The Effects of Personalized Sleep Feedback on Habitual Sleep Behavior and Momentary Symptoms in Daily Life: Mobile Health Intervention Trial using a Healthcare IoT System (Preprint)

Abstract

Several mobile and wearable sleep-tracking devices have been developed, and personalized sleep feedback is the most common functionality among these devices. Sleep is beneficial for physical and mental health. To date, no study has investigated the characteristics of habitual sleep behavior and diurnal self-reported mood and physical symptoms when receiving sleep feedback.

We conducted a mobile health (mHealth) intervention trial to examine whether sending daily sleep feedback messages changes the self-reported mood, physical symptoms, and sleep behavior of Japanese office workers.

Thirty-one office workers (mean age = 42.3 years; male: female = 21:10) participated in a trial from November 30 to December 19, 2020. The participants were instructed to indicate their momentary mood and physical symptoms (depressive mood, anxiety, stress, sleepiness, fatigue, and neck/shoulder stiffness) five times a day using a smartphone application (app). In addition, daily work performance was rated once a day after work. They were randomly assigned to either a feedback (experimental) or control group, wherein they did or did not receive messages about their sleep status on the app, every morning, respectively. All participants wore activity monitors on their non-dominant wrists, by which objective sleep data were registered online on a server. Based on the estimated sleep data on the server, personalized sleep feedback messages were generated and sent to the participants in the feedback group using the app. These processes were fully automated.

Using hierarchical statistical models, we examined differences in the statistical properties of sleep variables (sleep duration and midpoint of sleep) and daily work performance over the trial period. Group-difference in the diurnal slopes for mood and physical symptoms were examined by liner mixed effect model. We found a significant group difference of within-individual residuals in the midpoint of sleep (expected a posteriori for the difference in minutes) = -15 (95% credible interval: -26, -4), suggesting more stable sleep timing in the feedback group. However, there were no significant group differences in daily work performance. We also found significant group differences in the diurnal slopes for sleepiness, fatigue, and neck/shoulder stiffness (P < 0.01), which was largely because of better scores in the feedback group at wake-up time relative to that in the control group.

This is the first mHealth study to demonstrate that sleep feedback sent every morning improves sleep timing of and physical symptoms in healthy office workers. Future research should incorporate specific behavioral instructions intended to improve sleep habits and examine the effectiveness of these instruction.