Predicting nurse's depression based on self-compassion and resilience

Abstract

Introduction: Depression is one of the most important health problems in nurses. Despite the obvious protective role of some human abilities against psychological problems, there is limited information about the predictive role of self-compassion and resilience with depression in nurses. The purpose of present study was to determine the relationship of self-compassion and resilience with nurses’ depression.
 Method: This descriptive correlational study was conducted on170 nurses working in Yazd Afshar Hospital selected by convenience sampling method. Data collection tool was a questionnaire, including demographic characteristics, Beck Depression, Neff Self-compassion, and Connor and Davidson resilience completed through self-report. The data were analyzed by SPSS using Pearson correlation coefficient and multiple regression analysis.
 Results: Most of the subjects were female (62.35%) and had bachelor’s degree. Mean ± standard deviation of depression, self- compassion, and resilience scores were72/17 ±28/8; 65/31±46/1; 65/33 ±06/1, respectively. There was a significant relationship between depression and self-compassion, as well as depression and resilience. Furthermore, multiple regression analyses showed that self-compassion and resilience can predict depression (R=0.627).
 Conclusion: The results indicated the importance and protective role of self-compassion and resilience against depression in nurses. Therefore, designing counseling systems and self-compassion and resilience educational programs are recommended to reduce the problems caused by the stressful conditions of the profession.