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Understanding quantified-selfers' practices in collecting and exploring personal data
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.
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“Following methodological recommendations concerning compliance of Mechanical Turk participants [18], we eliminated 26 respondents based on their responses to open ended questions, leaving us with a sample of 74 users.”
From Progressive Disclosure: When, Why, and How Do Users Want Algorithmic Transparency Information? (2020) · cites this paper as [18]
In the citing paper
“Emotional analytics is perceived as a key application by many users [16,17,18,39,90].”
From Progressive Disclosure: When, Why, and How Do Users Want Algorithmic Transparency Information? (2020) · cites this paper as [18]
In the citing paper
“Research grounded in lived experiences of this extreme user group [5, 8] remains notably absent.”
From 'AI-Induced Delusional Spirals': Understanding Lived Experiences During Maladaptive Human-Chatbot Interactions (2026) · cites this paper as [8]
In the citing paper
“Recent studies suggest that individuals are willing to engage in this effortful process when they expect that the recorded information will serve one of the functions of autobiographical memory described above (Stone et al., 2022; see also Broekhuijsen et al., 2017;Choe et al., 2014;Elsden, Durrant, et al., 2016;Finley et al., 2018;Soares & Storm, 2022).”
From Understanding Autobiographical Memory in the Digital Age: The AMEDIA-Model (2024) · cites this paper as Choe et al., 2014
Citations
Cites
Single-Case Research Designs: Methods for Clinical and Applied Settings
Kazdin, A. E. (1982) · Cited by 2,852
Contextual Design: Defining Customer-Centered Systems
Beyer, H. R., & Holtzblatt, K. (1997) · Cited by 2,748
Single-case research designs: Methods for clinical and applied settings
Hayes, S. C. (1983) · Journal of Behavior Therapy and Experimental Psychiatry · doi:10.1016/0005-7916(83)90018-6 · Cited by 2,677
Experimenter Effects in Behavioral Research
McGuigan, F. J., & Rosenthal, R. (1968) · The American Journal of Psychology · doi:10.2307/1420816 · Cited by 1,633
Consolvo, S., McDonald, D. W., Toscos, T., Chen, M. Y., Froehlich, J. E., Harrison, B. L., Klasnja, P., LaMarca, A., LeGrand, L., Libby, R., et al. (2008) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1357054.1357335 · Cited by 1,133
A stage-based model of personal informatics systems
Li, I., Dey, A., & Forlizzi, J. (2010) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1753326.1753409 · Cited by 1,114
Healthcare in the pocket: Mapping the space of mobile-phone health interventions
Klasnja, P., & Pratt, W. (2012) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2011.08.017 · Cited by 970
Self-citationFish’n’Steps: Encouraging Physical Activity with an Interactive Computer Game
Lin, J. J.-W., Mamykina, L., Lindtner, S., Delajoux, G., & Strub, H. B. (2006) · Lecture notes in computer science · doi:10.1007/11853565_16 · Cited by 853
Swan, M. (2009) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph6020492 · Cited by 730
Kandel, S., Paepcke, A., Hellerstein, J. M., & Heer, J. (2011) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1978942.1979444 · Cited by 581
Research works printed but not linked: 1
- 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. 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.
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Pollack, A. H., Backonja, U., Miller, A., Mishra, S. R., Khelifi, M., Kendall, L., & Pratt, W. (2016) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2858036.2858240 · Cited by 86
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Roomkham, S., Lovell, D. R., Cheung, J., & Perrin, D. (2018) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2018.2811735 · Cited by 90
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Cho, J., Xu, T., Zimmermann-Niefield, A., & Voida, S. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3501991 · Cited by 83
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Sharing Patient-Generated Data in Clinical Practices: An Interview Study.
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GENSI: A new graphical tool to collect ego-centered network data
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The gamification of risk: how health apps foster self-confidence and why this is not enough
Maturo, A. F., & Setiffi, F. (2016) · Health Risk & Society · doi:10.1080/13698575.2015.1136599 · Cited by 72
Dragicevic, P., Jansen, Y., & Moere, A. V. (2021) · Springer eBooks · doi:10.1007/978-3-319-27648-9_94-1 · Cited by 87
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Self-citationLiu, W., Ploderer, B., & Hoang, T. N. (2015) · Australian Conference on Computer-Human Interaction (OzCHI) · doi:10.1145/2838739.2838742 · Cited by 67
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Sauvé, K., Bakker, S., & Houben, S. (2020) · Designing Interactive Systems Conference · doi:10.1145/3357236.3395509 · Cited by 64
Chen, J., Bauman, A. E., & Allman-Farinelli, M. A. (2016) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2015.0159 · Cited by 65
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Metadata
- Authors
- Choe, E. K., Lee, N. B., Lee, B., Pratt, W., & Kientz, J. A.
- Affiliations
- University of Washington (US)
- Microsoft (United States) (US)
- Venue
- Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2014-04-26
- Pages
- 1143-1152
- OpenAlex
- W2151586234
- Cited by
- 766
- References
- 21
- Citations by year
- 2026: 43 · 2025: 65 · 2024: 37 · 2023: 49 · 2022: 53 · 2021: 70 · 2020: 59 · 2019: 60 · 2018: 96 · 2017: 79 · 2016: 65 · 2015: 69 · 2014: 20
- FWCI
- 59.91
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- self-tracking, quantified self, personal data collection, scientific rigor, user practices
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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