Abstract: Using the Job Demands and Resources Framework to Predict Job Burnout Among Social Services Workers (Society for Social Work and Research 25th Annual Conference - Social Work Science for Social Change)

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Using the Job Demands and Resources Framework to Predict Job Burnout Among Social Services Workers

Wednesday, January 20, 2021
* noted as presenting author
Yong Li, Ph.D., Assistant Professor, California State University, Bakersfield, Bakersfield, CA
Madhavappallil Thomas, phd, professor, California State University, Bakersfield, CA
Background and Purpose

Job burnout among social service workers is an important issue that negatively impacts individuals, organizations, and their work environments. Using the Job Demands and Resources (JD-R) framework, researchers (e.g., Demerouti et al., 2001) have identified two main factors that contribute to job burnout: high job demands (such as physical caseload, time pressure, and client contact) and lack of job resources (such as supervisor support, job control, feedback, and rewards). While this framework has been applied to health care workers, it has not been studied in social service workers. The current study attempted to investigate the role of these two factors in predicting job burnout in social service workers. We hypothesized that high job demands and lack of job resources are positively associated with job burnout.


A total of 249 social service workers in Central California were surveyed using a self-reported questionnaire. Participants’ self-reported race/ethnicity was white (42%), Hispanic (40%), African American (10%), and other (8%). Most participants were female (77%) and worked fulltime (93%). The average years of age were 38 (SD = 10). Job demands were measured by five items (e.g., constant exposure to crisis and pressure at work); job resources were measured by four items (e.g., having no input on decisions affecting your work); job burnout was measured by three items (e.g., feeling trapped in a dead-end job). All items were rated on a Likert-type scale ranging from 1-5, where “1” is “disagree," and “5” is "agree." A two-step structural equation modeling (SEM) approach was used to examine the research questions. A measurement model, including three latent variables (i.e., job demands, job resources, and job burnout), was first built and examined. A subsequent structural model with the hypothesized relationships was then examined. M-plus version 8 was used for data analysis.


SEM analyses suggested that the initial measurement model yielded a satisfactory model fit (χ2(51) = 94.13, p < .001, CFI = .967, TLI = .958, RMSEA = .058). The subsequent model, with two structural paths (the path between job demands and burnout and the path between job resources and burnout), also fit the data well (χ2(51) = 94.13, p < .001, CFI = .967, TLI = .958, RMSEA = .058). Consistent with our hypotheses, high job demands and lack of job resources were significantly associated with job burnout (b = .77, β = .48, p < .001; b = .65, β = .41, p < .001; respectively).

Conclusions and Implications

This study confirmed that job burnout might be a direct result of high job demands and lack of job resources, thus providing evidence on the relevance and significance of the JD-R framework for social service agencies. In an effort to curb job burnout, social services administrators and agency directors may need to allocate more resources to make the work environment more supportive as well as to reduce the ever-increasing job-related demands.