(see Poster Gallery) The Effects of Covid-19 Stress and Support on Job Satisfaction and Turnover Intent Among Social Service Workers

Background and Purpose:

Social service workers often experience many job stressors due to the nature of their work and inadequate organizational support. Research has applied the job demands and resources (JD-R) model to examine how these factors impact individual perceptions about work such as job satisfaction and burnout. The Covid-19 pandemic is believed to add an extra layer of stress to these workers. This study aimed to investigate the direct effects of Covid-19 stress and Covid-19 support on job satisfaction and their indirect effects on turnover intention through job satisfaction among social service workers while controlling for job demands and resources and other demographic and work characteristics.

Methods:

The sample included 256 workers employed in various social service agencies in an urban area in California. Survey data were collected using a self-reported questionnaire. Participants’ self-reported race/ethnicity was white (16%), Hispanic (71%), African American (9%), Asian (2%), and other (2%). Most participants were female (87%), married (55%), and provided direct care to clients (82%). The average age was 36 years (SD = 9).

Job satisfaction was measured by a short scale of overall job satisfaction (5 items). Turnover intention taps into individual workers' intent to leave the agency (3 items). The job demands scale (6 items) captures organizational stressors such as high expectations and unmanageable caseloads; the job resources scale (8 items) includes supervision, teamwork, training, etc. Covid-19 stress included four items: overall stress due to Covid-19 and its impacts on individual mental, physical, and financial well-being, respectively. Covid-19 support was measured by organizational support for Covid-19 in three areas: communications, personal protective equipments, and technical support.

Results:

Hierarchical regression models predicting job satisfaction were established in three steps. Seven control variables (age, sex, race, marital status, direct care, overtime work, and perceived workload) were entered in Model 1, JD-R factors in Model 2, and Covid-19 stress and support in Model 3. Model fit was significantly improved in Model 2 (∆R2 = 0.24, F(2,241) = 45.95, p < .001) and Model 3 (∆R2 = 0.06, F(2,239) = 11.77, p < .001). In Model 3, significant predictors for job satisfaction included direct service (b = .33, p = .002), job demands (b = -.15, p = .004), lack of resources (b = -.18, p = .004), Covid-19 stress (b = -.10, p = .03), and Covid-19 support (b = .19, p < .001). Bootstrapping mediation analyses with all significant predictors in Model 3 revealed that job satisfaction was a significant mediator between turnover intent and lack of resources (95% CI [0.033, 0.134]), Covid-19 stress (95% CI [0.077, 0.213]), and Covid-19 support (95% CI [0.122, 0.375]).

Conclusions and Implications:

Job satisfaction was negatively related to Covid-19 stress and positively related to Covid-19 support among social service workers. It mediated the effects of Covid-19 stress and support on turnover intent. Social service agencies can use these findings to inform their efforts to curb the detrimental effects of Covid-19. These efforts should be at least two-fold: increasing job resources and enhancing Covid-19 support.