Structural Equation Model Approach to Understand Intentions to use Online Hospital Services (OHS) in Context of Rural China

Authors

  • Dr. Songyu Jiang,

Keywords:

waveguide, refraction index, triangular element, eigenmode, eigenmatrix equation, edge, node, electric equipotential, focus., online hospital services; technology acceptance model; perceived usefulness; perceived ease of use; trust

Abstract

This study aims to explore the factors influencing the adoption of Online Hospital Services (OHS) among rural residents in China, utilizing the Technology Acceptance Model (TAM) framework. A Structural Equation Model (SEM) was employed to analyze data collected from 422 participants with Internet hospital experience, selected through random sampling. Data collection involved online questionnaires distributed over 45 days, resulting in effective samples. The survey was divided into six sections, focusing on various aspects of user perceptions and intentions regarding OHS. The results indicate that perceived usefulness (PU) and perceived ease of use (PEOU) positively affect attitudes towards OHS, with trust acting as a crucial mediator between these variables and usage intentions. The studys theoretical contributions include extending TAM by highlighting the central role of trust in digital health adoption, particularly in rural contexts. Practically, the findings suggest that policymakers and technology developers should focus on enhancing trust and user-friendliness to promote OHS adoption, thereby bridging the urban-rural healthcare divide and improving healthcare accessibility.

Structural Equation Model Approach to Understand Intentions to use Online Hospital Services (OHS) in Context of Rural China

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Published

2024-08-05

How to Cite

Dr. Songyu Jiang,. (2024). Structural Equation Model Approach to Understand Intentions to use Online Hospital Services (OHS) in Context of Rural China. London Journal of Engineering Research, 24(5), 59–75. Retrieved from https://journalspress.uk/index.php/LJER/article/view/893