Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Nov 12, 2024
Open Peer Review Period: Nov 15, 2024 - Jan 10, 2025
Date Accepted: Nov 14, 2025
(closed for review but you can still tweet)
The landscape of mobile applications for healthy eating: A case study for a systematic review and quality assessment
ABSTRACT
Background:
Mobile applications are increasingly used to foster healthy lifestyles. There is a growing need for clear, standardized guidelines to help users select safe and effective health apps.
Objective:
Our study aims to identify mobile apps promoting healthy eating that are worthy of recommendation based on evidence-based practices.
Methods:
We conducted a systematic review of apps promoting healthy eating that had already been evaluated by one or more of 28 recognized health app certification bodies. We conducted three rounds of app evaluations using the Quality Evaluation Scoring Tool (QUEST) (first and second rounds). In addition, we used a subjective 0-10 score scale (second and third rounds) in which each reviewer answered the question “how probable is it that you would recommend this app?”. Subsequent discussions were held to resolve scoring discrepancies and to identify the top-quality apps. We also assessed correlations among QUEST scores, app store scores and certification body scores.
Results:
Out of 41 applications identified by 5 certification bodies, 19 met inclusion criteria and were examined. Only 16 of these remained accessible for the second round. Eight of these surpassed 20 points (out of a maximum of 28) on the QUEST scale and were evaluated by the 6 experts in the third round. Second Nature, Freshwell, Yazio, Lifesum and MyNetDiary emerged as the leading applications. No correlations among QUEST, app store and certification body scores were found.
Conclusions:
Despite numerous evaluations by various certifying bodies, only five apps met the quality standards set by our experts. Our results mark the importance of rigorous, transparent, and standardized app evaluation processes to guide users towards making informed decisions about health apps. Guidelines for app developers towards evidence-based, unbiased, high-quality apps, may be the most feasible path to solve this.
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.