Roque Nelson, Felt John
Center for Healthy Aging, The Pennsylvania State University, 422 Biobehavioral Health Building, University Park, PA, 16801, United States, 1 814-863-7502.
Department of Psychology, University of Central Florida, Orlando, FL, 32816, United States.
JMIR Form Res. 2025 Sep 12;9:e64082. doi: 10.2196/64082.
Digital health technologies, including wearable devices and app-based cognitive and health assessments, are pervasive and crucial to better understanding important public health problems (eg, Alzheimer's disease and related dementias). Central to understanding mechanisms driving individuals' willingness to share various data streams are concerns regarding data privacy, security, and control over generated data.
This survey was designed to learn more about attitudes and opinions related to digital health technologies and the sharing of associated data.
A total of 1509 adults were recruited from Prolific to complete an online survey via Qualtrics. Of these, 1489 participants provided valid data for analyses. Participants completed a structured survey consisting of multiple modules after informed consent was provided. These included: (1) demographic characteristics; (2) prior research experience; (3) mobility factors (eg, use of mobility aids, driving frequency); (4) technology ownership (eg, smartphones, tablets, home Wi-Fi); (5) social media use (eg, frequency of engagement with platforms such as Facebook, Instagram, and TikTok); (6) willingness to contribute different types of data across categories, including activities, sensors, and metadata; (7) opinions about data control and privacy options (eg, data deletion, stream-specific control); and (8) willingness to interact with assistive technologies such as robots, for Instrumental Activities of Daily Living.
The final cohort (N=1489) had a mean age of 35.5 years (SD 12.0), was 44% female (n=652), and predominantly identified as White (76%, n=1134), with high rates of smartphone ownership (99%, n=1479) and home Wi-Fi access (98%, n=1464). Participants were most willing to share data streams with clear health implications and least willing to share data streams with greater privacy or reidentification potential (eg, GPS location, in-vehicle dashcam footage). On average, people were willing to complete ambulatory cognitive assessments for 56.7 (SD 36.2) days, air quality monitoring for 58.1 (SD 37.7) days, and GPS location monitoring for 37 (SD 39.0) days. People expected control over their data, including the ability to delete all or specific streams of the data contributed for research. Most participants prioritized control over their data, with 71% (n=1061) favoring the ability to delete all data contributed for research purposes. Stream-specific data deletion (65%, n=960) and time-specific deletion (44%, n=653) were also valued; interest in sharing data with insurance providers (30%, n=453) or caregivers (26%, n=384) was notably lower.
Findings have implications for the design of digital health technologies and education-related to the use and implications of collected data.
数字健康技术，包括可穿戴设备以及基于应用程序的认知和健康评估，已广泛普及，对于更好地理解重要的公共卫生问题（如阿尔茨海默病及相关痴呆症）至关重要。理解驱动个体愿意共享各类数据流的机制，核心在于对数据隐私、安全以及对所生成数据的控制权的担忧。
本调查旨在进一步了解与数字健康技术及相关数据共享有关的态度和观点。
通过Prolific招募了1509名成年人，通过Qualtrics完成在线调查。其中，1489名参与者提供了有效数据用于分析。参与者在提供知情同意后完成了一个包含多个模块的结构化调查。这些模块包括：（1）人口统计学特征；（2）既往研究经历；（3）行动因素（如使用行动辅助工具、驾驶频率）；（4）技术拥有情况（如智能手机、平板电脑、家庭Wi-Fi）；（5）社交媒体使用情况（如参与Facebook、Instagram和TikTok等平台的频率）；（6）愿意贡献不同类型数据的意愿，包括活动、传感器和元数据；（7）对数据控制和隐私选项的看法（如数据删除、特定数据流控制）；（8）与机器人等辅助技术进行互动以完成日常生活活动的意愿。
最终队列（N = 1489）的平均年龄为35.5岁（标准差12.0），女性占44%（n = 652），主要为白人（76%，n = 1134），智能手机拥有率高（99%，n = 1479），家庭Wi-Fi接入率高（98%，n = 1464）。参与者最愿意共享对健康有明确影响的数据流，最不愿意共享具有更高隐私或重新识别潜力的数据流（如GPS位置、车内行车记录仪 footage）。平均而言，人们愿意进行动态认知评估56.7（标准差36.2）天，空气质量监测58.1（标准差37.7）天，GPS位置监测37（标准差39.0）天。人们期望对自己的数据进行控制，包括能够删除为研究贡献的所有或特定数据流。大多数参与者将数据控制权放在首位，71%（n = 1061）的人赞成能够删除为研究目的贡献的所有数据。特定数据流的数据删除（65%，n = 960）和特定时间的数据删除（44%，n = 653）也受到重视；与保险提供商（30%，n = 453）或护理人员（26%，n = 384）共享数据的兴趣明显较低。
研究结果对数字健康技术的设计以及与所收集数据的使用和影响相关的教育具有启示意义。
