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Principles for Designing Context-Aware Applications for Physical Activity Promotion

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Principles for Designing Context-Aware Applications for Physical Activity Promotion Principles for Designing Context-Aware Applications for Physical Activity Promotion by Gaurav Paruthi A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Information) in the University of Michigan 2018 Doctoral Committee: Associate Professor Mark W. Newman, Chair Associate Professor Natalie Colabianchi Assistant Professor Predrag 'Pedja' Klasnja Professor Ken Resnicow Gaurav Paruthi [email protected] ORCID iD: 0000-0002-5100-1578 © Gaurav Paruthi 2018 Acknowledgement I owe the most thanks to my supervisor Mark Newman for his unconditional support and guidance during my Ph.D. I most enjoyed the freedom given to me to pursue multiple intellectual streams. At times, I wasn’t sure how things would converge, but Mark’s confidence in me allowed me to keep pursuing the things that interest me the most. From choosing research projects to exploring startup opportunities, I was fortunate to have an advisor who encouraged and supported me in my endeavors. This freedom allowed me to explore three state of the art technologies- crowdsourcing, machine learning, and hardware prototyping that I was deeply excited about and then successfully explored through the projects described in this dissertation. I want to thank my dissertation committee members: Pedja Klasnja, Natalie Colabianchi, and Ken Resnicow. Their support and feedback helped me to focus and take the individual projects to completion. I would also like to note that I wouldn’t have had the opportunity to explore the area of Health behavior without Pedja’s support. I was always motivated by his excitement and vision of how research and design can have a significant impact in improving the health behavior of people. I was lucky to have great mentors throughout my Ph.D. and even before I came to Ann Arbor. I feel incredibly fortunate to be advised my Bill Thies at Microsoft Research who inspired me to pursue research and showed how hard work and dedication could have a positive impact on the lives of people. Thanks to Joyojeet Pal, who taught me two of the most memorable courses I took and for his mentoring throughout my Ph.D. journey. Many thanks to Mark Ackerman for his supervision during my earlier years. I also thank Qiaozhu Mei for being a great teacher and thereby influencing my research interests towards machine learning. ii I thank my colleagues and friends who helped make this long journey enjoyable. Thanks to my lab mates at the Interaction Ecologies Group- Tao Dong, Rayoung Yang, Yungju Chang, Chuanche Huang and Shriti Raj for being excellent collaborators and providing constant feedback to help me and my work reach the high quality. Thanks to my friends Priyank Chandra and Gaurav Singhal, with whom I brainstormed countless ideas, learned new things and shared some great memories. I also thank Seongseok You, Cindy Lin, Seyram Avle, Hariharan Subramonyam, Tawfiq Ammari, Daphne Chang, my Ph.D. cohort, and many other friends for being around to help out whenever needed. Finally, this journey wouldn’t have been completed without the support of my family. My mom and dad have been a tremendous source of inspiration and support during the long time I have been away from home. My brothers Saurab, Anshul and Adit for always being there and sharing many exciting adventures. Last but not the least a big thanks to my partner Chenfang who kept me going all these years and gave me many reasons to be excited about all that the future holds. iii Contents Acknowledgement .................................................................................................................. ii List of Figures ......................................................................................................................... vi List of Tables ........................................................................................................................ viii Abstract ................................................................................................................................. ix Chapter 1 Introduction ........................................................................................................... 1 Vision of Context-Aware Systems for Behavior Change .................................................................... 3 Challenges of Designing a Context-aware System for Physical Activity Promotion ............................ 5 The Thesis Statement ....................................................................................................................... 6 Chapter 2 Related Work ......................................................................................................... 8 Role of Context in Physical Activity Promotion ................................................................................. 9 Computational representations of Context ..................................................................................... 11 Scalable message generation .......................................................................................................... 15 Conclusion ..................................................................................................................................... 15 Chapter 3 Finding the Sweet Spot(s): Understanding Context to Support Physical Activity Plans ..................................................................................................................................... 17 Introduction ................................................................................................................................... 17 Related Work ................................................................................................................................. 19 Methods ........................................................................................................................................ 22 Findings .......................................................................................................................................... 24 iv Discussion ...................................................................................................................................... 32 Design Implications ........................................................................................................................ 36 Limitations ..................................................................................................................................... 39 Conclusion ..................................................................................................................................... 40 Chapter 4 Heed: Exploring the Design of Situated Self-Reporting Devices .............................. 41 Introduction ................................................................................................................................... 42 Related Work ................................................................................................................................. 44 Design Process and Implementation ............................................................................................... 46 Evaluation ...................................................................................................................................... 50 Method .......................................................................................................................................... 54 Results ........................................................................................................................................... 56 Discussion ...................................................................................................................................... 66 Design Implications ........................................................................................................................ 67 Limitations ..................................................................................................................................... 69 Conclusion ..................................................................................................................................... 70 Chapter 5 Crowdsourcing Messages for Behavior Change Interventions ................................ 71 Introduction ................................................................................................................................... 72 Related work .................................................................................................................................. 74 Crowdsourcing Systems .................................................................................................................. 76 System Design ................................................................................................................................ 77 Evaluation of Quality ...................................................................................................................... 81 Results: Quality and Cost of messages ............................................................................................ 87 Discussion ...................................................................................................................................... 90 Conclusion ..................................................................................................................................... 92 Chapter 6 Conclusion ............................................................................................................
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