Abstract: Medical Internet of Things (mIoT) is the IoT sub-set with vast potential in healthcare. However, the adoption of eHealth solutions such as mIoT has been a critical challenge in the health sector of the Kingdom of Saudi Arabia. Therefore, this study was conducted to explore the mIoT adoption determinants in Saudi public hospitals. Methods: A total of 271 participants were recruited from public hospitals in Riyadh, and a modified UTAUT model named UTAUT-HS was developed in this study to test its relevance with respect to mIoT adoption. Results: Ten path relationships were tested in this study, out of which six showed significant results. Similarly, three variables (Computer and English Language Self-efficacy or CESE, Performance Expectancy or PE and Social Influence or SI) showed a significant direct relationship with the behavioural intention to adopt mIoT. Furthermore, CESE showed the strongest relationship and emerged as a major sub-set of Effort Expectancy (EE) for mIoT adoption. However, moderator analysis showed substantial variations between different study demographic groups. In particular, the current study findings unravelled a comparatively novel relevance of Perceived Threat to Autonomy (PTA) for mIoT adoption for clinical and non-clinical and for older and younger participants. Conclusion: The study concludes that UTAUT-HS is an adequate model to explain the mIoT adoption in healthcare. However, it also suggests conducting future large-scale studies in KSA and elsewhere to validate the relevance of UTAUT-HS in other contexts and with much more confidence.

Abdulaziz Alomari and Ben Soh, “Determinants of Medical Internet of Things Adoption in Healthcare and the Role of Demographic Factors Incorporating Modified UTAUT” International Journal of Advanced Computer Science and Applications(IJACSA), 14(7), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140703

@article{Alomari2023,
title = {Determinants of Medical Internet of Things Adoption in Healthcare and the Role of Demographic Factors Incorporating Modified UTAUT},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140703},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140703},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {7},
author = {Abdulaziz Alomari and Ben Soh}
}