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<p>The co-occurrence of Internet addiction (IA) and depression is increasingly common among college students. However, the symptom-level comorbidity mechanism between IA and depression remains unclear. This study aims to apply the network approach to explore how IA and depression are related across symptoms. Data were collected from 795 Chinese college students (55.5% female, mean age = 20.93 ± 1.69, ranging from 18 to 26) via an online questionnaire. IA and depression were assessed by the 12-item Internet Addiction Test and the 13-item Beck Depression Inventory scales. 245 participants were divided into the comorbidity group by cutoff scores of the scales. Using R software, the regularized partial correlation network (RPCN) and the directed acyclic graph (DAG) were estimated. Findings indicated that IA symptoms “withdrawal symptoms” and “annoyed if bothered” together with depression symptoms “worthlessness” and “feeling the failure” played key roles in connecting other symptoms in the RPCN, and in the DAG these symptoms were more likely to activate other symptoms. In addition, “annoyed if bothered” and “reduced involvement with others” of IA symptoms and “tiredness” and “loss of interest” of depression symptoms acted as bridges connecting IA and depression in the RPCN, and the directions between these symptoms was from IA to depression in the DAG. The present study extends the application of combining undirected and directed networks in the filed of psychopathology and provides an in-depth understanding and potential intervention targets for the IA and depression comorbidity.</p>

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How does internet addiction interact with depression at the symptom level? a joint perspective of undirected and directed networks

  • 期刊论文

  • 发表日期：

    2025年6月26日

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  • Yue Zhao,
  • Diyang Qu,
  • Xiaoqi Wei,
  • Xinli Chi

摘要

The co-occurrence of Internet addiction (IA) and depression is increasingly common among college students. However, the symptom-level comorbidity mechanism between IA and depression remains unclear. This study aims to apply the network approach to explore how IA and depression are related across symptoms. Data were collected from 795 Chinese college students (55.5% female, mean age = 20.93 ± 1.69, ranging from 18 to 26) via an online questionnaire. IA and depression were assessed by the 12-item Internet Addiction Test and the 13-item Beck Depression Inventory scales. 245 participants were divided into the comorbidity group by cutoff scores of the scales. Using R software, the regularized partial correlation network (RPCN) and the directed acyclic graph (DAG) were estimated. Findings indicated that IA symptoms “withdrawal symptoms” and “annoyed if bothered” together with depression symptoms “worthlessness” and “feeling the failure” played key roles in connecting other symptoms in the RPCN, and in the DAG these symptoms were more likely to activate other symptoms. In addition, “annoyed if bothered” and “reduced involvement with others” of IA symptoms and “tiredness” and “loss of interest” of depression symptoms acted as bridges connecting IA and depression in the RPCN, and the directions between these symptoms was from IA to depression in the DAG. The present study extends the application of combining undirected and directed networks in the filed of psychopathology and provides an in-depth understanding and potential intervention targets for the IA and depression comorbidity.