Technology-Assisted Weight Loss Interventions in Primary Care: A Systematic Review
Open accessAbstract
Background The US Preventive Services Task Force recommends screening for and treating obesity. However, there are many barriers to successfully treating obesity in primary care (PC). Technology-assisted weight loss interventions offer novel ways of improving treatment, but trials are overwhelmingly conducted outside of PC and may not translate well into this setting. We conducted a systematic review of technology-assisted weight loss interventions specifically tested in PC settings.Methods We searched the literature from January 2000 to March 2014.Inclusion criteria (1) Randomized controlled trial; (2) trials that utilized the Internet, personal computer, and/or mobile device; and (3) occurred in an ambulatory PC setting. We applied the Cochrane Effective Practice and Organization of Care (EPOC) and Delphi criteria to assess bias and the Pragmatic-Explanatory Continuum Indicator Summary (PRECIS) criteria to assess pragmatism (whether trials occurred in the real world versus under ideal circumstances). Given heterogeneity, results were not pooled quantitatively.Results Sixteen trials met inclusion criteria. Twelve (75 %) interventions achieved weight loss (range: 0.08 kg - 5.4 kg) compared to controls, while 5-45 % of patients lost at least 5 % of baseline weight. Trial duration and attrition ranged from 3-36 months and 6-80 %, respectively. Ten (63 %) studies reported results after at least 1 year of follow-up. Interventions used various forms of personnel, technology modalities, and behavior change elements; trials most frequently utilized medical doctors (MDs) (44 %), web-based applications (63 %), and self-monitoring (81 %), respectively. Interventions that included clinician-guiding software or feedback from personnel appeared to promote more weight loss than fully automated interventions. Only two (13 %) studies used publically available technologies. Many studies had fair pragmatism scores (mean: 2.8/4), despite occurring in primary care.Discussion Compared to usual care, technology-assisted interventions in the PC setting help patients achieve weight loss, offering evidence-based options to PC providers. However, best practices remain undetermined. Despite occurring in PC, studies often fall short in utilizing pragmatic methodology and rarely provide publically available technology. Longitudinal, pragmatic, interdisciplinary, and open-source interventions are needed.
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Bousquet, J., Schünemann, H. J., Togias, A. G., Erhola, M., Hellings, P. W., Zuberbier, T., Agache, I. O., Ansotegui, I. J., Antó, J. M., Bachert, C., et al. (2019) · Kölner Universitäts PublikationsServer (Universität zu Köln) · doi:10.5167/uzh-184076
Designing Calorie Counter Smartphone Applications for Effective Weight Loss
Milliard, S. (2019) · Journal of International Crisis and Risk Communication Research
Changing lifestyle behaviors with personalized feedback delivered via the Internet
Marsaux, C. F. M. (2016) · Research Publications (Maastricht University) · doi:10.26481/dis.20160420cm
Almeida, F. A., You, W., Brito, F. A., Alves, T. F., Goessl, C. L., Wall, S. S., Seidel, R. W., Davy, B. M., Greenawald, M. H., Hill, J. L., et al. (2021) · doi:10.2196/preprints.29751
Rozenblum, R., Cruz, B. A. D. L., Nolido, N. V., McNulty, S., McManus, K. D., Halperin, F., Block, J. P., Bates, D. W., & Baer, H. J. (2022) · PEC Innovation · doi:10.1016/j.pecinn.2022.100057
- Authors
- Levine, D. M., Savarimuthu, S., Squires, A., Nicholson, J., & Jay, M.
- Affiliations
- New York University (US)
- Hofstra University (US)
- VA NY Harbor Healthcare System (US)
- Corresponding author
- Levine, David M.
- Venue
- Journal of General Internal Medicine
- Published
- 2014-08-19
- Volume
- 30
- Issue
- 1
- Pages
- 107-117
- ISSN
- 0884-8734 (ISSN-L)
- 1525-1497
- PMC
- PMC4284284
- OpenAlex
- W2018124350
- Cited by
- 105
- References
- 93
- Citations by year
- 2026: 3 · 2025: 1 · 2024: 2 · 2023: 5 · 2022: 6 · 2021: 14 · 2020: 11 · 2019: 23 · 2018: 8 · 2017: 9 · 2016: 14 · 2015: 6 · 2014: 3
- FWCI
- 1.81
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Journal of General Internal Medicine (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- U.S. Department of Veterans Affairs (IK2 HX000762)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Health Professions › Pharmacy › Obesity and Health Practices
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
- Keywords
- obesity treatment, primary care, online intervention, mobile health, self-monitoring, behavior change, pragmatic trials, weight loss outcomes
- MeSH terms
- Delivery of Health Care, Humans, Obesity, Primary Health Care, Weight Loss, Internet, Biomedical Technology, Mobile Applications
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.
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