ArticleJournal of medical Internet research2021
User Perspectives of Diet-Tracking Apps: Reviews Content Analysis and Topic Modeling.
Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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
10 citing papers in PubMed.
- Validity of the PortionSize application compared with that of MyFitnessPal for accurately estimating intake: a randomized crossover laboratory-based evaluation.The American journal of clinical nutrition · 2024Trial
- Evaluating function availability and user satisfaction with nutrition apps: user-generated content analysis and text mining study.Nutrition journal · 2026Article
- Build Deep Neural Network Models to Detect Common Edible Nuts from Photos and Estimate Nutrient Portfolio.Nutrients · 2024Article
- Digital Anti-Aging Healthcare: An Overview of the Applications of Digital Technologies in Diet Management.Journal of personalized medicine · 2024Review
- Review
- Rating analysis and BERTopic modeling of consumer versus regulated mHealth app reviews in Germany.NPJ digital medicine · 2023Article
- Incorporating Consumers' Needs in Nutrition Apps to Promote and Maintain Use: Mixed Methods Study.JMIR mHealth and uHealth · 2023Article
- Exploring mHealth applications for self-management of chronic low back pain: A survey of features and benefits.Heliyon · 2023Review
- Mining the Influencing Factors and Their Asymmetrical Effects of mHealth Sleep App User Satisfaction From Real-world User-Generated Reviews: Content Analysis and Topic Modeling.Journal of medical Internet research · 2023Article
- Football Fandom as a Platform for Digital Health Promotion and Behaviour Change: A Mobile App Case Study.International journal of environmental research and public health · 2022Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe availability and use of mobile apps in health and nutrition management are increasing. Ease of access and user friendliness make diet-tracking apps an important ally in their users' efforts to lose and manage weight. To foster motivation for long-term use and to achieve goals, it is necessary to better understand users' opinions and needs for dietary self-monitoring.
objectiveThe aim of this study was to identify the key topics and issues that users highlight in their reviews of diet-tracking apps on Google Play Store. Identifying the topics that users frequently mention in their reviews of these apps, along with the user ratings for each of these apps, allowed us to identify areas where further improvement of the apps could facilitate app use, and support users' weight loss and intake management efforts.
methodsWe collected 72,084 user reviews from Google Play Store for 15 diet-tracking apps that allow users to track and count calories. After a series of text processing operations, two text-mining techniques (topic modeling and topical n-grams) were applied to the corpus of user reviews of diet-tracking apps.
resultsUsing the topic modeling technique, 11 separate topics were extracted from the pool of user reviews. Most of the users providing feedback were generally satisfied with the apps they use (average rating of 4.4 out of 5 for the 15 apps). Most topics referred to the positive evaluation of the apps and their functions. Negatively rated topics mostly referred to app charges and technical difficulties encountered. We identified the positive and negative topic trigrams (3-word combinations) among the most frequently mentioned topics. Usability and functionality (tracking options) of apps were rated positively on average. Negative ratings were associated with trigrams related to adding new foods, technical issues, and app charges.
conclusionsMotivating users to use an app over time could help them better achieve their nutrition goals. Although user reviews generally showed positive opinions and ratings of the apps, developers should pay more attention to users' technical problems and inform users about expected payments, along with their refund and cancellation policies, to increase user loyalty.
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.