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Using sensing technologies, self-reported information, and interpersonal observations to promote health and well-being in the workplace

Published: 09 September 2019 Publication History

Abstract

This paper outlines a pilot study aimed at identifying salient themes in the awareness of health and well-being and the effects that this can have on one's home life and work behavior. We also sought to identify the factors that lead to lapses in one's awareness of health and well-being issues. Interviews were conducted with individuals who are known to work for extended durations (taxi / Uber drivers). A number of proven methods were used for the collection of pertinent data (i.e., sensing technologies, self-reported information, and interpersonal observations). Finally, design guidelines are presented for the development of technology-based solutions aimed at raising awareness of health and well-being among workers in high-stress occupations.

References

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Self-tracking technologies in the workplace: Quantifying health, behavior and productivity. 2017. Human Resource Management International Digest 25, 5 (2017), 10--12.
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Zhenyu Chen et al. 2013. Unobtrusive sleep monitoring using smartphones. In 2013 7th International Conference on Pervasive Computing Technologies for Healthcare and Workshops. 145--152.
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Marie Helweg-Larsen et al. 2001. Do Moderators of the Optimistic Bias Affect Personal or Target Risk Estimates? A Review of the Literature. Personality and Social Psychology Review 5, 1 (2001), 74--95.
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Sharoda A. Paul. 2010. Understanding Together: Sensemaking in Collaborative Information Seeking (doctoral dissertation ed.). The Pennsylvania State University, University Park, Pennsylvania, PA. https://etda.libraries.psu.edu/catalog/10724
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Yoshihiko Suhara et al. 2017. DeepMood: Forecasting Depressed Mood Based on Self-Reported Histories via Recurrent Neural Networks. In Proceedings of the 26th International Conference on World Wide Web (WWW '17). International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, Switzerland, 715--724.
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Braun Virginia and Clarke Victoria. 2006. Using thematic analysis in psychology. Qualitative Research in Psychology 3, 2 (2006), 77--101.
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Chuang-Wen You et al. 2018. SoberMotion: Leveraging the Force of Probation Officers to Reduce the Risk of DUI Recidivism. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2, 3, Article 146 (Sept. 2018), 34 pages.

Cited By

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  • (2023)Can AI Models Summarize Your Diary Entries? Investigating Utility of Abstractive Summarization for Autobiographical TextInternational Journal of Human–Computer Interaction10.1080/10447318.2023.228609040:24(8655-8673)Online publication date: 30-Nov-2023
  • (2021)Go Gig or Go Home: Enabling Social Sensing to Share Personal Data with Intimate Partner for the Health and Wellbeing of Long-Hour workersProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445278(1-16)Online publication date: 6-May-2021

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  1. Using sensing technologies, self-reported information, and interpersonal observations to promote health and well-being in the workplace

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      cover image ACM Conferences
      UbiComp/ISWC '19 Adjunct: Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers
      September 2019
      1234 pages
      ISBN:9781450368698
      DOI:10.1145/3341162
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Publication History

      Published: 09 September 2019

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      Author Tags

      1. collaborative sensemaking
      2. health
      3. interpersonal observations
      4. well-being
      5. work under influence

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      View all
      • (2023)Can AI Models Summarize Your Diary Entries? Investigating Utility of Abstractive Summarization for Autobiographical TextInternational Journal of Human–Computer Interaction10.1080/10447318.2023.228609040:24(8655-8673)Online publication date: 30-Nov-2023
      • (2021)Go Gig or Go Home: Enabling Social Sensing to Share Personal Data with Intimate Partner for the Health and Wellbeing of Long-Hour workersProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445278(1-16)Online publication date: 6-May-2021

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