Patients' Adoption of WSN-Based Smart Home Healthcare Systems: An Integrated Model of Facilitators and Barriers

Background: Patient-centered care emphasizes care coordination and communication through active involvement of patients, their families, physicians, and other professionals to improve decision making. Smart telecommunication technology and the Internet of Things, such as wireless-sensor-network-based smart home healthcare systems (WSN-SHHS) facilitate communication and collaboration among these different roles. Research problem: Despite the great potential of such systems to improve the quality and experience, and lower the cost of health care, the technology has not been widely adopted partly due to an inadequate understanding of user expectations, needs, and preferences. This study addresses facilitators and barriers with regard to WSN-SHHS adoption by identifying important sociotechnical, cognitive, affective, and contextual factors. Research questions: What are the main facilitators and barriers of patients' adoption of WSN-SHHS? How can we contextualize a generic technology adoption model for WSN-SHHS that takes into account unique characteristics of the domain? Literature review: We surveyed the literature in WSN-SHHS research and application, technology adoption theories, and the pleasure-arousal-dominance emotional state model. We discovered that WSN-SHHS research has focused on technology development but has given little attention to the issue of patients' adoption. Methodology: We used a mixed method design that combined an interview and survey over two studies. Participants were recruited from home healthcare agencies in the eastern US. In semistructured interviews, we collected data from 15 home healthcare patients and medical professionals, and analyzed the data using Kvale's approach. In our online- and paper-based surveys, we analyzed the data from 140 respondents using partial least square. Results and conclusions: We identified several new constructs in relation to WSN-SHHS adoption, including human detachment concerns, privacy concerns, life-quality expectancy and cost concerns. In addition, we confirmed the constructs from the general adoption model. Based on the findings of the qualitative study, the researchers created a research model. The quantitative study provided empirical support for the model, which has substantial predictive power accounting for more than half of the variance in WSN-SHHS adoption. In particular, our findings reveal that human detachment concerns rather than performance expectancy is the strongest predictor of patients' adoption of WSN-SHHS.