Quantifying the Importance of Non-Suicidal Self-Injury Characteristics in Predicting Different Clinical Outcomes: Using Random Forest Model.

Existing research on non-suicidal self-injury (NSSI) among adolescents has primarily concentrated on general risk factors, leaving a significant gap in understanding the specific NSSI characteristics that predict diverse psychopathological outcomes. This study aims to address this gap by using Rando...

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Bibliographic Details
Published in:	Journal of Youth & Adolescence Vol. 53; no. 7; pp. 1615 - 1630
Main Authors:	Wang, Zhenhai, Chen, Yanrong, Tao, Zhiyuan, Yang, Maomei, Li, Dongjie, Jiang, Liyun, Zhang, Wei
Format:	Article
Published:	Springer Nature Jul2024
Subjects:	Suicidal ideation Anxiety Self-mutilation Teenagers' conduct of life Mental depression Psychosocial factors Random forest algorithms Prediction models T-test (Statistics) Research funding Questionnaires Treatment effectiveness Chi-squared test Longitudinal method Research Data analysis software Algorithms
Online Access:	View this record in EBSCOhost