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...

Descripción completa

Detalles Bibliográficos
Publicado en:	Journal of Youth & Adolescence Vol. 53; no. 7; pp. 1615 - 1630
Autores principales:	Wang, Zhenhai, Chen, Yanrong, Tao, Zhiyuan, Yang, Maomei, Li, Dongjie, Jiang, Liyun, Zhang, Wei
Formato:	Artículo
Publicado:	Springer Nature Jul2024
Materias:	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
Acceso en línea:	Ver este registro en EBSCOhost