Contextual Expectations of Privacy in Self-Generated Health Information Flows
Contextual Expectations of Privacy in Self-Generated Health Information Flows
复制标题
自生成健康信息流中隐私的背景期望
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
H. Patterson
中科院分区：
文献类型：
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作者：
H. Patterson
技术、监管和社会力量的融合指向了健康决策日益个性化、数据驱动和协作的未来。这种转变的一个突出驱动力是低成本、现成的商业数字自我监测传感器和应用程序的现成可用性，这些传感器和应用程序使个人能够在接近真实的时间内记录大量高度精细的行为和生理健康属性。移动的健康自我量化工具，包括智能计步器、卡路里计数器、心率监测器、睡眠跟踪器和其他“参与式个人数据”收集设备，为个人和公共健康带来了巨大的希望，包括提高身体意识、主动健康参与和社区建设。它们的商业实现也引发了值得密切关注的重大隐私和安全问题。
Converging technological, regulatory, and social forces point to an increasingly personalized, data driven, and collaborative future of health decision-making. A prominent driver of this transition is the ready availability of low-cost, off-the-shelf commercial digital self-monitoring sensors and apps that enable individuals to log broad swaths of highly granular behavioral and physiological health attributes in near real time. Mobile health self-quantification tools, including smart pedometers, calorie counters, heart rate monitors, sleep trackers, and other “participatory personal data” collection devices hold great promise for individuals and for the public health, including increased bodily awareness, proactive health engagement, and community building. Their commercial implementation also raises significant privacy and security issues that warrant close attention.