Bridging symptoms between problematic social networking and generalized anxiety in adolescents with non-suicidal self-injury: a network analysis

Abstract

Background: Problematic social networking site use (PSNSU) may arise as a coping response to generalized anxiety and, in turn, intensify anxiety symptoms, creating a bidirectional cycle that poses increased risks for non-suicidal self-injury (NSSI) among adolescents. However, the symptom-level mechanisms underlying these intertwined associations remain unclear. To address this gap, the present study applied a symptom network analysis approach to examine. Methods: A total of 5,938 adolescents in Guangxi Province, China, completed an e-questionnaire and validated measures of generalized anxiety, social networking site addictive tendencies, and NSSI. Related to the aim of the current study, 1,544 participants who reported engaging in NSSI were included in the final data analysis, corresponding to a prevalence rate of 26.0% (age mean ± sd= 18.95 ± 0.90, 22.73% male). Bridge and flow network analyses were estimated using graphical LASSO models with extended Bayesian information criterion selection. Robustness was examined with nonparametric bootstrapping and case-dropping stability (CS-C). Sensitivity analyses controlled for age and gender. Results: Within the generalized anxiety network, the strongest edge was between uncontrollable worry and excessive worry (edge weight = 0.27). Within the PSNSU network, the most robust edge-linked online relationship satisfaction and virtual friend anxiety (edge weight = 0.35). Cross-community associations indicated irritability was the strongest positive association with social network addiction (edge weight = 0.07). Bridge centrality analysis identified dual existence (Z score = 2.47 and above 1) as the key bridge node. Flow network analysis showed that restlessness, irritability, feeling afraid, online relationship satisfaction, and virtual friend anxiety were the only symptoms directly associated with NSSI (edge weight = 0.04, 0.01, 0.03, 0.003, and 0.02, respectively). The network demonstrated strong stability (CS-C = 0.75), and structural consistency was observed after adjusting for covariates, such as age and gender (r ≥ 0.99, p