The mediating role of social support in the relationship between physician burnout and professionalism behaviors. Issue 12 (December 2021) - Song, Xinzhi; Li, Honghe; Jiang, Nan; Song, Wenwen; Ding, Ning; Wen, Deliang
Abstract: Objective: Burnout poses as an understudied challenge to professionalism, and social support may explain their relationship. We sought to investigate the role of social support (moderating or mediating) in the association between physician burnout and professionalism (with four behavioral domains: respect, integrity, excellence, responsibility). Methods: We invited 4100 physicians from nine tertiary hospitals in Liaoning province, China, during February 2017, to participate in a cross-sectional survey. Professionalism, burnout, and social support were respectively assessed using three standardized tools. Descriptive statistics, multivariable linear regression, and ordinal logistic regression were used to analyze the data. Results: 3506 physicians (85.5%) effectively completed the survey. After controlling for potential confounding factors, burnout was associated with lower professionalism (β = −0.65, SE = 0.07), particularly in respect (OR = 0.51, 95%CI: 0.41–0.64) and responsibility (OR=0.72, 95%CI: 0.57–0.90). However, there was no statistically significant association between burnout and integrity or excellence. Social support was associated with higher professionalism ((β = 0.24, SE = 0.02) and all of its behavioral domains and played a partial mediating effect on the association between burnout and professionalism. Conclusion: Social support partially mediates the relationship between physician burnout and behavior-based professionalism. Practice implications: Addressing burnout and promoting social support could be integral in fostering physician professionalism in the healthcare setting. Highlights: Elaborating the relationship between burnout and specific domains of professionalism. Clarifying the mediating role of social support in burnout and professionalism. Boasting a large sample size from physicians of different specializations. Using two regression models to ensure accuracy and consistency of results.