Departments of Medicine and Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States.
J Med Internet Res. 2021 Oct 21;23(10):e19789. doi: 10.2196/19789.
Wearable devices that are used for observational research and clinical trials hold promise for collecting data from study participants in a convenient, scalable way that is more likely to reach a broad and diverse population than traditional research approaches. Amazon Mechanical Turk (MTurk) is a potential resource that researchers can use to recruit individuals into studies that use data from wearable devices.
This study aimed to explore the characteristics of wearable device users on MTurk that are associated with a willingness to share wearable device data for research. We also aimed to determine whether compensation was a factor that influenced the willingness to share such data.
This was a secondary analysis of a cross-sectional survey study of MTurk workers who use wearable devices for health monitoring. A 19-question web-based survey was administered from March 1 to April 5, 2018, to participants aged ≥18 years by using the MTurk platform. In order to identify characteristics that were associated with a willingness to share wearable device data, we performed logistic regression and decision tree analyses.
A total of 935 MTurk workers who use wearable devices completed the survey. The majority of respondents indicated a willingness to share their wearable device data (615/935, 65.8%), and the majority of these respondents were willing to share their data if they received compensation (518/615, 84.2%). The findings from our logistic regression analyses indicated that Indian nationality (odds ratio [OR] 2.74, 95% CI 1.48-4.01, P=.007), higher annual income (OR 2.46, 95% CI 1.26-3.67, P=.02), over 6 months of using a wearable device (OR 1.75, 95% CI 1.21-2.29, P=.006), and the use of heartbeat and pulse tracking monitoring devices (OR 1.60, 95% CI 0.14-2.07, P=.01) are significant parameters that influence the willingness to share data. The only factor associated with a willingness to share data if compensation is provided was Indian nationality (OR 0.47, 95% CI 0.24-0.9, P=.02). The findings from our decision tree analyses indicated that the three leading parameters associated with a willingness to share data were the duration of wearable device use, nationality, and income.
Most wearable device users indicated a willingness to share their data for research use (with or without compensation; 615/935, 65.8%). The probability of having a willingness to share these data was higher among individuals who had used a wearable for more than 6 months, were of Indian nationality, or were of American (United States of America) nationality and had an annual income of more than US $20,000. Individuals of Indian nationality who were willing to share their data expected compensation significantly less often than individuals of American nationality (P=.02).
可穿戴设备可用于观察性研究和临床试验,有望以更便捷、可扩展的方式从研究参与者那里收集数据,比传统研究方法更有可能覆盖更广泛和更多样化的人群。亚马逊土耳其机器人(MTurk)是研究人员可以用来招募使用可穿戴设备数据的研究参与者的潜在资源。
本研究旨在探讨 MTurk 上可穿戴设备用户的特征,这些特征与他们愿意分享可穿戴设备数据进行研究有关。我们还旨在确定补偿是否是影响他们分享此类数据意愿的因素。
这是对使用可穿戴设备进行健康监测的 MTurk 工人进行的横断面调查研究的二次分析。2018 年 3 月 1 日至 4 月 5 日,使用 MTurk 平台,对年龄≥18 岁的参与者进行了一项包含 19 个问题的在线调查。为了确定与分享可穿戴设备数据意愿相关的特征,我们进行了逻辑回归和决策树分析。
共有 935 名使用可穿戴设备的 MTurk 工人完成了调查。大多数受访者表示愿意分享他们的可穿戴设备数据(615/935,65.8%),并且如果获得补偿,大多数愿意分享数据的受访者愿意分享他们的数据(518/615,84.2%)。我们的逻辑回归分析结果表明,印度国籍(比值比[OR]2.74,95%置信区间[CI]1.48-4.01,P=.007)、较高的年收入(OR2.46,95%CI1.26-3.67,P=.02)、使用可穿戴设备超过 6 个月(OR1.75,95%CI1.21-2.29,P=.006)和使用心跳和脉搏跟踪监测设备(OR1.60,95%CI0.14-2.07,P=.01)是影响分享数据意愿的显著参数。唯一与提供补偿时分享数据意愿相关的因素是印度国籍(OR0.47,95%CI0.24-0.9,P=.02)。决策树分析结果表明,与分享数据意愿相关的三个主要参数是可穿戴设备使用时间、国籍和收入。
大多数可穿戴设备用户表示愿意为研究目的(无论是否有补偿;615/935,65.8%)分享他们的数据。使用可穿戴设备超过 6 个月、印度国籍或美国(美利坚合众国)国籍且年收入超过 20000 美元的个人更有可能愿意分享这些数据。愿意分享数据的印度国籍个人对补偿的期望明显低于美国国籍个人(P=.02)。