Objective: The aim of the study was to present first representative data on burnout measured as exhaustion in German employees.
Methods: Data were taken from the Study on Mental Health at Work (n = 4058). Computer-assisted personal interviews were conducted in 2011 to 2012. Multiple linear regression models were estimated to investigate the association between work-related and personal variables and burnout.
Results: Severe burnout was detected in nearly 3% of employees. Job demands were associated with higher burnout scores, more resources with lower scores. Independent of personal factors, higher quantitative demands (men: regression coefficient [β] = 0.19; 95% confidence interval [CI], 0.16 to 0.23; women: β = 0.24; 95% CI, 0.20 to 0.27) was identified as the strongest predictor of burnout measured as exhaustion. The model explained 28% to 33% of the total variance.
Conclusions: Quantitative demands seem to be important risk factors for burnout independent of critical life events and general self-efficacy.