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An Integrated Structural Equation Model of eHealth Behavioral Intention
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Author(s): Gayle Prybutok (University of North Texas, Denton, USA), Anh Viet Ta (University of Nebraska Omaha, Omaha, USA), Xiaotong Liu (University of Wisconsin Platteville, Platteville, USA)and Victor Prybutok (University of North Texas, Denton, USA)
Copyright: 2020
Volume: 15
Issue: 1
Pages: 20
Source title:
International Journal of Healthcare Information Systems and Informatics (IJHISI)
Editor(s)-in-Chief: Qiang (Shawn) Cheng (University of Kentucky, USA)and Joseph Tan (McMaster University, Canada)
DOI: 10.4018/IJHISI.2020010102
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Abstract
eHealth offers promising tools and services to manage and improve the quality of health as well as the potential to provide accessible health information all over the world. The relatively low adoption rates among eHealth users motivates us to develop an integrated model to explain the learning process and provide essential antecedents of eHealth behavioral intention. The integrated model is empirically tested by using different structural equation modeling (SEM) methods, including partial least squares SEM (PLS-SEM), PLSc, and covariance-based SEM (CB-SEM). The model successfully explains the learning process and provides essential antecedents of eHealth behavioral intention. The findings support the interplay of social, cognitive, and personal factors that impact 18-30-year-old users' learning process related to eHealth behavioral intention. The results empirically show that these three types of SEM techniques provide consistent results with respect to path coefficients and coefficients of determination. The findings indicate that CB-SEM and PLS-SEM provide adverse consequences of interaction-term path coefficients.
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