Predicting model for the impact of Internet usage characteristics on suicidal ideation among vocational high school students
10.16835/j.cnki.1000-9817.2025242
- VernacularTitle:网络使用特征对职业高中学生自杀意念影响的预测模型
- Author:
YU Bin, YAN Jingyan, ZHANG Liqun, XIAO Chenchang, LI Fang, GUO Yan, YAN Hong
1
Author Information
1. School of Public Health, Wuhan University, Wuhan 430071, Hubei Province, China
- Publication Type:Journal Article
- Keywords:
Internet;
Suicide;
Mental health;
Regression analysis;
Students
- From:
Chinese Journal of School Health
2025;46(8):1175-1179
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the association between the Internet usage characteristics and suicidal ideation among vocational high school students, so as to provide a theoretical basis for precise intervention of suicide among vocational high school students.
Methods:A total of 1 781 students were recruited from three vocational high schools in Wuhan and Xianning in March 2023 by using the cluster random sampling method. The Columbia-Suicide Severity Rating Scale and Revised Chen Internet Addiction Scale were used to measure suicidal ideation and Internet addiction, respectively. LASSO regression model was used to select influential factors related to suicidal ideation, and the gradient boosting decision tree algorithm XGBoost was used to develop prediction models and evaluate predictive performance. By calculating the SHAP values, the contribution of each influential factor was quantified.
Results:The prevalence of suicidal ideation among vocational high school students was 42.22% and prevalence of Internet addiction was 26.39%. LASSO regression results indicated that age, gender, experience of being left behind, parental relationship, holding a class cadre position, using the Internet for learning, Internet use during dawn, morning and late night, Internet addiction, and depressive symptoms were all the influential factors of suicidal ideation among vocational high school students ( β= -0.05 , 0.29, 0.09, 0.27, 0.10, -0.01, 0.09, 0.05, 0.24, 0.28, 0.78, all P <0.05). The AUC of the prediction model was 0.75. The results based on SHAP values indicated that all influential factors identified through multivariate analysis contributed positively to the model predictions ( SHAP >0). Among these, depressive symptoms and parental relationship had the greatest impact on suicidal ideation ( SHAP =0.77, 0.26), and the joint effect of features with higher contribution could improve the prediction probability.
Conclusions:Depressive symptoms, parental relationships, Internet addiction, and time of Internet use are most important risk factors of suicidal behaviors for vocational high school students. Thus, effective interventions should be conducted to reduce their suicidal ideation.
