Incorporating UTAUT Predictors for Understanding Home Care Patients' and Clinician's Acceptance of Healthcare Telemedicine Equipment

Abstract

Telemedicine programs within health care are experiencing significant growth as healthcare organizations seek to reduce expenditures and improve efficiency. The high costs of treating chronic diseases, compounded by an aging population, has given focus to creating technology-enabled alternatives to support, enhance, or expand patient services. As investments in telemedicine products and services grow at a rapid pace, user technology acceptance has become a key issue in successful implementation. Drawing from the Unified Theory of Acceptance in Technology (UTAUT), this study investigated the predictors of behavioral intention to use Telehealth equipment by patients, clinicians, and agency personnel at Henry Ford e-Home Health Care. Survey data were provided by 126 participants recruited from an eligible population who were either currently using the Telehealth equipment or were familiar with it. Structural equation modeling was used to study the overall fit of the UTAUT model in predicting behavioral intention. Participant type, self-efficacy, anxiety and attitude were tested as moderators. Implications for increasing adoption of Telehealth technology are discussed.

Client, provider and community referrer perceptions of telehealth for the delivery of rural paediatric allied health services

“…22 Trainee clinicians and referrers should be invited to observe or co-deliver telehealth sessions with familiar telehealth users as part of professional development. 22 Trainee clinicians and referrers should be invited to observe or co-deliver telehealth sessions with familiar telehealth users as part of professional development.…”

“…As self-efficacy concerns are linked to referrer and provider refusal, this should be monitored during telehealth adoption. 22 Trainee clinicians and referrers should be invited to observe or co-deliver telehealth sessions with familiar telehealth users as part of professional development. Lack of physical touch concerns are unlikely to be altered without major changes in available technology.…”

Technology-induced anxiety: Manifestations, cultural influences, and its effect on the adoption of sensor-based technology in German and Australian hospitals

“…Acceptance has been investigated in relation to several technologies (Hsiao & Yang, 2011;Marangunić & Granić, 2015). In healthcare settings, studies have explored the acceptance of telemedicine (Kohnke, Cole, & Bush, 2014;Rho, Choi, & Lee, 2014;Zailani, Gilani, Nikbin, & Iranmanesh, 2014), mobile services (Kuo, Liu, & Ma, 2013;Lee & Rho, 2013;Wu, Li, & Fu, 2011), mobile devices (Jeon & Park, 2015;Moon & Chang, 2014;Wan Ismail, Chan, Buhari, & Muzaini, 2012), and hospital information systems (Abdekhoda, Ahmadi, Dehnad, & Hosseini, 2014;Chen & Hsiao, 2012;Lin, 2015). Issues related to the acceptance of sensorbased systems have been raised but not investigated empirically (Al Ameen, Liu, & Kwak, 2012;Bick et al, 2015).…”

Critical Factors of the Adoption of e-Textbooks: A Comparison Between Experienced and Inexperienced Users

“…Venkatesh et al (2003) claimed that the UTAUT can explain more than 70% of the intentions for using different technologies, and that the theory represents a more extensive and complete model for acceptance research. The UTAUT has gained increased attention from researchers recently (e.g., Isa & Wong, 2015;Kaba & Touré, 2014;Kohnke, Cole, & Bush, 2014). Venkatesh, Thong, and Xu (2012) have extended the UTAUT by adding hedonic, habit, and price value factors, which is occasionally named UTAUT2.…”