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User acceptance of wearable intelligent medical devices through a modified unified theory of acceptance and use of technology

BACKGROUND: The acceptance of wearable intelligent medical devices and the factors influencing behavioral intention to use them have been scarcely studied. This study aimed to increase the current understanding of wearable intelligent medical devices and investigate the factors influencing their acc...

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Detalles Bibliográficos
Autores principales: Yin, Zheng, Yan, Jiayu, Fang, Shengyu, Wang, Dongbo, Han, Demin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9263785/
https://www.ncbi.nlm.nih.gov/pubmed/35813345
http://dx.doi.org/10.21037/atm-21-5510
Descripción
Sumario:BACKGROUND: The acceptance of wearable intelligent medical devices and the factors influencing behavioral intention to use them have been scarcely studied. This study aimed to increase the current understanding of wearable intelligent medical devices and investigate the factors influencing their acceptance. METHODS: Integrating the unified theory of acceptance and use of technology and the theory of perceived risk, and based on the features of wearable intelligent medical devices, we proposed a modified unified theory of acceptance and use of technology model to identify factors influencing the acceptance of these devices. Using data collected from 2,192 respondents in China from an online survey, we used structural equation modeling to test the measurement and structural models. RESULTS: The findings suggested that facilitating conditions (path coefficient =0.942, P<0.001) were critical to the use of wearable intelligent medical devices. Behavioral intention significantly mediated the effects of perceived risk, perceived cost, health expectation, perceived ease of use, and social influence on user behavior (path coefficient =0.210, P<0.001). Health expectation (path coefficient =0.860, P<0.001), perceived ease of use (path coefficient =0.289, P<0.001), and social influence (path coefficient =0.153, P<0.001) were found to play essential roles in predicting behavioral intention. Perceived cost (path coefficient =0.034, P<0.05) and perceived risk (path coefficient =−0.031, P<0.05) had no significant effect on behavioral intention. People with underlying diseases had lower health expectations and perceived costs. CONCLUSIONS: The modified unified theory of acceptance and use of technology model in our research is a reliable model to evaluate the user acceptance of wearable intelligent medical devices.