Accepted for/Published in: JMIR Formative Research
Date Submitted: Jan 18, 2022
Date Accepted: Jan 24, 2023
Date Submitted to PubMed: Feb 3, 2023
A Protection Motivation Perspective among Public Users on the Utilization of COVID-19 Mobile Tracing Apps: An Empirical Study
ABSTRACT
Background:
COVID-19 continues to cause global health and economic turmoil. In the U.S., Federal, State, Local Agencies, and multiple private sector organizations require individuals report positive COVID test results and vaccination status. There are both personal and politically motivated legal challenges to reporting mandates and general distrust about sharing COVID-related information. Even though leveraging technology is considered beneficial for tackling COVID-19, people may have concerns about sharing their data with the government or private sector organizations that can provide the analytics necessary to assess the risks of contracting the virus.
Objective:
This study examines individuals’ perceptions about sharing data on COVID-related metrics such as testing frequency, diagnosis, and vaccination status on mobile applications.
Methods:
The hypothesized research model was tested using a cross-sectional survey instrument. Data was collected from 367 participants through Amazon Mechanical Turk (MTurk). We analyzed the theoretical model using structural equation modeling (SEM).
Results:
Self-efficacy and perceived vulnerability both have statistically significant positive impacts on the intention to use mobile tracing apps. Privacy concerns and risk aversion have statistically significant negative influence on the intention to use mobile tracing apps.
Conclusions:
Utilizing mobile applications to combat COVID is possible; however, Federal, State, Local and private organizations must address the concerns of individuals to improve utilization.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.