Volume 30, Issue 189 (10-2020)
J Mazandaran Univ Med Sci 2020, 30(189): 71-84 |
Back to browse issues page
Siavash EtemadiNezhad 
, Seyed Ehsan Samaei , Jamshid Yazdani Charati , Mohammad Reza Davoodi Moghaddam
, Seyed Ehsan Samaei , Jamshid Yazdani Charati , Mohammad Reza Davoodi Moghaddam
Abstract: (1719 Views)
Background and purpose: Health inspectors are faced with high levels of workload and stress. There is lack of evidence on the relationship between job burnout and the quality of working life in this group. So, research on this issue is highly needed.
Materials and methods: This cross-sectional descriptive-analytical study was conducted on census based population (n=245 health inspectors) in Golestan University of Medical Sciences. Demographic information were collected and the Quality of Work Life (QWL) scale and Maslach Burnout Inventory (MBI) were also used. Data analysis was done in SPSS V18 applying Pearson's correlation coefficient and backward LR logistics regression to investigate the relationship between the quality of work life and job burnout and predicting the factors affecting job burnout, respectively.
Results: Total QWL score and MBI score were 70.40±13.42 and 42.64±20.24, respectively. According to Pearson's correlation coefficient, there were significant inverse correlations between all dimensions of QWL and job burnout (P<0.05). According to logistics regression, increase in QWL scores, from low to medium level, could 11 times reduce burnout (OR = 11.143, 95%CI: 1.32 - 93.69).
Conclusion: Based on current study, one of the intervention programs to reduce job burnout syndrome in health inspectors is focusing on factors that improve their quality of work life.
Materials and methods: This cross-sectional descriptive-analytical study was conducted on census based population (n=245 health inspectors) in Golestan University of Medical Sciences. Demographic information were collected and the Quality of Work Life (QWL) scale and Maslach Burnout Inventory (MBI) were also used. Data analysis was done in SPSS V18 applying Pearson's correlation coefficient and backward LR logistics regression to investigate the relationship between the quality of work life and job burnout and predicting the factors affecting job burnout, respectively.
Results: Total QWL score and MBI score were 70.40±13.42 and 42.64±20.24, respectively. According to Pearson's correlation coefficient, there were significant inverse correlations between all dimensions of QWL and job burnout (P<0.05). According to logistics regression, increase in QWL scores, from low to medium level, could 11 times reduce burnout (OR = 11.143, 95%CI: 1.32 - 93.69).
Conclusion: Based on current study, one of the intervention programs to reduce job burnout syndrome in health inspectors is focusing on factors that improve their quality of work life.
Type of Study: Research(Original) |
Subject:
Health Professiona
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |