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Risk prediction models for adolescent suicide: A systematic review and meta-analysis.
Ruitong Li1, Yuchuan Yue2, Xujie Gu1
1School of Nursing, Chengdu University of Traditional Chinese Medicine, Chengdu 610075, China.
Psychiatry Research
|February 23, 2025
Summary
Adolescent suicide risk prediction models show strong predictive power, but high bias and limited external validation necessitate further research for clinical use. Key predictors include gender, depression, stress, and prior self-harm.
Area of Science:
- Public Health
- Psychiatry
- Data Science
Background:
- Adolescent suicide is a critical global public health issue.
- Suicide risk is rising among adolescents worldwide.
- Developing effective prediction tools is essential.
Purpose of the Study:
- Systematically review and evaluate adolescent suicide risk prediction models.
- Identify key predictors of suicide risk in adolescents.
- Inform the development of future risk assessment tools.
Main Methods:
- Comprehensive search of international and Chinese databases.
- Independent literature screening and data extraction.
- Quality assessment using PROBAST and meta-analysis with Stata/R software.
Main Results:
- 25 studies with 62 models analyzed; 51 internally validated (AUC > 0.7).
- Pooled AUC for internal validation: 0.846; external validation: 0.810.
- Significant predictors: gender, depression, stress, prior suicidal ideation/self-harm, drug abuse, bullying, family relationships.
Conclusions:
- Adolescent suicide risk models show excellent predictive performance.
- High risk of bias and insufficient external validation limit current clinical applicability.
- Future research should focus on identified key predictors for improved risk assessment.
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