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Network analysis of problematic internet use and its association with depressive and anxiety symptoms among adolescents: structural characteristics and group comparisons

Year: 2026
Type: article
Study design: Observational Study
Abstract: Background Problematic internet use (PIU) is a growing public health concern among adolescents, often co-occurring with depression and anxiety. This study aimed to (1) examine network structures of PIU and its association with depressive and anxiety symptoms; and (2) compare these networks across PIU severity levels and educational stages. Methods A total of 5,228 adolescents participated in the survey and were classified by PIU severity (PIU vs. non-problematic internet use, NPIU) and educational stage (primary vs. secondary school). Network analysis and network comparison test were performed to identify core and bridge symptoms and to assess group differences. Results Significant differences in the global network strength were observed across PIU severity levels and educational stages. Compared with the PIU group, the NPIU group showed higher global strength, while network structure and node centrality remained comparable. Across educational stages, secondary school students displayed higher global strength and a significantly different overall network structure compared with primary school students, whereas local connectivity and centrality estimates were largely similar. In the joint network with depression and anxiety, global network strength differed by PIU severity, and both overall network strength and structure differed by educational stage. Bridge symptoms connecting PIU with depression and anxiety were identified in both PIU and NPIU groups, and across primary and secondary school groups. Conclusions This study highlights developmental and severity-dependent patterns in PIU and its comorbidities, informing stage-specific and severity-adapted interventions. Clinical trial number Not applicable.
Language: English
Open Access status: gold
Estimated APC paid: $1,990
OpenAlex ID: W7203769437
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