Users' Perspective on the AI-Based Smartphone PROTEIN App for Personalized Nutrition and Healthy Living: A Modified Technology Acceptance Model (mTAM) Approach - Dias, Sofia Balula; Oikonomidis, Yannis; Diniz, José Alves; Baptista, Fátima; Carnide, Filomena; Bensenousi, Alex; Botana, José María; Tsatsou, Dorothea; Stefanidis, Kiriakos; Gymnopoulos, Lazaros; Dimitropoulos, Kosmas; Daras, Petros; et al. (Frontiers in Nutrition, 2022)
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 via 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 towards 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 two months, were subjected to regression analysis 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 via the acceptance/rejection of six related hypotheses (H1-H6), respectively. The regression results have shown that all hypotheses H1-H6 can be accepted (p<0.001), exhibiting adjusted coefficient of determination (R^2) 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. 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 physiologists experts and marketing experts for app design/development towards behavior change.