社交网络(社会语言学)
心理学
社会网络分析
互联网隐私
计算机科学
互联网
移动设备
智能手机应用
领域(数学)
数据收集
应用心理学
社会心理学
统计分析
社会支持
计算机安全
社会关系
透视图(图形)
网络分析
作者
Min-Fang Kang,Yue Pan,Li Zhu,Kai-Mo Ding,Jun Zhu,Bei Zhao,Guo-Hai Li,Dan-Wei Zhang,Xian-Lu Chang,Hui Zheng,Qiang Hu,Ziliang Wang
标识
DOI:10.1016/j.chbr.2026.101166
摘要
Background and aims The multifaceted nature of problematic online behaviors (POBs) among adolescents presents a significant clinical challenge, yet their underlying constructs and developmental pathways remain unclear. This study proposes the Conditioned Hierarchical Transition Model (CHTM) and provides an initial longitudinal test of one core directional premise: whether baseline content-specific POB symptoms prospectively predict later generalized, medium-based POBs (e.g., problematic smartphone use, PSU). Methods A two-wave, one-year longitudinal study was conducted with 2,188 Chinese adolescents ( M age = 16.46, SD = 0.88; 57.3% female) who completed measures of PSU, POGU and PSNU. We employed cross-lagged panel network analysis to estimate the directed temporal network of symptoms and used network comparison tests to examine sex differences. Results Results revealed a clear directional pathway from content-specific POBs to generalized PSU. Tolerance and withdrawal from POGU and loss of control over PSNU emerged as key driving symptoms. Conversely, PSU's own tolerance and withdrawal symptoms were the primary vulnerable symptoms. While initiating pathways were sex-specific—driven by externalizing factors (e.g., concealment) in males and internalizing factors (e.g., mood regulation) in females—both converged on generalized PSU. Conclusions Our findings provide preliminary longitudinal and symptom-level support for a core premise of the Conditioned Hierarchical Transition Model, wherein specific content dependencies evolve into a generalized dependency on the smartphone. This model empirically reconciles the long-standing "content vs. medium" debate in behavioral addiction. Identifying the driving symptoms and sex-specific pathways can inform precise, mechanism-based interventions to support adolescent digital well-being.
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