Psychology Research, ISSN 2159-5542 October 2011, Vol. 1, No. 4, 227-238 Predicting Tendency for Suicide Based on Risk Factors and Ontological Identity Using Artificial Neural Network Hojjat A. Farahani Tehran University, Tehran, Iran Zeynab Kazemi, Somayeh Aghamohamadi University of Isfahan, Isfahan, Iran Mojtaba Ansari Tehran Science and Research University, Tehran, Iran Mehdi Aghamohamadi Payame Noor University, Najafabad, Iran 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. Keywords: tendency for suicide, risk factors, ontological identity, artificial neural network Introduction Suicide is a phenomenon existing as long as human kinds have existed. Inconsistent with life principle, suicide has been condemned in all societies and cultures. Suicide is an action aimed at deliberate terminating of one’s life and is committed consciously. A suicidal individual sends out some signals springing from suffering and stress (B. Sadock & V. Sadock, 2005). Suicide is a major problem in health and hygiene of society. About 9% of all deaths are due to suicide and nearly 1,000 suicides are committed each day all over the world (Levin, 2009). The rate of suicide has increased during the last 50 years. One million people die due to suicide each year in the world (Grzywa, A. Kucmin, & T. Kucmin, 2009). In spite of the facts, suicide is a complex and multi-dimensional phenomenon influenced by individual, social and cognitive factors. During last few decades, many studies have been done on suicide and the results have shown that suicide is correlated with Hojjat A. Farahani, Ph.D., Instructor of Faculty of Educational Sciences and Psychology, Tehran University. Zeynab Kazemi, Faculty of Educational Sciences and Psychology, University of Isfahan. Somayeh Aghamohamadi, Faculty of Educational Sciences and Psychology, University of Isfahan. Mojtaba Ansari, Clinical Psychology Department, Tehran Science and Research University. Mehdi Aghamohamadi, Computer Engineering and IT Department, Payame Noor University.