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Assessing The Adoption of Artificial Intelligence in the Practice of Physical Activity

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Detalhes bibliográficos
Resumo:This study investigates the factors influencing the adoption of AI technologies for physical activity by integrating the UTAUT2 model with the Health Consciousness Scale. Survey data from recreational exercisers were analyzed using PLS-SEM. The results reveal that hedonic motivation, performance expectancy, price value, and habit significantly drive intention to use, while habit is the strongest predictor of actual behavior. In contrast, effort expectancy, social influence, and facilitating conditions had a limited impact. Health consciousness influenced intention modestly but not behavior. These findings provide insight into how psychological and functional factors influence user adoption of AI fitness technologies.
Autores principais:Martins, Eva Isabel Martins
Assunto:Artificial Intelligence Fitness Technology adoption UTAUT Health Consciousness Scale SDG 3 - Good health and well-being SDG 9 - Industry, innovation and infrastructure
Ano:2025
País:Portugal
Tipo de documento:dissertação de mestrado
Tipo de acesso:acesso embargado
Instituição associada:Universidade Nova de Lisboa
Idioma:inglês
Origem:Repositório Institucional da UNL
Descrição
Resumo:This study investigates the factors influencing the adoption of AI technologies for physical activity by integrating the UTAUT2 model with the Health Consciousness Scale. Survey data from recreational exercisers were analyzed using PLS-SEM. The results reveal that hedonic motivation, performance expectancy, price value, and habit significantly drive intention to use, while habit is the strongest predictor of actual behavior. In contrast, effort expectancy, social influence, and facilitating conditions had a limited impact. Health consciousness influenced intention modestly but not behavior. These findings provide insight into how psychological and functional factors influence user adoption of AI fitness technologies.