Context-Dependent Expectations of Privacy in Self-Generated Mobile Health Data

Abstract

Converging technological, regulatory, and social forces point to a future of health care delivery that will emphasize personalized information generation, open access, and collaborative decision-making. One driver of this transition is the increasing availability of health apps, digital sensors, and other health self monitoring tools that enable individuals to track a broad swath of their own physiological and behavioral health in near-real-time and selectively share that information with an expanding team of supportive clinical care providers, family, friends, and public health experts. Because self-generated health data are subject to few statutory privacy protections, users’ privacy and security rest heavily on their own data management practices, which in turn rest on a number of complex factors, including individual conceptualizations of tracking devices, device wearing habits, and understandings of information flows and privacy rights.The broad goal of this exploratory research was to investigate how users of health self-tracking services engage with and understand the wider context of the health self-tracking ecosystem. We were particularly interested in understanding how individuals understand and utilize their privacy options to manage online health information.