is lacking. This individual participant data (IPD) meta-analysis of randomized controlled trials (RCTs) aimed to provide robust estimates of therapeutic intervention effects and explore which treatments are best suited to different subgroups. METHOD: Databases and trial registers to January 2022 were searched. RCTs compared therapeutic intervention to control, targeted adolescents ages 11 to 18 with a history of self-harm and receiving clinical care, and reported on outcomes related to self-harm or suicide attempt. Primary outcome was repetition of self-harm 12 months after randomization. Two-stage random-effects IPD meta-analyses were conducted overall and by intervention. Secondary analyses incorporated aggregate data from RCTs without IPD. RESULTS: The search identified 39 eligible studies; 26 provided IPD (3,448 participants), and 7 provided aggregate data (698 participants). There was no evidence that interventions were more or less effective than controls at preventing repeat self-harm by 12 months in IPD (odds ratio 1.06 [95% CI 0.86, 1.31], 20 studies, 2,949 participants) or IPD and aggregate data (odds ratio 1.02 [95% CI 0.82, 1.27], 22 studies, 3,117 participants) meta-analyses and no evidence of heterogeneity of treatment effects on study and treatment factors. Across all interventions, participants with multiple prior self-harm episodes showed evidence of improved treatment effect on self-harm repetition 6 to 12 months after randomization (odds ratio 0.33 [95% CI 0.12, 0.94], 9 studies, 1,771 participants). CONCLUSION: This large-scale meta-analysis of RCTs provided no evidence that therapeutic intervention was more, or less, effective than control for reducing repeat self-harm. Evidence indicating more effective interventions in youth with 2 or more self-harm incidents was observed. Funders and researchers need to agree on a core set of outcome measures to include in subsequent studies. PLAIN LANGUAGE SUMMARY: Self-harm is common in adolescents and linked to higher risks of repeated self-harm and suicide. This meta-analysis of 33 randomized controlled trials involving 4,146 adolescents found that therapeutic interventions were no more effective than standard care at preventing repeat self-harm at 12 months. However, interventions were more effective in youth with 2 or more self-harm incidents. The authors discuss limitations posed by the lack of uniform outcome measures for self-harm. CLINICAL GUIDANCE: STUDY PREREGISTRATION INFORMATION: Reducing Self-harm in Adolescents: An Individual Participant Data Meta-analysis; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=152119.
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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 | 0.045 | 0.127 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.036 | 0.064 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".