Background <p>The comorbidity mechanisms between ADHD symptoms and Internet addiction are not yet clear, and network analysis provides a new perspective for clarifying this research question.</p> Aim <p>Therefore, this study employed a cross-lagged panel network model to examine how specific symptom levels of ADHD and Internet addiction interact.</p> Method <p>A total of 732 Chinese adolescents (55.6% girls, <i>M</i>age = 13.95 years, <i>SD</i> = 1.55) completed assessments at three time points spaced six months apart. </p> Results <p>Between 4.51 and 6.83% of participants showed severe Internet issues, and 8.06–9.97% fell into the ADHD abnormal range across the three time points. The results of the contemporaneous network indicated that the bridge symptom at all three-time points was “Inattention”. The results of the temporal network showed: (1) the core symptoms responsible for the comorbidity mostly belong to ADHD symptoms; (2) the comorbidity mechanisms change over time, with the most predictive bridge symptom being “Hyperactivity” in the T1 to T2 network, and changing to “Inattention” in the T2 to T3 network. In addition, “Excessive use” was the most vulnerable symptom.</p> Conclusion <p>These findings suggest that hyperactivity in early adolescence and inattention at later stages may serve as temporal risk indicators for Internet addiction, and that interventions targeting these symptoms could be worthy of further investigation.</p>

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Longitudinal relationships between ADHD symptoms and internet addiction among Chinese adolescents: a cross-lagged panel network analysis

  • Xiang Niu,
  • Yu-Xin Xie,
  • Li-Xing Gou,
  • Zheng-Ling Jing,
  • Jian-Jun Huang,
  • Hai-Zhen Wang,
  • Jin-Liang Wang

摘要

Background

The comorbidity mechanisms between ADHD symptoms and Internet addiction are not yet clear, and network analysis provides a new perspective for clarifying this research question.

Aim

Therefore, this study employed a cross-lagged panel network model to examine how specific symptom levels of ADHD and Internet addiction interact.

Method

A total of 732 Chinese adolescents (55.6% girls, Mage = 13.95 years, SD = 1.55) completed assessments at three time points spaced six months apart.

Results

Between 4.51 and 6.83% of participants showed severe Internet issues, and 8.06–9.97% fell into the ADHD abnormal range across the three time points. The results of the contemporaneous network indicated that the bridge symptom at all three-time points was “Inattention”. The results of the temporal network showed: (1) the core symptoms responsible for the comorbidity mostly belong to ADHD symptoms; (2) the comorbidity mechanisms change over time, with the most predictive bridge symptom being “Hyperactivity” in the T1 to T2 network, and changing to “Inattention” in the T2 to T3 network. In addition, “Excessive use” was the most vulnerable symptom.

Conclusion

These findings suggest that hyperactivity in early adolescence and inattention at later stages may serve as temporal risk indicators for Internet addiction, and that interventions targeting these symptoms could be worthy of further investigation.