Title of article :
Prediction of depression symptoms based on personality traits and romantic relationships among students
Author/Authors :
Dehestani, Mehdi Department of Psychology - Faculty of Psychology and Education - Payam Noor University, Tehran , Ghanbarian Sharabiani, Sara Department of Psychology - Faculty of Psychology and Education - Payam Noor University, Tehran , Nooripour, Roghieh Department of Counseling - Faculty of Education and Psychology - Alzahra University, Tehran , Zanganeh, Firuzeh Department of Psychology - Faculty of Humanities - Islamic Azad University of Arak, Arak
Pages :
9
From page :
173
To page :
181
Abstract :
Depression is one of the most common mental disorders in modern societies which also including student populations. Etiology of depression is naturally very complicated matter. Some of the effective parameters that have recently gained scholars’ attention are personality traits including romantic relationships that can affect depression. The purpose of this study was to evaluate relationship between personality traits and romantic relationships with depression. Research population was students of Payam Noor University of Tehran that 50 married students and were selected by using random sampling method. Research instruments were Beck’s depression Inventory II (BDI-II), shortened revised NEO personality Inventory (NEO-FFI-60) and sternberg's triangular love scale. Data analysis showed that neuroticism component of personality traits as well as intimacy component of Sternberg’s love theory has significant relationship with depression. Moreover, this research showed that neuroticism and intimacy could predict depression symptoms by 37 percent and 10 percent respectively. In order to prevent depression in students, interventional actions are needed to provide more clear relationships based on personality traits.
Keywords :
Depression , Personality Traits , Relationship , Students
Journal title :
Journal of Research and Health
Serial Year :
2018
Record number :
2521255
Link To Document :
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