Self-Tracking to Do Less: An Autoethnography of Long COVID That Informs the Design of Pacing Technologies

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Long COVID is a post-viral illness where symptoms are still experienced more than three months after an infection of COVID 19. In line with a recent shift within HCI and research on self-tracking towards first-person methodologies, I present the results of an 18-month long autoethnographic study of using a Fitbit fitness tracker whilst having long COVID. In contrast to its designed intentions, I misused my Fitbit to do less in order to pace and manage my illness. My autoethnography illustrates three modes of using fitness tracking technologies to do less and points to the new design space of technologies for reducing, rather than increasing, activity in order to manage chronic illnesses where over-exertion would lead to a worsening of symptoms. I propose that these "pacing technologies"should acknowledge the interoceptive and fluctuating nature of the user's body and support user's decision-making when managing long-term illness and maintaining quality of life.

Original languageEnglish
Title of host publicationCHI 2023 - Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery, Inc.
Publication date2023
Article number656
ISBN (Electronic)9781450394215
Publication statusPublished - 2023
Event2023 CHI Conference on Human Factors in Computing Systems, CHI 2023 - Hamburg, Germany
Duration: 23 Apr 202328 Apr 2023


Conference2023 CHI Conference on Human Factors in Computing Systems, CHI 2023
SponsorACM SIGCHI, Apple, Bloomberg, Google, NSF, Siemens

Bibliographical note

Publisher Copyright:
© 2023 Owner/Author.

    Research areas

  • autoethnography, COVID 19, Fitbit, fitness tracking technologies, Heart-rate monitor, Long COVID, pacing technologies, Phenomenology, Post COVID-19 syndrome, Self-Tracking, Step counting

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