phillps smartsleep wearable enhancement system

It is important to identify factors affecting the continuous use intention for healthcare wearable devices.

There is little empirical research on user acceptance behavior and the actual use of such wearable devices. In addition, previous studies on healthcare wearable devices and their applications generally focused on specific age groups (e.g., younger generations), using the technology acceptance model (TAM), TAM2, Unified Theory of Acceptance and Use of Technology (UTAUT), and UTAUT2 models, or the analysis of technology or market trends (Wang et al. Despite the rapid growth of the healthcare wearable devices market, the adoption of these devices and related technologies is diverse as different social segments and countries have varying degrees of socio-technical development (Yoon et al. As such, many companies have developed wearables and smartphone apps to provide a wide range of healthcare services, and this trend is expected to accelerate (Braithwaite 2018). They can measure the heart rate, body temperature, blood pressure, and respiration of the elderly living in homes and facilities, and by detecting their risk indicators, such as worsening disease conditions, falls, and other life-threatening situations (O’Donovan et al. Today’s digital wearables, converged products of smart sensors, artificial intelligence (AI), the Internet of Things (IoT), big data, robots, and radar technologies, can help manage and prevent diseases. Furthermore, the shift in the medical paradigm, from disease treatment to prevention and health management, has provided the users of wearable devices new experiences that are not available from traditional healthcare-related products and services (Lee 2019). Wearable devices are becoming an increasingly popular platform for healthcare services, particularly given the increasing interest in health, well-being, disease prevention, and fitness, as well as the paradigm shift toward healthcare that is personalized and controlled by individuals (Lee 2018). According to Strategy Analytics ( 2019), global smartwatch shipments reached 12.3 million units in June 2019, representing a 44 percent increase from 8.6 million units in June 2018. Markets and Markets ( 2017) predicts that the global mobile healthcare market will grow from USD 63.4 billion in 2013 to 90.4 billion in 2022. It is estimated that more than 70% of the world’s population use mobile devices (Ericsson 2017). With the rapid advances in mobile technology, the use of mobile devices has skyrocketed. 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. The comparative analysis of the two groups showed that medical personnel had higher relationships among the study factors than general public. 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. 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 study proposed a research model with its associated hypotheses that were tested using structural equation modeling. 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.

Phillps smartsleep wearable enhancement system