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Understanding quantified-selfers' practices in collecting and exploring personal data

Authors:

Eun Kyoung Choe,

Julie A. KientzAuthors Info & Claims

CHI '14: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Pages 1143 - 1152

https://doi.org/10.1145/2556288.2557372

Published: 26 April 2014 Publication History

Abstract

Researchers have studied how people use self-tracking technologies and discovered a long list of barriers including lack of time and motivation as well as difficulty in data integration and interpretation. Despite the barriers, an increasing number of Quantified-Selfers diligently track many kinds of data about themselves, and some of them share their best practices and mistakes through Meetup talks, blogging, and conferences. In this work, we aim to gain insights from these "extreme users," who have used existing technologies and built their own workarounds to overcome different barriers. We conducted a qualitative and quantitative analysis of 52 video recordings of Quantified Self Meetup talks to understand what they did, how they did it, and what they learned. We highlight several common pitfalls to self-tracking, including tracking too many things, not tracking triggers and context, and insufficient scientific rigor. We identify future research efforts that could help make progress toward addressing these pitfalls. We also discuss how our findings can have broad implications in designing and developing self-tracking technologies.

References

[1]

Ali, A.A., Hossain, S.M., Hovsepian, K., Rahman, M.M., Plarre, K., & Kumar, S. mPuff: automated detection of cigarette smoking puffs from respiration measurements. IPSN '12, (2012), 269--80.

Digital Library

[2]

Bentley, F. et al. Health Mashups: Presenting statistical patterns between wellbeing data and context in natural language to promote behavior change. ToCHI, (2013).

Digital Library

[3]

Beyer, H. & Holtzblatt, K. Contextual Design: Defining Customer-Centered Systems. Morgan Kaufmann (1998).

Digital Library

[4]

Consolvo, S. et al. Activity sensing in the wild: a field trial of Ubifit garden. CHI '08, (2008), 1797--806.

Digital Library

[5]

d3. d3js.org.

[6]

Fitbit. http://www.fitbit.com.

[7]

Fox, S., & Duggan, M. Tracking for health. Pew Internet & American Life Project, January 28, 2013. http://pewinternet.org/Reports/2013/Tracking-forHealth.aspx, accessed on September 17, 2013.

[8]

Google Charts. https://developers.google.com/chart.

[9]

Jawbone UpBand. https://jawbone.com/up.

[10]

Kandel, S., Paepcke, A., Hellerstein, J., & Heer, J. Wrangler: Interactive visual specification of data transformation scripts. CHI '11, (2011), 3363--72.

Digital Library

[11]

Kay, M. et al. Lullaby: a capture & access system for understanding the sleep environment. UbiComp '12, (2012), 226--34.

Digital Library

[12]

Kazdin, A.E. Single-case research designs: Methods for clinical and applied settings. Oxford University Press (2011).

[13]

Klasnja, P., & Pratt, W. Healthcare in the pocket: Mapping the space of mobile-phone health interventions. J Biomed Inform 1 (2012), 184--98.

Digital Library

[14]

Kopp, J. Self-monitoring: A literature review of research and practice. Social Work Research & Abstracts 24, 4, Oxford University Press (1988), 8--20.

[15]

Korotitsch, W.J., & Nelson-Gray, R.O. An overview of self-monitoring research in assessment and treatment. Psychological Assessment 11(4) (1999), 415--25.

[16]

larklife. http://lark.com/products/larklife/experience.

[17]

Li, I., Dey, A., & Forlizzi, J. A stage-based model of personal informatics systems. CHI '10, (2010), 557--66.

Digital Library

[18]

Li, I., Dey, A., & Forlizzi, J. Understanding my data, myself: supporting self-reflection with Ubicomp technologies. UbiComp '11, (2011), 405--14.

Digital Library

[19]

Lin, J.J., Mamykina, L., Lindtner, S., Delajoux, G., Strub, H. Fish-n-Steps: encouraging physical activity with an interactive computer game. UbiComp '06, (2006), 261--78.

Digital Library

[20]

Mamykina, L., Mynatt, E., Davidson, P., Greenblatt, D. MAHI: investigation of social scaffolding for reflective thinking in diabetes management. CHI '08, (2008), 477--86.

Digital Library

[21]

Morris, M., & Guilak, F. Mobile heart health: project highlight. Pervasive Computing 8(2) (2009), 57--61.

Digital Library

[22]

Nike Fuelband. http://www.nike.com/cdp/fuelband.

[23]

Patel, R.A., Klasnja, P., Hartzler, A., Unruh, K.T., & Pratt, W. Probing the benefits of real-time tracking during cancer care. AMIA '12 Fall Symposium, (2012).

[24]

Quantified Mind. http://www.quantified-mind.com.

[25]

Quantified Self. http://quantifiedself.com.

[26]

Rosenthal, R. Experimenter effects in behavioral research. Appleton-Century-Crofts (1966).

[27]

Swan, M. Emerging patient-driven health care models: an examination of health social networks, consumer personalized medicine and quantified self-tracking. Int J Environ Res Public Health 6(2) (2009), 492--525.

[28]

Technology Review. http://www.technologyreview.com /news/514356/stephen-wolfram-on-personal-analytics.

[29]

Troshynski, E., Lee, C., & Dourish, P. Accountabilities of presence: reframing location-based systems. CHI '08, (2008), 487--96.

Digital Library

[30]

Wolfram. http://www.wolfram.com.

[31]

Zeo. http://myzeo.com.

Cited By

Arueyingho OAprioku JMarshall PO'Kane A(2024)A Quantitative Report on Type 2 Diabetes Care in Port Harcourt: Insights into Socio-demographic Influences and Opportunities for Digital Health Promotion (Preprint)JMIR Diabetes10.2196/56756Online publication date: 29-Jan-2024
https://doi.org/10.2196/56756
Kelders SKip HBeerlage-de Jong NKöhle N(2024)What does it mean to be engaged with digital health interventions? A qualitative study into the experiences of engaged users and the views of professionalsDIGITAL HEALTH10.1177/2055207624128353010Online publication date: 3-Oct-2024
https://doi.org/10.1177/20552076241283530
Rigal A(2024)On the cult of the individual: The Quantified Self public gatherings, self-tracking, and individualismCurrent Sociology10.1177/00113921241275680Online publication date: 22-Sep-2024
https://doi.org/10.1177/00113921241275680
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Index Terms

Understanding quantified-selfers' practices in collecting and exploring personal data
1. Applied computing
  1. Life and medical sciences
2. Human-centered computing
  1. Human computer interaction (HCI)

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Published In

cover image ACM Conferences

CHI '14: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

April 2014

4206 pages

ISBN:9781450324731

DOI:10.1145/2556288

General Chairs:
Matt Jones
Swansea University, Wales, UK
,
Philippe Palanque
Université Paul Sabatier, France
,
Program Chairs:
Albrecht Schmidt
University of Stuttgart, Germany
,
Tovi Grossman
Autodesk Research, Canada

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 26 April 2014

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CHI '14: CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2014

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CHI '14 Paper Acceptance Rate 465 of 2,043 submissions, 23%;

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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Cited By

Arueyingho OAprioku JMarshall PO'Kane A(2024)A Quantitative Report on Type 2 Diabetes Care in Port Harcourt: Insights into Socio-demographic Influences and Opportunities for Digital Health Promotion (Preprint)JMIR Diabetes10.2196/56756Online publication date: 29-Jan-2024
https://doi.org/10.2196/56756
Kelders SKip HBeerlage-de Jong NKöhle N(2024)What does it mean to be engaged with digital health interventions? A qualitative study into the experiences of engaged users and the views of professionalsDIGITAL HEALTH10.1177/2055207624128353010Online publication date: 3-Oct-2024
https://doi.org/10.1177/20552076241283530
Rigal A(2024)On the cult of the individual: The Quantified Self public gatherings, self-tracking, and individualismCurrent Sociology10.1177/00113921241275680Online publication date: 22-Sep-2024
https://doi.org/10.1177/00113921241275680
Kouaho WEpstein D(2024)Investigating Perspectives of and Experiences with Low Cost Commercial Fitness WearablesProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36997408:4(1-22)Online publication date: 21-Nov-2024
https://dl.acm.org/doi/10.1145/3699740
Wang DEng JTurpitka MEpstein D(2024)Exploring Activity-Sharing Response Differences Between Broad-Purpose and Dedicated Online Social PlatformsProceedings of the ACM on Human-Computer Interaction10.1145/36868988:CSCW2(1-37)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3686898
Krämer SKottwitz GWoźniak MMeyer JKoelle M(2024)Stepping on the scale? Only in the morning, of course! - Exploring the Lived Experience of Consumer Self-Tracking Technology in the Context of Citizen ScienceProceedings of the 13th Nordic Conference on Human-Computer Interaction10.1145/3679318.3685372(1-17)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3679318.3685372
Yan DBourgeois JKortuem G(2024)Say You, Say Me: Investigating the Personal insights Generated from One's Own data and Other's dataProceedings of the 13th Nordic Conference on Human-Computer Interaction10.1145/3679318.3685345(1-14)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3679318.3685345
Ong ESamson B(2024)Exploring Design Opportunities for Improved Self-motivation in Self-tracking and Health Goal AchievementProceedings of the ACM on Human-Computer Interaction10.1145/36765018:MHCI(1-17)Online publication date: 24-Sep-2024
https://dl.acm.org/doi/10.1145/3676501
Li RKostakos VKay JHoang T(2024)Improving Medical Outcomes through At-Home, Longitudinal Health MonitoringCompanion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing10.1145/3675094.3678364(262-266)Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1145/3675094.3678364
Hu DBhuiyan MLim SWiese JLee S(2024)Unpacking Task Management Tools, Values, and Worker DynamicsProceedings of the 3rd Annual Meeting of the Symposium on Human-Computer Interaction for Work10.1145/3663384.3663402(1-16)Online publication date: 25-Jun-2024
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