大学生使用智能手机预测社交时差的评估

IF 0.2 Q4 PSYCHIATRY
Karan Mehta, Neeraj Mahajan, Dishant B. Upadhyay, Taxashil Jadeja, Rajkumar J Sevak
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引用次数: 0

摘要

背景:个体的睡眠和活动模式表现出很大的差异,并受到社会作息的极大干扰。社会时差(Social jetlag, SJL)是内在昼夜节律和外在强迫性睡眠-觉醒周期之间的差异。然而,对影响SJL严重程度的变量知之甚少。方法:我们评估了与睡眠或智能手机相关的变量是否会影响印度大学生SJL的严重程度。来自印度古吉拉特邦医学、牙科、工程、辅助医学和其他学院的1175名学生完成了一项基于网络的调查。该调查包括人口统计问题和智能手机成瘾量表-短版本(SAS-SV)的问题,简化的霍恩和奥斯伯格晨昏性问卷(rMEQ)和慕尼黑时间类型问卷(MCTQ)。MCTQ的回答决定了SJL的分数。结果:多元线性回归分析结果显示,自由日睡眠时长(B = 0.42)、睡眠类型(B = 0.44, B2 = 0.40)、起床后最大智能手机使用时间(B = 0.92)、智能手机成瘾严重程度(B = -0.01)和自由日睡眠开始范围(B = -0.02)对SJL评分有显著预测作用(P < 0.03)。晨型和晚型个体的SJL严重程度分别比中性型个体高0.42和0.40个单位。起床后使用智能手机最多的人的SJL严重程度比在一天中的其他时间使用最多的人高0.92个单位。SAS评分每升高1个单位,SJL降低0.01个单位。结论:这些结果表明,SJL的严重程度受多个因素的影响,可以有针对性地制定减少印度大学生SJL的干预措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of smartphone usage as a predictor of social jetlag in university students
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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自引率
25.00%
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38
审稿时长
23 weeks
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