Exploring the Association Between Self-Reported Asthma Impact and Fitbit-Derived Sleep Quality and Physical Activity Measures in Adolescents

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.