Modeling Job Burnout Based on Resilience and Social Support with the Mediation of Job Self-efficacy in Military Industry Employees

Human existence in society is created by work, and many aspects of human life are achieved through work and daily activities. Although work is one of the important factors in assessing basic needs and improving social conditions, sometimes it may become the main factor of mental pressure. Several factors contribute to employees' physical and psychological health; one of the most important is job burnout. Several studies have pointed out that military employees are more likely to be exposed to burnout, acute stress, posttraumatic stress, and substance abuse. Considering the importance of job burnout, it is possible to identify the factors related to the mental health and better productivity of military industry employees by conducting various research projects. So, this research aimed to explain job burnout based on resilience and social support with the mediation of job self–efficacy among military industry staff.

This is an analytical study using structural equation modeling. The study population comprised all the employees living in the residential settlements of the Defense Industries Organization between 2021 and 2022. The sample size based on the structural equation modeling method is estimated as between 10 and 15 people for each obvious variable. Considering 14 obvious variables, the sample size should be between 140 and 280 people. The sampling method in this research was purposeful. The inclusion criteria were all participants with a diploma or higher working in the defense industry. The number of participants in this research was 179. The study data were gathered via Job Burnout Scale (Maslach & Jackson, 1981), the Connor–Davison Resilience Scale (Connor & Davison, 2003), the Multidimensional Scale of Perceived Social Support (Zimet et al., 1988), and Job Self–Employment Questionnaire (Riggs et al., 1994). The Pearson correlation coefficient and structural equation modeling were performed for data analysis in SPSS version 22 and AMOS software version 22. The significance level of all tests was set at 0.05.

Examining the direct path coefficients showed that resilience had a significant positive direct effect on job self–efficacy (Beta=0.547, p<0.001), and job self–efficacy had a significant negative direct effect on job burnout (Beta=–0.502, p<0.001). Also, resilience had an indirect, negative, and significant effect on job burnout (Beta=–0.680, p=0.003). Meanwhile, social support had no effect either directly (Beta=–0.032, p=0.742) or indirectly (Beta=–0.127, p=0.289) on job burnout. In addition, the goodness of fit indices (AGFI=0.898, CFI=0.938, GFI=0.934, RMSEA=0.035, χ2</sup>/df=1.212) did not reject the fit of the data model with the conceptual model of the research.

Based on the research findings, resilience, and social support due to job self–efficacy effectively reduce job burnout of military employees.