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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 Orcid Logo

Frontiers in Computer Science, Volume: 6

Swansea University Author: Julian Hough Orcid Logo

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DOI (Published version): 10.3389/fcomp.2024.1258289

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
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URI: https://cronfa.swan.ac.uk/Record/cronfa65923
first_indexed 2024-03-27T16:06:52Z
last_indexed 2024-11-25T14:17:07Z
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spelling 2024-04-15T16:16:51.3912519 v2 65923 2024-03-27 “The sleep data looks way better than I feel.” An autoethnographic account and diffractive reading of sleep-tracking 082d773ae261d2bbf49434dd2608ab40 0000-0002-4345-6759 Julian Hough Julian Hough true false 2024-03-27 MACS 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. Journal Article Frontiers in Computer Science 6 Frontiers Media SA 2624-9898 sleep, sleep-tracking, autoethnography, personal informatics, design research, biodata,wearable technology, diract 21 2 2024 2024-02-21 10.3389/fcomp.2024.1258289 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University Another institution paid the OA fee 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]. 2024-04-15T16:16:51.3912519 2024-03-27T16:00:36.8590713 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Anna Nolda Nagele 1 Julian Hough 0000-0002-4345-6759 2 65923__29864__ff0be4f9a39144f3b73a58e20595247f.pdf NageleHough2024.pdf 2024-03-27T16:09:18.5153180 Output 9163234 application/pdf Version of Record true 2024-03-27T00:00:00.0000000 © 2024 Nagele and Hough. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). true eng http://creativecommons.org/licenses/by/4.0/
title “The sleep data looks way better than I feel.” An autoethnographic account and diffractive reading of sleep-tracking
spellingShingle “The sleep data looks way better than I feel.” An autoethnographic account and diffractive reading of sleep-tracking
Julian Hough
title_short “The sleep data looks way better than I feel.” An autoethnographic account and diffractive reading of sleep-tracking
title_full “The sleep data looks way better than I feel.” An autoethnographic account and diffractive reading of sleep-tracking
title_fullStr “The sleep data looks way better than I feel.” An autoethnographic account and diffractive reading of sleep-tracking
title_full_unstemmed “The sleep data looks way better than I feel.” An autoethnographic account and diffractive reading of sleep-tracking
title_sort “The sleep data looks way better than I feel.” An autoethnographic account and diffractive reading of sleep-tracking
author_id_str_mv 082d773ae261d2bbf49434dd2608ab40
author_id_fullname_str_mv 082d773ae261d2bbf49434dd2608ab40_***_Julian Hough
author Julian Hough
author2 Anna Nolda Nagele
Julian Hough
format Journal article
container_title Frontiers in Computer Science
container_volume 6
publishDate 2024
institution Swansea University
issn 2624-9898
doi_str_mv 10.3389/fcomp.2024.1258289
publisher Frontiers Media SA
college_str Faculty of Science and Engineering
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hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
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description 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.
published_date 2024-02-21T14:29:55Z
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