Author(s):

  • Nanna Gorm
  • Irina Shklovski

Abstract:

The development of self-tracking technologies has resulted in a burst of research considering how self-tracking practices manifest themselves in everyday life. Based on a 5-month-long photo elicitation study of Danish self-trackers, we argue that no matter how committed people might be to tracking their activities, their use of self-tracking technologies can be best described as episodic rather than continuous. Using Annemarie Mol’s theoretical framework for understanding care practices as a lens, we show how episodic use can be interpreted through the logic of care. By using self-tracking devices episodically, users employ strategies of care in a way that can be productive and useful. These strategies often come in conflict with the logics of choice that underlie the design of many self-tracking technologies. We argue that this has consequences for the way self-tracking devices need to be imagined, designed, and introduced as part of workplace and insurance-type tracking programs.

Documentation:

https://doi.org/10.1177/1461444819851239

References:
Baumer, E, Katz, S, Freeman, J, et al. (2012) Prescriptive persuasion and open-ended social awareness: expanding the design space of mobile health. In: CSCW ’12, Seattle, WA, 11–15 February, pp. 475–484. New York: ACM.
Google Scholar | Crossref
Christophersen, M, Langhoff, T, Bjørn, P (2015) Unforeseen challenges: adopting wearable health data tracking devices to reduce health insurance costs in organizations. In: Antona, M, Stephanidis, C (eds) Universal Access in Human-Computer Interaction. Access to Learning, Health and Well-Being. UAHCI 2015. Lecture Notes in Computer Science, vol. 9177. Springer, Cham, pp. 1–12.
Google Scholar | Crossref
Chung, C, Gorm, N, Shklovski, I, et al. (2017) Finding the right fit: understanding health tracking in workplace wellness programs. In: CHI2017, Denver, CO, 6–11 May.
Google Scholar | Crossref
Clawson, J, Pater, JA, Miller, AD, et al. (2015) No longer wearing: investigating the abandonment of personal health-tracking technologies on craigslist. In: Ubicomp ’15, Osaka, Japan, 7–11 September.
Google Scholar | Crossref
Consolvo, S, Klasnja, P, McDonald, DW, et al. (2008) Flowers or a robot army? Encouraging awareness & activity with personal, mobile displays. In: UbiComp ’08, Seoul, Korea, 21–24 September.
Google Scholar
Danmarks Statistik (2018) Familiernes besiddelse af elektronik i hjemmet efter forbrugsart. Available at: https://www.dst.dk/da/Statistik/emner/priser-og-forbrug/forbrug/elektronik-i-hjemmet
Google Scholar
Didžiokaitė, G, Saukko, P, Greiffenhagen, C (2017) The mundane experience of everyday calorie trackers: beyond the metaphor of quantified self. New Media & Society 20: 1470–1487.
Google Scholar | SAGE Journals
Epstein, DA, Caraway, M, Johnston, C, et al. (2016) Beyond abandonment to next steps: understanding and designing for life after personal informatics tool use. In: CHI’16, San Jose, CA, 7–12 May.
Google Scholar | Crossref
Epstein, DA, Ping, A, Fogarty, J, et al. (2015) A lived informatics model of personal informatics. In: UbiComp ’15, Osaka, Japan, 7–11 September.
Google Scholar | Crossref
Fritz, T, Huang, E, Murphy, G, et al. (2014) Persuasive technology in the real world: a study of long-term use of activity sensing devices for fitness. In: CHI ’14, Toronto, ON, Canada, 26 April–1 May.
Google Scholar | Crossref
Gorm, N, Shklovski, I (2016) Steps, choices, and moral accounting: observations from a step-counting campaign in the workplace. In: CSCW ’16, San Francisco, CA, 27 February–2 March.
Google Scholar | Crossref
Gorm, N, Shklovski, I (2017) Participant driven photo elicitation for understanding episodic activity tracking: benefits and limitations. In: CSCW2017, Portland, OR, 25 February–1 March.
Google Scholar
Gorm, N, Chung, C, Shklovski, I, et al. (2018) 10 years of Qualitative Self-Tracking Studies: A Literature Review. Unpublished Manuscript.
Google Scholar
Kaziunas, E, Lindtner, S, Ackerman, MS, et al. (2018) Lived data: tinkering with bodies, code, and care work. Human-Computer Interaction 33: 49–92.
Google Scholar | Crossref
Kristensen, DB, Ruckenstein, M (2018) Co-evolving with self-tracking technologies. New Media & Society 20: 3624–3640.
Google Scholar | SAGE Journals | ISI
Ledger, D, McCaffrey, D (2014) Inside wearables: how the science of human behavior change offers the secret to long-term engagement. Available at: http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=96736583&site=ehost-live&scope=site
Google Scholar
Lomborg, S, Thylstrup, NB, Schwartz, J (2018) The temporal flows of self-tracking: checking in, moving on, staying hooked. New Media & Society 20: 4590–4607.
Google Scholar | SAGE Journals | ISI
Lupton, D (2013) Quantifying the body: monitoring and measuring health in the age of mHealth technologies. Critical Public Health 23(4): 393–403.
Google Scholar | Crossref | ISI
Lupton, D (2014) Self-tracking modes: reflexive self-monitoring and data practices. Workshop paper, ANU, Canberra, ACT, Australia, August, pp. 1–19.
Google Scholar | Crossref
Lupton, D (2016) The Quantified Self: A Sociology of Self-tracking. Cambridge: Polity Press.
Google Scholar
Lupton, D (2017) How does health feel? Towards research on the affective atmospheres of digital health. Digital Health 3, p.2055207617701276. DOI: 10.1177/2055207617701276.
Google Scholar | SAGE Journals
Maturo, A, Setiffi, F, Maturo, A (2016) The gamification of risk: how health apps foster self-confidence and why this is not enough why this is not enough. Health, Risk & Society 17(7–8): 477–494.
Google Scholar | Crossref
Mol, A (2008) The Logic of Care: Health and the Problem of Patient Choice. New York: Routledge.
Google Scholar | Crossref
Moore, P, Piwek, L (2017) Regulating wellbeing in the brave new quantified workplace. Employee Relations 39(3): 308–316.
Google Scholar | Crossref
Moore, P, Robinson, A (2016) The quantified self: what counts in the neoliberal workplace. New Media & Society 18: 2774–2792.
Google Scholar | SAGE Journals | ISI
Munson, S, Consolvo, S (2012) Exploring goal-setting, rewards, self-monitoring, and sharing to motivate physical activity. In: 2012 6th international conference on pervasive computing technologies for healthcare (PervasiveHealth) and workshops, San Diego, CA, 21–24 May. New York: IEEE.
Google Scholar | Crossref
Nafus, D, Sherman, J (2014) This one does not go up to 11: the quantified self movement as an alternative big data practice. International Journal of Communication 8: 1–11.
Google Scholar
Neff, G, Nafus, D (2016) Self-tracking. Cambridge, MA: MIT Press.
Google Scholar | Crossref
Nissenbaum, H, Patterson, H (2016) Biosensing in context: health privacy in a connected world. In: Nafus, D (ed.) Quantified: Biosensing Technologies in Everyday Life. Cambridge, MA: The MIT Press, pp. 79–100.
Google Scholar | Crossref
Pink, S, Fors, V (2017) Being in a mediated world: self-tracking and the mind–body–environment. Cultural Geographies 24: 375–388.
Google Scholar | SAGE Journals | ISI
Pink, S, Ruckenstein, M, Willim, R, et al. (2018) Broken data: conceptualising data in an emerging world. Big Data & Society 5(1); 2053951717753228 DOI: 10.1177/2053951717753228.
Google Scholar | SAGE Journals
Rooksby, J, Rost, M, Morrison, A, et al. (2014) Personal tracking as lived informatics. In: CHI ’14, Toronto, ON, Canada, 26 April–1 May, pp. 1163–1172. New York: ACM.
Google Scholar | Crossref
Schüll, ND (2016) Data for life: wearable technology and the design of self-care. Biosocieties 11: 317–333.
Google Scholar | Crossref | ISI
Shih, PC, Han, K, Poole, ES, et al. (2015) Use and adoption challenges of wearable activity trackers, pp. 1–12, https://www.ideals.illinois.edu/bitstream/handle/2142/73649/164_ready.pdf?sequence=2&isAllowed=y
Google Scholar
Stokols, D (1996) Translating social ecological theory into guidelines for community health promotion. American Journal of Health Promotion 10: 282–298.
Google Scholar | SAGE Journals | ISI
Weinstein, M (n.d.) TAMS analyzer. Available at: http://tamsys.sourceforge.net/ (accessed 21 August 2018).
Google Scholar
Why Fitbit (n.d.) Available at: https://www.fitbit.com/dk/whyfitbit (accessed 12 September 2018).
Google Scholar
Wijas-Jensen, J (2014) It-anvendelse i Befolkningen 2014. NYT Fra Danmarks Statistik Nr. 339. Danmarks Statistik. Denmark.
Google Scholar
Wilde, N, Hänsel, K, Haddadi, H, et al. (2015) Wearable computing for health and fitness: exploring the relationship between data and human behaviour, pp. 1–23. Available at: https://arxiv.org/abs/1509.05238
Google Scholar