• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 1
  • Tagged with
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Information Privacy and Security Associated with Healthcare Technology Use

Amin, M A Shariful 07 1900 (has links)
This dissertation consists of three studies that investigate the information privacy & security associated with healthcare technology use. Essay 1 PRISMA-style systematically reviews the existing literature on privacy information disclosure in IoT technology and serves as the theoretical foundation of the current research. It is crucial to comprehend why, how, and under what consequences individuals choose to disclose their personal and health information since doing so is beneficial to the company. This SLR method allows us to find those factors that significantly impact individuals' behavioral intention to disclose personal information while using IoT technologies. Essay 2 posits, develops, and tests a comprehensive theoretical framework built upon the theory of planned behavior and the health belief model to examine factors affecting willingness to disclose PHI in order to use WFDs. A research survey is designed and distributed to a crowdsourcing platform, Mechanical Turk (M-Turk). Research hypotheses are tested using partial least square – structural equation modeling (PLS-SEM). To achieve this purpose, Essay 3 extends the findings from the previous essay and further investigates the caregiver context. Therefore, we developed a novel theoretical model utilizing privacy calculus theory and the technology acceptance model to investigate the willingness of the elderly to disclose personal health information needed to use caregiver robots. Survey data were collected using crowdsourcing utilizing Amazon's Mechanical Turk (M-Turk) and Prolific. Research hypotheses are tested using partial least square – structural equation modelling (PLS-SEM). The findings provide value for academia, practitioners, and policymakers.

Page generated in 0.0691 seconds