Examining the Factors for Wearable Healthcare Devices Adoption in the Event of COVID-19: A Classification and Regression Tree Approach
Wearable devices have attracted a great deal of attention and popularity among academics and industry in the last decade. The potential of wearable technology to improve health efficiency and cut healthcare costs has been demonstrated. Wearable devices are believed to be of a very strong value, both for detection and for the tracking and control of the spread of infectious diseases such as COVID-19. Regardless of whether this technology is imported, inadequate scientists focused on the factors impacting the acceptability of wearable medical devices. Using the model for confirmation of expectations and technology acceptance, this study has developed a theoretical model to study user perceptions about wearable healthcare devices and introduces an extensive research model that uses mainly extracted factors. The data collected from 163 study samples were examined using Classification and Regression Tree (CART) technique. The study results showed that security and privacy is an important factor for the adoption of wearable healthcare devices in the event of COVID-19.
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