Analysis of the interactive effects between sleep quality, trait mindfulness, vigor, and five types of negative emotions using EBICglasso network analysis - Ding, Xiaoqian; Qiao, Lijie; Li, Qingmin; Yang, Zirong (Frontiers in Psychology, 2025)
IntroductionNetwork analysis offers a powerful approach for identifying complex interaction patterns that traditional statistical methods often overlook. However, limited research has applied network analysis to examine the interrelationships among sleep quality, trait mindfulness, vigor, and multiple negative emotions. This study aimed to investigate the structural associations among these psychological factors in Chinese college students.MethodsA total of 1,529 college students completed measures of sleep quality, trait mindfulness, vigor, depression, anxiety, confusion, hostility, and fatigue using the Pittsburgh Sleep Quality Index (PSQI), the Mindful Attention Awareness Scale (MAAS), and the Profile of Mood States (POMS). EBICglasso network analysis was conducted to estimate conditional associations and identify central nodes within the psychological network.ResultsResults showed that Vigor-Activity was positively associated with Trait Mindfulness (r = 0.23) and negatively associated with Sleep Quality (r = –0.10). Depression-Dejection displayed the strongest edge with Anger-Hostility (r = 0.53) and was also positively associated with Tension-Anxiety (r = 0.36). Centrality analysis indicated that Depression-Dejection had the highest strength centrality, whereas Vigor-Activity demonstrated the highest betweenness and closeness centrality.DiscussionThe findings suggest that depression functions as the core negative emotional factor within the network affecting sleep quality, while vigor serves as a key bridging variable linking trait mindfulness and sleep quality. These results support theoretical models of energy-related psychological functioning and highlight potential intervention targets for improving sleep quality among college students.