Internet addiction among nursing students: application of latent profile analysis and network analysis

Background: Internet addiction is widely reported and heterogeneous among nursing students. However, variable-centered approaches may not fully capture profile differences and core symptom patterns, potentially limiting precise interventions. Therefore, identifying distinct profiles and key symptoms is important for informing effective prevention. Objective: This study aims to identify distinct internet addiction profiles among nursing students, explore the characteristics and core symptoms of these profiles, and investigate the factors associated with their variation. Methods: A cross-sectional survey was conducted among undergraduate nursing students from September to November 2025. Latent profile analysis (LPA) and network analysis were performed to characterize the patterns of problematic internet use across identified profiles. Result: Latent Profile Analysis revealed four distinct problematic internet use profiles: No-Problematic Internet Use Profile (17.895%), Low-Problematic Internet Use Profile (41.957%), Moderate-Problematic Internet Use Profile (26.676%), and High-Problematic Internet Use Profile (13.472%). Multinomial logistic regression identified gender, monthly household income, and physical activity as significant factors associated with profile membership. Network analysis highlighted central symptoms specific to each profile: Health-related problems (RP-IH) and compulsive internet use and withdrawal symptoms (Sym-C & Sym-W) exhibited the highest centrality within the Moderate- and High-Problematic Internet Use Profiles. Conclusion: Internet addiction among undergraduate nursing students is a heterogeneous phenomenon that can be categorized into four distinct profiles. Our findings clarify key associated factors and identify central symptoms specific to each profile, potentially providing an empirical basis for nursing educators to develop targeted psychological interventions.