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◆ International Journal of Community Medicine and Public Health2026-07-31· Pittsburgh Sleep Quality Index

Association of internet addiction with sleep quality among university students

Muhammad Shaheer, Muhammad Muttahar Khalil, Samira Faiz Bari, Farhan Qureshi, Syeda Saniya Zehra, Jaweria Basharat, Muhammad Owais Baloch

原始摘要(英文原文)· Original abstract
Background: Initially an educational and entertainment tool, the internet has become additive, impairing time management, circadian rhythm and sleep quality. The objective of the study is to observe the frequency of internet addiction (IA) and poor sleep quality among university students of Karachi, Pakistan and to determine the association of IA with sleep quality. Methods: The cross-sectional study was conducted from 15th July 2025 to 21st January 2026 among 373 university students of Karachi. Students from public and private sector institutions were recruited through convenience sampling. Internet addiction test and pittsburgh sleep quality index assessed IA and sleep quality. The correlation between IA scores and sleep quality scores was accessed using Spearman's correlation test. Univariate and multivariable logistic regression identified predictors of poor sleep (vs. normal sleep) based on p<0.25 selection criterion. Data were entered and analyzed using SPSS version 25. Results: Of 373 participants (median age 21 years, 71.3% male), the prevalence of internet addiction was found to be 85.7% while 60.3% of our study participants reported poor sleep quality. A statistically significant, weak positive correlation was found between IA and sleep quality, rs=0.295, p<0.001. Univariate analysis showed female sex (OR=2.18), asthma, other illnesses and IA severity were significantly associated with poor sleep (p<0.05). Multivariable regression identified female sex (AOR=2.29), other illnesses (AOR=2.20) and moderate-to-severe IA (AOR=5.58) as independent predictors of poor sleep. Conclusions: Internet addiction and poor sleep were highly prevalent, while moderate-to-severe internet addiction was the strongest independent predictor of poor sleep.
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