Predicting high-risk behaviors based on early maladaptive schemas in university students

Document Type : Original Article

Authors

1 Assistant Professor, Department of Psychology and Educational Sciences, Faculty of Humanities, Arak University, Arak, Iran

2 Ph.D. student of Clinical Psychology, Department of Psychology, Rudehen Branch, Islamic Azad University, Rudehen, Iran

3 Ph.D. in counseling, Department of Counseling, School of Psychology and Educational Sciences, Kharazmi University, Tehran, Iran.

Abstract

Early maladaptive schemas are the basis of many high-risk behaviors and psychological disorders. The objective of this study was to predict high-risk behaviors based on early maladaptive schemas among university students. The statistical population of this study included all male and female students at Sari University. The sample included 182 college students) 88 males and94 females) who were chosen via the convenience sampling method? The instruments included the Schema Questionnaire (Young, 1991) and Risk Behaviors Questionnaire (Zadeh Mohammadi & Ahmadabadi 2009). Data were analyzed through stepwise multiple regression. It showed that dependence could explain 13%of the variance of violence. Shame, perfectionism, entitlement, ment, and failure (in four steps) could explain 21% of the variance of drug abuse. In addition, shame and perfectionism (in two steps) could explain 9.3%of the variance of alcohol consumption. Moreover, dependency and emotional inhibition (in two steps) could explain 6.4% of the variance of involvement the romantic activity. According to the findings of this study considering the predictability of students’ high-risk behaviors based on some early maladaptive schemas in order to prevent the spread of high-risk behaviors, the factors affecting the formation of early maladaptive schemas among students should be considered. Also, the results, have important implications for the pathology, prediction, prevention, and treatment of high-risk behaviors among university students.

Keywords


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