Users' Perspective on the AI-Based Smartphone PROTEIN App for Personalized Nutrition and Healthy Living: A Modified Technology Acceptance Model (mTAM) Approach.
Sofia Balula Dias, Yannis Oikonomidis, José Alves Diniz, Fátima Baptista, Filomena Carnide, Alex Bensenousi, José María Botana, Dorothea Tsatsou, Kiriakos Stefanidis, Lazaros Gymnopoulos, Kosmas Dimitropoulos, Petros Daras, Anagnostis Argiriou, Konstantinos Rouskas, Saskia Wilson-Barnes, Kathryn Hart, Neil Merry, Duncan Russell, Jelizaveta Konstantinova, Elena Lalama, Andreas Pfeiffer, Anna Kokkinopoulou, Maria Hassapidou, Ioannis Pagkalos, Elena Patra, Roselien Buys, Véronique Cornelissen, Ana Batista, Stefano Cobello, Elena Milli, Chiara Vagnozzi, Sheree Bryant, Simon Maas, Pedro Bacelar, Saverio Gravina, Jovana Vlaskalin, Boris Brkic, Gonçalo Telo, Eugenio Mantovani, Olga Gkotsopoulou, Dimitrios Iakovakis, Stelios Hadjidimitriou, Vasileios Charisis, Leontios J Hadjileontiadis
Author Information
Sofia Balula Dias: CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, Estrada da Costa, Lisbon, Portugal.
Yannis Oikonomidis: Intrasoft International SA, Thessaloniki, Greece.
José Alves Diniz: CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, Estrada da Costa, Lisbon, Portugal.
Fátima Baptista: CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, Estrada da Costa, Lisbon, Portugal.
Filomena Carnide: CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, Estrada da Costa, Lisbon, Portugal.
Alex Bensenousi: Intrasoft International SA, Thessaloniki, Greece.
José María Botana: Grupo CMC, Madrid, Spain.
Dorothea Tsatsou: Centre for Research and Technology Hellas, Thessaloniki, Greece.
Kiriakos Stefanidis: Centre for Research and Technology Hellas, Thessaloniki, Greece.
Lazaros Gymnopoulos: Centre for Research and Technology Hellas, Thessaloniki, Greece.
Kosmas Dimitropoulos: Centre for Research and Technology Hellas, Thessaloniki, Greece.
Petros Daras: Centre for Research and Technology Hellas, Thessaloniki, Greece.
Anagnostis Argiriou: Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece.
Konstantinos Rouskas: Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece.
Saskia Wilson-Barnes: School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom.
Kathryn Hart: School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom.
Neil Merry: OCADO Technology, London, United Kingdom.
Duncan Russell: OCADO Technology, London, United Kingdom.
Jelizaveta Konstantinova: OCADO Technology, London, United Kingdom.
Elena Lalama: Department of Endocrinology, Diabetes and Nutrition and German Institute of Human Nutrition, Charité, Universitätsmedizin Berlin, Berlin, Germany.
Andreas Pfeiffer: Department of Endocrinology, Diabetes and Nutrition and German Institute of Human Nutrition, Charité, Universitätsmedizin Berlin, Berlin, Germany.
Anna Kokkinopoulou: Department of Nutritional Sciences and Dietetics, International Hellenic University, Thessaloniki, Greece.
Maria Hassapidou: Department of Nutritional Sciences and Dietetics, International Hellenic University, Thessaloniki, Greece.
Ioannis Pagkalos: Department of Nutritional Sciences and Dietetics, International Hellenic University, Thessaloniki, Greece.
Elena Patra: Department of Nutritional Sciences and Dietetics, International Hellenic University, Thessaloniki, Greece.
Roselien Buys: Department of Rehabilitation Sciences and Department of Cardiovascular Sciences, Katholieke Universiteit Leuven, Leuven, Belgium.
Véronique Cornelissen: Department of Rehabilitation Sciences and Department of Cardiovascular Sciences, Katholieke Universiteit Leuven, Leuven, Belgium.
Ana Batista: Sport Lisboa Benfica Futebol, Lisbon, Portugal.
Stefano Cobello: Polo Europeo della Conoscenza, Verona, Italy.
Elena Milli: Polo Europeo della Conoscenza, Verona, Italy.
Chiara Vagnozzi: Fluviale SRL, Rome, Italy.
Sheree Bryant: European Association for the Study of Obesity (EASO), Middlesex, United Kingdom.
Simon Maas: AgriFood Capital BV, Hertogenbosch, Netherlands.
Pedro Bacelar: Healthium/Nutrium Software, Porto, Portugal.
Saverio Gravina: Datawizard SRL, Rome, Italy.
Jovana Vlaskalin: BioSense Institute, Research and Development Institute for Information Technology in Biosystems, Novi Sad, Serbia.
Boris Brkic: BioSense Institute, Research and Development Institute for Information Technology in Biosystems, Novi Sad, Serbia.
Eugenio Mantovani: Research Group on Law, Science, Technology and Society, Faculty of Law & Criminology, Vrije Universiteit Brussel, Ixelles, Belgium.
Olga Gkotsopoulou: Research Group on Law, Science, Technology and Society, Faculty of Law & Criminology, Vrije Universiteit Brussel, Ixelles, Belgium.
Dimitrios Iakovakis: Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Stelios Hadjidimitriou: Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Vasileios Charisis: Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Leontios J Hadjileontiadis: Department of Biomedical Engineering, Healthcare Engineering Innovation Center (HEIC), Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates.
The ubiquitous nature of smartphone ownership, its broad application and usage, along with its interactive delivery of timely feedback are appealing for health-related behavior change interventions mobile apps. However, users' perspectives about such apps are vital in better bridging the gap between their design intention and effective practical usage. In this vein, a modified technology acceptance model (mTAM) is proposed here, to explain the relationship between users' perspectives when using an AI-based smartphone app for personalized nutrition and healthy living, namely, PROTEIN, and the mTAM constructs toward behavior change in their nutrition and physical activity habits. In particular, online survey data from 85 users of the PROTEIN app within a period of 2 months were subjected to confirmatory factor analysis (CFA) and regression analysis (RA) to reveal the relationship of the mTAM constructs, i.e., perceived usefulness (PU), perceived ease of use (PEoU), perceived novelty (PN), perceived personalization (PP), usage attitude (UA), and usage intention (UI) with the users' behavior change (BC), as expressed the acceptance/rejection of six related hypotheses (H1-H6), respectively. The resulted CFA-related parameters, i.e., factor loading (FL) with the related -value, average variance extracted (AVE), and composite reliability (CR), along with the RA results, have shown that all hypotheses H1-H6 can be accepted ( < 0.001). In particular, it was found that, in all cases, FL > 0.5, CR > 0.7, AVE > 0.5, indicating that the items/constructs within the mTAM framework have good convergent validity. Moreover, the adjusted coefficient of determination ( ) was found within the range of 0.224-0.732, justifying the positive effect of PU, PEoU, PN, and PP on the UA, that in turn positively affects the UI, leading to the BC. Additionally, using a hierarchical RA, a significant change in the prediction of BC from UA when the UI is used as a mediating variable was identified. The explored mTAM framework provides the means for explaining the role of each construct in the functionality of the PROTEIN app as a supportive tool for the users to improve their healthy living by adopting behavior change in their dietary and physical activity habits. The findings herein offer insights and references for formulating new strategies and policies to improve the collaboration among app designers, developers, behavior scientists, nutritionists, physical activity/exercise physiology experts, and marketing experts for app design/development toward behavior change.
