Predicting teachers' psychological burnout based on quality of life and job engagement during the corona pandemic in Marvdasht

The aim of this study was to predict teachers' psychological burnout based on quality of life and job engagement during the corona pandemic in Marvdasht. The research method is applied in terms of purpose and descriptive-correlation in terms of method. The statistical population of this study includes all teachers working in schools of Marvdasht city، whose number was over 750 people in the academic year 1400-1399.To determine the sample size based on the population size and using simple random sampling method based on Morgan table، 256 samples were selected as a sample and questionnaires were distributed virtually among these individuals. Data collection tools including three questionnaires of Smiths (1996)، Kanungo job conflict (1982) and quality of life questionnaire of the World Health Organization (1998) were used. To analyze the data، statistical methods were used at the level of descriptive and inferential statistics in Spss software environment. In this regard، at the level of descriptive statistics (frequency، percentage، mean and standard deviation) and at the level of inferential statistics، multiple regression test was used. The results showed that quality of life and job conflict are able to predict psychological burnout; All dimensions of quality of life are able to predict psychological burnout; Among the dimensions of quality of life، living environment is the most important predictor of psychological burnout; All dimensions of job conflict are able to predict psychological burnout; Among the dimensions of job conflict، loyalty is the most important predictor of psychological burnout.