ArticleFrontiers in psychiatry2022
Mapping network connectivity between internet addiction and residual depressive symptoms in patients with depression.
Article in Frontiers in psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 17 citations in OpenAlex.
- Cross-Lagged Panel Network Analysis Between Internet Addiction and Depression: Gender and Mid-Late Adolescent Differences.Child psychiatry and human development · 2026Article
- The relationship among short-form video addiction, self-control, and emotional symptoms in college students: a network analysis.BMC public health · 2026Article
- Network analysis of comorbid internet addiction, anxiety, and depression symptoms among Chinese junior high school students.Frontiers in public health · 2026Article
- The temporal stability of core symptoms of social media addiction and their comorbidity with anxiety and depression in adolescents: a longitudinal network analysis.Frontiers in psychiatry · 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
- A Narrative Inquiry Into Problematic Internet Use Among Young Adults: A Narrative Review.Cureus · 2025Review
- Cross-cultural insights into internet addiction and mental health: a network analysis from China and Malawi.BMC public health · 2025Article
- Internet Addiction and Depressive Symptoms in University Students: Latent Profiles, Network Structure, and Symptomatic Pathways to Suicide Risk.Depression and anxiety · 2025Article
- 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
- Fear of disease in patients with epilepsy - a network analysis.Frontiers in neurology · 2024Article
- The Inter-Relationships Between Depressive Symptoms and Suicidality Among Macau Residents After the "Relatively Static Management" COVID-19 Strategy: A Perspective of Network Analysis.Neuropsychiatric disease and treatment · 2024Article
- The impact of internet adaptability on internet addiction: the serial mediation effect of meaning in life and anxiety.Frontiers in psychiatry · 2023Article
Corrections and comments
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Authors and funding
18 authors at 9 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and aims: Depression often triggers addictive behaviors such as Internet addiction. In this network analysis study, we assessed the association between Internet addiction and residual depressive symptoms in patients suffering from clinically stable recurrent depressive disorder (depression hereafter). Materials and methods: In total, 1,267 depressed patients were included. Internet addiction and residual depressive symptoms were measured using the Internet Addiction Test (IAT) and the two-item Patient Health Questionnaire (PHQ-2), respectively. Central symptoms and bridge symptoms were identified via centrality indices. Network stability was examined using the case-dropping procedure. Results: The prevalence of IA within this sample was 27.2% (95% CI: 24.7-29.6%) based on the IAT cutoff of 50. IAT15 ("Preoccupation with the Internet"), IAT13 ("Snap or act annoyed if bothered without being online") and IAT2 ("Neglect chores to spend more time online") were the most central nodes in the network model. Additionally, bridge symptoms included the node PHQ1 ("Anhedonia"), followed by PHQ2 ("Sad mood") and IAT3 ("Prefer the excitement online to the time with others"). There was no gender difference in the network structure. Conclusion: Both key central and bridge symptoms found in the network analysis could be potentially targeted in prevention and treatment for depressed patients with comorbid Internet addiction and residual depressive symptoms.
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