Social Media Addiction and Sleep Quality Among High School Graduates in Bangladesh: A Network Perspective

Abstract

Objective: Social media has been implicated in curtailing the quality and quantity of sleep. This study applied a network analysis approach to explore associations between social media addiction (SMA) and sleep quality among prospective university students, to identify central and bridge symptoms and compare networks by gender. Methods: A cross-sectional survey was conducted among 1139 Bangladeshi university entrance examinees in February 2025 using a convenience sampling technique. Participants completed the Bergen Social Media Addiction Scale and the Pittsburgh Sleep Quality Index. A Gaussian Graphical Model was estimated using the Extended Bayesian Information Criterion Graphical Lasso (EBICglasso). Network centrality, bridge centrality, stability, and accuracy were evaluated. Network comparison tests (NCT) were performed across genders. All analyses were conducted using R (version 4.4.1) and SPSS (version 27). Results: Strong intra-domain connections emerged within both SMA (Conflict–Relapse; Tolerance–Withdrawal) and sleep (Sleep Quality–Latency; Disturbance–Medication Use). Cross-domain associations included Relapse–Daytime Dysfunction and Mood Modification–Sleep Efficiency. Bridge centrality identified Daytime dysfunction, Mood modification, and sleep latency as prominent connectors. Males reported higher SMA scores, whereas females exhibited poorer sleep quality. The NCT indicated significant gender-based structural differences (M = 0.203, p = 0.013), though global strength remained similar. Conclusion: Findings highlight symptom-level associations between SMA and sleep quality and suggest gender-sensitive targets for behavioral intervention among adolescents and young adults.