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<p>Mobile phone addiction, academic achievement, and depression present intricate challenges among today’s adolescents. The prevalence of co-occurring issues, gender differences in these associations, adds complexity to treatment strategies. This study investigates the dynamic relationships within these factors using cross-lagged panel network analysis, a method that enables the identification of symptom-to-symptom pathways across time and provides greater insight than traditional variable-centered approaches. A school-based sample of 665 adolescents (47.4% girls, 52.6% boys;&#xa0;Mage = 13.35) completed measures at two time points, half a year apart. In the symptoms of mobile phone addiction, 'try to hide usage time' and 'influences school work,' academic subjects like ‘Moral and Law ’ and ‘English’ are recognized as the most predictive of subsequent issues for girls and boys, respectively, while the depression indicator ‘appetite’ is significant for both. Additionally, among girls, the primary cross-cluster edges were directed from depression (e.g., appetite) to mobile phone addiction (e.g., always check missed calls or messages). However, for boys, the cross-cluster edges are intricate, involving symptoms of mobile phone addiction (e.g., influences school work), academic achievement (e.g., Math), and depression (e.g., suicide), all of which may influence the emergence of other mental health issues. These findings reveal gender-specific patterns in the interplay among mobile phone addiction, academic achievement, and depression, underscoring that interventions should prioritize central symptoms and account for gender-specific pathways to improve both academic and mental health outcomes in adolescents.</p>

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Mobile Phone Addiction, Academic Achievement, and Depression in Adolescence: Gender-Specific Cross-Lagged Panel Network Models

  • 期刊论文

  • 发表日期：

    2026年1月7日

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  • Chao Song,
  • Danyuan Liu,
  • Hao Yuan,
  • Wenchao Wang

摘要

Mobile phone addiction, academic achievement, and depression present intricate challenges among today’s adolescents. The prevalence of co-occurring issues, gender differences in these associations, adds complexity to treatment strategies. This study investigates the dynamic relationships within these factors using cross-lagged panel network analysis, a method that enables the identification of symptom-to-symptom pathways across time and provides greater insight than traditional variable-centered approaches. A school-based sample of 665 adolescents (47.4% girls, 52.6% boys; Mage = 13.35) completed measures at two time points, half a year apart. In the symptoms of mobile phone addiction, 'try to hide usage time' and 'influences school work,' academic subjects like ‘Moral and Law ’ and ‘English’ are recognized as the most predictive of subsequent issues for girls and boys, respectively, while the depression indicator ‘appetite’ is significant for both. Additionally, among girls, the primary cross-cluster edges were directed from depression (e.g., appetite) to mobile phone addiction (e.g., always check missed calls or messages). However, for boys, the cross-cluster edges are intricate, involving symptoms of mobile phone addiction (e.g., influences school work), academic achievement (e.g., Math), and depression (e.g., suicide), all of which may influence the emergence of other mental health issues. These findings reveal gender-specific patterns in the interplay among mobile phone addiction, academic achievement, and depression, underscoring that interventions should prioritize central symptoms and account for gender-specific pathways to improve both academic and mental health outcomes in adolescents.