Journal
JMIR MHEALTH AND UHEALTH
Volume 5, Issue 7, Pages -Publisher
JMIR PUBLICATIONS, INC
DOI: 10.2196/mhealth.7346
Keywords
mobile health; mHealth; asthma; Fitbit; physical activity; sleep; sleep quality
Funding
- NIH [UL1TR000039, UL1TR001427]
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Background: Smart wearables such as the Fitbit wristband provide the opportunity to monitor patients more comprehensively, to track patients in a fashion that more closely follows the contours of their lives, and to derive a more complete dataset that enables precision medicine. However, the utility and efficacy of using wearable devices to monitor adolescent patients' asthma outcomes have not been established. Objective: The objective of this study was to explore the association between self-reported sleep data, Fitbit sleep and physical activity data, and pediatric asthma impact (PAI). Methods: We conducted an 8-week pilot study with 22 adolescent asthma patients to collect: (1) weekly or biweekly patient-reported data using the Patient-Reported Outcomes Measurement Information System (PROMIS) measures of PAI, sleep disturbance (SD), and sleep-related impairment (SRI) and (2) real-time Fitbit (ie, Fitbit Charge HR) data on physical activity (F-AM) and sleep quality (F-SQ). To explore the relationship among the self-reported and Fitbit measures, we computed weekly Pearson correlations among these variables of interest. Results: We have shown that the Fitbit-derived sleep quality F-SQ measure has a moderate correlation with the PROMIS SD score (average r =-. 31, P =. 01) and a weak but significant correlation with the PROMIS PAI score (average r =-. 18, P =. 02). The Fitbit physical activity measure has a negligible correlation with PAI (average r =. 04, P =. 62). Conclusions: Our findings support the potential of using wrist-worn devices to continuously monitor two important factors-physical activity and sleep-associated with patients' asthma outcomes and to develop a personalized asthma management platform.
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