Disentangling Heterogeneity in the Co‐Developmental of Anxiety and Depression During the COVID‐19 Pandemic: Insights From Cross‐Lagged Panel Network

Background: Previous studies have indicated substantial variations in anxiety and depressive symptoms over the course of the COVID-19 pandemic. However, little is known about the comorbidity rates, heterogeneous co-developmental trajectories, and temporal network dynamics of these symptoms. Integrating person-centered and network psychopathology approaches, this study aimed to investigate the comorbidity rates and longitudinal network structures of anxiety and depressive symptoms across distinct co-developmental trajectories during the pandemic. Methods: A total of 35,516 college students completed three-wave surveys during the COVID-19 pandemic. Anxiety and depressive symptoms were assessed using the Generalized Anxiety Disorder-7-item and the 9-item Patient Health Questionnaire, respectively. Co-developmental trajectories were identified via a Parallel-Process Latent Growth Curve Model, and symptom networks were constructed using a cross-lagged panel network (CLPN). Results: Results showed that over 40% of individuals with depression also experienced anxiety across different pandemic phases. Three heterogeneous co-developmental trajectories were identified: a resistance group, a persistent growth group, and a chronic co-occurring group. The most influential symptoms-those exerting the strongest effect on subsequent symptoms-varied across the three networks. In the resistance group, "Anhedonia" was the most central symptom; in the persistent growth group, "Motor" exhibited the strongest predictive effect; and in the chronic co-occurring group, "Guilt" was the most influential symptom. Conclusions: These findings highlight the necessity of developing targeted and individualized interventions tailored to specific symptom dynamics in different youth subgroups to alleviate the overall symptom burden in future public health crises.