%0 Journal Article
%@ 2291-5222
%I JMIR Publications
%V 7
%N 5
%P e13421
%T Validation of the Mobile App–Recorded Circadian Rhythm by a Digital Footprint
%A Lin,Yu-Hsuan
%A Wong,Bo-Yu
%A Pan,Yuan-Chien
%A Chiu,Yu-Chuan
%A Lee,Yang-Han
%+ Institute of Population Health Sciences, National Health Research Institutes, 35 Keyan Road, Zhunan, Miaoli, 35053, Taiwan, 886 37 246166 ext 36383, yuhsuanlin@nhri.org.tw
%K circadian rhythm
%K sleep
%K smartphone
%K mobile applications
%D 2019
%7 16.05.2019
%9 Original Paper
%J JMIR Mhealth Uhealth
%G English
%X Background: Modern smartphone use is pervasive and could be an accessible method of evaluating the circadian rhythm and social jet lag via a mobile app. Objective: This study aimed to validate the app-recorded sleep time with daily self-reports by examining the consistency of total sleep time (TST), as well as the timing of sleep onset and wake time, and to validate the app-recorded circadian rhythm with the corresponding 30-day self-reported midpoint of sleep and the consistency of social jetlag. Methods: The mobile app, Rhythm, recorded parameters and these parameters were hypothesized to be used to infer a relative long-term pattern of the circadian rhythm. In total, 28 volunteers downloaded the app, and 30 days of automatically recorded data along with self-reported sleep measures were collected. Results: No significant difference was noted between app-recorded and self-reported midpoint of sleep time and between app-recorded and self-reported social jetlag. The overall correlation coefficient of app-recorded and self-reported midpoint of sleep time was .87. Conclusions: The circadian rhythm for 1 month, daily TST, and timing of sleep onset could be automatically calculated by the app and algorithm. 
%M 31099340
%R 10.2196/13421
%U https://mhealth.jmir.org/2019/5/e13421/
%U https://doi.org/10.2196/13421
%U http://www.ncbi.nlm.nih.gov/pubmed/31099340