Abstract
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.
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Nunes, F., Verdezoto, N., Fitzpatrick, G., Kyng, M., Grönvall, E., Storni, C.: Self-care technologies in HCI: trends, tensions, and opportunities. ACM Trans. Comput.-Hum. Interact. 22(6), 1–45 (2015)
Andersen, T.O., Langstrup, H., Lomborg, S.: Experiences with wearable activity data during self-care by chronic heart patients: qualitative study. J. Med. Internet Res. (7), e15873 (2020)
Ayobi, A., Marshall, P., Cox, A.L., Chen, Y.: Quantifying the body and caring for the mind: self-tracking in multiple sclerosis. In: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, New York, NY, USA, pp. 6889–690. ACM (2017)
Bossen, C., Pine, K.H., Cabitza, F., Ellingsen, G., Piras, E.M.: Data work in healthcare: an introduction. Health Inform. J. 25(3), 465–474 (2019)
Torenholt, R., Saltbæk, L., Langstrup, H.: Patient data work: filtering and sensing patient-reported outcomes. Sociol. Health Illn. 42(6), 1379–1393 (2020)
Epstein, D.A., et al.: Mapping and taking stock of the personal informatics literature. In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, New York, NY, USA, vol. 4, no. 4, pp. 1–38. ACM (2020)
Shin, G., et al.: Wearable activity trackers, accuracy, adoption, acceptance and health impact: a systematic literature review. J. Biomed. Inform. 93(1), 103153 (2019)
Ancker, J.S., Witteman, H.O., Hafeez, B., Provencher, T., Van de Graaf, M., Wei, E.: “You get reminded you’re a sick person”: personal data tracking and patients with multiple chronic conditions. J. Med. Internet Res. 17(8), e4209 (2015)
Rosenberg, D., Kadokura, E.A., Bouldin, E.D., Miyawaki, C.E., Higano, C.S., Hartzler, A.L.: Acceptability of Fitbit for physical activity tracking within clinical care among men with prostate cancer. In: AMIA Annual Symposium Proceedings, Bethesda, MD, USA, vol. 2016, p. 1050. American Medical Informatics Association (2016)
Mamykina, L., Mynatt, E., Davidson, P., Greenblatt, D.: MAHI: investigation of social scaffolding for reflective thinking in diabetes management. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, New York, NY, USA, pp. 477–486. ACM (2008)
Chung, C.F., et al.: Boundary negotiating artifacts in personal informatics: patient-provider collaboration with patient-generated data. In: Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing, New York, NY, USA, pp. 770–786. ACM (2016)
Figueiredo, M.C., Caldeira, C., Reynolds, T.L., Victory, S., Zheng, K., Chen, Y.: Self-tracking for fertility care: collaborative support for a highly personalized problem. In: Proceedings of the ACM on Human-Computer Interaction, New York, NY, USA, pp. 1–21. ACM (2017)
Kaziunas, E., Ackerman, M.S., Lindtner, S., Lee, J.M.: Caring through data: attending to the social and emotional experiences of health datafication. In: Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing, New York, NY, USA, pp. 2260–2272. ACM (2017)
Sanches, P., et al.: HCI and affective health: taking stock of a decade of studies and charting future research directions. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, New York, NY, USA, pp. 1–17. ACM (2019)
Lee, K., et al.: Toward future-centric personal informatics: expecting stressful events and preparing personalized interventions in stress management. In: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, pp. 1–13. ACM, New York, NY, USA (2020)
Desai, P.M., Mitchell, E.G., Hwang, M.L., Levine, M.E., Albers, D.J., Mamykina, L.: Personal health oracle: explorations of personalized predictions in diabetes self-management. In: Cui, W., Zheng, J., Lewis, B., Vogel, D., Bi, X. (eds.) Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, New York, NY, USA, pp. 1–13. ACM (2019)
Rho, S., et al.: FutureSelf: what happens when we forecast self-trackers’ future health statuses? In: Marshall, J., Tennet, P. (eds.) Proceedings of the 2017 Conference on Designing Interactive Systems, New York, NY, USA, pp. 637–648. ACM (2017)
Piras, E.M., Miele, F.: Clinical self-tracking and monitoring technologies: negotiations in the ICT-mediated patient–provider relationship. Health Sociol. Rev. 26(1), 38–53 (2017)
Mercer, K., Giangregorio, L., Schneider, E., Chilana, P., Li, M., Grindrod, K.: Acceptance of commercially available wearable activity trackers among adults aged over 50 and with chronic illness: a mixed-methods evaluation. JMIR Mhealth Uhealth 4(1), e4225 (2016)
Zhu, H., Colgan, J., Reddy, M., Choe, E.K.: Sharing patient-generated data in clinical practices: an interview study. In: AMIA Annual Symposium Proceedings, Bethesda, MD, USA, vol. 2016, p. 1303. American Medical Informatics Association (2016)
Ancker, J.S., Witteman, H.O., Hafeez, B., Provencher, T., Van de Graaf, M., Wei, E.: The invisible work of personal health information management among people with multiple chronic conditions: qualitative interview study among patients and providers. J. Med. Internet Res. 17(6), e4381 (2015)
Li, I., Dey, A., Forlizzi, J.: A stage-based model of personal informatics systems. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, New York, NY, USA, pp. 557–566. ACM (2010)
Fleck, R., Fitzpatrick, G.: Reflecting on reflection: framing a design landscape. In: Viller, SA., Kraal, B. (eds.) Proceedings of the 22nd Conference of the Computer-Human Interaction Special Interest Group of Australia on Computer-Human Interaction, New York, NY, USA, pp. 216–223. ACM (2010)
Piras, E.M.: Beyond self-tracking: exploring and unpacking four emerging labels of patient data work. Health Informatics J. 25(3), 598–607 (2019)
Ruckenstein, M., Schüll, N.D.: The datafication of health. Annu. Rev. Anthropol. 46(1), 261–278 (2017)
Andersen, T.O., Andersen, PR., Kornum, A.C., Larsen, T.M.: Understanding patient experience: a deployment study in cardiac remote monitoring. In: Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare, New York, NY, USA, pp. 221–230. ACM (2017)
Marent, B., Henwood, F., Darking, M.: Ambivalence in digital health: co-designing an mHealth platform for HIV care. Soc. Sci. Med. 215(1), 133–141 (2018)
Salmela, T., Valtonen, A., Lupton, D.: The affective circle of harassment and enchantment: reflections on the ŌURA Ring as an intimate research device. Qual. Inq. 25(3), 260–270 (2019)
Picard, R.W.: Affective Computing. MIT Press, Cambridge (1997)
Aboulafia, A., Bannon, L.J.: Understanding affect in design: an outline conceptual framework. Theor. Issues Ergon. Sci. 5(1), 4–15 (2004)
Sengers, P., et al.: The enigmatics of affect. In: Proceedings of the 4th Conference on Designing Interactive Systems: Processes, Practices, Methods, and Techniques, New York, NY, USA, pp. 87–98. ACM (2002)
Boehner, K., DePaula, R., Dourish, P., Sengers, P.: Affect: from information to interaction. In: Proceedings of the 4th Decennial Conference on Critical Computing: Between Sense and Sensibility, New York, NY, USA, pp. 59–68. ACM (2005)
Höök, K.: Affective loop experiences – what are they? In: Oinas-Kukkonen, H., Hasle, P., Harjumaa, M., Segerståhl, K., Øhrstrøm, P. (eds.) Persuasive Technology. Lecture Notes in Computer Science, vol. 5033, pp. 1–12. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-68504-3_1
Lottridge, D., Chignell, M., Jovicic, A.: Affective interaction: understanding, evaluating, and designing for human emotion. Rev. Hum. Factors Ergon. 7(1), 197–217 (2011)
Fritsch, J.: Affective interaction design at the end of the world. In: Proceedings of DRS 2018: Catalyst, pp. 896–908. Design Research Society (2018)
Charmaz, K.: Constructing Grounded Theory: A Practical Guide Through Qualitative Analysis. Introducing Qualitative Methods Series (2006)
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Andersen, T.O., Fritsch, J., Matthiesen, S. (2023). Patient Data Work with Consumer Self-tracking: Exploring Affective and Temporal Dimensions in Chronic Self-care. In: Tsanas, A., Triantafyllidis, A. (eds) Pervasive Computing Technologies for Healthcare. PH 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 488. Springer, Cham. https://doi.org/10.1007/978-3-031-34586-9_44
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