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THE CORRELATION OF NEUROTICISM WITH SYMPTOMS OF DEPRESSION AND ANXIETY IN STUDENTS ACCORDING TO THE MEDIATING ROLE OF WORRY AND RUMINATION

Michaeli Manee Farzaneh, Asadi Majreh Samereh

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Abstract

Different models and studies have tried to define symptoms of depression and anxiety through examining the correlation between cognitive and personality variables. In this respect, this study was conducted to determine the role of worry and rumination in the correlation between neuroticism and symptoms of depression and anxiety in students. The participants included 210 university students (164 females and 46 males). The students completed the Penn state worry questionnaire, Zung depression scale, ruminative responses scale of Nolen-Hoeksema and Morrow, Spielberger’s trait anxiety subscale, and neuroticism subscale of the NEO personality inventory. The data were analyzed using structural equation modeling. The results showed that the neurotic and ruminative variables respectively showed the highest effect on depression. Based on the path analysis, the indirect effect of worry on depression was significant. The correlation of anxiety with variables of worry, rumination, and neuroticism in the structural equation modeling was insignificant and was consequently ignored. However, worry and neuroticism significantly correlated with rumination. The variables of worry, rumination, and neuroticism could predict depression in the students.

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What this paper is about

Different models and studies have tried to define symptoms of depression and anxiety through examining the correlation between cognitive and personality variables. In this respect, this study was conducted to determine the role of worry and rumination in the correlation between neuroticism and symptoms of depression and anxiety in students. The participants included 210 university students (164 females and 46 males). The students completed the Penn state worry questionnaire, Zung depression scale, ruminative responses scale of Nolen-Hoeksema and Morrow, Spielberger’s trait anxiety subscale, and neuroticism subscale of the NEO personality inventory. The data were analyzed using structural equation modeling. The results showed that the neurotic and ruminative variables respectively showed the highest effect on depression. Based on the path analysis, the indirect effect of worry on depression was significant. The correlation of anxiety with variables of worry, rumination, and neuroticism in the structural equation modeling was insignificant and was consequently ignored. However, worry and neuroticism significantly correlated with rumination. The variables of worry, rumination, and neuroticism could predict depression in the students.

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Available abstract

Different models and studies have tried to define symptoms of depression and anxiety through examining the correlation between cognitive and personality variables. In this respect, this study was conducted to determine the role of worry and rumination in the correlation between neuroticism and symptoms of depression and anxiety in students. The participants included 210 university students (164 females and 46 males). The students completed the Penn state worry questionnaire, Zung depression scale, ruminative responses scale of Nolen-Hoeksema and Morrow, Spielberger’s trait anxiety subscale, and neuroticism subscale of the NEO personality inventory. The data were analyzed using structural equation modeling. The results showed that the neurotic and ruminative variables respectively showed the highest effect on depression. Based on the path analysis, the indirect effect of worry on depression was significant. The correlation of anxiety with variables of worry, rumination, and neuroticism in the structural equation modeling was insignificant and was consequently ignored. However, worry and neuroticism significantly correlated with rumination. The variables of worry, rumination, and neuroticism could predict depression in the students.

Key concepts: Worry, Rumination, Neuroticism, Psychology, Anxiety, Clinical psychology, Personality, Structural equation modeling

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