Objective: To investigate the incidence and influencing factors of new onset suicidal behaviors among junior and senior high school students, so as to provide evidence for early warning and intervention. Methods: Using a cluster sampling method, baseline data were collected from September to November 2023 among 2 379 adolescents selected from 2 junior high schools, 2 general senior high schools and 2 vocational senior high schools in Wuhan, Hubei Province, with follow up carried out from September to November 2024. Data were collected using the School Adaptation Scale, the Essential Resilience Scale, the Personal Social Support Scale, the Adverse Childhood Experiences Questionnaire, the Adolescent Life Events Scale, the Pittsburgh Sleep Quality Index, the Center for Epidemiologic Studies Depression Scale, and the Columbia-Suicide Severity Rating Scale. Multivariate Logistic regression analysis was used to identify factors influencing new onset suicidal behavior among junior and senior high school students. Results: Among junior and senior high school students without suicide risk at baseline, 53.55% remained stable risk free during follow up, while 13.28% developed new suicidal behavior during follow up, of which suicidal ideation, suicide plan and suicide attempts accounted for 11.69%, 8.83% and 6.52%, respectively. Multivariate Logistic regression revealed that increased depressive symptoms at follow up elevated the risk of overall new onset suicidal behaviors ( OR =4.14), ideation ( OR = 4.59), plans ( OR =4.24), and attempts ( OR =4.09); poor sleep quality also increased the risk of overall new onset suicidal behaviors ( OR =2.23), plans ( OR =2.03), and attempts ( OR =2.65) (all P <0.05). Non boarding junior and senior high school students had lower risks of overall new onset suicidal behaviors and ideation ( OR=0.70 and 0.49, respectively); secondary school students with academic performance ranking in the top 20%-30% of their class had a lower risk of new onset ideation ( OR =0.27); and those whose place of origin was outside the city had a lower risk of new onset plans ( OR =0.49) (all P <0.05). Conclusions New onset suicidal behaviors among junior and senior high school students exhibit dynamic and stage specific differences. Depressive symptoms serve as a common core risk factor across all stages, whereas sleep quality, academic performance, boarding status, and place of origin exert differential influences at distinct stages.

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.