Network Analysis of Anxiety and Depression Symptoms in Help-Seeking Youth: A Two-Wave Study

Anxiety and depression often co-occur in youth, but the symptom-level processes driving this comorbidity remain unclear. Network theory conceptualizes mental disorders as systems of interacting symptoms. We applied a two-wave longitudinal network approach to examine depression and anxiety symptoms comorbidity in help-seeking youth (N = 836, aged 10-24).

Depression and anxiety were measured using the Zung Self-Rating Depression Scale and Zung Self-Rating Anxiety Scale respectively. We estimated Gaussian graphical models at baseline (T1) and follow-up (T2, 3-12 months later), and used a Cross-Lagged Panel Network (CLPN) model to assess predictive relations between symptoms across time.

Results revealed that symptom networks tightened even as symptoms decreased; feelings of uselessness and panic were central symptoms at both time points, poor sleep consistently served as the pivotal bridge between anxiety and depression at both baseline and follow-up, while crying spells and stomach pain emerged as early drivers of wider symptom spread.

These results suggest that intervening on these symptoms may disrupt anxiety-depression cycles. This study supports the use of network models to identify targets for early intervention in youth mental health.