ABSTRACT
We conducted semi-structured interviews with 20 users of Canada's exposure-notification app, COVID Alert. We identified several types of users' mental models for the app. Participants' concerns were found to correlate with their level of understanding of the app. Compared to a centralized contact-tracing app, COVID Alert was favored for its more efficient notification delivery method, its higher privacy protection, and its optional level of cooperation. Based on our findings, we suggest decision-makers rethink the app's privacy-utility trade-off and improve its utility by giving users more control over their data. We also suggest technology companies build and maintain trust with the public. Further, we recommend increasing diagnosed users' motivation to notify the app and encouraging exposed users to follow the guidelines. Last, we provide design suggestions to help users with Unsound and Innocent mental models to better understand the app. © 2022 ACM.
ABSTRACT
Numerous information-Tracking solutions have been implemented worldwide to fight the COVID-19 pandemic. While prior work has heavily explored the factors affecting people's willingness to adopt contact-Tracing solutions, which inform people when they have been exposed to someone positive for COVID-19, numerous countries have implemented other information-Tracking solutions that use more data and more sensitive data than these commonly studied contact-Tracing apps. In this work, we build on existing work focused on contact-Tracing apps to explore adoption and design considerations for six representative information-Tracking solutions for COVID-19, which differ in their goals and in the types of information they collect. To do so, we conducted semi-structured interviews with 44 participants to investigate the factors that influence their willingness to adopt these solutions. We find four main categories of influences on participants' willingness to adopt such solutions: individual benefits of the solution, societal benefits of the solution, functionality concern, and digital safety (e.g., security and privacy) concerns. Further, we enumerate the factors that inform participants' evaluations of these categories. Based on our findings, we make recommendations for the future design of information-Tracking solutions and discuss how different factors may balance against benefits in future crisis situations. © 2022 ACM.