Despite the proliferation of health and nursing informatics applications in the past decade, factors influencing consumer acceptance of the applications are not well understood. This study was conducted to investigate factors affecting acceptance of a consumer-used nursing informatics application (ie, online health information portal) within the framework of the Technology Acceptance Model. A cross-sectional study was conducted in which 201 Chinese young adults were invited to participate in usability testing with a typical health information portal and to complete a self-report questionnaire measuring the model's constructs and five hypothesized variables drawn from consumer and portal characteristics. Hierarchical regression analyses were used to test research hypotheses. Fifteen of the 22 research hypotheses were supported. Perceived ease of use and perceived usefulness predicted satisfaction and behavioral intention, respectively, over and above the portal and consumer characteristics examined in the study. All portal and consumer characteristics had significant, although varied, impacts on the original model constructs. This study demonstrated that an adapted Technology Acceptance Model, extended with portal and consumer characteristics, provides an effective means to understand consumer acceptance of health portals. The findings hold important implications for design and implementation strategies to increase the likelihood of acceptance of consumer-used nursing informatics applications.
Author Affiliations: Institute of Human Factors and Ergonomics College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen (Dr Tao, Mss Yuan and Shao, and Dr Qu); Department of Management Science and Engineering, Fuzhou University, Fuzhou (Dr Li); and China Institute of Atomic Energy, Beijing (Ms Zhou), China.
This work received funding support from the Young Talents Foundation of Ministry of Education of Guangdong, China (grant 2016KQNCX143), the Natural Science Foundation of Shenzhen University (grants 827000228 and 827000033), CES-Kingfar Excellent Young Scholar Joint Research Funding (grant CES-KF-2016-2018), and the Start-up Grant of Shenzhen University (grant 2016041).
The authors have disclosed that they have no significant relationships with, or financial interest in, any commercial companies pertaining to this article.
Corresponding Address: Xingda Qu, PhD, Institute of Human Factors and Ergonomics, College of Mechatronics and Control Engineering, Shenzhen University, 3688 Nanhai Ave, Shenzhen City, Guangdong Province, China (firstname.lastname@example.org).