@ARTICLE{Ashoori, author = {Ashoori, Jamal and }, title = {Prediction nurse’s job burnout based on social capital, perceived social support and organizational citizenship behavior}, volume = {15}, number = {2}, abstract ={Abstract Introduction: Nursing is a stressful jobs and stress causes burnout. Job burnout has a lot negative psychological consequences. Thus, the aim of this study was to predict nurse’s job burnout based on the social capital, perceived social support and organizational citizenship behavior. Methods: The current research was a descriptive and analytical cross-sectional study. The population included the nurses of Varamin’s hospitals in 2016. Totally, 180 nurses were selected by the simple random sampling method. All of them completed the questionnaires included social capital, perceived social support, organizational citizenship behavior and job burnout. Data were analyzed by Pearson correlation and multivariate regression by enter model and with Assistance SPSS-19 software. Results: The results showed that social capital, perceived social support and organizational citizenship behavior had a negative significant relationship with nurse’s job burnout. In other words, the rate of nurse’s job burnout decreases with increasing social capital, perceived social support and organizational citizenship behavior (P≤0/01). A model predicting organizational citizenship behavior, perceived social support and social capital could predict 31.2% of the variations of nurse’s job burnout. The share of organizational citizenship behavior in predicting nurse’s job burnout was over than other variables (P≤0/001). Conclusion: Social capital, perceived social support and organizational citizenship behavior had an effective role in predicting the nurse’s job burnout. Therefore, it is suggested that, in order to decrease the nurse’s job burnout, counselors and therapists increase the rate of organizational citizenship behavior, perceived social support and social capital of nurses. }, URL = {http://psj.umsha.ac.ir/article-1-332-en.html}, eprint = {http://psj.umsha.ac.ir/article-1-332-en.pdf}, journal = {Pajouhan Scientific Journal}, doi = {10.21859/psj-15023}, year = {2017} }