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      The Impacts of the Perceived Transparency of Privacy Policies and Trust in Providers for Building Trust in Health Information Exchange: Empirical Study

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          Abstract

          Background

          In the context of exchange technologies, such as health information exchange (HIE), existing technology acceptance theories should be expanded to consider not only the cognitive beliefs resulting in adoption behavior but also the affect provoked by the sharing nature of the technology.

          Objective

          We aimed to study HIE adoption using a trust-centered model. Based on the Theory of Reasoned Action, the technology adoption literature, and the trust transfer mechanism, we theoretically explained and empirically tested the impacts of the perceived transparency of privacy policy and trust in health care providers on cognitive and emotional trust in an HIE. Moreover, we analyzed the effects of cognitive and emotional trust on the intention to opt in to the HIE and willingness to disclose health information.

          Methods

          A Web-based survey was conducted using data from a sample of 493 individuals who were aware of the HIE through experiences with a (or multiple) provider(s) participating in an HIE network.

          Results

          Structural Equation Modeling analysis results provided empirical support for the proposed model. Our findings indicated that when patients trust in health care providers, and they are aware of HIE security measures, HIE sharing procedures, and privacy terms, they feel more in control, more assured, and less at risk. Moreover, trust in providers has a significant moderating effect on building trust in HIE efforts ( P<.05). Results also showed that patient trust in HIE may take the forms of opt-in intentions to HIE and patients’ willingness to disclose health information that are exchanged through the HIE ( P<.001).

          Conclusions

          The results of this research should be of interest to both academics and practitioners. The findings provide an in-depth dimension of the HIE privacy policy that should be addressed by the health care organizations to exchange personal health information in a secure and private manner. This study can contribute to trust transfer theory and enrich the literature on HIE efforts. Primary and secondary care providers can also identify how to leverage the benefit of patients’ trust and trust transfer process to promote HIE initiatives nationwide.

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          Most cited references82

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          Trust and TAM in Online Shopping: An Integrated Model

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            Conducting behavioral research on Amazon's Mechanical Turk.

            Amazon's Mechanical Turk is an online labor market where requesters post jobs and workers choose which jobs to do for pay. The central purpose of this article is to demonstrate how to use this Web site for conducting behavioral research and to lower the barrier to entry for researchers who could benefit from this platform. We describe general techniques that apply to a variety of types of research and experiments across disciplines. We begin by discussing some of the advantages of doing experiments on Mechanical Turk, such as easy access to a large, stable, and diverse subject pool, the low cost of doing experiments, and faster iteration between developing theory and executing experiments. While other methods of conducting behavioral research may be comparable to or even better than Mechanical Turk on one or more of the axes outlined above, we will show that when taken as a whole Mechanical Turk can be a useful tool for many researchers. We will discuss how the behavior of workers compares with that of experts and laboratory subjects. Then we will illustrate the mechanics of putting a task on Mechanical Turk, including recruiting subjects, executing the task, and reviewing the work that was submitted. We also provide solutions to common problems that a researcher might face when executing their research on this platform, including techniques for conducting synchronous experiments, methods for ensuring high-quality work, how to keep data private, and how to maintain code security.
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              Structural Equation Modeling and Regression: Guidelines for Research Practice

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                Author and article information

                Contributors
                Journal
                JMIR Med Inform
                JMIR Med Inform
                JMI
                JMIR Medical Informatics
                JMIR Publications (Toronto, Canada )
                2291-9694
                Oct-Dec 2019
                26 November 2019
                : 7
                : 4
                : e14050
                Affiliations
                [1 ] Department of Information Systems and Business Analytics College of Business Florida International University Miami, FL United States
                Author notes
                Corresponding Author: Pouyan Esmaeilzadeh pesmaeil@ 123456fiu.edu
                Author information
                https://orcid.org/0000-0002-3885-8112
                Article
                v7i4e14050
                10.2196/14050
                6913631
                31769757
                9ef118d3-bddd-4114-97aa-aa0f0cd553b4
                ©Pouyan Esmaeilzadeh. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 26.11.2019.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on http://medinform.jmir.org/, as well as this copyright and license information must be included.

                History
                : 18 March 2019
                : 4 September 2019
                : 11 September 2019
                : 28 September 2019
                Categories
                Original Paper
                Original Paper

                cognitive trust in competence,cognitive trust in integrity,emotional trust,perceived transparency of privacy policy,trust in health care providers

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