Analysis of the interactive effects between sleep quality, trait mindfulness, vigor, and five types of negative emotions using EBICglasso network analysis
Year: 2025
Type: article
Study design: Observational Study
Abstract: Introduction: Network 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. Methods: A 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. Results: = 0.36). Centrality analysis indicated that Depression-Dejection had the highest strength centrality, whereas Vigor-Activity demonstrated the highest betweenness and closeness centrality. Discussion: The 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.
Source: Frontiers in Psychology
Authors: Xiaoqian Ding, Lijie Qiao, Qingmin Li, Zirong Yang
Language: English
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W4417415246