Volume 7, Issue 3 (12-2020)                   jhbmi 2020, 7(3): 282-292 | Back to browse issues page

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Golshan A, Pournasir Roudbane M. An Exploration of Factors Affecting the Acceptance of Smart Healthcare Devices Using Integrated Technology Acceptance Model. jhbmi 2020; 7 (3) :282-292
URL: http://jhbmi.ir/article-1-447-en.html
Ph.D. in Information Technology Management, Assistant Professor, Information Technology Management Dept., Lahijan Branch, Islamic Azad University, Lahijan, Iran
Abstract:   (2728 Views)
Introduction: Recently, the Internet of Things (IoT) allows patients and healthcare providers to transfer the treatment process to the patients and enables them to manage the disease and receive help from the healthcare team and mobile devices. This has been considered as a promising solution to improve the quality of healthcare. The objective of this study was to investigate the factors affecting the acceptance of smart healthcare devices using an integrated technology acceptance model.
Method: In this descriptive-survey research, 169 out of 300 patients of Gil hospital in Rasht were selected based on Morgan table. The questionnaires by Papa et al. and Li et al. were applied to test the hypothesis. The structural equation technique and t-test were used to analyze the data.
Results: According to the research findings, the effect of “permeability”, “comfort”, “perceived social risk”, and “performance risk” on “perceived usefulness and ease”, the effect of “perceived usefulness and ease” on “attitude towards the acceptance of smart healthcare devices”, and finally, the effect of “attitudes toward the acceptance of smart healthcare devices” on the “behavioral intention to use these devices” were confirmed.
Conclusion: The results showed that the integrated technology model can play an effective role in identifying and examining the factors affecting the acceptance of smart healthcare devices and can be utilized as an important source of information for the use of these devices.
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Type of Study: Applicable | Subject: Artificial Intelligence in Healthcare
Received: 2019/10/23 | Accepted: 2020/07/20

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