ArticleLife (Basel, Switzerland)2024
Personal Goals, User Engagement, and Meal Adherence within a Personalised AI-Based Mobile Application for Nutrition and Physical Activity.
Article in Life (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Effect of a Personalized Mobile App on Glucose Control in Adults With Prediabetes and Type 2 Diabetes: Exploratory Pilot Randomized Controlled Trial.JMIR human factors · 2026Trial
- Article
- The mediating role of E-health literacy and physical literacy in developing nutrition, physical activity, and health beliefs.Frontiers in public health · 2026Article
- Four night eating behavior subtypes in young and middle-aged adults with type 2 diabetes: insights for targeted public health interventions.Frontiers in public health · 2026Article
- Artificial Intelligence in Nutrition and Dietetics: A Comprehensive Review of Current Research.Healthcare (Basel, Switzerland) · 2025Review
- The Influence of an AI-Driven Personalized Nutrition Program on the Human Gut Microbiome and Its Health Implications.Nutrients · 2025Article
- Applications of Artificial Intelligence in Food Industry.Foods (Basel, Switzerland) · 2025Article
- Validation of a personalized AI prompt generator (NExGEN-ChatGPT) for obesity management using fuzzy Delphi method.Biology methods & protocols · 2025Article
- Editorial: Smart devices for personalized nutrition and healthier lifestyle behavior change.Frontiers in nutrition · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
25 authors.
Funding
Abstract
Mobile applications have been shown to be an effective and feasible intervention medium for improving healthy food intake in different target groups. As part of the PeRsOnalized nutriTion for hEalthy livINg (PROTEIN) European Union H2020 project, the PROTEIN mobile application was developed as an end-user environment, aiming to facilitate healthier lifestyles through artificial intelligence (AI)-based personalised dietary and physical activity recommendations. Recommendations were generated by an AI advisor for different user groups, combining users' personal information and preferences with a custom knowledge-based system developed by experts to create personalised, evidence-based nutrition and activity plans. The PROTEIN app was piloted across different user groups in five European countries (Belgium, Germany, Greece, Portugal, and the United Kingdom). Data from the PROTEIN app's user database (
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Identifiers
What Socratic 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 Socratic graph.