ArticleBehavioral sciences (Basel, Switzerland)2023
The Impact of Long-Term Online Learning on Internet Addiction Symptoms among Depressed Secondary School Students: Insights from a Cross-Panel Network Analysis.
Article in Behavioral sciences (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 15 citations in OpenAlex.
- A scoping review of internet addiction and academic performance among health sciences students.BMC psychology · 2026Article
- Article
- Longitudinal Associations Between Depression Symptoms and Cognitive Functions in Chinese Older Adults: A Cross-Lagged Panel Network Analysis.Depression and anxiety · 2025Article
- A longitudinal network analysis of interaction factors among Chinese women at high risk for perinatal depression.Midwifery · 2024Article
- The association between online learning, perceived parental relationship, anxiety, and depression symptoms among secondary school students: insight from symptom network and cross-lagged panel network approach.BMC public health · 2024Article
- The impact of long-term online learning on social anxiety and problematic smartphone use symptoms among secondary school students with different levels of fear of missing out: Evidence from a symptom network and longitudinal panel network analysis.Journal of behavioral addictions · 2024Article
- A bibliometric analysis of mental health among high school students.Frontiers in psychiatry · 2024Article
- The interrelationship between sleep disturbance symptoms and aggression before and after the campus closure of the COVID-19 pandemic: insight from a cross-lagged panel network model.Frontiers in public health · 2024Article
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe COVID-19 pandemic and the shift to online learning have increased the risk of Internet addiction (IA) among adolescents, especially those who are depressed. This study aims to identify the core symptoms of IA among depressed adolescents using a cross-lagged panel network framework, offering a fresh perspective on understanding the interconnectedness of IA symptoms.
methodsParticipants completed the Internet addiction test and the Patient Health Questionnaire-9. A total of 2415 students were initially included, and after matching, only 342 students (a cutoff score of 8) were retained for the final data analysis. A cross-lagged panel network analysis was conducted to examine the autoregressive and cross-lagged trajectories of IA symptoms over time.
resultsThe incidence rate of depression rose remarkably from 14.16% (N = 342) to 17.64% (N = 426) after the four-month online learning. The symptom of "Anticipation" exhibited the highest out-expected influence within the IA network, followed by "Stay online longer" and "Job performance or productivity suffer". Regarding the symptom network of depression, "Job performance or productivity suffer" had the highest in-expected influence, followed by "Life boring and empty", "Snap or act annoyed if bothered", "Check email/SNS before doing things", and "School grades suffer". No significant differences were found in global network strength and network structure between waves 1 and 2.
conclusionThese findings prove the negative effects of online learning on secondary students' mental health and have important implications for developing more effective interventions and policies to mitigate IA levels among depressed adolescents undergoing online learning.
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