Understanding emotional and health indicators underlying the burnout risk of healthcare workers

Background: Burnout of healthcare workers is of increasing concern as workload pressures mount. Burnout is usually conceptualised as resulting from external pressures rather than internal resilience and although is not a diagnosable condition, it is related to help seeking for its psychological sequelae. Objective: To understand how staff support services can intervene with staff heading for burnout, it is important to understand what other intrapsychic factors that are related to it. Methods: A diary tool was used by staff in a region of England to self monitor their wellbeing over time. The tool explores many areas of mental health and wellbeing and enabled regression analysis to predict which of the various factors predicted scores on the burnout item. Findings: Burnout can be best explained with independent variables including depression, receptiveness, mental wellbeing, and connectedness (p<0.05) using a multiple linear regression model. It was also shown that 71% of the variance present in the response variable, i.e. burnout, explained by independent variables. There is no evidence found for multicollinearity in our regression models confirmed by both the Spearman Rank Correlation and the Variance Inflation Factor methods. Conclusion: We showed how burnout can be explained using a handful number of factors including emotional and mental health indicators. Clinical implications: The findings suggest a simple set of items can predict burnout and could be used for screening. The data suggests attention to four factors around social safeness, grounding and care in the self, hope and meaning and having sufficient energy could form the basis of attention in weelbeing programs.