Welcome to Psychiatryai.com: Latest Evidence - RAISR4D

A Predictive Nomogram for Suicide Attempts in Chinese Adolescents With Both Non-Suicidal Self-Injury and Suicidal Ideation

Asia Pac Psychiatry. 2025 Jun;17(2):e70003. doi: 10.1111/appy.70003.

ABSTRACT

INTRODUCTION: Non-suicidal self-injury (NSSI) and suicidal ideation (SI) are prevalent and co-occurring among adolescents, serving as critical predictors of suicide. This study aimed to develop a predictive model and nomogram for suicide attempts (SA) in Chinese adolescents with mood disorders exhibiting NSSI and SI.

METHODS: Data were collected from 134 participants. Predictors were selected via LASSO regression from data collected using the Self-Injurious Thoughts and Behaviors Interview-Revised and self-report scales, followed by multivariate logistic regression to build the nomogram. Model performance was assessed through discriminatory ability, calibration curves, and clinical decision analysis.

RESULTS: Adolescents with SA history had fewer education years, higher prevalence and future likelihood of self-injurious thoughts and behaviors, earlier NSSI onset, more frequent and severe NSSI, and more intense and persistent SI compared to those without SA. Three key predictors for SA were identified: NSSI emotion regulation scores, average SI persistence duration, and history of interrupted attempts. The developed nomogram exhibited robust predictive accuracy with an AUC of 0.756.

DISCUSSION: This study presents a predictive model for suicide risk in adolescents with mood disorders exhibiting NSSI and SI. The model demonstrates high predictive accuracy and clinical applicability, offering a practical tool for clinicians to prioritize high-risk cases and guide personalized interventions.

PMID:40269582 | DOI:10.1111/appy.70003

Document this CPD

AI-assisted Evidence Research

Share Evidence Blueprint

QR Code

Psychiatry AI: Real-Time AI Scoping Review (RAISR4D)