The Effect of Emotion Regulation on Predicting Depressive Symptoms in Students

Abstract

Background: Many people around the world have been affected by depression, which causes a great deal of problems. Emotion regulation refers to processes influencing emotion, experiences, and expresses. Objectives: This study aimed to evaluate the role of emotion regulation to predict depressive symptoms among Kermanshah University of Medical Sciences students. Methods: This descriptive-analytical study was conducted on 305 students at Kermanshah University of Medical Sciences, Iran, who were randomly selected by convenient sampling method. The informed consent forms were signed by the participants. Then the Beck Depression Inventory - Second Edition (BDI-II) and the Cognitive Emotion Regulation Scale (CERQ-18) were completed in a virtual/face-to-face manner due to the COVID-19 pandemic. The data were analyzed with SPSS software version 26. A total of 296 participants were analyzed, of whom 198 (66.9%) were female, and 98 (33.1%) were male. Results: The self-blame strategies (β = 0.31, P ≤ 0.001), positive reassessment (β = -0.26, P ≤ 0.001), catastrophic (β = 0.26, P ≤ 0.001), numerical importance (β = -0.12, P ≤ 0.001) and positive refocus (β = -0.10, P ≤ 0.001) predict 40% of the variance of depression in five steps. Inconsistent strategies such as self-blame and catastrophe directly predict depression. Further, depression is inversely related to positive reassessment, insignificance, and positive refocus. Conclusions: According to the results, there was a significant direct relationship between self-blame and catastrophic thinking as maladaptive cognitive emotion regulation strategies with depression. In addition, positive refocusing and positive reassessment had a significant negative correlation with depression among adaptive emotion regulation strategies.