12th EAI International Conference on Pervasive Computing Technologies for Healthcare – Demos, Posters, Doctoral Colloquium

Research Article

Design of a Large-scale Self-Experimentation Tool for Scientific Self-Explorations

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  • @INPROCEEDINGS{10.4108/eai.20-4-2018.2276355,
        author={Sayali S Phatak and Elaine Chen and Stephen M Schueller and Richard L Kravitz and Ida Sim and Christopher H Schmid and Eric B Hekler},
        title={Design of a Large-scale Self-Experimentation Tool for Scientific Self-Explorations},
        proceedings={12th EAI International Conference on Pervasive Computing Technologies for Healthcare -- Demos, Posters, Doctoral Colloquium},
        publisher={EAI},
        proceedings_a={PERVASIVEHEALTH - EAI},
        year={2018},
        month={8},
        keywords={self-experimentation personal informatics self-tracking},
        doi={10.4108/eai.20-4-2018.2276355}
    }
    
  • Sayali S Phatak
    Elaine Chen
    Stephen M Schueller
    Richard L Kravitz
    Ida Sim
    Christopher H Schmid
    Eric B Hekler
    Year: 2018
    Design of a Large-scale Self-Experimentation Tool for Scientific Self-Explorations
    PERVASIVEHEALTH - EAI
    EAI
    DOI: 10.4108/eai.20-4-2018.2276355
Sayali S Phatak1,*, Elaine Chen2, Stephen M Schueller3, Richard L Kravitz4, Ida Sim5, Christopher H Schmid6, Eric B Hekler7
  • 1: Arizona State University
  • 2: WNYC
  • 3: Northwestern University
  • 4: University of California, Davis
  • 5: University of California, San Francisco
  • 6: Brown University
  • 7: University of California, San Diego
*Contact email: sayali.phatak@asu.edu

Abstract

Many behavioral interventions can improve health and wellbeing. However, behavior change is complex and multifaceted, and not all interventions work for everyone. Most evidence for popular interventions is from group-based studies, which poorly predict whether a given intervention would work for a speci c individual. One way in which individuals can nd out if a given intervention works for them is via self-experimentation using N-of-1 study de- signs. We are designing Hack Your Health, a self-experimentation tool where individuals can try popular health-promoting activities (e.g., physical activity, meditation) to test whether they improve their psychological well-being. In this work, we describe insights gained through user research and highlight design implications and challenges in self-experimentation in the context of public health interventions.