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.

TitelCHI 2023 - Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
ForlagAssociation for Computing Machinery, Inc.
ISBN (Elektronisk)9781450394215
StatusUdgivet - 2023
Begivenhed2023 CHI Conference on Human Factors in Computing Systems, CHI 2023 - Hamburg, Tyskland
Varighed: 23 apr. 202328 apr. 2023


Konference2023 CHI Conference on Human Factors in Computing Systems, CHI 2023
SponsorACM SIGCHI, Apple, Bloomberg, Google, NSF, Siemens

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