A Network Analysis of Smartphone Addiction, Depression, Anxiety, Fatigue, Sleep, and Learning Engagement in Nursing Students: A Cross-Sectional Study

Objectives: This study used psychological network analysis to examine the interrelationships among smartphone addiction, depression, anxiety, fatigue, sleep quality, and learning engagement in nursing students. Methods: A cross-sectional survey was conducted among 200 nursing students in South Korea using validated self-report instruments. Psychological network analysis was performed using the qgraph and bootnet packages in R. A non-regularized partial correlation network based on Spearman correlations was estimated, and bootstrap was conducted to evaluate the stability and accuracy of network estimates. Results: The strongest positive association was observed between fatigue and depression, whereas smartphone addiction showed the strongest negative association with learning engagement. Depression demonstrated relatively higher centrality within the network, while anxiety showed comparatively lower centrality values. Strength and expected influence estimates demonstrated acceptable stability. Conclusions: The findings suggest meaningful associations among depression, fatigue, sleep quality, smartphone addiction, and learning engagement in nursing students. Learning engagement demonstrated relatively strong connectivity within the network, highlighting its close association with psychological and behavioral factors. These findings support the utility of network analysis for understanding complex interrelationships among psychological variables in nursing students.