Emotion Cognitive Regulation

Purpose: in the present study, the relationship between cognitive emotion regulation and academic buoyancy with the role of mediating self-disability in students has been studied. Methodology: The present study was descriptive-correlational. The research population included all female secondary school students in Sabzevar City. 323 students were randomly selected as the sample in a multistage cluster sampling method. They completed Jones and Rodwellt Self-Handicapping Scale (1982), Garnfesky, Kareev and Spinhaun (2001) Emotional Cognitive Regulation Questionnaire and Dehghanizadeh and حسینchary (2012) Academic Buoyancy Questionnaire. Findings: The results of the research indicated that the model of the research had excellent fitting and self-handicapping has a mediating role in the relationship between emotional cognitive regulation and students’ academic buoyancy. Also, 79% of the variations in academic buoyancy are explained through the strategies of positive and negative cognitive emotion regulation and academic self-handicapping and 74% of the variations in academic self-handicapping are explained through the strategies of positive and negative emotion cognitive regulation. Discussion: As a result, it should be acknowledged that students who grow up to develop strong emotions could handle social barriers and pressure well, and manage behaviors that can mitigate their academic achievement. Therefore, the emotional stress of students in dealing with stressful situations affects self-handicapping and, consequently, their academic buoyancy.

Aim: This study aimed to investigate the role of cognitive emotion regulation strategies and behavioral activator-inhibitor systems in depression. Methods: The research method was descriptive correlational with 240 female undergraduate and graduate students of Shahrekord University (Western province of Iran) selected through a random sampling method. They answered Beck Depression Inventory, Granovsky’s Cognitive Emotion Regulation Questionnaire, and Carver and White’s Brain Systems Scale. The data were analyzed using SPSS 22.  Results: The mean and standard deviation of each variable were calculated as descriptive statistics, and Pearson correlation was employed to evaluate the relationships of variables. The results showed a significant negative correlation between behavioral activator systems and depression, and a significant positive correlation between behavioral inhibitor systems and depression. In general, the behavioral activator-inhibitor systems predicted 33% of depression variance. In addition, there was a significant positive relationship between maladaptive strategies of cognitive emotion regulation and depression and a significant negative relationship between adaptive strategies of cognitive emotion regulation and depression. Conclusion: The results showed that among the maladaptive strategies of cognitive emotion regulation, the catastrophic component predicted about 29% of depression variance, and among the adaptive strategies of cognitive emotion regulation, the acceptance component predicted about 39% of depression variance. In general, the results of this study indicated that brain-behavioral systems and emotional cognitive regulation strategies had chief roles in predicting depression. Relying on the findings of this study, we can present a practical framework to explain the symptoms of depression and its treatment.