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Changes in the Networks of Bedtime Procrastination and Anxiety Symptoms Among Chinese Adolescents
Tingting Gao1,2,3,4, Chengchao Zhou1,2,3, Yingying Su5
1Department of Social Medicine and Health Management, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Abstract:
Objective: While traditional psychometric approaches, such as latent variable modeling, have primarily focused on the association between bedtime procrastination and anxiety, they often fail to capture symptom-level temporal and directional relationships. Therefore, this study aims to explore the temporal dynamics of symptom-level associations between bedtime procrastination and anxiety, examining both within-person and between-person variations over time in an adolescent population. Methods: This study utilized panel data-based network analyses to examine both within-person effects (temporal and contemporaneous networks) and between-person dynamics across 3,296 adolescents. Specifically, we examined symptom-to-symptom associations of bedtime procrastination and anxiety using both cross-sectional and temporal network analyses and assessed the symptom centrality to identify key drivers of symptom dynamics. Results: At the within-person level, the temporal network analysis indicated that restlessness (GAD5) was the most stable and predictive node across time. Additionally, nervousness (GAD1) and going to bed later than intended (BPS1) had the most significant influence on other symptoms in the T1→T2 and T2→T3 networks, respectively. In the contemporaneous network, inability to control worry (GAD2), excessive worry (GAD3), and trouble relaxing (GAD4) were identified as the central symptoms. At the between-person level, positive relationships between specific bedtime procrastination symptoms were consistently observed. Conclusions: Our findings elucidate the potential complex interactions between bedtime procrastination and anxiety symptoms, highlighting central symptoms that vary across temporal and contemporaneous networks. The identification of central symptoms and their dynamic associations within these networks can inform the causal mechanisms underlying bedtime procrastination and anxiety, thereby guiding the design of targeted interventions for adolescents.
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