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Does the Quantified-Self Lead to Behavior Change?

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Nov 08, 2017

In 2006, marketing commentator, Michael Palmer said “Data is just like crude. It’s valuable, but if unrefined it cannot really be used” [15]. Over a decade on, our lives are more saturated with data than ever, but we still seem far from harnessing its full potential.

Health and well-being is one area in particular where this issue is very prevalent. In recent years, fitness technologies have produced a plethora of data for individuals who want to change, abandon, or adopt particular habits related to their health. Just like crude oil, health data has subsequently become hugely abundant.

However, if we don’t learn how to best navigate and refine the large amounts of data offered by this technology, then it will be difficult to help people use it for the betterment of their health and well-being. This article explores how these difficulties can be overcome, and highlights how behavioral science can untangle the complex relationship between technology and long-lasting behavior change.

References

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[2] Bildl, S. (2014). Gamification of the quantified self. In Stokinger, T., Lindemann, P., Koelle, M., & Kranz, M. Fun, Secure, Embedded. Advances in Embedded Interactive Systems Technical Report – Summer 2014, 2(3), 5-10.

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[7] Fritz, T., Huang, E. M., Murphy, G. C., Zimmerman, T. (2013) Persuasive technology in the real world: A study of long-term use of activity sensing devices for fitness. Proceedings of the ACM Conference on Human Factors in Computing Systems – CHI 14.

[8] Harrison, D., Marshall, P., Bianchi-Berthouze, N., & Bird, J. (2015). Activity tracking. Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing – UbiComp 15.

[9] Hayward, J., Chansin, G., & Zervos, H. (2017) Wearable technology 2017-2027: Markets, Players, Forecasts. Retrieved September 27th 2017, from https://www.idtechex.com/research/reports/wearable-technology-2017-2027-markets-players-forecasts-000536.asp.

[10] Klasnja, P., Consolvo, S., Mcdonald, D. W., Landay, J. A., & Pratt, W. (2009). Using mobile and personal sensing technologies to support health behavior change in everyday life: Lessons learned. AMIA Annual Symposium Proceedings, 2009, 338-342.

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[14] Norman, D. A. (2009). THE WAY I SEE IT. Memory is more important than actuality. Interactions, 16 (2), 24-26.

[15] Palmer, M. (2006). Data is the new oil. 2006. Retrieved September 27th, 2017, from: https://ana.blogs.com/maestros/2006/11/data_is_the_new.html.

[16] Patel, M. S., Asch, D. A., & Volpp, K. G. (2015). Wearable Devices as Facilitators, Not Drivers, of Health Behavior Change. Jama, 313 (5), 459-460.

[17] Pinder, C., Vermeulen, J., Beale, R., & Hendley, R. (2015). Exploring Nonconscious Behavior Change Interventions on Mobile Devices. Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct – MobileHCI 15.

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[19] Sjöklint, M., Constantiou, I. D., & Trier, M. (2015). The Complexities of Self-Tracking – An Inquiry into User Reactions and Goal Attainment. SSRN Electronic Journal.

[20] Stawarz, K., Cox, A. L., & Blandford, A. (2015). Beyond Self-Tracking and Reminders. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems – CHI 15.

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About the Author

Smiling woman with short, straight, light purple hair and red lipstick, wearing a white earring, in front of a dark, patterned background.

Zoe Adams

Queen Mary University of London

Zoe is a PhD candidate in Linguistics at Queen Mary University of London. She is bridging the gap between public health and language attitudes by studying how British accents affect the persuasiveness of public health interventions. Her interests include consumer psychology, attitude change, and stereotyping.

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