Motivation and Its Relationship to Adherence to Self-monitoring and Weight Loss in a 16-week Internet Behavioral Weight Loss Intervention
Abstract
Objective To examine changes in motivation and the relationship of motivation to adherence to self-monitoring and weight loss in a 16-week Internet behavioral weight-loss intervention. Design Two-group randomized design. Setting This study was conducted over the Internet. Participants Sixty-six women, ages 22-65, with a body mass index (BMI) between 25 and 40, and with a home computer with Internet access, participated. Intervention These data are from an Internet behavioral weight-loss program in which all participants received a face-to-face initial session followed by the 16-week Internet program. Main outcome measures Adherence to self-monitoring and weight loss were the main outcome measures. Analysis Linear regression and mediation analysis using the Baron and Kenny method were conducted. Results Autonomous motivation increased initially and remained high for those who ultimately achieved a 5% weight loss, but declined over time for participants who did not achieve a 5% weight loss. Autonomous motivation at 4 weeks was a predictor of adherence to self-monitoring and 16-week weight loss. Adherence mediated the relationship between autonomous motivation and weight loss. Conclusions and implications These results suggest that autonomous motivation may be a promising intervention target for promoting program procedure adherence and weight loss.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
It is likely that adherence behaviors have shared variance and clustering because they are behavioral representations of similar constructs such as motivation.
“For example, it is likely that adherence behaviors have shared variance and clustering given that they are behavioral representations of similar constructs such as motivation (Webber et al., 2010).”
From Associations Between Self-Monitoring and Weight Change in Behavioral Weight Loss Interventions (2019) · cites this paper as Webber et al., 2010
Cites
Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin
(2002) · New England Journal of Medicine · doi:10.1056/nejmoa012512 · Cited by 19,011 · see citing works
Self-determination theory: A macrotheory of human motivation, development, and health
Deci, E. L., & Ryan, R. M. (2008) · Canadian Psychology / Psychologie canadienne · doi:10.1037/a0012801 · Cited by 6,664 · see citing works
Elfhag, K., & Rössner, S. (2005) · Obesity Reviews · doi:10.1111/j.1467-789x.2005.00170.x · Cited by 1,343 · see citing works
Using Internet technology to deliver a behavioral weight loss program
Tate, D. F. (2001) · JAMA · doi:10.1001/jama.285.9.1172 · Cited by 925 · see citing works
Self-citationTate, D. F., Jackvony, E. H., & Wing, R. R. (2003) · JAMA · doi:10.1001/jama.289.14.1833 · Cited by 666 · see citing works
Self-citationResnicow, K., Jackson, A., Wang, T., De, A. K., McCarty, F., Dudley, W. N., & Baranowski, T. (2001) · American Journal of Public Health · doi:10.2105/ajph.91.10.1686 · Cited by 495 · see citing works
A review of psychosocial pre‐treatment predictors of weight control
Teixeira, P. J., Going, S. B., Sardinha, L. B., & Lohman, T. G. (2005) · Obesity Reviews · doi:10.1111/j.1467-789x.2005.00166.x · Cited by 449 · see citing works
Pretreatment predictors of attrition and successful weight management in women
Teixeira, P. J., Going, S. B., Houtkooper, L. B., Cussler, E. C., Metcalfe, L. L., Blew, R. M., Sardinha, L. B., & Lohman, T. G. (2004) · International Journal of Obesity · doi:10.1038/sj.ijo.0802727 · Cited by 371 · see citing works
Smith, D. E., Heckemeyer, C. M., Kratt, P. P., & Mason, D. A. (1997) · Diabetes Care · doi:10.2337/diacare.20.1.52 · Cited by 359 · see citing works
Predicting short-term weight loss using four leading health behavior change theories
Palmeira, A. L., Teixeira, P. J., Branco, T. L., Martins, S. S., Minderico, C. S., Barata, J. T., Serpa, S. O., & Sardinha, L. B. (2007) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/1479-5868-4-14 · Cited by 167 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Meta-analysis of internet-delivered interventions to increase physical activity levels
Davies, C. A., Spence, J. C., Vandelanotte, C., Caperchione, C. M., & Mummery, W. (2012) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/1479-5868-9-52 · Cited by 488 · see citing works
Wieland, L. S., Falzon, L., Sciamanna, C. N., Trudeau, K. J., Brodney Folse, S., Schwartz, J. E., & Davidson, K. W. (2012) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd007675.pub2 · Cited by 195 · see citing works
Desroches, S., Lapointe, A., Ratté, S., Gravel, K., Légaré, F., & Turcotte, S. (2013) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd008722.pub2 · Cited by 187 · see citing works
Christie, D., & Channon, S. (2014) · Diabetes, Obesity and Metabolism · doi:10.1111/dom.12195 · Cited by 180 · see citing works
Asbjørnsen, R. A., Smedsrød, M. L., Solberg Nes, L., Wentzel, J., Varsi, C., Hjelmesæth, J., & van Gemert-Pijnen, J. E. (2019) · Journal of Medical Internet Research · doi:10.2196/14265 · Cited by 150 · see citing works
Forman, E. M., Butryn, M. L., Manasse, S. M., Crosby, R. D., Goldstein, S. P., Wyckoff, E. P., & Thomas, J. G. (2016) · Obesity · doi:10.1002/oby.21601 · Cited by 145 · see citing works
Solbrig, L., Jones, R., Kavanagh, D., May, J., Parkin, T., & Andrade, J. (2017) · Internet Interventions · doi:10.1016/j.invent.2016.12.003 · Cited by 86 · see citing works
Zarski, A.-C., Berking, M., Reis, D., Lehr, D., Buntrock, C., Schwarzer, R., & Ebert, D. D. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.8814 · Cited by 87 · see citing works
“There is empirical evidence showing that the intrinsic motivation to commence an intervention, treatment expectancy, and the ability to focus on future goals influence adherence and attrition in Internet-based interventions [7,14-16].”
BackgroundYardley, L., Ware, L. J., Smith, E. R., Williams, S., Bradbury, K. J., Arden-Close, E. J., Mullee, M. A., Moore, M. V., Peacock, J. L., Lean, M. E., et al. (2014) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/1479-5868-11-67 · Cited by 84 · see citing works
Associations Between Self-Monitoring and Weight Change in Behavioral Weight Loss Interventions
Goldstein, S. P., Goldstein, C. M., Bond, D. S., Raynor, H. A., Wing, R. R., & Thomas, J. G. (2019) · Health Psychology · doi:10.1037/hea0000800 · Cited by 63 · see citing works
“For example, it is likely that adherence behaviors have shared variance and clustering given that they are behavioral representations of similar constructs such as motivation (Webber et al., 2010).”
BackgroundDicker, D., Alfadda, A. A., Coutinho, W., Cuevas, A., Halford, J. C. G., Hughes, C. A., Iwabu, M., Kang, J.-H., Nawar, R., Reynoso, R., et al. (2021) · European Journal of Internal Medicine · doi:10.1016/j.ejim.2021.01.019 · Cited by 56 · see citing works
Webber, K. H., Gabriele, J. M., Tate, D. F., & Dignan, M. B. (2010) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/1479-5868-7-4 · Cited by 50 · see citing works
Self-citationAdherence to a low-fat vs. low-carbohydrate diet differs by insulin resistance status
McClain, A. D., Otten, J. J., Hekler, E. B., & Gardner, C. D. (2013) · Diabetes, Obesity and Metabolism · doi:10.1111/j.1463-1326.2012.01668.x · Cited by 47 · see citing works
“The dominant framework to investigate the determinants of dietary adherence focuses on psychosocial characteristics [2].”
Idris, I., Hampton, J., Moncrieff, F., & Whitman, M. (2020) · JMIR Diabetes · doi:10.2196/15189 · Cited by 25 · see citing works
Frie, K., Hartmann-Boyce, J., Jebb, S., Oke, J., & Aveyard, P. (2020) · Journal of Medical Internet Research · doi:10.2196/15790 · Cited by 20 · see citing works
Factors that influence the use of electronic diaries in health care: scoping review
Daniëls, N. E. M., Hochstenbach, L. M. J., van Zelst, C., van Bokhoven, M. A., Delespaul, P. A. E. G., & Beurskens, A. J. H. M. (2021) · JMIR mhealth and uhealth · doi:10.2196/19536 · Cited by 20 · see citing works
Rodriguez, R., & Quintanilla, C. (2020) · Health Marketing Quarterly · doi:10.1080/07359683.2020.1805892 · Cited by 1 · see citing works
- Authors
- Webber, K. H., Tate, D. F., Ward, D. S., & Bowling, J. M.
- Affiliations
- University of Kentucky (US)
- University of North Carolina at Chapel Hill (US)
- Corresponding author
- Webber, Kelly H.
- Venue
- Journal of Nutrition Education and Behavior
- Publisher
- Elsevier BV
- Published
- 2010-05
- Volume
- 42
- Issue
- 3
- Pages
- 161-167
- ISSN
- 1499-4046 (ISSN-L)
- OpenAlex
- W2022614952
- Cited by
- 134
- References
- 10
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 3 · 2023: 6 · 2022: 10 · 2021: 8 · 2020: 12 · 2019: 12 · 2018: 9 · 2017: 11 · 2016: 5 · 2015: 8 · 2014: 14 · 2013: 7 · 2012: 12
- FWCI
- 12.18
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Nutrition Education and Behavior (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Motivation and Self-Concept in Sports
- Social Sciences › Psychology › Applied Psychology › Behavioral Health and Interventions
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Keywords
- autonomous motivation, weight loss, obesity, women
- MeSH terms
- Adult, Aged, Behavior Therapy, Female, Humans, Middle Aged, Motivation, Patient Compliance, Self Care, Weight Loss, Exercise, Internet, Overweight, Young Adult
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
