Department of Computer Science, University of Vermont, Burlington, VT, United States.
School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, United States.
J Med Internet Res. 2024 Aug 29;26:e57309. doi: 10.2196/57309.
The COVID-19 pandemic gave rise to countless user-facing mobile apps to help fight the pandemic ("COVID-19 mitigation apps"). These apps have been at the center of data privacy discussions because they collect, use, and even retain sensitive personal data from their users (eg, medical records and location data). The US government ended its COVID-19 emergency declaration in May 2023, marking a unique time to comprehensively investigate how data privacy impacted people's acceptance of various COVID-19 mitigation apps deployed throughout the pandemic.
This research aims to provide insights into health data privacy regarding COVID-19 mitigation apps and policy recommendations for future deployment of public health mobile apps through the lens of data privacy. This research explores people's contextual acceptance of different types of COVID-19 mitigation apps by applying the privacy framework of contextual integrity. Specifically, this research seeks to identify the factors that impact people's acceptance of data sharing and data retention practices in various social contexts.
A mixed methods web-based survey study was conducted by recruiting a simple US representative sample (N=674) on Prolific in February 2023. The survey includes a total of 60 vignette scenarios representing realistic social contexts that COVID-19 mitigation apps could be used. Each survey respondent answered questions about their acceptance of 10 randomly selected scenarios. Three contextual integrity parameters (attribute, recipient, and transmission principle) and respondents' basic demographics are controlled as independent variables. Regression analysis was performed to determine the factors impacting people's acceptance of initial data sharing and data retention practices via these apps. Qualitative data from the survey were analyzed to support the statistical results.
Many contextual integrity parameter values, pairwise combinations of contextual integrity parameter values, and some demographic features of respondents have a significant impact on their acceptance of using COVID-19 mitigation apps in various social contexts. Respondents' acceptance of data retention practices diverged from their acceptance of initial data sharing practices in some scenarios.
This study showed that people's acceptance of using various COVID-19 mitigation apps depends on specific social contexts, including the type of data (attribute), the recipients of the data (recipient), and the purpose of data use (transmission principle). Such acceptance may differ between the initial data sharing and data retention practices, even in the same context. Study findings generated rich implications for future pandemic mitigation apps and the broader public health mobile apps regarding data privacy and deployment considerations.
COVID-19 大流行催生了无数面向用户的移动应用程序，以帮助抗击疫情（“COVID-19 缓解应用程序”）。这些应用程序一直是数据隐私讨论的焦点，因为它们从用户那里收集、使用甚至保留敏感的个人数据（例如，医疗记录和位置数据）。美国政府于 2023 年 5 月结束了 COVID-19 紧急状态声明，标志着全面调查数据隐私如何影响人们在整个大流行期间对各种 COVID-19 缓解应用程序的接受程度的独特时期。
本研究旨在通过数据隐私视角，为 COVID-19 缓解应用程序的健康数据隐私提供见解，并为未来公共卫生移动应用程序的部署提供政策建议。本研究通过应用情境完整性隐私框架，探讨了人们对不同类型 COVID-19 缓解应用程序的情境接受程度。具体来说，本研究旨在确定影响人们在各种社会情境下接受数据共享和数据保留实践的因素。
2023 年 2 月，通过在 Prolific 上招募简单的美国代表性样本（N=674），进行了一项混合方法的基于网络的调查研究。该调查包括 60 个虚拟场景，代表 COVID-19 缓解应用程序可能使用的现实社会情境。每位调查受访者回答了 10 个随机选择场景的接受程度问题。三个情境完整性参数（属性、接收者和传输原则）和受访者的基本人口统计学特征被控制为自变量。进行回归分析以确定影响人们通过这些应用程序接受初始数据共享和数据保留实践的因素。调查的定性数据也进行了分析，以支持统计结果。
许多情境完整性参数值、情境完整性参数值的成对组合以及受访者的一些人口统计学特征对他们在各种社会情境下使用 COVID-19 缓解应用程序的接受程度有显著影响。在某些场景中，受访者对数据保留实践的接受程度与他们对初始数据共享实践的接受程度不同。
本研究表明，人们对使用各种 COVID-19 缓解应用程序的接受程度取决于特定的社会情境，包括数据类型（属性）、数据接收者（接收者）和数据使用目的（传输原则）。在同一情境下，这种接受可能在初始数据共享和数据保留实践之间有所不同。研究结果为未来的大流行缓解应用程序和更广泛的公共卫生移动应用程序提供了有关数据隐私和部署考虑的丰富启示。
