Miles for Mental Health

Conditions: Generalized Anxiety Disorder (GAD); Depressive and Anxiety Disorders

Interventions: Behavioral: Exercise

Sponsors: Emporia State University; National Institute of General Medical Sciences (NIGMS)

Not yet recruiting

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

BackgroundInternet 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.ObjectiveThis 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.MethodsA 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.ResultLatent 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.ConclusionInternet 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.

Shinya Yamanaka

Dr. Shinya Yamanaka is recognized for the generation of induced pluripotent stem cells (iPSCs) from fibroblasts by a combination of multiple transcription factors, and he won the Nobel Prize in Physiology or Medicine in 2012 jointly with Sir John B. Gurdon for this discovery. Twenty years after the discovery, the Cell Reports Medicine editorial team discusses with Dr. Yamanaka the scientific, technical, and translational milestones that have shaped the field of regenerative medicine. We also discuss the role of iPSCs in disease modeling and drug discovery, the interplay with genome editing, and ongoing issues that still prevent the widespread clinical application of iPSC-derived therapies.