Technology Category
Application Domains: Humanities & Computational Social ScienceData Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, TrustMachine Learning: Privacy
Digital Contact Tracing: Examining the Effects of Understanding and Release Organization on Public Trust
🤖 AI Summary
This study investigates whether public trust in COVID-19 digital contact tracing applications is influenced by individuals’ understanding of their privacy-preserving mechanisms and the institutional identity of the app publisher (public vs. private sector). Analyzing online survey data from 101 U.S. adults, we employed correlation and regression analyses to test hypothesized relationships. Results indicate that: (1) comprehension of privacy mechanisms exhibits no statistically significant association with trust levels; and (2) the publisher’s institutional affiliation—whether governmental (e.g., U.S. federal agencies) or private-sector consortia (e.g., the Google–Apple Exposure Notification framework)—does not significantly predict trust. These findings challenge two prevailing assumptions in digital health governance: that privacy literacy drives trust, and that institutional provenance inherently determines credibility. Instead, trust appears contingent on unmeasured factors—such as perceived risk, social norms, or firsthand usability experiences. The study thus provides novel empirical evidence and prompts theoretical reconsideration of trust formation in digital public health interventions.
Technology Category
Application Category
📝 Abstract
Contact tracing has existed in various forms for a very long time. With the rise of COVID-19, the concept has become increasingly important to help slow the spread of the virus. One approach to modernizing contact tracing is to introduce applications that detect all close contacts without individuals having to interact knowingly. 101 United States adults were surveyed in June of 2022 regarding their perceptions and trust of COVID-19 contact tracing applications. We see no definitive correlation between an individual's understanding of privacy protection procedures for contact tracing applications and their willingness to trust such an application. We also see that the release of the application by a private entity like Google-Apple or by a public entity like the United States Federal Government has no significant correlation with a person's trust in the application.
Problem
Research questions and friction points this paper is trying to address.
Examining public trust in digital contact tracing apps
Assessing impact of privacy understanding on app trust
Comparing trust in private vs public sector app releases
Innovation
Methods, ideas, or system contributions that make the work stand out.
Surveyed US adults on contact tracing trust
No link between privacy understanding and trust
No trust difference between private and public releases
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