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.

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Abstract-Mobile health technologies allow patients to collect their health information outside the hospital and share this information with others. But how can data consumers know whether to trust the sensor-collected and human-entered data they receive? Data consumers might be able to verify the accuracy and authenticity of the data if they have information about its origin and about changes made to it, i.e., the provenance of the data. We propose a provenance framework for mHealth devices, to collect and share provenance metadata and help the data consumer verify whether certain provenance properties are satisfied by the data they receive. This paper describes the programming model for this framework, which describes the rules to be implemented for providing provenance-collecting capabilities to an mHealth application. I. PROVENANCE IN MHEALTHConsider Jane, who is using one or more mobile health (mHealth) devices, continuously or periodically collecting her health-related information into her mobile phone. The phone periodically uploads this information, along with other healthrelated information that Jane manually inputs to her phone, to her electronic health record (EHR). Jane can then share her health information with her health providers, family and friends, peers, employer, insurer, and researchers. But how can these data consumers know whether to trust the sensorcollected and human-entered data they receive? What confidence do they have that it is accurate and authentic? Suppose Jane falls sick, and her husband Jack (her caregiver) collects her health information on her behalf. Jack has no experience using the devices. Can the system help him understand when he is not collecting accurate information?Since personal and home-use devices are not maintained regularly, like hospital devices, users like Jane and Jack might not realize when the devices are malfunctioning or uncalibrated. If other people in Jane's household use similar devices, they might accidentally confuse their own device for Jane's. mHealth devices, being mobile, can be stolen or misplaced -and then used by another person. Jane, or her caregivers, might deliberately fake or hide data collected using mHealth devices, when there is an incentive to do so. In all these scenarios, the data collected and shared by the devices might be inaccurate, or about the wrong person. If so, its use could prove damaging or even fatal, especially if the data is used by health providers for diagnosis or treatment.Data consumers might be able to verify the accuracy and authenticity of the data if they have information about its origin and about changes made to it, i.e., the provenance of the data. Previous research has looked at provenance of electronic health records and our work complements this research [1], [2]. In the case of health data that is collected using mobile sensors, it is necessary to collect information about the data's origin, so that consumers can determine the accuracy and authenticity of the data; our framework provides these capabilities, ...

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