TY - GEN

T1 - Patient Data Work with Consumer Self-tracking

T2 - 16th EAI International Conference on Pervasive Computing Technologies for Healthcare, PH 2022

AU - Andersen, Tariq Osman

AU - Fritsch, Jonas

AU - Matthiesen, Stina

N1 - Publisher Copyright: © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

KW - Affective computing

KW - Personal informatics

KW - Self-care

KW - Self-tracking

KW - Wearable activity trackers

UR - http://www.scopus.com/inward/record.url?scp=85164156652&partnerID=8YFLogxK

U2 - 10.1007/978-3-031-34586-9_44

DO - 10.1007/978-3-031-34586-9_44

M3 - Article in proceedings

AN - SCOPUS:85164156652

SN - 9783031345852

T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST

SP - 666

EP - 680

BT - Pervasive Computing Technologies for Healthcare - 16th EAI International Conference, PervasiveHealth 2022, Proceedings

A2 - Tsanas, Athanasios

A2 - Triantafyllidis, Andreas

PB - Springer

Y2 - 12 December 2022 through 14 December 2022

ER -