Burnout and Engagement Within Medical Education: A Repeated Measures Study on Their Evolution and Main Determinants

Abstract

Introduction: Burnout is a major concern in medical education and healthcare. Despite growing attention, little is known about how burnout and engagement evolve within the different phases of medical education or which factors shape these outcomes within each phase. This study assesses phase-specific trajectories of burnout and engagement and identifies the demands, resources, and personality traits associated with these outcomes. Methods: A prospective cohort study with three annual measurement waves was conducted among medical students and residents (n = 1.257) from all five universities in Flanders, Belgium. Three cohorts (i.e. bachelor students, master students, and residents) were followed for three consecutive years, using an open cohort design. Data were collected annually: at baseline (T0), after one year (T1), and after two years (T2). Linear mixed-effects models and cross-lagged panel analyses were used to examine temporal changes in burnout complaints and engagement; and to identify key demands, resources and personality traits within each cohort. Results: Within each cohort, burnout complaints increased gradually over time, while engagement declined. Within all learning phases, workload and work-home conflict were identified as primary demands, whereas meaningfulness was identified as the main resource, followed by learning opportunities. Neuroticism was positively associated with burnout complaints and negatively with engagement, while perfectionistic strivings correlated positively with engagement. Conclusion: This study demonstrates how burnout complaints and engagement evolve within learning phases in medical education and identifies key determinants underlying these trajectories. Efforts should prioritize reducing perceived workload and work–home conflict, while strengthening meaningfulness and learning opportunities. In addition, acknowledging individual personality traits may help tailor interventions.