The Association between Job Wellbeing and Employee Demographic and Job Characteristics Among Behavioral Health Workers

Background and purpose

Behavioral health organizations in the U.S. continue to struggle with high rates of employee burnout, ranging from 21% to 67% among behavioral health professionals. Community behavioral health organizations (CBHO) are complex systems of diverse employees with varying demographics, job roles, and workplace experiences, which may affect employee job wellbeing differently. Therefore, it is critical to understand how varying employee characteristics are associated with job wellbeing. However, most studies overlook the potential job wellbeing differences across employee subgroups. Understanding the differential impacts is the first step to developing more tailored interventions to improve job wellbeing in their contexts. The current study examined the association between 11 job wellbeing indicators and employee demographic and job characteristics.

Methods

We obtained employee demographics and job characteristics (i.e., race, gender, marital status, age, educational degree, work year, full-time, clinical, exempt status) from the HR department and distributed a confidential Qualtrics survey with 11 job wellbeing indicators (e.g., communication clarity, job fairness) to all employees (N=342) at a CBHO in a midwestern state. The job wellbeing indicators were developed for single-item use with confirmed validity. Bivariate analyses were conducted to examine the association between job wellbeing indicators and employee demographic and job characteristics.

Results

We obtained 168 responses. The participants had an average age of 43.8 (±13) years and an average tenure of 5.2 (±6) years. Seventy-eight percent were clinical staff, 69% were Caucasian, and most were female (76%), single (63%), non-exempt (75%), and 54% had Bachelor’s degree or below. White employees rated their involvement in decision-making processes (d = .4, p < .01) and clarity of communication (d = .4, p = .02) lower than employees of color, although employees of color rated supervisory support for the quality of work lower (d = .3, p = .063). Clinical employees rated decision-making process involvement (d = .3, p = .09) and job fairness (d = .3, p = .10) lower than non-clinical employees. Employees who were not married rated job fairness lower (d = .3, p = .06) and perceived that their degree paid off less (d = .3, p =.10) than married employees. Employees with a Bachelor’s degree or below perceived that their degree paid off (d = .3, p =.07) less and reported less stress (d = .3, p =.09) than employees with a Master’s degree or higher. Non-exempt employees perceived that their degree paid off (d = .3, p =.09) less than exempt employees. Age or previous work years were not associated with the job wellbeing indicators.

Conclusion and Implications

Our study suggested varying responses to the job wellbeing indicators based on employees’ demographics and job characteristics. The key variables include employee race, marital status, educational degree, exempt status, and clinical position. Efforts to understand varying job wellbeing characteristics among diverse employees in their local contexts may eventually help develop organization-tailored interventions to improve job wellbeing and reduce turnover. As social workers are the backbone of the behavioral health care systems, the current study has critical implications for social workers.