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ORIGINAL ARTICLE
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Evaluation of smartphone usage as a predictor of social jetlag in university students


1 Department of Physiology, Smt. Nathiba Hargovandas Lakhmichand Municipal Medical College, Ahmedabad, Gujarat, India
2 Department of Pharmacy Practice, University of The Pacific School of Pharmacy, Stockton, California, USA

Correspondence Address:
Dishant B Upadhyay,
B401 Grand Riviera Rajnagar Soc., Riverfront Road, Paldi, Ahmedabad - 380 007, Gujarat
India
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/aip.aip_24_22

Background: Individual sleep and activity patterns show large variations and are interfered considerably by social schedules. Social jetlag (SJL) is the difference between intrinsic circadian rhythm and extrinsically enforced sleep-wake cycle. However, little is known about the variables affecting the severity of SJL. Methodology: We evaluated whether sleep- or smartphone-related variables affected the severity of SJL among college students in India. A total of 1175 students from medicine, dental, engineering, paramedical, and other colleges in Gujarat, India, completed a web-based survey. The survey included demographic questions and questions from the Smartphone Addiction Scale-Short Version (SAS-SV), reduced Horne and Ostberg Morningness-Eveningness Questionnaire (rMEQ), and Munich Chronotype Questionnaire (MCTQ). The responses to the MCTQ determined SJL scores. Results: Outcomes from multiple linear regression analysis indicated that the sleep length on free-day (B = 0.42), chronotypes (B = 0.44, B2 = 0.40) maximum smartphone usage time after waking up (B = 0.92), smartphone addiction severity (B = ‒0.01) and free-day sleep onset range (B = ‒0.02) significantly predicted SJL scores (P < 0.03). The SJL severity was 0.42 and 0.40 units greater in individuals with morning-type and evening-type, respectively, compared to the neutral-type rMEQ category. The SJL severity was 0.92 units greater in individuals whose smartphone usage was maximum right after waking up compared to those whose usage was maximum during other times of the day. Every unit increase in SAS score decreased SJL by 0.01 units. Conclusion: These results indicate that SJL severity is affected by several factors, which can be targeted for developing interventions for reducing SJL among college students in India.


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