| Sumario: | Objective: The prevalence of COVID-19-related posttraumatic stress disorder (PTSD), depression, and insomnia remains high in Chinese adolescents. Existing research suggests strong links between them and the influence of internet addiction (IA) on their development. This study therefore examined a longitudinal network of these psychological symptoms and explored the influence of IA on them. Method: Analyses included 811 adolescents (Mage = 14.65, SD = 1.77, 44.2% female), and measures were taken at two time points 2 months apart. A cross-lagged panel network model was used to construct a common network of PTSD symptoms, depressive symptoms, and insomnia to estimate the longitudinal relationship between symptoms. Furthermore, networks of subgroups with different IA levels were compared. Results: Suicidal ideation at T1 had the strongest predictive effect on other symptoms at T2. Insomnia had the strongest bridging effect, sustaining the coactivation of depression and PTSD symptoms. The similarity between symptom networks across different IA groups was low. However, hyperarousal was strongly predicted by other symptoms in both high and low-level IA groups, respectively. Conclusions: Findings emphasize the important roles of suicidal ideation and insomnia in the network of PTSD symptoms, depressive symptoms, and insomnia in adolescents. This may make these symptoms a priority to be considered in interventions. Among adolescents with different levels of IA, the most central symptom varies, suggesting that intervention priorities should vary in groups with different levels of IA. Clinical Impact Statement: The results of the present study emphasize the possible influence of suicidal ideation on other symptoms in the network of posttraumatic stress disorder, insomnia, and depressive symptoms, as well as the possible role of insomnia in triggering comorbidities. These findings suggest key targets when intervening in related disorders. In addition, network analyses of different internet addiction groups implied that there may be different optimal targets for intervention in groups with different levels of internet addiction.
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