Personal Goals, User Engagement, and Meal Adherence within a Personalised AI-Based Mobile Application for Nutrition and Physical Activity
Elena Patra,
Anna Kokkinopoulou,
Saskia Wilson-Barnes,
Kathryn Hart,
Lazaros P. Gymnopoulos,
Dorothea Tsatsou,
Vassilios Solachidis,
Kosmas Dimitropoulos,
Konstantinos Rouskas,
Anagnostis Argiriou,
Elena Lalama,
Marta Csanalosi,
Andreas F. H. Pfeiffer,
Véronique Cornelissen,
Elise Decorte,
Sofia Balula Dias,
Yannis Oikonomidis,
José María Botana,
Riccardo Leoni,
Duncan Russell,
Eugenio Mantovani,
Milena Aleksić,
Boris Brkić,
Maria Hassapidou,
Ioannis Pagkalos
Affiliations
Elena Patra
Nutrition Information Systems Laboratory (NISLAB), Department of Nutritional Sciences and Dietetics, International Hellenic University, 57400 Thessaloniki, Greece
Anna Kokkinopoulou
Nutrition Information Systems Laboratory (NISLAB), Department of Nutritional Sciences and Dietetics, International Hellenic University, 57400 Thessaloniki, Greece
Saskia Wilson-Barnes
School of Biosciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7WG, UK
Kathryn Hart
School of Biosciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7WG, UK
Lazaros P. Gymnopoulos
Centre for Research & Technology Hellas, 57001 Thessaloniki, Greece
Dorothea Tsatsou
Centre for Research & Technology Hellas, 57001 Thessaloniki, Greece
Vassilios Solachidis
Centre for Research & Technology Hellas, 57001 Thessaloniki, Greece
Kosmas Dimitropoulos
Centre for Research & Technology Hellas, 57001 Thessaloniki, Greece
Konstantinos Rouskas
Centre for Research & Technology Hellas, 57001 Thessaloniki, Greece
Anagnostis Argiriou
Centre for Research & Technology Hellas, 57001 Thessaloniki, Greece
Elena Lalama
Department of Endocrinology and Metabolic Diseases, Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
Marta Csanalosi
Department of Endocrinology and Metabolic Diseases, Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
Andreas F. H. Pfeiffer
Department of Endocrinology and Metabolic Diseases, Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
Véronique Cornelissen
Department of Rehabilitation Sciences, KU Leuven, 3001 Leuven, Belgium
Elise Decorte
Department of Rehabilitation Sciences, KU Leuven, 3001 Leuven, Belgium
Sofia Balula Dias
Interdisciplinary Centre for the Study of Human Performance (CIPER), Faculdade de Motricidade Humana, Universidade de Lisboa, 1499-002 Lisbon, Portugal
Yannis Oikonomidis
Intrasoft International S.A., 55535 Thessaloniki, Greece
José María Botana
CGI Information Systems and Management Consultants S.A., 28050 Madrid, Spain
Riccardo Leoni
Datawizard, 00138 Rome, Italy
Duncan Russell
Ocado Group, Hatfield, London AL10 9UL, UK
Eugenio Mantovani
Research Group on Law, Science, Technology and Society, Faculty of Law & Criminology, Vrije Universiteit Brussel, 1050 Brussels, Belgium
Milena Aleksić
Research and Development Institute for Information Technology in Biosystems, BioSense Institute, 21000 Novi Sad, Serbia
Boris Brkić
Research and Development Institute for Information Technology in Biosystems, BioSense Institute, 21000 Novi Sad, Serbia
Maria Hassapidou
Nutrition Information Systems Laboratory (NISLAB), Department of Nutritional Sciences and Dietetics, International Hellenic University, 57400 Thessaloniki, Greece
Ioannis Pagkalos
Nutrition Information Systems Laboratory (NISLAB), Department of Nutritional Sciences and Dietetics, International Hellenic University, 57400 Thessaloniki, Greece
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 (n = 579) and the PROTEIN end-user questionnaire (n = 446) were analysed using the chi-square test of independence to identify associations between personal goals, meal recommendations, and meal adherence among different gender, age, and user groups. The results indicate that weight loss-related goals are more prevalent, as well as more engaging, across all users. Health- and physical activity-related goals are key for increased meal adherence, with further differentiation evident between age and user groups. Congruency between user groups and their respective goals is also important for increased meal adherence. Our study outcomes, and the overall research framework created by the PROTEIN project, can be used to inform the future development of nutrition mobile applications and enable researchers and application designers/developers to better address personalisation for specific user groups, with a focus on user intent, as well as in-app features.
