Weight loss—there is an app for that! But does it adhere to evidence-informed practices?
Open accessAbstract
Little is known about how much smartphone apps for weight control adhere to evidence-informed practices. The aim of this study was to review and summarize the content of available weight control apps. Information on content, user rating, and price was extracted from iTunes on September 25, 2009. Apps (n = 204) were coded for adherence to 13 evidence-informed practices for weight control. Latent class analysis was used to identify subgroups of apps based on endorsement practices. Only a small percentage of apps had five or more of the 13 practices (15%). Latent class analysis revealed three main types of apps: diet, physical activity, and weight journals (19%); dietary advice and journals (34%); and weight trackers (46%). User ratings were not associated with apps from these three classes. Many apps have insufficient evidence-informed content. Research is needed that seeks to develop, improve, and evaluate these apps.
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?
Considerable attention has been paid to whether existing, often commercial, apps provide theory and evidence-based BCTs.
“To date, considerable attention has been paid to whether existing, often commercial, apps provide theory and evidence-based BCTs [66-71].”
From Understanding Usage of a Hybrid Website and Smartphone App for Weight Management: A Mixed-Methods Study (2014) · cites this paper as [66]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 33 · Cited by 276
Research works printed but not linked: 2
- Abroms, L. C. P. N., & Evans, W. D. (2011). Using mobile phones for health promotion. In N. Harrington (Ed.), eHealth Technologies, in press.
- Hagenaars, J. A., & McCutcheion, A. L. (2002). Applied latent class models. Cambridge: Cambridge University Press.
- Authors
- Breton, E. R., Fuemmeler, B. F., & Abroms, L. C.
- Affiliations
- George Washington University (US)
- Duke University (US)
- Corresponding author
- Fuemmeler, Bernard F
- Venue
- Translational Behavioral Medicine
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-09-13
- Volume
- 1
- Issue
- 4
- Pages
- 523-529
- ISSN
- 1613-9860 (ISSN-L)
- 1869-6716
- PMC
- PMC3717669
- OpenAlex
- W1999652000
- Cited by
- 276
- References
- 33
- Citations by year
- 2025: 4 · 2024: 14 · 2023: 4 · 2022: 5 · 2021: 10 · 2020: 19 · 2019: 23 · 2018: 24 · 2017: 36 · 2016: 42 · 2015: 48 · 2014: 24 · 2013: 17 · 2012: 5
- FWCI
- 27.31
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- public-domain
- Locations
- Translational Behavioral Medicine (publishedVersion, public-domain)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Cancer Institute (K07CA124905)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
- Keywords
- weight loss apps, mobile application, evidence-informed practice, weight management, user ratings, diet apps, physical activity apps, dietary recommendations, app pricing
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