Predicting Tendency for Suicide Based on Risk Factors and Ontological Identity Using Artificial Neural Network

Abstract

The purpose of this research was to offer a model for predicting the rate of tendency for suicide in individuals and also the importance number of the risk factors involved in suicide, using artificial neural network. Furthermore, the relationship between ontological identity and suicide was examined. Six hundred and ninety-eight participants (557 females and 141 males) in this research in Isfahan were selected by convenience sampling method. The age range of the sample individuals was 19 to 41 years (M = 22.2). In this research, an artificial neural network was offered to draw the relationship among 32 suicide risk factors. All the risk factors presented in former researches, besides ontological identity had a role in the network. The accuracy of classification of this network in predicting the tendency of suicide in various individuals was 90.5. Also, the importance number of the suicide risk factors was shown using neural network. Ontological identity obtained the first rank among all the risk factors. Therefore, this research confirmed the roles of all presented risk factors in former researches, besides ontological identity, in suicide and provided a hierarchy of risk factors in suicide.