Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Apr 10, 2023
Open Peer Review Period: Apr 9, 2023 - Jun 4, 2023
Date Accepted: Nov 22, 2023
(closed for review but you can still tweet)
Examining Human-Smartphone Interaction as a Proxy for Circadian Rhythm in Patients with Insomnia: A Cross-Sectional Study
ABSTRACT
Background:
The sleep and circadian rhythm of smartphone usage, which is based on mental activities, may correlate with sleep quality and depressive symptoms as much as the current standard of physical activity-based actigraphy does.
Objective:
This study aimed to develop app-defined circadian rhythm and sleep indicators, and compare them with actigraphy circadian rhythm and sleep indicators, as well as examine the clinical validation of these indicators in insomnia patients and healthy controls
Methods:
We developed the mobile app, Rhythm, to record the timestamps of smartphone usage and calculate circadian rhythms in 33 insomnia patients and 33 age-, gender-matched healthy controls, totaling 2,097 person-days, and in parallel utilized standard actigraphy to quantify subjects’ sleep-wake cycles. Sleep indicators included sleep onset, wake time, wake after sleep onset (WASO), and the number of awakenings (NAWK). Circadian rhythm metrics quantified the relative amplitude (RA), interdaily stability, and intradaily variability (IV) based on either smartphone usage or physical activity data.
Results:
There were no significant differences between app-defined and actigraphy-defined sleep onsets, wake times, total sleep times and NAWK. Both app-defined sleep indicators, as well as actigraphy-defined sleep indicators could identify clinical manifestations of insomnia; they include longer WASO, higher NAWK, and later sleep onset and wake time in insomnia patients than in healthy controls. In addition, the PSQI scores were positively correlated with WASO and NAWK, whether measured by app or actigraphy. Depressive symptom scores were positively correlated with IVapp, and negatively correlated with RAact, as individuals with depression typically presented disrupted circadian rhythmicity. Meanwhile, the depressive symptom scores were negatively correlated with IVact and not significantly correlated with RAapp.
Conclusions:
Sleep and circadian rhythms derived from smartphone usage showed potential to be digital biomarkers, similar to those from standard actigraphy. Clinical Trial: None
Citation
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