Network analysis of smartphone addiction, attentional control, and learning adaptation among nursing undergraduates

In the digital learning environment, learning adaptation and attentional control have been shown to be important factors associated with academic success among nursing undergraduates. Smartphone addiction has been associated with impaired attentional control and poorer learning outcomes; however, although previous studies have investigated smartphone addiction and learning-related outcomes, the multidimensional relationships among smartphone addiction, attentional control, and learning adaptation remain unclear. Therefore, this study aimed to examine the network structure among these constructs and identify candidate targets for future intervention research.

A cross-sectional survey was conducted among 452 nursing undergraduates from two universities in China from February to May 2025. Participants completed the Mobile Phone Addiction Index Scale, the Attentional Control Scale, and the Learning Adaptation Scale. An EBICglasso Gaussian graphical model was estimated using R. Node strength and bridge strength were calculated, and bootstrap procedures were performed to assess network accuracy and stability. To examine sex-specific mechanisms, we applied NCT to compare network structure, global strength, and node strength across sexes.

Network analysis shows that the strongest associations were observed between attentional focusing (A1) and attentional shifting (A2) (edge weight = 0.38), feeling anxious and lost (M2) and withdrawal or escape (M3) (edge weight = 0.27), and teaching methodology (L2) and learning attitude (L4) (edge weight = 0.23). Attentional focusing (A1), learning capability (L3), and learning motivation (L1) showed the highest strength centrality values and emerged as the most central nodes in the network. Bridge strength identified attentional focusing (A1), learning motivation (L1), and productivity loss (M4) as key bridge nodes linking the three domains.

Smartphone addiction, attentional control, and learning adaptation were found to be closely interconnected among nursing undergraduates. The identified central and bridge nodes may serve as candidate targets for future intervention research aimed at reducing smartphone addiction and improving learning adaptation in this population. However, given the cross-sectional design, these findings should be interpreted as preliminary and require validation through longitudinal and experimental studies.