Causal Model of Working-Life Quality, Based on Job Engagement and Emotional Intelligence by the Mediating Role of Job Satisfaction in Medi-cal University of Zanjan Employees

The purpose of this research was to determine the fit of the causal model of work-life quality based on job attachment and emotional intelligence with the mediating role of job satisfaction in employees of Zanjan University of Medical Sciences. In terms of its purpose, this is an applied research, and in terms of the data collection method, it is a descriptive correlation type. The statistical population included all the personnel of Zanjan University of Medical Sciences, numbering 10,000 people in 1400, and 370 people were selected as a sample by simple sampling method. The research tools were Walton's (1973) quality-of-work-life questionnaires, Brafield and Roth's (1967) job satisfaction, Barr-Anne's emotional intelligence (2002) and Kanongo's job attachment (1982). To analyze the data, Pearson's correlation test and structural equations were used by pls and SPSS software. The results showed that the effect of job attachment, emotional intelligence and job satisfaction on the quality of work life of employees and the effect of job attachment on the job satisfaction of employees is positive and significant. However, the effect of emotional intelligence on job satisfaction of employees was not positive and significant. Also, the indirect effect of job attachment on work-life quality through job satisfaction was significant, so the role of job satisfaction as a mediator between job attachment and work-life quality was confirmed. And the indirect effect of emotional intelligence on quality of work life through job satisfaction was not significant, so the role of job satisfaction as a mediator between emotional intelligence and quality of work life was not confirmed. In general, it is concluded that the causal model of quality of working life based on job attachment and emotional intelligence with the mediating role of job satisfaction does not fit with the empirical model.