Our study about users’ expectations, experiences, and concerns with the COVID Alert app has been accepted by CSCW 2022.
Numerous smartphone apps have been implemented worldwide to help with contact tracing during the COVID-19 pandemic. Previous studies focused on identifying the privacy and security risks associated with contact tracing apps as well as learning the public’s intentions of adopting the app. However, real users’ experiences of contact tracing apps have received little attention.
In this study, we conducted semi-structured interviews with 20 users of the exposure notification app COVID Alert. We identified several types of users’ mental models of COVID Alert. Participants’ concerns were found to be correlated with their understanding of the app. Compared to a centralized contact tracing app, COVID Alert was favored due to its more efficient notification delivery method, its higher privacy protection level, and the personal choice to cooperate. Based on the findings, we suggest decision-makers rethink the app’s privacy-utility trade-off to improve its utility by giving users more control over their data. We also suggest that 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 better understand the app.
You can find more information in the paper:
Yue Huang, (website, LinkedIn), Borke Obada-Obieh, Satya Lokam, and Konstantin Beznosov, “Users’ Expectations, Experiences, and Concerns With COVID Alert, an Exposure-Notification App.” Proc. ACM Hum.-Comput. Interact. 6, CSCW2, Article 350 (November 2022), 33 pages, https://doi.org/10.1145/3555770
This video provides a quick overview of the research.