ArticleTranslational behavioral medicine2011
Weight loss-there is an app for that! But does it adhere to evidence-informed practices?
Article in Translational behavioral medicine, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 140 papers, 8 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
140 citing papers in PubMed, 8 syntheses or guidelines pooled it, 299 citations in OpenAlex.
- Comprehensively addressing postpartum maternal health: a content and image review of commercially available mobile health apps.BMC pregnancy and childbirth · 2021Pooled it
- Adherence of popular smoking cessation mobile applications to evidence-based guidelines.BMC public health · 2019Pooled it
- Gamification for health promotion: systematic review of behaviour change techniques in smartphone apps.BMJ open · 2016Pooled it
- The role of interdisciplinary research team in the impact of health apps in health and computer science publications: a systematic review.Biomedical engineering online · 2016Pooled it
- Mobile Phone and Web 2.0 Technologies for Weight Management: A Systematic Scoping Review.Journal of medical Internet research · 2015Pooled it
- Conditions potentially sensitive to a personal health record (PHR) intervention, a systematic review.BMC medical informatics and decision making · 2015Pooled it
- Pooled it
- Mobile Phone Interventions for the Secondary Prevention of Cardiovascular Disease.Progress in cardiovascular diseasesPooled it
- Trial
- Feasibility of a Digital Health Intervention to Improve Diet Quality Among Women With High Blood Pressure: Randomized Controlled Feasibility Trial.JMIR mHealth and uHealth · 2020Trial
- Quality Measurement and Improvement Study of Surgical Coronary Revascularization: Medication Adherence (MISSION-2).Chinese medical journal · 2018Trial
- Effect of a mobile app intervention on vegetable consumption in overweight adults: a randomized controlled trial.The international journal of behavioral nutrition and physical activity · 2017Trial
- Choosing between responsive-design websites versus mobile apps for your mobile behavioral intervention: presenting four case studies.Translational behavioral medicine · 2017Trial
- Cell phone intervention for you (CITY): A randomized, controlled trial of behavioral weight loss intervention for young adults using mobile technology.Obesity (Silver Spring, Md.) · 2015Trial
- Efficacy of SmartLoss, a smartphone-based weight loss intervention: results from a randomized controlled trial.Obesity (Silver Spring, Md.) · 2015Trial
- Understanding usage of a hybrid website and smartphone app for weight management: a mixed-methods study.Journal of medical Internet research · 2014Trial
- Click "like" to change your behavior: a mixed methods study of college students' exposure to and engagement with Facebook content designed for weight loss.Journal of medical Internet research · 2014Trial
- Trial
- The use of mHealth to deliver tailored messages reduces reported energy and fat intake.The Journal of cardiovascular nursingTrial
- Evaluation of Mobile Intermittent Fasting Applications in Chinese App Stores: Quality Evaluations and Content Analysis.JMIR mHealth and uHealth · 2025Article
80 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.