Cargando…

Validation of the Mobile App–Recorded Circadian Rhythm by a Digital Footprint

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),...

Descripción completa

Detalles Bibliográficos
Autores principales: Lin, Yu-Hsuan, Wong, Bo-Yu, Pan, Yuan-Chien, Chiu, Yu-Chuan, Lee, Yang-Han
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6542252/
https://www.ncbi.nlm.nih.gov/pubmed/31099340
http://dx.doi.org/10.2196/13421
_version_ 1783422906889404416
author Lin, Yu-Hsuan
Wong, Bo-Yu
Pan, Yuan-Chien
Chiu, Yu-Chuan
Lee, Yang-Han
author_facet Lin, Yu-Hsuan
Wong, Bo-Yu
Pan, Yuan-Chien
Chiu, Yu-Chuan
Lee, Yang-Han
author_sort Lin, Yu-Hsuan
collection PubMed
description 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.
format Online
Article
Text
id pubmed-6542252
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher JMIR Publications
record_format MEDLINE/PubMed
spelling pubmed-65422522019-06-07 Validation of the Mobile App–Recorded Circadian Rhythm by a Digital Footprint Lin, Yu-Hsuan Wong, Bo-Yu Pan, Yuan-Chien Chiu, Yu-Chuan Lee, Yang-Han JMIR Mhealth Uhealth Original Paper 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. JMIR Publications 2019-05-16 /pmc/articles/PMC6542252/ /pubmed/31099340 http://dx.doi.org/10.2196/13421 Text en ©Yu-Hsuan Lin, Bo-Yu Wong, Yuan-Chien Pan, Yu-Chuan Chiu, Yang-Han Lee. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 16.05.2019. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mhealth and uhealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Lin, Yu-Hsuan
Wong, Bo-Yu
Pan, Yuan-Chien
Chiu, Yu-Chuan
Lee, Yang-Han
Validation of the Mobile App–Recorded Circadian Rhythm by a Digital Footprint
title Validation of the Mobile App–Recorded Circadian Rhythm by a Digital Footprint
title_full Validation of the Mobile App–Recorded Circadian Rhythm by a Digital Footprint
title_fullStr Validation of the Mobile App–Recorded Circadian Rhythm by a Digital Footprint
title_full_unstemmed Validation of the Mobile App–Recorded Circadian Rhythm by a Digital Footprint
title_short Validation of the Mobile App–Recorded Circadian Rhythm by a Digital Footprint
title_sort validation of the mobile app–recorded circadian rhythm by a digital footprint
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6542252/
https://www.ncbi.nlm.nih.gov/pubmed/31099340
http://dx.doi.org/10.2196/13421
work_keys_str_mv AT linyuhsuan validationofthemobileapprecordedcircadianrhythmbyadigitalfootprint
AT wongboyu validationofthemobileapprecordedcircadianrhythmbyadigitalfootprint
AT panyuanchien validationofthemobileapprecordedcircadianrhythmbyadigitalfootprint
AT chiuyuchuan validationofthemobileapprecordedcircadianrhythmbyadigitalfootprint
AT leeyanghan validationofthemobileapprecordedcircadianrhythmbyadigitalfootprint