Exploring the interrelationships between athlete burnout, depression, and anxiety: a network analysis approach

BackgroundAthlete burnout frequently co-occurs with depression and anxiety, yet prior studies relying on total scores obscure how individual symptoms interact across these constructs.ObjectiveTo identify central and bridge symptoms linking athlete burnout, depression, and anxiety using network analysis.MethodsA total of 1,226 Chinese collegiate athletes (637 male, 589 female; Mage = 18.11, SD = 1.39) completed the ABQ-15, PHQ-9, and GAD-7. A regularized partial-correlation network was estimated with the EBIC-LASSO; expected influence (EI) and bridge expected influence (bEI) indexed centrality.ResultsGAD-2 (uncontrollable worry; EI = 1.07), PHQ-2 (depressed mood; EI = 1.22), and ABQ-E8 (physical exhaustion; EI = 1.11) were the most central nodes. PHQ-3 (sleep disturbance; bEI = 0.47) emerged as the strongest bridge across the three clusters. The strongest edges connected ABQ-E8, PHQ-4 (fatigue; r = 0.37) and ABQ-E2 (training fatigue), PHQ-1 (anhedonia; r = 0.29).ConclusionGAD-2, PHQ-2, and ABQ-E8 exhibited high centrality and represent key intervention targets for reducing the overall symptomatology of burnout, depression, anxiety comorbidity in athletes, and should therefore be prioritized; PHQ-3, as the strongest bridge symptom connecting the three clusters, represents a target whose treatment may interrupt the transdiagnostic symptom-transmission pathways that maintain the comorbidity. These clearly defined intervention targets also facilitate the development of a brief, multi-symptom screening tool tailored to athlete populations.