Prediction of non-suicidal self-injury (NSSI) among rural Chinese junior high school students: a machine learning approach.

ABSTRACT:

Aims

Non-suicidal self-injury (NSSI) is a serious issue that is increasingly prevalent among children and adolescents, especially in rural areas. Developing a suitable predictive model for NSSI is crucial for early identification and intervention.

Methods

This study included 2090 Chinese rural children and adolescents. Participants' sociodemographic information, symptoms of anxiety as well as depression, personality traits, family environment and NSSI behaviors were collected through a questionnaire survey. Gender, age, grade, and all survey results except sociodemographic information were used as relevant factors for prediction. Support vector machines, decision tree and random forest models were trained and validated by the train set and valid set, respectively. The metric

SUBMITTER: Jiang Z 

PROVIDER: S-EPMC11622475 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature