Yoonju Lee1, Heejin Kim1, Yesul Lee1, Hyesun Jeong2. 1. College of Nursing, Pusan National University, Yangsan, Korea. 2. College of Nursing, Pusan National University, Yangsan, Korea. pointsun@naver.com.
Abstract
PURPOSE: The purpose of this study was to develop and compare the prediction model for suicide attempts by Korean adolescents using logistic regression and decision tree analysis. METHODS: This study utilized secondary data drawn from the 2019 Youth Health Risk Behavior web-based survey. A total of 20 items were selected as the explanatory variables (5 of sociodemographic characteristics, 10 of health-related behaviors, and 5 of psychosocial characteristics). For data analysis, descriptive statistics and logistic regression with complex samples and decision tree analysis were performed using IBM SPSS ver. 25.0 and Stata ver. 16.0. RESULTS: A total of 1,731 participants (3.0%) out of 57,303 responded that they had attempted suicide. The most significant predictors of suicide attempts as determined using the logistic regression model were experience of sadness and hopelessness, substance abuse, and violent victimization. Girls who have experience of sadness and hopelessness, and experience of substance abuse have been identified as the most vulnerable group in suicide attempts in the decision tree model. CONCLUSION: Experiences of sadness and hopelessness, experiences of substance abuse, and experiences of violent victimization are the common major predictors of suicide attempts in both logistic regression and decision tree models, and the predict rates of both models were similar. We suggest to provide programs considering combination of high-risk predictors for adolescents to prevent suicide attempt.
PURPOSE: The purpose of this study was to develop and compare the prediction model for suicide attempts by Korean adolescents using logistic regression and decision tree analysis. METHODS: This study utilized secondary data drawn from the 2019 Youth Health Risk Behavior web-based survey. A total of 20 items were selected as the explanatory variables (5 of sociodemographic characteristics, 10 of health-related behaviors, and 5 of psychosocial characteristics). For data analysis, descriptive statistics and logistic regression with complex samples and decision tree analysis were performed using IBM SPSS ver. 25.0 and Stata ver. 16.0. RESULTS: A total of 1,731 participants (3.0%) out of 57,303 responded that they had attempted suicide. The most significant predictors of suicide attempts as determined using the logistic regression model were experience of sadness and hopelessness, substance abuse, and violent victimization. Girls who have experience of sadness and hopelessness, and experience of substance abuse have been identified as the most vulnerable group in suicide attempts in the decision tree model. CONCLUSION: Experiences of sadness and hopelessness, experiences of substance abuse, and experiences of violent victimization are the common major predictors of suicide attempts in both logistic regression and decision tree models, and the predict rates of both models were similar. We suggest to provide programs considering combination of high-risk predictors for adolescents to prevent suicide attempt.
Authors: Laura Kann; Tim McManus; William A Harris; Shari L Shanklin; Katherine H Flint; Barbara Queen; Richard Lowry; David Chyen; Lisa Whittle; Jemekia Thornton; Connie Lim; Denise Bradford; Yoshimi Yamakawa; Michelle Leon; Nancy Brener; Kathleen A Ethier Journal: MMWR Surveill Summ Date: 2018-06-15
Authors: Andrea Miranda-Mendizabal; Pere Castellví; Oleguer Parés-Badell; Itxaso Alayo; José Almenara; Iciar Alonso; Maria Jesús Blasco; Annabel Cebrià; Andrea Gabilondo; Margalida Gili; Carolina Lagares; José Antonio Piqueras; Tiscar Rodríguez-Jiménez; Jesús Rodríguez-Marín; Miquel Roca; Victoria Soto-Sanz; Gemma Vilagut; Jordi Alonso Journal: Int J Public Health Date: 2019-01-12 Impact factor: 3.380