Exploring Predictive Factors of Burnout Among Low-Wage Healthcare Workers

Abstract

Burnout among healthcare workers (HCWs) has reached a crisis point within the U.S. healthcare system. Low-wage HCWs, such as nursing assistants, remain at the forefront of vulnerable healthcare populations. However, much of the current literature on burnout focuses on physicians and nurses, omitting perhaps the most vulnerable healthcare workers. Therefore, this study will further investigate the factors associated with burnout among low-wage HCWs. The results of this study aim to help us answer which specific areas need to be addressed to prevent burnout and its associated harmful effects. This research is a cross-sectional study. Healthcare support workers (HSWs) at Ohio State University Wexner Medical Center, including patient care associates or nursing assistants who earn low wages were recruited to complete an online survey covering social determinants of health, demographics, and burnout. We conducted descriptive statistics and logistic regression analyses to examine the associations between demographic and organizational factors and burnout. In total, we included 288 responses in the analysis. Over half of the sample was under the age of 29 (n=163, 56.60%), mostly female (n=227, 80.21%), and had an annual household income less than $80,0000 (n=221, 76.74%). More than 50% of respondents reported experiencing burnout (n = 152, 51.15%), and over a third of participants reported that their organization did not appreciate those in their position (n = 108, 36.61%). Being a male, having pain, a younger age, and a lower household income were significantly associated with higher rates of burnout. Being black/African American had a statistically significant association with lower rates of burnout. The results of this study showed that HSWs experience a high rate of burnout due to multiple personal factors. Healthcare organizations must develop a better understanding of the factors associated with burnout to implement effective prevention strategies for at-risk populations. Furthermore, predictive and protective factors should be distinguished to identify specific organizational opportunities to reduce burnout rates among HSWs