Huayu Li, Hongyuan Lv, Jiahui Zhang, Yu Fu, Jianpeng Zhang, Hongmei Wang
Interventions focused on improving self-regulation and addressing sleep problems should be prioritized to help reduce internet addiction, insomnia, depression, and suicidality in this population.
BACKGROUND: Internet addiction is prevalent among college students and is linked to adverse mental health outcomes such as insomnia, depression, and suicidality. However, the variability in internet addiction patterns among college students and its connection to mental disorders remains insufficiently explored. This study examined the comorbidity network of internet addiction, insomnia, depression, and suicidality in Chinese college students through latent profile analysis (LPA) and network analysis (NA).
METHODS: Data from 3127 Chinese college students were collected using the Internet Addiction Test (IAT), Insomnia Severity Index (ISI), Patient Health Questionnaire-9 (PHQ-9), and Suicidal Behavior Questionnaire-Revised (SBQ-R). LPA was applied to identify subgroups with similar internet addiction profiles. NA was conducted among addicted users to map symptom associations, and network comparison tests (NCT) were used to evaluate subgroup differences.
RESULTS: Three distinct user profiles emerged: regular users, moderate users, and addicted users. NA revealed that the central symptom of internet addiction was "lack of self-control when online". Furthermore, "trouble sleeping", "frequency of suicidal ideation over the past year" and "sleep maintenance (middle)" were identified as bridge symptoms, connecting insomnia, depression, and suicidality with internet addiction. NCT indicated no significant gender differences in overall network strength.
CONCLUSIONS: Interventions focused on improving self-regulation and addressing sleep problems should be prioritized to help reduce internet addiction, insomnia, depression, and suicidality in this population.