This dissertation enhances the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) by integrating information privacy concerns and examining their influence on adopting web-based healthcare portals. Through a survey of 298 U.S. residents using healthcare technologies, the study investigates the interplay between UTAUT2 predictors—Performance Expectancy, Effort Expectancy, Facilitating Conditions, Habit, Social Influence, and Hedonic Motivation—and the intention to use these technologies while assessing how privacy concerns modulate these relationships. Regression analysis highlights the positive impact of Performance Expectancy, Effort Expectancy, and Habit on adoption intent, with privacy concerns significantly moderating the relationship between Effort Expectancy and usage intention.
The research enriches the UTAUT2 model by showcasing the pivotal role of privacy concerns, thus advancing theoretical understanding and enhancing model predictability in the context of healthcare technology. Practically, it offers insights for practitioners and policymakers on addressing privacy concerns to improve technology adoption. This synthesis of privacy concerns within the technology acceptance framework paves the way for targeted strategies to increase the uptake of healthcare technologies, marking a significant contribution to both academic discourse and practical application.