Jakowski Sarah, Stork Moritz
Faculty of Sport Science, Ruhr University Bochum, Gesundheitscampus Nord 10, 44801 Bochum, Germany.
Somnologie (Berl). 2022;26(4):244-251. doi: 10.1007/s11818-022-00395-z. Epub 2022 Oct 25.
As sleep problems are highly prevalent among university students and competitive athletes, and the application of commercial sleep technologies may be either useful or harmful, this study investigated the effects of a 2-week sleep self-monitoring on the sleep of physically active university students ( 98, 21 ± 1.7 years). Two intervention groups used a free sleep app (; SleepScore Labs™, Carlsbad, CA, USA: = 20 or ; Sleep Cycle AB, Gothenburg, Sweden: = 24) while answering online sleep diaries. They used the app analysis function in week 1 and the 'smart alarm' additionally in week 2. As controls, one group answered the online sleep diary without intervention ( 21) and another the pre-post questionnaires only ( 33). Facets of subjective sleep behaviour and the role of bedtime procrastination were analysed. Multilevel models did not show significant interactions, indicating intervention effects equal for both app groups. Sleep Cycle users showed trends toward negative changes in sleep behaviour, while the online sleep diary group showed more, tendentially positive, developments. Bedtime procrastination was a significant predictor of several variables of sleep behaviour and quality. The results indicate neither benefits nor negative effects of app-based sleep self-tracking. Thus, student athletes do not seem to be as susceptible to non-validated sleep technologies as expected. However, bedtime procrastination was correlated with poor sleep quality and should be addressed in sleep intervention programmes.
由于睡眠问题在大学生和竞技运动员中非常普遍,而且商业睡眠技术的应用可能有益也可能有害,本研究调查了为期2周的睡眠自我监测对身体活跃的大学生(98名,21±1.7岁)睡眠的影响。两个干预组使用免费睡眠应用程序(美国加利福尼亚州卡尔斯巴德市SleepScore Labs™:n = 20;或瑞典哥德堡市Sleep Cycle AB:n = 24),同时填写在线睡眠日记。他们在第1周使用应用程序分析功能,在第2周额外使用“智能闹钟”。作为对照组,一组在无干预的情况下填写在线睡眠日记(n = 21),另一组仅填写前后调查问卷(n = 33)。分析了主观睡眠行为的各个方面以及睡前拖延的作用。多层次模型未显示出显著的交互作用,表明两个应用程序组的干预效果相同。使用Sleep Cycle的用户睡眠行为有呈负面变化的趋势,而在线睡眠日记组则有更多、倾向于积极的变化。睡前拖延是睡眠行为和质量的几个变量的重要预测因素。结果表明基于应用程序的睡眠自我追踪既没有益处也没有负面影响。因此,学生运动员似乎不像预期的那样容易受到未经验证的睡眠技术的影响。然而,睡前拖延与睡眠质量差有关,应在睡眠干预计划中加以解决。