Department of Kinesiology and Nutrition, College of Applied Health Sciences, University of Illinois at Chicago, Chicago, IL, United States.
Rheumatology Division, School of Medicine, University of Sao Paulo, Sao Paulo, Brazil.
JMIR Mhealth Uhealth. 2021 Mar 1;9(3):e25289. doi: 10.2196/25289.
Consumer-based physical activity (PA) trackers, also known as wearables, are increasingly being used in research studies as intervention or measurement tools. One of the most popular and widely used brands of PA trackers is Fitbit. Since the release of the first Fitbit in 2009, hundreds of experimental studies have used Fitbit devices to facilitate PA self-monitoring and behavior change via goal setting and feedback tools. Fitbit's ability to capture large volumes of PA and physiological data in real time creates enormous opportunities for researchers. At the same time, however, it introduces a number of challenges (eg, technological, operational, logistical), most of which are not sufficiently described in study publications. Currently, there are no technical reports, guidelines, nor other types of publications discussing some of these challenges and offering guidance to researchers on how to best incorporate Fitbit devices in their study design and intervention to achieve their research goals. As a result, researchers are often left alone to discover and address some of these issues during the study through "trial and error." This paper aims to address this gap. Drawing on our cumulative experience of conducting multiple studies with various Fitbit PA trackers over the years, we present and discuss various key challenges associated with the use of Fitbit PA trackers in research studies. Difficulties with the use of Fitbit PA trackers are encountered throughout the entire research process. Challenges and solutions are categorized in 4 main categories: study preparation, intervention delivery, data collection and analysis, and study closeout. Subsequently, we describe a number of empirically tested strategies used in 4 of our interventional studies involving participants from a broad range of demographic characteristics, racial/ethnic backgrounds, and literacy levels. Researchers should be prepared to address challenges and issues in a timely fashion to ensure that the Fitbit effectively assists participants and researchers in achieving research and outcome goals.
基于消费者的身体活动 (PA) 追踪器,也称为可穿戴设备,越来越多地被用于研究作为干预或测量工具。PA 追踪器中最受欢迎和广泛使用的品牌之一是 Fitbit。自 2009 年发布第一款 Fitbit 以来,数以百计的实验研究使用 Fitbit 设备通过设定目标和提供反馈工具来促进 PA 自我监测和行为改变。Fitbit 实时捕获大量 PA 和生理数据的能力为研究人员创造了巨大的机会。然而,与此同时,它也带来了许多挑战(例如,技术、操作、后勤),其中大多数在研究出版物中没有充分描述。目前,没有技术报告、指南或其他类型的出版物讨论其中的一些挑战,并为研究人员提供关于如何在研究设计和干预中最好地整合 Fitbit 设备以实现其研究目标的指导。因此,研究人员经常在研究过程中通过“反复试验”独自发现和解决其中的一些问题。本文旨在解决这一差距。借鉴我们多年来使用各种 Fitbit PA 追踪器进行多项研究的累积经验,我们提出并讨论了与在研究中使用 Fitbit PA 追踪器相关的各种关键挑战。在整个研究过程中都会遇到使用 Fitbit PA 追踪器的困难。挑战和解决方案分为 4 个主要类别:研究准备、干预交付、数据收集和分析以及研究结束。随后,我们描述了我们的 4 项干预研究中使用的一些经过实证检验的策略,这些研究涉及来自广泛的人口统计学特征、种族/民族背景和文化程度的参与者。研究人员应该及时解决挑战和问题,以确保 Fitbit 有效地帮助参与者和研究人员实现研究和结果目标。