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Go Gig or Go Home: Enabling Social Sensing to Share Personal Data with Intimate Partner for the Health and Wellbeing of Long-Hour workers

Chuang-Wen You,Tina Chien-Wen Yuan,Nanyi Bi,Min-Wei Hung,Po-Chun Huang,Hao-Chuan Wang

Published 2021 in International Conference on Human Factors in Computing Systems

ABSTRACT

Maintaining an awareness of one’s well-being and making work-related decisions to achieve work-life balance is critical for flexible long-hour workers. In this study, we propose that social sensing could address bottlenecks in worker’s awareness, interpretation of the informatics, and subsequent behavioral change. We conducted a four-week technology probe study by recruiting flexible long-hour professional drivers (Taxi and Uber drivers) and their significant others to use a social sensing prototype which collects data from the drivers and shares it with their partners as well as incorporates partners’ observations. We interviewed them before and after the probe study and found that while technological sensing was able to increase drivers’ awareness of their well-being status and intention to modify behaviors. The “social sensing” design was able to further shape such awareness or intention into action, highlighting the potential of using the sociotechnical approach in promoting work-life balance among long-hour workers.

PUBLICATION RECORD

  • Publication year

    2021

  • Venue

    International Conference on Human Factors in Computing Systems

  • Publication date

    2021-05-06

  • Fields of study

    Medicine, Computer Science

  • Identifiers
    DOI 10.1145/3411764.3445278
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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