ReviewJMIR mHealth and uHealth2019
A Focused Review of Smartphone Diet-Tracking Apps: Usability, Functionality, Coherence With Behavior Change Theory, and Comparative Validity of Nutrient Intake and Energy Estimates.
Review in JMIR mHealth and uHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 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
85 citing papers in PubMed, 8 syntheses or guidelines pooled it, 184 citations in OpenAlex.
- The Effect of the Menstrual Cycle on Energy Intake: A Systematic Review and Meta-analysis.Nutrition reviews · 2025Pooled it
- Sustainability of Weight Loss Through Smartphone Apps: Systematic Review and Meta-analysis on Anthropometric, Metabolic, and Dietary Outcomes.Journal of medical Internet research · 2022Pooled it
- System Usability Scale Benchmarking for Digital Health Apps: Meta-analysis.JMIR mHealth and uHealth · 2022Pooled it
- Usage of Mobile Applications or Mobile Health Technology to Improve Diet Quality in Adults.Nutrients · 2022Pooled it
- Measurement Properties of Smartphone Approaches to Assess Diet, Alcohol Use, and Tobacco Use: Systematic Review.JMIR mHealth and uHealth · 2022Pooled it
- Middle-aged and older adults' acceptance of mobile nutrition and fitness apps: A systematic mixed studies review.PloS one · 2022Pooled it
- A Systematic Review and Meta-Analysis of Validation Studies Performed on Dietary Record Apps.Advances in nutrition (Bethesda, Md.) · 2021Pooled it
- Mobile Apps for Health Behavior Change in Physical Activity, Diet, Drug and Alcohol Use, and Mental Health: Systematic Review.JMIR mHealth and uHealth · 2020Pooled it
- Effect of a mobile phone application for dietary self-monitoring on obesity in adolescents: a pilot randomized controlled trial.European journal of clinical nutrition · 2026Trial
- Trial
- Usability of myfood24 Healthcare and Mathematical Diet Optimisation in Clinical Populations: A Pilot Feasibility Randomised Controlled Trial.Nutrients · 2022Trial
- Mobile health assisted self-monitoring is acceptable for supporting weight loss in rural men: a pragmatic randomized controlled feasibility trial.BMC public health · 2021Trial
- Functionality Review of Mobile Apps for the Tracking and Self-Management of Fatigue: Systematic Search in App Stores and Content Analysis.JMIR mHealth and uHealth · 2026Article
- Spanish Version of the mHealth App Usability Questionnaire (S-MAUQ): Translation, Adaptation, and Validation Study.JMIR mHealth and uHealth · 2026Article
- Calorie-Counting Apps for Monitoring and Managing Calorie Intake in Adults Living With Weight-Related Chronic Diseases: Decade-Long Scoping Review (2013-2024).JMIR mHealth and uHealth · 2026Article
- Designing a Case Management Mobile Health App for Violence Intervention Programs: Mixed Methods Human-Centered Design Study.JMIR formative research · 2026Article
- A Methodological Framework for Aggregating Branded Food Composition Data in mHealth Nutrition Databases: A Case Presentation.Nutrients · 2026Article
- Responsible data selection method for algorithmic personalization of health apps: a case study on promoting mental health.Frontiers in digital health · 2026Article
- Reliability and Validity of Nutrient Assessment Applications for Canadian Endurance Athletes: MyFitnessPal and Cronometer.Journal of human nutrition and dietetics : the official journal of the British Dietetic Association · 2025Observational
- Emerging Adults Report Internal, External, and Social/Environmental Motivations for Weight-Related Self-Monitoring Application Use.Journal of nutrition education and behavior · 2025Article
25 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
5 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundSmartphone diet-tracking apps may help individuals lose weight, manage chronic conditions, and understand dietary patterns; however, the usabilities and functionalities of these apps have not been well studied.
objectiveThe aim of this study was to review the usability of current iPhone operating system (iOS) and Android diet-tracking apps, the degree to which app features align with behavior change constructs, and to assess variations between apps in nutrient coding.
methodsThe top 7 diet-tracking apps were identified from the iOS iTunes and Android Play online stores, downloaded and used over a 2-week period. Each app was independently scored by researchers using the System Usability Scale (SUS), and features were compared with the domains in an integrated behavior change theory framework: the Theoretical Domains Framework. An estimated 3-day food diary was completed using each app, and food items were entered into the United States Department of Agriculture (USDA) Food Composition Databases to evaluate their differences in nutrient data against the USDA reference.
resultsOf the apps that were reviewed, LifeSum had the highest average SUS score of 89.2, whereas MyDietCoach had the lowest SUS score of 46.7. Some variations in features were noted between Android and iOS versions of the same apps, mainly for MyDietCoach, which affected the SUS score. App features varied considerably, yet all of the apps had features consistent with Beliefs about Capabilities and thus have the potential to promote self-efficacy by helping individuals track their diet and progress toward goals. None of the apps allowed for tracking of emotional factors that may be associated with diet patterns. The presence of behavior change domain features tended to be weakly correlated with greater usability, with R
conclusionsAlmost all reviewed diet-tracking apps scored well with respect to usability, used a variety of behavior change constructs, and accurately coded calories and carbohydrates, allowing them to play a potential role in dietary intervention studies.
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.