Partial least squares (PLS-SEM) technique was used for data analysis. Results The results showed that performance expectancy, effort expectancy, social influence, perceived health threat, M-Health app quality, and life quality expectancy have a direct positive effect on patients' intention to use M-Health.
This study focuses on identifying the influential factors of patients' adoption intention of m-Health. A structural equation model is constructed, and the ...
Jun 12, 2017 · The results show that perceived usefulness and perceived ease of use have the strongest positive effect on patients' adoption intention.
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Meanwhile, subjective norm, existing degree of satisfaction, network effect, and cost factor also influence adoption intention. Finally, the House of Quality ...
Aug 9, 2023 · This study aims to design a conceptual model to investigate the elements that affect individuals' openness to accepting and using mobile ...
from publication: Factors that influence users' adoption intention of mobile health: a structural equation modeling approach | Mobile health represents the ...
The objectives of this study are to examine the factors affecting the intention and actual usage behavior on mHealth adoption.
Factors that influence users' adoption intention of mobile health: a structural equation modeling approach. https://doi.org/10.1080/00207543.2017.1336681 ·.
Results: The study determined that performance expectancy, effort expectancy, social influence, technology anxiety, and resistance to change (p<0.05) had a ...
Jul 24, 2022 · SEM results suggested that Social Influence, Hedonic Motivation, Price Value, Habit, and Service Quality had significant impact (p < 0.05) on ...