The associated factors of suicide attempt in French sexual minority adolescents

Abstract

BACKGROUND: Sexual minority adolescents have greater risk for suicide attempt (SA) than heterosexual youth. However, research on risk and protective factors is lacking in sexual minority youth. In this study, we aimed to identify novel risk and protective factors for suicide attempt using machine learning decision tree method.METHODS: The French cross-sectional study Portraits d’adolescents included 14,265 aged 13-20 years old adolescents. Decision tree algorithm was used to predict SA and to compare the different risk and protective factors between sexual minority youth and heterosexual peers.RESULTS: Twenty predictive factors were identified among the 70 survey fields output from the predictive modeling for SA. Substance consumptions were among the top risk factors for SA. Parental support was an important protective factor among all adolescents regardless of sexual orientation. Interestingly, through the decision tree, real-life friend support was found protective in heterosexual youth, online friend support was a protective factor in homosexual adolescents.CONCLUSIONS: Using the decision tree-based algorithm, we not only verified those important protective factors that were demonstrated in existing studies, but also discovered novel protective and attributive factors, such as real-life and online friend support. We urge that social networks should be optimized to provide safety and support for the sexual minority adolescents.