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Usability of Wearable Devices to Remotely Monitor Sleep Patterns Among Patients With Ischemic Heart Disease: Observational Study

Overview
Journal JMIR Form Res
Publisher JMIR Publications
Date 2020 Apr 8
PMID 32254044
Citations 2
Authors
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Abstract

Background: There is growing interest in using wearable devices to remotely monitor patient behaviors. However, there has been little evaluation of how often these technologies are used to monitor sleep patterns over longer term periods, particularly among more high-risk patients.

Objective: The goal of the research was to evaluate the proportion of time that patients with ischemic heart disease used wearable devices to monitor their sleep and identify differences in characteristics of patients with higher versus lower use.

Methods: We evaluated wearable device data from a previously conducted clinical trial testing the use of wearable devices with personalized goal-setting and financial incentives. Patients with ischemic heart disease established a sleep baseline and were then followed for 24 weeks. The proportion of days that sleep data was collected was compared over the 24 weeks and by study arm. Characteristics of patients were compared to groups with high, low, or no sleep data.

Results: The sample comprised 99 patients with ischemic heart disease, among which 79% (78/99) used the wearable device to track their sleep. During the 6-month trial, sleep data were collected on 60% (10,024/16,632) of patient-days. These rates declined over time from 77% (4292/5544) in months 1 and 2 to 58% (3188/5544) in months 3 and 4 to 46% (2544/5544) in months 5 and 6. Sleep data were collected at higher rates among the intervention group compared with control (67% vs 55%, P<.001). In the main intervention period (months 3 and 4), patients with higher rates of sleep data were on average older (P=.03), had a history of smoking (P=.007), and had higher rates of commercial health insurance (P=.03).

Conclusions: Among patients with ischemic heart disease in a physical activity trial, a high proportion used wearable devices to track their sleep; however, rates declined over time. Future research should consider larger evaluations coupled with behavioral interventions.

Trial Registration: ClinicalTrials.gov NCT02531022; https://clinicaltrials.gov/ct2/show/NCT02531022.

Citing Articles

Sleep as a window of cardiometabolic health: The potential of digital sleep and circadian biomarkers.

van den Brink W, Oosterman J, Smid D, de Vries H, Atsma D, Overeem S Digit Health. 2025; 11:20552076241288724.

PMID: 39980570 PMC: 11840856. DOI: 10.1177/20552076241288724.


Exploring Variations in Sleep Perception: Comparative Study of Chatbot Sleep Logs and Fitbit Sleep Data.

Jang H, Lee S, Son Y, Seo S, Baek Y, Mun S JMIR Mhealth Uhealth. 2023; 11:e49144.

PMID: 37988148 PMC: 10698662. DOI: 10.2196/49144.


Acceptability and Usability of a Wearable Device for Sleep Health Among English- and Spanish-Speaking Patients in a Safety Net Clinic: Qualitative Analysis.

Purnell L, Sierra M, Lisker S, Lim M, Bailey E, Sarkar U JMIR Form Res. 2023; 7:e43067.

PMID: 37098152 PMC: 10280334. DOI: 10.2196/43067.

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