Determinants for Sustained Use of an Activity Tracker: Observational Study
Determinants for Sustained Use of an Activity Tracker: Observational Study
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DOI：
10.2196/mhealth.7311
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发表时间：
2017-10-01
影响因子：
5
通讯作者：
De Groot, Martijn
中科院分区：
文献类型：
--
作者：
Hermsen, Sander;Moons, Jonas;De Groot, Martijn
背景：缺乏身体活动被认为是全球6%的死亡原因。来自活动跟踪器等可穿戴设备的反馈有可能鼓励日常身体活动。到目前为止，几乎没有关于活动跟踪器依从性的自然发展或预测哪些用户在第一年内设法继续使用其活动跟踪器的潜在因素的研究（从而增加健康行为改变的机会）以及用户在短时间后停止使用他们的跟踪器。目的：本研究的目的是确定购买后第一年持续使用的决定因素。具体来说，我们研究了反馈设备使用的人口统计学和社会经济学、心理学、健康相关、目标相关、技术、用户体验相关和社会预测因素的相对重要性。此外，本研究测试这些预测因素对身体activity.Methods的影响：共有711名参与者从四个城市地区在法国收到了活动跟踪器（Fitbit Zip），并允许使用他们的记录数据。参与者填写了三份基于网络的问卷：开始时，98天后和232天后，以测量上述决定因素。此外，对于每个参与者，我们收集了他们的Fitbit跟踪器跟踪320天的活动数据。我们通过使用随机森林（Random Forest）确定了所有预测因素的相对重要性，这是一种机器学习分析技术。结果：数据显示，Fitbit的使用呈缓慢的指数衰减，73.9%（526/711）的参与者在100天后仍在跟踪，16.0%（114/711）的参与者在320天后仍在跟踪。参与者平均使用跟踪器129天。退出追踪的最重要原因是技术问题，如电池耗尽、追踪器损坏或丢失（占第三季度所有受访者的21.5%，130/601）。随机森林预测分析显示，最具影响力的决定因素是年龄，用户体验相关因素，移动的手机类型，家庭类型，Fitbit跟踪器的感知效果和目标相关因素。我们探讨的作用，这些预测显示有意义的差异的天数的跟踪weared.Conclusions：本研究提供了一个概述的自然发展的使用活动跟踪器，以及从文献的一系列决定因素的相对重要性。衰减是指数级的，但比现有文献预期的要慢。许多因素对持续使用有很小的贡献。最重要的决定因素是技术条件，年龄，用户体验和目标相关因素。这一发现表明，活动跟踪可能对广泛的目标群体有益，但应更多地关注活动跟踪器的技术和用户体验相关方面。
Background: A lack of physical activity is considered to cause 6% of deaths globally. Feedback from wearables such as activity trackers has the potential to encourage daily physical activity. To date, little research is available on the natural development of adherence to activity trackers or on potential factors that predict which users manage to keep using their activity tracker during the first year (and thereby increasing the chance of healthy behavior change) and which users discontinue using their trackers after a short time.Objective: The aim of this study was to identify the determinants for sustained use in the first year after purchase. Specifically, we look at the relative importance of demographic and socioeconomic, psychological, health-related, goal-related, technological, user experience-related, and social predictors of feedback device use. Furthermore, this study tests the effect of these predictors on physical activity.Methods: A total of 711 participants from four urban areas in France received an activity tracker (Fitbit Zip) and gave permission to use their logged data. Participants filled out three Web-based questionnaires: at start, after 98 days, and after 232 days to measure the aforementioned determinants. Furthermore, for each participant, we collected activity data tracked by their Fitbit tracker for 320 days. We determined the relative importance of all included predictors by using Random Forest, a machine learning analysis technique.Results: The data showed a slow exponential decay in Fitbit use, with 73.9% (526/711) of participants still tracking after 100 days and 16.0% (114/711) of participants tracking after 320 days. On average, participants used the tracker for 129 days. Most important reasons to quit tracking were technical issues such as empty batteries and broken trackers or lost trackers (21.5% of all Q3 respondents, 130/601). Random Forest analysis of predictors revealed that the most influential determinants were age, user experience-related factors, mobile phone type, household type, perceived effect of the Fitbit tracker, and goal-related factors. We explore the role of those predictors that show meaningful differences in the number of days the tracker was worn.Conclusions: This study offers an overview of the natural development of the use of an activity tracker, as well as the relative importance of a range of determinants from literature. Decay is exponential but slower than may be expected from existing literature. Many factors have a small contribution to sustained use. The most important determinants are technical condition, age, user experience, and goal-related factors. This finding suggests that activity tracking is potentially beneficial for a broad range of target groups, but more attention should be paid to technical and user experience-related aspects of activity trackers.