Analysis of the Interactive Effects Between Sleep Quality, Trait Mindfulness, Vigor, and Five Types of Negative Emotions Using EBICglasso Network Analysis

Xiaoqian Ding^1*Zirong Yang^2*Lijie Qiao¹Qingmin Li¹

• ¹Liaoning Normal University, Dalian, China
• ²Affiliated Zhongshan Hospital of Dalian University, Dalian, China

Network analysis is adept at uncovering complex interaction patterns that traditional statistical methods often fail to capture. However, few studies have utilized network analysis to explore the intricate relationships between sleep quality, trait mindfulness, vigor, and various negative emotions. This study assessed the sleep quality, trait mindfulness, vigor, depression, anxiety, confusion, hostility, and fatigue of 1,529 Chinese college students using the Pittsburgh Sleep Quality Index (PSQI), the Mindful Attention Awareness Scale (MAAS), and the Profile of Mood States (POMS). The EBICglasso network analysis method was employed to investigate the complex psychological factors influencing college students' sleep quality. The network analysis revealed that: (1) the node Vigor-Activity was positively associated with the node Trait Mindfulness (r = 0.23) and negatively associated with the node Sleep Quality (r = -0.10); the node Depression-Dejection was positively associated with the node Anger-Hostility (r = 0.53), showing the strongest edge strength; and the node Depression-Dejection was positively associated with the node Tension-Anxiety (r = 0.36). (2) The node Depression-Dejection had the highest strength centrality in the overall network, while the node Vigor-Activity exhibited the highest betweenness and closeness centrality. In the network comprising sleep quality, trait mindfulness, vigor, anxiety, depression, hostility, confusion, and fatigue, depression emerged as the core factor, with vigor serving as a bridging factor.