ArticleJournal of ambient intelligence and humanized computing2023
A model to improve user acceptance of e-services in healthcare systems based on technology acceptance model: an empirical study.
Article in Journal of ambient intelligence and humanized computing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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Who cites it
8 citing papers in PubMed.
- Article
- Acceptance of Technological Innovations in Emergency Departments: An Empirical Study Based on an Extended TAM.Healthcare (Basel, Switzerland) · 2026Article
- Doctor performance drivers: insights from various theoretical perspectives.Frontiers in sociology · 2026Article
- Understanding Psychosocial Barriers to Healthcare Technology Adoption: A Review of TAM Technology Acceptance Model and Unified Theory of Acceptance and Use of Technology and UTAUT Frameworks.Healthcare (Basel, Switzerland) · 2025Review
- Bridging the gap: a practical step-by-step approach to warrant safe implementation of large language models in healthcare.Frontiers in artificial intelligence · 2025Article
- Quality factors affecting the continued use of mobile health apps in ethnic minority regions of Southwest China using PLS-SEM and ANN.Scientific reports · 2024Article
- Article
- Perceptions and attitudes of nurse practitioners toward artificial intelligence adoption in health care.Health science reports · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Improving the quality of electronic services (e-services) is essential when dealing with unforeseen factors and uncertainties in healthcare, such as the outbreak of coronavirus (COVID-19) and changes in the needs and expectations of patients. This paper presents a comprehensive conceptual model in healthcare systems for improving the user acceptance of e-services. A model referred to as the technology acceptance model (TAM) is considered that includes several factors. The factors are computer literacy, website quality, service quality, user attitude, perceived enjoyment, and user satisfaction. According to the collected data and the performed analysis, the fit indices of this survey reveal that the conceptual model has an acceptable fit. The findings are as follows. Computer literacy has positive effects on perceived enjoyment and ease of use. Website quality has positive effects on perceived enjoyment, ease of use, and user satisfaction. Perceived enjoyment has a positive effect on perceived usefulness. Ease of use has positive effects on the usefulness, willingness to use e-services, and user attitude. User satisfaction has a positive effect on user attitude. Perceived usefulness has a positive effect on the willingness to use e-services. Finally, among these variables, only the user attitude has no significant effect on the willingness to use e-services in the healthcare system. Therefore, to promote performance quality and to motivate people to use e-services, healthcare managers should improve these factors.
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Registered trials
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