JMIR Publications

ABSTRACT

Background:

There has been growing amount of evidence suggested the high rates of co-occurring Internet addiction (IA) symptoms and psychological distress in youths. However, the extent to how IA symptoms develop over time, how IA symptoms interact with psychological distress symptoms dynamically and how these symptoms predict each other remains unclear. Additionally, which specific distress including depressive, anxious, stress symptoms are more closely associated with IA symptoms remains inconclusive.

Objective:

This longitudinal study aims to explore the development and changes of IA symptoms over time and the directional relationship between IA and various psychological distress.

Methods:

This study followed a sample of 2,497 Chinese college students (M age = 19.14 years) across three waves of data collection span two years. Their IA and psychological distress symptoms were assessed at baseline (T1), 12-month follow-up (T2) and 24-month follow-up (T3). We employed network analysis to examine the network structure of IA symptoms at each wave, and cross-lagged panel network analysis (CLPN) to investigate longitudinal associations between IA symptoms and psychological distress including depressive, anxious and stress symptoms.

Results:

The cross-sectional networks of IA symptoms at three time points showed high similarity in terms of structure, existence of edges, and centrality indices. Nodes A2 (‘excessive use’), A1 (‘salience’), and A5 (‘lack of control’) emerged as the nodes with the highest expected influence centrality (EI) in the IA symptom networks across time (A2, EI=1.13 at T1, 1.15 at T2, 1.17 at T3; A1, EI=1.10 at T1, 1.13 at T2, 1.15 at T3; A5, EI=0.86 at T1, 0.88 at T2, 0.92 at T3). CLPN revealed that psychological distress predicted IA symptoms, but not the other way around. Depressive symptoms played a key role in predicting various IA-related problems (T1→T2, edge weight = 0.11; T2→T3, edge weight = 0.28; T1→T3, edge weight = 0.22), and may also serve as bridge symptoms connecting IA and psychological distress issues (T1→T2, Bridge-EI = 0.15; T2→T3, Bridge-EI = 0.14; T1→T3, Bridge-EI = 0.19).

Conclusions:

Findings revealed a relatively stable network structure of IA symptoms among college students and suggested that psychological distress, especially depressive symptoms, may play a central role in activating IA symptoms over time. These results provide evidence for understanding the directional relationship between the central characteristics of distress symptoms and IA. The current study also underscores the importance of depressive symptoms in their co-occurrence with IA, indicating that the key and bridge symptoms identified in this study can be prioritized as targets for preventing and treating IA in Chinese youth. Through identification and early intervention of depressive symptoms, we may avoid the progression of co-occurring issues, leading to more effective treatment outcomes.