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Time Loss Aversion

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HCI International 2023 Posters (HCII 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1832))

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Abstract

The present paper introduces “Time Loss Aversion” - people’s tendency to fear previous misallocations of time, which then motivates people to change their future behaviour. Loss aversion has previously been achieved through framing outcomes as losses. Previous research has induced loss aversion by framing monetary outcomes as losses rather than gains.. It presents a case study where time loss aversion was used to decrease people’s social media use. Social media use was framed in a manner of time spent in one week, a month or a year, rather than in terms of daily averages (the usual approach in screen time apps). This framing significantly motivated people to reduce their future social media use. Time loss aversion has implications for “time-based addictions” - addictions where the misallocation of time results in negative outcomes to people’s health, productivity and well-being. Finally, the paper discusses how time loss aversion can be implemented in the UX and UI of mobile devices and wearables to promote better outcomes for users.

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Author information

Authors and Affiliations

  1. University College London, London, UK

    Ziwei Gao

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  1. Ziwei Gao
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Correspondence to Ziwei Gao .

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Editors and Affiliations

  1. University of Crete and Foundation for Research and Technology - Hellas (FORTH), Heraklion, Crete, Greece

    Constantine Stephanidis

  2. University of Crete and Foundation for Research and Technology - Hellas (FORTH), Heraklion, Crete, Greece

    Margherita Antona

  3. University of Crete and Foundation for Research and Technology - Hellas (FORTH), Heraklion, Crete, Greece

    Stavroula Ntoa

  4. University of Central Florida, Orlando, FL, USA

    Gavriel Salvendy

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Gao, Z. (2023). Time Loss Aversion. In: Stephanidis, C., Antona, M., Ntoa, S., Salvendy, G. (eds) HCI International 2023 Posters. HCII 2023. Communications in Computer and Information Science, vol 1832. Springer, Cham. https://doi.org/10.1007/978-3-031-35989-7_72

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  • DOI: https://doi.org/10.1007/978-3-031-35989-7_72

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-35988-0

  • Online ISBN: 978-3-031-35989-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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