This dissertation research investigates the social implications of computing artifacts that make use of sensor driven self-quantification to implicitly or explicitly direct user behaviors. These technologies are referred to here as self-sensoring prescriptive applications (SSPA’s). This genre of technological application has a strong presence in healthcare as a means to monitor health, modify behavior, improve health outcomes, and reduce medical costs. However, the commercial sector is quickly adopting SSPA’s as a means to monitor and/or modify consumer behaviors as well (Swan, 2013).
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- Partial requirement for: Ph. D., Arizona State University, 2016Note typethesis
- Includes bibliographical references (pages 83-96)Note typebibliography
- Field of study: Psychology