We found no difference between values of wakefulness, sleep, NREM, REM sleep, and RDI calculated from manually scored PSG recordings with those derived through analyses of HRV.
Insomnia is a high prevalence sleep disorder. Current theories point towards the role of cognitive and physiological hyperarousal in the pathophysiology of Insomnia. Our aim was to investigate the potential application of autonomic nervous system viewed through the prism of heart rate variability for understanding and assessing insomnia.Inter beat intervals were recorded using a mobile app, SleepRate, and an off-the-shelf sport belt. 98 users who participated in a sleep assessment and therapy program were labeled by the app as insomniacs (IN). They were compared to 250 users who just monitored their sleep. Heart-rate variability analysis was performed for each night. Mean heart-rate in IN was significantly higher than in reference group (RG). Sympathovagal balance values for each of the different sleep stages and for the period prior to sleep onset were significantly higher in IN compared to the RG. Mobile technology enabled very large scale, measurement of physiological signals. The findings indicate an increased sympathetic predominance in IN. This is consistent with recent theories linking physiological hyperarousal and insomnia. The autonomic approach to sleep evaluation may be a useful alternative to the gold standard whole-night PSG for poor sleepers.
Introduction
Academic achievements and social life on campus represent the main focus for students, while sleep is neglected. The emergence of social media, gaming reduces sleep opportunity, quality and ability. Students are sleep challenged and prone to develop chronic sleep difficulties in later life. Cognitive behavioral interventions are recognized as effective for insomnia and circadian misalignment. We aimed at detecting sleep difficulties, related habits, and at testing the efficacy of a mobile app in improving sleep in students with insomnia symptoms.
Methods
Observational study of US students who approached wellness staff and were offered the Refresh by Sleeprate mobile app that provides a sleep assessment followed by weekly cycles of personalized digital cognitive and behavioral reframing. The app collects perceived, and optional objective sleep data acquired using wearable devices. 892 students aged 18-30 years registered an account between Jan 1 and Oct 30, 2019. The study reports engagement data and outcomes of the assessment and the digital intervention.
Results
507 completed their assessment (6.2 avg nights). 69% presented insomnia symptoms with or without circadian misalignment, 8% circadian misalignment, 12% sleep deprivation, 11% poor sleep hygiene. 192 (55.3% of students with insomnia symptoms) completed at least one week of intervention (5.6 weekly avg nights, 28 avg total nights). Sleep Latency (SL) in minutes decreased from 28.8 (21.5) (Mean/SD) to 22.1 (19.3), p<0.001. When the initial mean SL was longer than 30 minutes, the improvement was larger, from 53.9 (20.8) to 32.7 (25.4) (p<0.001). Mean perceived Wake After Sleep Onset (WASO) longer than 30 minutes decreased from 46.3 (19.0) to 35.8 (21.4), p<0.05. Sleep Efficiency (SE) increased by 1.6% (p<0.002) for all, and by 7.1% (p<0.001) for SE<85%.
Conclusion
The mobile app used reveals sleep problems and is efficient in improving insomnia symptoms in those who remain engaged. 55% of those who started the program also completed it. Engagement remains the main barrier to sleep improvement at scale.
Support
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