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

机译:探索自我报告的哮喘影响和青少年根据Fitbit得出的睡眠质量和体育锻炼量度之间的关联

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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.
机译:背景技术诸如Fitbit腕带之类的智能可穿戴设备提供了机会,可以更全面地监视患者,以更紧密地跟随其生活轮廓的方式跟踪患者,并获得支持精确医学的更完整的数据集。但是,尚未建立使用可穿戴设备监测青少年患者哮喘预后的实用性和有效性。目的本研究的目的是探讨自我报告的睡眠数据,Fitbit睡眠和身体活动数据与小儿哮喘影响(PAI)之间的关系。方法我们对22名青少年哮喘患者进行了为期8周的先导研究,以收集:(1)每周或每两周一次的患者报告数据,使用患者报告结果测量信息系统(PROMIS)的PAI,睡眠障碍(SD)和睡眠相关障碍(SRI)和(2)关于身体活动(F-AM)和睡眠质量(F?SQ)的实时Fitbit(即Fitbit Charge HR)数据。为了探索自我报告和Fitbit测度之间的关系,我们计算了这些关注变量之间的每周皮尔逊相关性。结果我们已经表明,Fitbit派生的睡眠质量F-SQ量度与PROMIS SD得分具有中等相关性(平均r = ?. 31,P = .01),而与PROMIS PAI得分具有弱但显着的相关性(平均r = ?. 18,P = .02)。 Fitbit身体活动量度与PAI的相关性可忽略不计(平均值r = .04,P = .62)。结论我们的发现支持使用腕戴式设备连续监测与患者哮喘预后相关的两个重要因素(体力活动和睡眠)以及开发个性化哮喘管理平台的潜力。

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