ArticleJournal of medical Internet research2022
Addiction Symptom Network of Young Internet Users: Network Analysis.
Article in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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25 citing papers in PubMed, 43 citations in OpenAlex.
- Dynamic Risk and Protective Factors of NSSI in Middle School Students: A Longitudinal Study.Actas espanolas de psiquiatria · 2026Article
- Exploring the Comorbidity Mechanism of Internet Addiction, Insomnia, Depression, and Suicidality Among Chinese College Students Through Network Analysis.Alpha psychiatry · 2026Article
- Non-linear association between cyberbullying victimization and Internet addiction in Chinese adolescents: a cross-sectional study.BMC public health · 2026Article
- Paternal emotional warmth buffers maternal rejection in adolescent NSSI: a network and Bayesian analysis.BMC psychology · 2026Article
- Experiences of internet addiction among junior college students in Taiwan: a qualitative descriptive phenomenological study.BMJ open · 2026Article
- [Bayesian network analysis of harsh parenting, experiential avoidance, and adolescent short video addiction risk].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2026Article
- Cross-lagged analysis of depression symptoms and internet addiction tendencies among first-year university students and the moderating effects of urban-rural background and sibling status.Frontiers in psychiatry · 2026Article
- Development and validation of a machine learning-based risk prediction model for non-suicidal self-injury in adolescents.Frontiers in psychiatry · 2026Article
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- The relationship between sport motivation and problematic social networking sites use among adolescents: a study integrating mediation modeling and network analysis.Frontiers in psychology · 2026Article
- Relationship between loneliness and academic procrastination with cyberspace addiction in single-parent adolescents' academic.Frontiers in psychology · 2026Article
- The prevalence of internet addiction and its association with quality of life among inflight security officers based on a national survey: a network analysis perspective.European archives of psychiatry and clinical neuroscience · 2025Article
- Perioperative symptoms in patients with thyroid cancer: a cross-sectional and longitudinal network analysis.BMC endocrine disorders · 2025Observational
- Longitudinal Network Relationships Between Symptoms of Deviant Peer Affiliation and Internet Gaming Disorder in Adolescents: Prospective Cohort Study.Journal of medical Internet research · 2025Article
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- Alteration in network centrality of psychopathology symptoms in public bus driver between the COVID-19 control policies unbundling.BMC psychiatry · 2025Observational
- The association between school bullying involvement and Internet addiction among Chinese Southeastern adolescents: a moderated mediation model with depression and smoking.Frontiers in psychiatry · 2025Article
- Problematic online behaviors and their early patterns of co-occurrence in young adults: insights from directed and undirected networks.Frontiers in psychiatry · 2025Article
- Network Analysis of Contemporaneous Symptoms and Identification of Core Symptoms in Patients with Lumbar Disc Herniation.Journal of pain research · 2025Article
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Authors and funding
10 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAn increasing number of people are becoming addicted to the internet as a result of overuse. The Internet Addiction Test (IAT) is a popular tool for evaluating internet use behaviors. The interaction between different symptoms and the relationship between IAT and clinical diagnostic criteria are not well understood.
objectiveThis study aimed to explore the core symptoms of internet addiction (IA) and the correlation between different symptoms of the IA symptom network. Network analysis was also conducted to explore the association between the IAT scale and the Diagnostic and Statistical Manual of Mental Disorders-5th edition (DSM-5) criteria for IA.
methodsWe recruited 4480 internet users (aged 14-24 years), and they completed the IAT. The final analysis included 63.50% (2845/4480) of the participants after screening the submitted questionnaires. Participants were classified into IA group and non-IA (NIA) group. By using partial correlation with Lasso regularization networks, we identified the core symptoms of IA in each group and compared the group differences in network properties (strength, closeness, and betweenness). Then, we analyzed the symptom networks of the DSM-5 diagnostic criteria and IAT scale for IA.
resultsA total of 12.47% (355/2845) of the patients were in the IA group and 87.52% (2490/2845) of the patients were in the NIA group, and both groups were evaluated for the following nodes: IAT_06 (school work suffers; strength=0.511), IAT_08 (job performance suffers; strength=0.531), IAT_15 (fantasize about being on the web; strength=0.474), IAT_17 (fail to stop being on the web; strength=0.526), and IAT_12 (fear about boredom if offline; strength=0.502). The IA groups had a stronger edge between IAT_09 (defensive or secretive about being on the web) and IAT_18 (hidden web time) than the NIA groups. The items in DSM-5 had a strong association with IAT_12 (weight=-0.066), IAT_15 (weight=-0.081), IAT_17 (weight=-0.106), IAT_09 (weight=-0.198), and IAT_18 (weight=-0.052).
conclusionsThe internet use symptom network of the IA group is significantly different from that of the NIA group. Nodes IAT_06 (school work affected) and IAT_08 (work performance affected) are the resulting symptoms affected by other symptoms, whereas nodes IAT_12 (fear about boredom if offline), IAT_17 (inability to stop being on the web), and IAT_15 (fantasize about being on the web) are key symptoms that activate other symptoms of IA and are strongly linked to the inability to control the intention to play games in the DSM-5.
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