AI‐Driven Personalized Recommendations and Real‐Time Monitoring for the Prevention and Management of Obesity: Clinical Trial Protocol for the Multicentre BETTER4All Personalized Intervention

BACKGROUND: Obesity arises from complex interactions among genetic, biological, behavioral, and environmental factors. Traditional "one-size-fits-all" interventions often yield modest, short-term outcomes, failing to account inter-individual variability. Advances in artificial intelligence (AI), polygenic risk scores (PRS), and digital health technologies now enable personalized and adaptive lifestyle interventions. OBJECTIVE: This paper presents the design and evaluation framework of the BETTER4All personalized intervention, a multicentre randomized controlled trial within the EU-funded BETTER4U project. The trial aims to integrate biological and behavioral data into tailored obesity prevention and management strategies. METHODS: . Participants will be randomized to an intervention group receiving AI and PRS-based lifestyle recommendations via a smartphone application, wearable device, and structured counseling, or to a control group receiving standard hypocaloric diet and lifestyle advice. The primary outcome is change in BMI at 6 months. Secondary outcomes include weight-loss maintenance at 1 year, metabolomic and gut microbiota biomarkers, lifestyle behaviors, and psychosocial parameters. Process evaluation incorporates measures of fidelity, acceptability, feasibility, and appropriateness, alongside adherence metrics from the digital tools. CONCLUSION: The BETTER4All trial will provide evidence on the effectiveness and scalability of AI-driven, biologically informed personalization in obesity care, offering a methodological framework for integrating multimodal digital data, from omics and biomarkers to behavior and lifestyle, contributing to the advancement of precision public health strategies. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT06997510.

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Journal
Obesity Reviews
Published
2026-10-27
DOI
https://doi.org/10.1111/obr.70243
Primary Topic
Nutrition, Genetics, and Disease
Type
article
Field-Weighted Citation Impact
0.00

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article

AI‐Driven Personalized Recommendations and Real‐Time Monitoring for the Prevention and Management of Obesity: Clinical Trial Protocol for the Multicentre BETTER4All Personalized Intervention

Eva Karaglani, Christos Diou, Paris Kantaras, Maira Bes‐Rastrollo et al.
3 links
Obesity Reviews
Nutrition, Genetics, and Disease
article

AI‐Driven Personalized Recommendations and Real‐Time Monitoring for the Prevention and Management of Obesity: Clinical Trial Protocol for the Multicentre BETTER4All Personalized Intervention

Eva Karaglani, Christos Diou, Paris Kantaras, Maira Bes‐Rastrollo, Vanessa Bullón‐Vela, Dimitrios Aletras, Anastasios N. Delopoulos, Aristotelis Ballas, George V. Dedoussis, Panagiota Veloudi, Paulina Krzywicka, Aleksandra Łuszczyńska, Constantinos C. Deltas, Ioannis Ioakeimidis, Stavroula Georgia Mougiakakou, Louise Seconda, Ana Isabel Rito, Julie‐Anne Nazare, Maria Kafyra, Alexis Kyriacou, Vera Stavroulaki, Yannis Μanios, Ioannis Papathanail, Anna E Ek, Anestis Dougkas, Gianna E. Karanasiou, Chrysa Episkopou, Ioanna Panagiota Kalafati, Vasiliki Vavouraki, Rooholla Poursoleymani, Christina Patmiou, Ioannis Roumeliotis, Marta Gaspar
article en

Abstract

BACKGROUND: Obesity arises from complex interactions among genetic, biological, behavioral, and environmental factors. Traditional "one-size-fits-all" interventions often yield modest, short-term outcomes, failing to account inter-individual variability. Advances in artificial intelligence (AI), polygenic risk scores (PRS), and digital health technologies now enable personalized and adaptive lifestyle interventions. OBJECTIVE: This paper presents the design and evaluation framework of the BETTER4All personalized intervention, a multicentre randomized controlled trial within the EU-funded BETTER4U project. The trial aims to integrate biological and behavioral data into tailored obesity prevention and management strategies. METHODS: . Participants will be randomized to an intervention group receiving AI and PRS-based lifestyle recommendations via a smartphone application, wearable device, and structured counseling, or to a control group receiving standard hypocaloric diet and lifestyle advice. The primary outcome is change in BMI at 6 months. Secondary outcomes include weight-loss maintenance at 1 year, metabolomic and gut microbiota biomarkers, lifestyle behaviors, and psychosocial parameters. Process evaluation incorporates measures of fidelity, acceptability, feasibility, and appropriateness, alongside adherence metrics from the digital tools. CONCLUSION: The BETTER4All trial will provide evidence on the effectiveness and scalability of AI-driven, biologically informed personalization in obesity care, offering a methodological framework for integrating multimodal digital data, from omics and biomarkers to behavior and lifestyle, contributing to the advancement of precision public health strategies. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT06997510.

Obesity Reviews
Université Claude Bernard Lyon 1 (FR), University of Bern (CH), Bern University of Applied Sciences (CH), University of Thessaly (GR), Inserm (FR), Aristotle University of Thessaloniki (GR), Mediterranean University (ME), Instituto de Salud Carlos III (ES), Spanish Biomedical Research Centre in Physiopathology of Obesity and Nutrition (ES), Karolinska Institutet (SE), Hellenic Mediterranean University (GR), Harokopio University of Athens (GR), University of Cyprus (CY), Uniwersytet SWPS (PL), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Navarre Institute of Health Research (ES), WINGS ICT Solutions (Greece) (GR), Centre de Recherche en Nutrition Humaine Rhône-Alpes (FR), Laboratoire de recherche en cardiovasculaire, métabolisme, diabétologie et nutrition (FR), National Institute of Health Dr. Ricardo Jorge (PT), Universidad de Navarra (ES)
BioClinica, Helsingin Yliopisto, University of Bern, Queen Mary University of London, University of Cyprus, Università degli Studi di Cagliari, QIMR Berghofer Medical Research Institute, Government of the United Kingdom, UK Research and Innovation, Hellenic Academic Libraries Link, European Commission, Weizmann Institute of Science, Universität Wien, Karolinska Institutet, Universiteit Gent, Universidad de Navarra, Medizinische Universität Wien, Aristotle University of Thessaloniki, Tartu Ülikool, Harokopio University, HORIZON EUROPE Framework Programme, Leibniz-Gemeinschaft, Staatssekretariat für Bildung, Forschung und Innovation, Helmholtz Zentrum München
Good health and well-being
Openalex Percentile: Top 15%
Nutrition, Genetics, and Disease
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