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“The sleep data looks way better than I feel.” An autoethnographic account and diffractive reading of sleep-tracking

Anna Nolda Nagele, Julian Hough

Frontiers in Computer Science, Volume: 6

Swansea University Author: Julian Hough

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Abstract

Sleep-tracking products are promising their users an improvement to their sleep by focusing on behavior change but often neglecting the contextual and individual factors contributing to sleep quality and quantity. Making good sleep for productive scheduling a personal responsibility does not necessa...

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Published in: Frontiers in Computer Science
ISSN: 2624-9898
Published: Frontiers Media SA 2024
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa65923
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Abstract: Sleep-tracking products are promising their users an improvement to their sleep by focusing on behavior change but often neglecting the contextual and individual factors contributing to sleep quality and quantity. Making good sleep for productive scheduling a personal responsibility does not necessarily lead to better sleep and may cause stress and anxiety. In an autoethnographic study, the first author of this paper tracked her sleep for one month using a diary, body maps and an Oura ring and compared her subjectively felt sleep experience with the data produced by the Oura app. A thematic analysis of the data resulted in four themes describing the relationship between the user-researcher and her wearable sleep-tracker: (1) good sleep scores are motivating, (2) experience that matches the data leads to sense-making, (3) contradictory information from the app leads to frustration, and (4) the sleep-tracker competes with other social agents. A diffractive reading of the data and research process, following Karen Barad's methodology, resulted in a discussion of how data passes through the analog and digital apparatus and what contextual factors are left out but still significantly impact sleep quality and quantity. We add to a canon of sleep research recommending a move away from representing sleep in terms of comparison and competition, uncoupling it from neoliberal capitalistic productivity and self-improvement narratives which are often key contributing factors to bad sleep in the first place.
Keywords: sleep, sleep-tracking, autoethnography, personal informatics, design research, biodata,wearable technology, diract
College: Faculty of Science and Engineering
Funders: The author(s) declare financial support was received for the research, authorship, and/or publication of this article. AN’s work was funded by the EPSRC and AHRC Centre for Doctoral Training in Media and Arts Technology at Queen Mary University of London [grant number EP/L01632X/1]. JH’s work was partly funded by UKRI EPSRC’s FLUIDITY project [grant number EP/X009343/1].