Location disclosure to social relations: why, when, & what people want to share
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A study of preferences for sharing and privacy
CHI '05 Extended Abstracts on Human Factors in Computing Systems
Privacy practices of Internet users: self-reports versus observed behavior
International Journal of Human-Computer Studies - Special isssue: HCI research in privacy and security is critical now
Privacy in Location-Aware Computing Environments
IEEE Pervasive Computing
Exploring Privacy Concerns about Personal Sensing
Pervasive '09 Proceedings of the 7th International Conference on Pervasive Computing
Understanding and capturing people's privacy policies in a mobile social networking application
Personal and Ubiquitous Computing
Do i do what i say?: observed versus stated privacy preferences
INTERACT'07 Proceedings of the 11th IFIP TC 13 international conference on Human-computer interaction
Privacy risks emerging from the adoption of innocuous wearable sensors in the mobile environment
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Designing for peer involvement in weight management
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Exploring reactive access control
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Exposing privacy concerns in mHealth
HealthSec'11 Proceedings of the 2nd USENIX conference on Health security and privacy
Proceedings of the 13th international conference on Ubiquitous computing
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If people are not in control of the collection and sharing of their personal health information collected using mobile health (mHealth) devices and applications, privacy concerns could limit their willingness to use and reduce potential benefits provided via mHealth. We investigated users' willingness to share their personal information, collected using mHealth sensing devices, with their family, friends, third parties, and the public. Previous work employed hypothetical scenarios, surveys and interviews to understand people's information-sharing behavior; to the best of our knowledge, ours is the first privacy study where participants actually have the option to share their own information with real people. We expect our results can guide the development of privacy controls for mobile devices and applications that collect any personal and activity information, not restricted to health or fitness information. Our study revealed three interesting findings about people's privacy concerns regarding their sensed health information: 1) We found that people share certain health information less with friends and family than with strangers, but more with specific third parties than the public. 2) Information that people were less willing to share could be information that is indirectly collected by the mobile devices. 3) We confirmed that privacy concerns are not static; mHealth device users may change their sharing decisions over time. Based on our findings, we emphasize the need for sensible default settings and flexible privacy controls to allow people to choose different settings for different recipients, and to change their sharing settings at any time.