Patterns in Weight and Physical Activity Tracking Data Preceding a Stop in Weight Monitoring: Observational Analysis
Open accessPublished version of a preprint
Abstract
Background: Self-regulation for weight loss requires regular self-monitoring of weight, but the frequency of weight tracking commonly declines over time. Objective: This study aimed to investigate whether it is a decline in weight loss or a drop in motivation to lose weight (using physical activity tracking as a proxy) that may be prompting a stop in weight monitoring. Methods: We analyzed weight and physical activity data from 1605 Withings Health Mate app users, who had set a weight loss goal and stopped tracking their weight for at least six weeks after a minimum of 16 weeks of continuous tracking. Mixed effects models compared weight change, average daily steps, and physical activity tracking frequency between a 4-week period of continuous tracking and a 4-week period preceding the stop in weight tracking. Additional mixed effects models investigated subsequent changes in physical activity data during 4 weeks of the 6-week long stop in weight tracking. Results: People lost weight during continuous tracking (mean −0.47 kg, SD 1.73) but gained weight preceding the stop in weight tracking (mean 0.25 kg, SD 1.62; difference 0.71 kg; 95% CI 0.60 to 0.81). Average daily steps (beta=−220 daily steps per time period; 95% CI −320 to −120) and physical activity tracking frequency (beta=−3.4 days per time period; 95% CI −3.8 to −3.1) significantly declined from the continuous tracking to the pre-stop period. From pre-stop to post-stop, physical activity tracking frequency further decreased (beta=−6.6 days per time period; 95% CI −7.12 to −6.16), whereas daily step count on the day’s activity was measured increased (beta=110 daily steps per time period; 95% CI 50 to 170). Conclusions: In the weeks before people stop tracking their weight, their physical activity and physical activity monitoring frequency decline. At the same time, weight increases, suggesting that declining motivation for weight control and difficulties with making use of negative weight feedback might explain why people stop tracking their weight. The increase in daily steps but decrease in physical activity tracking frequency post-stop might result from selective measurement of more active days.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In some studies (15/189, 7.9%), wearable prices were not transparent.
“In some studies (15/189, 7.9%), wearable prices were not transparent, as data were provided through a variety of participant-owned wearables [87] or the wearable hardware was part of a subscription or a membership fee, that is, Whoop strap of Whoop [178].”
From The impact of wearable technologies in health research: scoping review (2022) · cites this paper as [87]
Some large-scale population-based studies (11/179, 6.1%) relied on secondary data collected with mobile apps or web-based wearable platforms or provided through a wearable company.
“Some large-scale population-based studies (11/179, 6.1%) relied on secondary data collected with mobile apps [87] or web-based wearable platforms [153] or provided through a wearable company [189].”
From The impact of wearable technologies in health research: scoping review (2022) · cites this paper as [87]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Carver, C. S., & Scheier, M. F. (1982) · Psychological Bulletin · doi:10.1037//0033-2909.92.1.111 · Cited by 2,650 · see citing works
Self-monitoring in weight loss: a systematic review of the literature
Burke, L. E., Wang, J., & Sevick, M. A. (2011) · Journal of the American Dietetic Association · doi:10.1016/j.jada.2010.10.008 · Cited by 1,203 · cited 2× · see citing works
“The repeated measurement and tracking of weight over time, also referred to as self-monitoring, is a common component of weight loss interventions and is consistently associated with greater weight loss [1].”
BackgroundDennison, L., Morrison, L., Conway, G., & Yardley, L. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2583 · Cited by 895 · see citing works
Understanding the Hawthorne effect
Sedgwick, P., & Greenwood, N. (2015) · BMJ · doi:10.1136/bmj.h4672 · Cited by 824 · see citing works
Understanding quantified-selfers' practices in collecting and exploring personal data
Choe, E. K., Lee, N. B., Lee, B., Pratt, W., & Kientz, J. A. (2014) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/2556288.2557372 · Cited by 766 · see citing works
Should We Use a Case-Crossover Design?
Maclure, M., & Mittleman, M. A. (2000) · Annual Review of Public Health · doi:10.1146/annurev.publhealth.21.1.193 · Cited by 750 · see citing works
Carter, M. C., Burley, V. J., Nykjaer, C., & Cade, J. E. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2283 · Cited by 666 · see citing works
Self-control: A behavioristic excursion into the lion's den
Kanfer, F. H., & Karoly, P. (1972) · Behavior Therapy · doi:10.1016/s0005-7894(72)80140-0 · Cited by 477 · see citing works
Medical Records That Guide and Teach
Weed, L. L. (1968) · New England Journal of Medicine · doi:10.1056/nejm196803212781204 · Cited by 457 · see citing works
(2015) · doi:10.1145/2750858.2804288 · Cited by 409 · see citing works
Kirk, M. D., Pires, S. M., Black, R. E., Caipo, M., Crump, J. A., Devleesschauwer, B., Döpfer, D., Fazil, A., Fischer-Walker, C. L., Hald, T., et al. (2015) · PLOS Medicine · doi:10.1371/journal.pmed.1001940 · Cited by 346 · see citing works
Burke, L. E., Conroy, M. B., Sereika, S. M., Elci, O. U., Styn, M. A., Acharya, S. D., Sevick, M. A., Ewing, L. J., & Glanz, K. (2011) · Obesity · doi:10.1038/oby.2010.208 · Cited by 329 · see citing works
Clawson, J., Pater, J. A., Miller, A., Mynatt, E. D., & Mamykina, L. (2015) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/2750858.2807554 · Cited by 312 · see citing works
Beyond Abandonment to Next Steps
Epstein, D. A., Caraway, M., Johnston, C., Ping, A., Fogarty, J. A., & Munson, S. A. (2016) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2858036.2858045 · Cited by 256 · see citing works
The efficacy of a daily self‐weighing weight loss intervention using smart scales and e‐mail
Steinberg, D. M., Tate, D. F., Bennett, G. G., Ennett, S., Samuel‐Hodge, C., & Ward, D. S. (2013) · Obesity · doi:10.1002/oby.20396 · Cited by 212 · see citing works
Harrison, D., Marshall, P., Bianchi‐Berthouze, N., & Bird, J. (2015) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/2750858.2805832 · Cited by 162 · see citing works
Determinants for Sustained Use of an Activity Tracker: Observational Study
Hermsen, S., Moons, J., Kerkhof, P., Wiekens, C. J., & de Groot, M. (2017) · JMIR mhealth and uhealth · doi:10.2196/mhealth.7311 · Cited by 148 · see citing works
Occupational and nonoccupational factors in job satisfaction and psychological distress among nurses
Decker, F. H. (1997) · Research in Nursing & Health · doi:10.1002/(sici)1098-240x(199710)20:5 · Cited by 143 · see citing works
‘The Ostrich Problem’: Motivated Avoidance or Rejection of Information About Goal Progress
Webb, T. L., Chang, B. P. I., & Benn, Y. (2013) · Social and Personality Psychology Compass · doi:10.1111/spc3.12071 · Cited by 135 · see citing works
Webber, K. H., Tate, D. F., Ward, D. S., & Bowling, J. M. (2010) · Journal of Nutrition Education and Behavior · doi:10.1016/j.jneb.2009.03.001 · Cited by 134 · see citing works
Patel, M. L., Hopkins, C. M., Brooks, T. L., & Bennett, G. G. (2019) · JMIR mhealth and uhealth · doi:10.2196/12209 · Cited by 130 · see citing works
Using instrumented paper diaries to document self-monitoring patterns in weight loss
Burke, L. E., Sereika, S. M., Music, E., Warziski, M., Styn, M. A., & Stone, A. (2008) · Contemporary Clinical Trials · doi:10.1016/j.cct.2007.07.004 · Cited by 129 · see citing works
Self-weighing promotes weight loss for obese adults
VanWormer, J. J., Martinez, A. M., Martinson, B. C., Crain, A. L., Benson, G. A., Cosentino, D. L., & Pronk, N. P. (2009) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2008.09.022 · Cited by 111 · see citing works
Steinberg, D., Bennett, G. G., Askew, S., & Tate, D. F. (2015) · Journal of the Academy of Nutrition and Dietetics · doi:10.1016/j.jand.2014.12.011 · Cited by 108 · see citing works
Stories of weight management: Factors associated with successful and unsuccessful weight maintenance
Chambers, J. A., & Swanson, V. (2011) · British Journal of Health Psychology · doi:10.1111/j.2044-8287.2011.02030.x · Cited by 63 · see citing works
Huisman, S., Maes, S., De Gucht, V. J., Chatrou, M., & Haak, H. R. (2010) · International Journal of Behavioral Medicine · doi:10.1007/s12529-009-9071-3 · Cited by 60 · see citing works
Weight Maintenance: Self-Regulatory Factors Underpinning Success and Failure
McKee, H., Ntoumanis, N., & Smith, B. (2013) · Psychology & Health · doi:10.1080/08870446.2013.799162 · Cited by 53 · see citing works
Adherent Use of Digital Health Trackers Is Associated with Weight Loss
Pourzanjani, A., Quisel, T., & Foschini, L. (2016) · PLoS ONE · doi:10.1371/journal.pone.0152504 · Cited by 51 · see citing works
Development of tools to study personal weight control strategies: Ox FAB taxonomy
Hartmann‐Boyce, J., Aveyard, P. N., Koshiaris, C., & Jebb, S. A. (2016) · Obesity · doi:10.1002/oby.21341 · Cited by 47 · see citing works
Self-citationPatterns of self-weighing behavior and weight change in a weight loss trial
Zheng, Y., Burke, L. E., Danford, C. A., Ewing, L. J., Terry, M. A., & Sereika, S. M. (2016) · International Journal of Obesity · doi:10.1038/ijo.2016.68 · Cited by 45 · see citing works
Ross, K. M., Eastman, A., & Wing, R. R. (2019) · Obesity · doi:10.1002/oby.22400 · Cited by 43 · see citing works
Hartmann‐Boyce, J., Boylan, A. R., Jebb, S. A., & Aveyard, P. N. (2018) · Qualitative Health Research · doi:10.1177/1049732318784815 · Cited by 40 · see citing works
Self-citationAre Breaks in Daily Self-Weighing Associated with Weight Gain?
Helander, E. E., Vuorinen, A., Wansink, B. C., & Korhonen, I. (2014) · PLoS ONE · doi:10.1371/journal.pone.0113164 · Cited by 38 · see citing works
Frie, K., Hartmann‐Boyce, J., Jebb, S. A., Albury, C., Nourse, R., & Aveyard, P. N. (2017) · JMIR mhealth and uhealth · doi:10.2196/mhealth.8791 · Cited by 34 · see citing works
Self-citationParticipant characteristics as predictors of attrition in worksite weight loss
Fowler, J. L., Follick, M. J., Abrams, D. B., & Rickard-Figueroa, K. (1985) · Addictive Behaviors · doi:10.1016/0306-4603(85)90044-9 · Cited by 25 · see citing works
Chang, B. P. I., Webb, T. L., & Benn, Y. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.00152 · Cited by 22 · see citing works
LaRose, J. G., Lanoye, A. M., Tate, D. F., & Wing, R. R. (2016) · Obesity Science & Practice · doi:10.1002/osp4.24 · Cited by 20 · see citing works
Boutelle, K. N. (2006) · Journal of Nutrition Education and Behavior · doi:10.1016/j.jneb.2006.04.002 · Cited by 18 · see citing works
Making Sense in the Long Run: Long-Term Health Monitoring in Real Lives
Meyer, J., Beck, E., Wasmann, M., & Boll, S. (2017) · IEEE International Conference on Healthcare Informatics (ICHI) · doi:10.1109/ichi.2017.11 · Cited by 17 · see citing works
Weighing and Body Monitoring Among College Women: The Scale Number as an Emotional Barometer
Mintz, L. B., Awad, G. H., Stinson, R. D., Bledman, R. A., Coker, A. D., Kashubeck‐West, S., & Connelly, K. E. (2013) · Journal of College Student Psychotherapy · doi:10.1080/87568225.2013.739039 · Cited by 16 · see citing works
Zheng, Y., Sereika, S. M., Ewing, L. J., Danford, C. A., Terry, M. A., & Burke, L. E. (2015) · Journal of the Academy of Nutrition and Dietetics · doi:10.1016/j.jand.2015.10.014 · Cited by 16 · see citing works
Benefits of Lifestyle Modification in the Pharmacologic Treatment of Obesity: A Randomized Trial
Wadden, T. A., Berkowitz, R. I., Sarwer, D. B., Prus-Wisniewski, R., & Steinberg, C. (2001) · Archives of Internal Medicine · doi:10.1001/archinte.161.2.218 · Cited by 1 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [18]Shih PC Han K Poole E Rosson M Carroll JM Use and Adoption Challenges of Wearable Activity Trackers Proceedings of the 2015 iConference 2015 iConference'15 March 24-27, 2015 Newport Beach, CA, USA
Cited by
Sorted by citations
The impact of wearable technologies in health research: scoping review
Huhn, S., Axt, M., Gunga, H.-C., Maggioni, M. A., Munga, S., Obor, D., Sié, A., Boudo, V., Bunker, A., Sauerborn, R., et al. (2022) · JMIR mHealth and uHealth · doi:10.2196/34384 · Cited by 379 · see citing works
Pépin, J. L., Bruno, R. M., Yang, R.-Y., Vercamer, V., Jouhaud, P., Escourrou, P., & Boutouyrie, P. (2020) · Journal of Medical Internet Research · doi:10.2196/19787 · Cited by 108 · see citing works
Wren, G. M., Koutoukidis, D. A., Scragg, J., Whitman, M., & Jebb, S. (2023) · Journal of Medical Internet Research · doi:10.2196/43869 · Cited by 25 · see citing works
Self-citation
- Authors
- Frie, K., Hartmann-Boyce, J., Jebb, S., Oke, J., & Aveyard, P.
- Affiliations
- University of Oxford (GB)
- Corresponding author
- Frie, Kerstin
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2020-03-17
- Volume
- 22
- Issue
- 3
- Pages
- e15790
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC7109615
- OpenAlex
- W3010798840
- Cited by
- 20
- References
- 42
- Citations by year
- 2025: 4 · 2024: 3 · 2023: 2 · 2022: 4 · 2021: 6 · 2020: 1
- FWCI
- 3.75
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Wellcome Trust
- National Institute for Health and Care Research (NF-SI-0617-10064, NF-SI-0617-10080)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- weight monitoring, weight loss, physical activity monitoring, self-monitoring, motivation, step count, wearable activity trackers, weight gain, selective measurement, negative feedback
- MeSH terms
- Body Weight, Female, Humans, Male, Middle Aged, Weight Loss, Exercise, Cross-Over Studies
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.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
