Designing personal systems for mindful decision making
Author(s)
Farve, Niaja Nichole![Thumbnail](/bitstream/handle/1721.1/105667/964448324-MIT.pdf.jpg?sequence=3&isAllowed=y)
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Other Contributors
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Pattie Maes.
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Today's personal technologies are generally seen as reducing mindfulness. Users are so absorbed in their devices that they behave in more distracted ways, are less engaged in face-to-face social interactions and increase their sedentary behaviors. This often results in behaviors and habits that are misaligned with the user's goals. Current attempts to use technology to improve well-being, such as fitness trackers, do not take advantage of some of the benefits that mobile, personal technologies have to offer. Specifically, increasingly mobile personal technologies have the opportunity to intervene in the moment when a person is making a decision with personalized, "just-in- time" nudges that may result in a more mindful decision. This thesis explores how to design personalized, wearable technologies that can support more mindful behavior. It investigates the various challenges that exists when designing such systems-.and provides design considerations for future systems. Human behavior researchers have argued that although a user may have the motivation and the ability to change behavior, a trigger is required to make a new behavior happen. This thesis specifically focuses on considerations that should be made when designing triggers for persuasive, wearable systems. These include ensuring the user's attention, utilizing contextual cues to determine timing of triggers and using personalized messages in a trigger. The thesis presents several pilots studies in using personal, wearable technologies to offer "just-in-time" triggers for behavior. The design and implementation of these systems is detailed and preliminary data regarding their effectiveness is discussed. These systems explore what challenges emerge when applying traditional behavior change theories on personalized, wearable systems.
Description
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016. Cataloged from PDF version of thesis. Includes bibliographical references (pages 169-177).
Date issued
2016Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer SciencePublisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.