Garett Renee, Liu Sam, Young Sean D
ElevateU, Los Angeles, CA USA.
University of California Institute for Prediction Technology (UCIPT), Department of Family Medicine, UCLA, Los Angeles, CA 90024, USA.
Inf Commun Soc. 2018;21(2):163-173. doi: 10.1080/1369118X.2016.1266374. Epub 2016 Dec 20.
Insufficient sleep is a growing health problem among University students, especially for freshmen during their first quarter/semester of college. Little research has studied how social media technologies impact sleep quality among college students. This study aims to determine the relationship between social media use and sleep quality among freshman undergraduates during their first quarter in college. Specifically, we explored whether variations in Twitter use across the time of day and day of the week would be associated with self-reported sleep quality. We conducted a study of Freshman Twitter-using students (N = 197) over their first quarter of college, between October to December of 2015. We collected students' tweets, labeled the content of the tweets according to different emotional states, and gave theme weekly surveys on sleep quality. Tweeting more frequently on weekday late nights was associated with lower sleep quality (β = -0.937, SE = 0.352); tweeting more frequently on weekday evenings was associated with better quality sleep (β = 0.189, SE = 0.097). Tweets during the weekday that were labeled related to the emotion of fear were associated with lower sleep quality (β = -0.302, SE = 0.131). Results suggest that social media use is associated with sleep quality among students. Results provide can be used to inform future interventions to improve sleep quality among college students.
睡眠不足是大学生中日益严重的健康问题,尤其是对于大学第一季度/学期的新生而言。很少有研究探讨社交媒体技术如何影响大学生的睡眠质量。本研究旨在确定大学新生第一季度期间社交媒体使用与睡眠质量之间的关系。具体而言,我们探讨了一天中不同时间和一周中不同日子的推特使用差异是否与自我报告的睡眠质量相关。我们对2015年10月至12月大学第一季度使用推特的新生(N = 197)进行了一项研究。我们收集了学生的推文,根据不同的情绪状态对推文内容进行标注,并每周进行一次关于睡眠质量的调查。工作日深夜更频繁地发推文与较低的睡眠质量相关(β = -0.937,标准误 = 0.352);工作日晚上更频繁地发推文与较好的睡眠质量相关(β = 0.189,标准误 = 0.097)。工作日期间标注与恐惧情绪相关的推文与较低的睡眠质量相关(β = -0.302,标准误 = 0.131)。结果表明,社交媒体使用与学生的睡眠质量相关。研究结果可用于为未来改善大学生睡眠质量的干预措施提供参考。