Patient Data Work with Consumer Self-tracking: Exploring Affective and Temporal Dimensions in Chronic Self-care

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

Emerging studies are reporting on the implications of self-tracked data in patients’ everyday life and how it influences self-care activities in chronic care. The increased uptake of consumer wearable activity trackers in healthcare contexts and the wider application of advanced analytics is changing the temporal scope from ‘past-centric’ to ‘future-centric’ personal informatics. At the same time, a stream of research is making clear that experiences of emotion are constitutive of patient data work suggesting that the micro practices of engaging with personal data has an important affective dimension. We conducted an exploratory interview study with five chronic heart patients with an implanted cardiac device to conceptualize the data work, which is involved in making sense of self-tracked data from a consumer wearable activity tracker (Fitbit Alta HR). In this paper, we contribute to understanding patient data work as seven forms of micro practices: Verifying, Questioning, Motivating, Reacting, Accepting, Distancing, and Sharing. We discuss how these practices relate to temporal and affective dimensions of engaging with self-tracked data in chronic care and point to future research.

TitelPervasive Computing Technologies for Healthcare - 16th EAI International Conference, PervasiveHealth 2022, Proceedings
RedaktørerAthanasios Tsanas, Andreas Triantafyllidis
Antal sider15
ISBN (Trykt)9783031345852
StatusUdgivet - 2023
Begivenhed16th EAI International Conference on Pervasive Computing Technologies for Healthcare, PH 2022 - Thessaloniki, Grækenland
Varighed: 12 dec. 202214 dec. 2022


Konference16th EAI International Conference on Pervasive Computing Technologies for Healthcare, PH 2022
NavnLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Vol/bind488 LNICST

Bibliografisk note

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© 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

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