The Longitudinal Effect of Psychological Distress on Internet Addiction Symptoms Among Chinese College Students: Cross-Lagged Panel Network Analysis
BackgroundThere is a growing amount of evidence suggesting high rates of co-occurring internet addiction (IA) symptoms and psychological distress in youth. However, the extent to which IA symptoms develop over time, how they interact with psychological distress symptoms dynam...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2025-05-01
|
| Series: | Journal of Medical Internet Research |
| Online Access: | https://www.jmir.org/2025/1/e70680 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850195073896022016 |
|---|---|
| author | Yuxuan Jiang Chuman Xiao Xiang Wang Dongling Yuan Qian Liu Yan Han Jie Fan Xiongzhao Zhu |
| author_facet | Yuxuan Jiang Chuman Xiao Xiang Wang Dongling Yuan Qian Liu Yan Han Jie Fan Xiongzhao Zhu |
| author_sort | Yuxuan Jiang |
| collection | DOAJ |
| description |
BackgroundThere is a growing amount of evidence suggesting high rates of co-occurring internet addiction (IA) symptoms and psychological distress in youth. However, the extent to which IA symptoms develop over time, how they interact with psychological distress symptoms dynamically, and how they predict one another remain unclear. Additionally, what specific types of distress, including depression, anxiety, and stress, are more closely associated with IA symptoms remains inconclusive.
ObjectiveThis longitudinal study aimed to explore the development of and changes in IA symptoms over time and the directional relationship between IA and various psychological distress symptoms.
MethodsThis study followed a sample of 2497 Chinese college students (mean age 19.14, SD 0.72 years) across 3 waves of a data collection span of 2 years. Their IA and psychological distress symptoms were assessed at baseline (T1), 12-month follow-up (T2), and 24-month follow-up (T3). We used network analysis to examine the network structure of IA symptoms at each wave and cross-lagged panel network (CLPN) analysis to investigate longitudinal associations between IA symptoms and psychological distress, including depressive, anxiety, and stress symptoms.
ResultsThe cross-sectional networks of IA symptoms at 3 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 nodes with the highest expected influence (EI) centrality 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 analysis revealed that psychological distress predicts IA symptoms but not the other way around. Depressive symptoms played a key role in predicting various IA-related problems (T1 to T2, edge weight=0.11; T2 to T3, edge weight=0.28; T1 to T3, edge weight=0.22) and served as bridge symptoms connecting IA and psychological distress (T1 to T2: bridge–expected influence [BEI]=0.15; T2 to T3: BEI=0.14; T1 to T3: BEI=0.19).
ConclusionsFindings 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 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. |
| format | Article |
| id | doaj-art-0ad8be92a1b7440b90750b2bd2a8e72b |
| institution | OA Journals |
| issn | 1438-8871 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | Journal of Medical Internet Research |
| spelling | doaj-art-0ad8be92a1b7440b90750b2bd2a8e72b2025-08-20T02:13:51ZengJMIR PublicationsJournal of Medical Internet Research1438-88712025-05-0127e7068010.2196/70680The Longitudinal Effect of Psychological Distress on Internet Addiction Symptoms Among Chinese College Students: Cross-Lagged Panel Network AnalysisYuxuan Jianghttps://orcid.org/0009-0001-5978-7560Chuman Xiaohttps://orcid.org/0009-0001-9666-5001Xiang Wanghttps://orcid.org/0000-0003-0994-8124Dongling Yuanhttps://orcid.org/0009-0005-1715-123XQian Liuhttps://orcid.org/0009-0005-1824-7970Yan Hanhttps://orcid.org/0000-0001-5371-5884Jie Fanhttps://orcid.org/0009-0000-7598-6095Xiongzhao Zhuhttps://orcid.org/0000-0002-7573-0740 BackgroundThere is a growing amount of evidence suggesting high rates of co-occurring internet addiction (IA) symptoms and psychological distress in youth. However, the extent to which IA symptoms develop over time, how they interact with psychological distress symptoms dynamically, and how they predict one another remain unclear. Additionally, what specific types of distress, including depression, anxiety, and stress, are more closely associated with IA symptoms remains inconclusive. ObjectiveThis longitudinal study aimed to explore the development of and changes in IA symptoms over time and the directional relationship between IA and various psychological distress symptoms. MethodsThis study followed a sample of 2497 Chinese college students (mean age 19.14, SD 0.72 years) across 3 waves of a data collection span of 2 years. Their IA and psychological distress symptoms were assessed at baseline (T1), 12-month follow-up (T2), and 24-month follow-up (T3). We used network analysis to examine the network structure of IA symptoms at each wave and cross-lagged panel network (CLPN) analysis to investigate longitudinal associations between IA symptoms and psychological distress, including depressive, anxiety, and stress symptoms. ResultsThe cross-sectional networks of IA symptoms at 3 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 nodes with the highest expected influence (EI) centrality 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 analysis revealed that psychological distress predicts IA symptoms but not the other way around. Depressive symptoms played a key role in predicting various IA-related problems (T1 to T2, edge weight=0.11; T2 to T3, edge weight=0.28; T1 to T3, edge weight=0.22) and served as bridge symptoms connecting IA and psychological distress (T1 to T2: bridge–expected influence [BEI]=0.15; T2 to T3: BEI=0.14; T1 to T3: BEI=0.19). ConclusionsFindings 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 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.https://www.jmir.org/2025/1/e70680 |
| spellingShingle | Yuxuan Jiang Chuman Xiao Xiang Wang Dongling Yuan Qian Liu Yan Han Jie Fan Xiongzhao Zhu The Longitudinal Effect of Psychological Distress on Internet Addiction Symptoms Among Chinese College Students: Cross-Lagged Panel Network Analysis Journal of Medical Internet Research |
| title | The Longitudinal Effect of Psychological Distress on Internet Addiction Symptoms Among Chinese College Students: Cross-Lagged Panel Network Analysis |
| title_full | The Longitudinal Effect of Psychological Distress on Internet Addiction Symptoms Among Chinese College Students: Cross-Lagged Panel Network Analysis |
| title_fullStr | The Longitudinal Effect of Psychological Distress on Internet Addiction Symptoms Among Chinese College Students: Cross-Lagged Panel Network Analysis |
| title_full_unstemmed | The Longitudinal Effect of Psychological Distress on Internet Addiction Symptoms Among Chinese College Students: Cross-Lagged Panel Network Analysis |
| title_short | The Longitudinal Effect of Psychological Distress on Internet Addiction Symptoms Among Chinese College Students: Cross-Lagged Panel Network Analysis |
| title_sort | longitudinal effect of psychological distress on internet addiction symptoms among chinese college students cross lagged panel network analysis |
| url | https://www.jmir.org/2025/1/e70680 |
| work_keys_str_mv | AT yuxuanjiang thelongitudinaleffectofpsychologicaldistressoninternetaddictionsymptomsamongchinesecollegestudentscrosslaggedpanelnetworkanalysis AT chumanxiao thelongitudinaleffectofpsychologicaldistressoninternetaddictionsymptomsamongchinesecollegestudentscrosslaggedpanelnetworkanalysis AT xiangwang thelongitudinaleffectofpsychologicaldistressoninternetaddictionsymptomsamongchinesecollegestudentscrosslaggedpanelnetworkanalysis AT donglingyuan thelongitudinaleffectofpsychologicaldistressoninternetaddictionsymptomsamongchinesecollegestudentscrosslaggedpanelnetworkanalysis AT qianliu thelongitudinaleffectofpsychologicaldistressoninternetaddictionsymptomsamongchinesecollegestudentscrosslaggedpanelnetworkanalysis AT yanhan thelongitudinaleffectofpsychologicaldistressoninternetaddictionsymptomsamongchinesecollegestudentscrosslaggedpanelnetworkanalysis AT jiefan thelongitudinaleffectofpsychologicaldistressoninternetaddictionsymptomsamongchinesecollegestudentscrosslaggedpanelnetworkanalysis AT xiongzhaozhu thelongitudinaleffectofpsychologicaldistressoninternetaddictionsymptomsamongchinesecollegestudentscrosslaggedpanelnetworkanalysis AT yuxuanjiang longitudinaleffectofpsychologicaldistressoninternetaddictionsymptomsamongchinesecollegestudentscrosslaggedpanelnetworkanalysis AT chumanxiao longitudinaleffectofpsychologicaldistressoninternetaddictionsymptomsamongchinesecollegestudentscrosslaggedpanelnetworkanalysis AT xiangwang longitudinaleffectofpsychologicaldistressoninternetaddictionsymptomsamongchinesecollegestudentscrosslaggedpanelnetworkanalysis AT donglingyuan longitudinaleffectofpsychologicaldistressoninternetaddictionsymptomsamongchinesecollegestudentscrosslaggedpanelnetworkanalysis AT qianliu longitudinaleffectofpsychologicaldistressoninternetaddictionsymptomsamongchinesecollegestudentscrosslaggedpanelnetworkanalysis AT yanhan longitudinaleffectofpsychologicaldistressoninternetaddictionsymptomsamongchinesecollegestudentscrosslaggedpanelnetworkanalysis AT jiefan longitudinaleffectofpsychologicaldistressoninternetaddictionsymptomsamongchinesecollegestudentscrosslaggedpanelnetworkanalysis AT xiongzhaozhu longitudinaleffectofpsychologicaldistressoninternetaddictionsymptomsamongchinesecollegestudentscrosslaggedpanelnetworkanalysis |