Resiliency Prediction Based on Emotion Levels in Nurses Who Work in Hospitals of Tehran

The present research aims to predict resiliency based on emotions' level in nurses who working in hospitals in Tehran. This is applied research in terms of the goal and is correlational in terms of execution method. The research population included all nurses working in the hospitals of Tehran in 2018 (2200 individuals). To select samples, 300 nurses (181 females and 119 males) were selected by a random simple sampling method and based on Morgan's table. Research tools included the resiliency questionnaire (2005) and the Positive and Negative Affect Schedule of Watson et al (1988) which have validity and reliability. The data of the research was analyzed by multiple regressions and SPSS software. The results showed that predictor variables include emotion levels that have 72% common variance with criterion variable (resiliency). The multiple correlation coefficient between variables was 0.70 and the determination's adjusted coefficient was 0.70. According to the research results, the negative emotion is a significant predictor for the variable of resiliency and has predicted nurses' resiliency as negative with a significance level of 0.01 and a β coefficient of -0.21. The positive emotion was also a significant predictor for the variable of resiliency and has predicted nurses' resiliency as positive with a significance level of 0.01 and a β coefficient of 0.71. According to the β coefficients' results, the positive emotion with the β coefficient of 0.71 has the highest prediction for the variable of resiliency.