Healthcare wearable devices: an analysis of key factors for continuous use intention

Abstract

This study empirically examined the effects of internal and external factors on actual use behavior, health improvement expectancy, and continuous use intention of healthcare wearable devices. The study proposed a research model with its associated hypotheses that were tested using structural equation modeling. We also performed a comparative analysis of the two sample groups (medical personnel and general public), based on data collected from 288 healthcare wearable devices/apps users. The findings of the study indicated that internal and external factors have positive effects on actual use behavior, and health improvement expectancy and continuous use intention of healthcare wearable devices can be promoted through actual use behavior. The comparative analysis of the two groups showed that medical personnel had higher relationships among the study factors than general public. The study results shed theoretical and practical implications regarding how healthcare wearable devices or apps can be effectively used for disease prevention and health management for the users.

Application of Artificial Intelligence-Based Technologies in the Healthcare Industry: Opportunities and Challenges

“…Responding quickly is the most effective way to minimize damage in situations where it is difficult to predict the future. Beyond time and space limitations, AI-based technology, which can surpass the limits of expert knowledge, is breaking the boundaries of healthcare, well-being, and life itself [ 2 , 74 ]. In this regard, although AI-based medical systems focus on patient-centered management of diseases, it is expected that, in the long term, the scope will expand from pre-disease to treatment and post-care to daily life.…”

“…Information and communication technology (ICT) is a core element of digitized organizations that can facilitate operational effectiveness and enhance competitive advantage [ 1 , 2 , 3 , 4 ]. In today’s Fourth Industrial Revolution (4IR) era, advanced digital technologies and devices are widely applied for innovation and value creation across industries [ 5 ].…”

“…Recently, there has been widespread applications of AI-supported technologies in healthcare institutions for improved care service quality and efficiency of medical resources [ 2 , 7 ]. Since AI encompasses machine learning, natural language processing, and smart robots, AI-based technologies provide numerous opportunities for innovation in the knowledge-intensive healthcare industry [ 8 , 9 ].…”

“…In addition, AI has attracted the attention of researchers, physicians, technology and program developers, and consumers in various fields in terms of its potential for transformative innovations in treating human diseases and public health [ 2 , 9 , 11 , 12 ]. According to Accenture [ 13 ], hospitals will invest $6.6 billion annually in AI-related technologies by 2021.…”

“…Some of the notable challenges involved in the widespread application of AI and digital devices include privacy concerns, cybersecurity, data integrity concerns, data ownership, the problem of data-sharing by various organizational silos, medical ethics issues, responsibility for medical errors, and risks of system failures [ 7 , 9 , 22 ]. Considering the nature of healthcare services, ethical issues are real challenges because AI technology may threaten patients’ preferences, safety, and privacy [ 2 , 7 , 19 ]. Currently, policies and ethical guidelines for healthcare services that incorporate AI and its applications lag behind the speed of advances in AI [ 19 ].…”