Self-Tracking to Do Less: An Autoethnography of Long COVID That Informs the Design of Pacing Technologies, 2023, Homewood

Sarah Homewood Department of Computer Science, University of Copenhagen sfh@di.ku.dk

Free fulltext:
https://dl.acm.org/doi/pdf/10.1145/3544548.3581505

ABSTRACT

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 frst-person methodologies, I present the results of an 18- month long autoethnographic study of using a Fitbit ftness 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 ftness 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 fuctuating nature of the user’s body and support user’s decision-making when managing long-term illness and maintaining quality of life.

CCS CONCEPTS
• Human-centered computing → Interaction design; Interaction design theory, concepts and paradigms.

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

ACM Reference Format: Sarah Homewood. 2023. Self-Tracking to Do Less: An Autoethnography of Long COVID That Informsthe Design of Pacing Technologies. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI ’23), April 23–28, 2023, Hamburg, Germany. ACM, New York, NY, USA, 14 pages. https://doi.org/10.1145/3544548.3581505