PREDICTING THE INTENTION TO LEAVE OF THE NURSING PROFESSION IN IMAM KHOMEINI HOSPITAL IN MAHABAD DURING THE CORONA PANDEMIC PERIOD BASED ON THE COMPONENTS OF JOB STRESS AND RESILIENCE

In difficult and critical situations like the corona pandemic, nurses always face a
great deal of stress that may increase their intention to leave. Since resilience is considered as one of the
individuals’ abilities to adapt to stressful situations, this study was aimed at predicting the intention to
leave among nurses in Imam Khomeini Hospital in Mahabad city during the corona pandemic period
based on job stress and resilience components.
Materials & Methods: This is a descriptive-correlational study. The statistical population of this study
included all nurses in Imam Khomeini Hospital in Mahabad (n= 250) in 2020. Using Cochran’s formula,
151 subjects were chosen as the sample by simple random sampling method. 140 accurate and
measurable, and citable questionnaires were returned. The study tool included three standard
questionnaires: Intention to Leave by Kim et al. (2007), Resilience Questionnaire by Connor and David
Seven (2003), and Job Stress Questionnaire by Philip Al Rice (1999). Data analysis was conducted by
Pearson correlation test and stepwise regression using SPSS software version 19.
Results: According to the research findings, a positive and significant relationship between the intention
to leave the job and job stress was revealed and job stress predicts the nurses’ intention to leave (r =
0.746 and p<.001). Moreover, there was a negative and significant relationship between resilience and
the intention to leave and resilience predicts the nurses’ intention to leave (r = -0.887 and p<.001).
Conclusion: Resilience and job stress may predict the nurses’ intention to leave the profession in Imam
Khomeini Hospital in Mahabad during the corona pandemic. Hence, managers are better to reduce the
nurses’ intention to leave their work in the Corona pandemic through decreasing job stressors besides
implementing resilience-training programs.