New study finds ways to improve COVID-19 digital tracking tools
More than two years have passed since the World Health Organization declared COVID-19 to be a pandemic. Yet the virus still continues to spread, and the need for effective countermeasures remains as urgent as ever.
One such countermeasure is the use of digital technology to monitor individuals who may have contracted COVID-19. To date, over 120 contact tracing apps, home quarantine apps and other digital tracking tools have been launched globally.
The more widely these solutions are used, the more they may help reduce the spread of infections. So how can people be encouraged to adopt them? This question was explored in a recent study out of UBC's Department of Electrical and Computer Engineering. We spoke with lead author Yue Huang, a UBC doctoral student, about her work.
What was the purpose of your study?
Digital tools that use personal data to achieve certain tracking goals — we call them "information-tracking solutions" — have played an important role in helping health authorities manage the pandemic. In order to remove barriers to the adoption of these solutions, we wanted to determine what factors make people less or more likely to use them. These findings could inform the design of solutions that better contain the current pandemic — and future ones, as well.
How did you carry out your study?
We conducted semi-structured interviews with 44 people living in Canada. During each interview, we showed the participant descriptions of six representative information-tracking solutions. These included contact tracing apps, which notify individuals who have been exposed to a COVID-positive person, and home quarantine apps, which can verify whether someone follows a quarantine order or not. By asking open-ended questions, we were able to have an in-depth discussion with the participants about their perceptions of each solution.
What were the key factors that influenced people's willingness to adopt a tool?
Generally speaking, people asked themselves the following four questions when they decided whether or not to use a particular solution:
- How does this solution benefit me?
- How does this solution benefit society?
- Does the technology used by the solution — for example, facial recognition — work the way it should?
- Will this solution keep my personal information safe?
We also identified the factors that influence how people answer each of these questions. For example, if the user would need to put in a great deal of effort to obtain the individual benefits of a specific solution, then they would be less willing to adopt that solution.
How can designers improve digital tracking tools?
To attract new users, all information-tracking solutions should highlight their benefits to society. At the same time, they should inform users about their limitations — for example, by advertising their success rates — so that potential users can better manage their expectations.
To build trust among users, information-tracking solutions should clearly communicate their solutions' data practices to the public. Governments must also be transparent and direct about their pandemic strategies. This means that users should be told which solution provider has access to the information they provide, as well as why their information is being accessed and how long their data will be retained. For instance, a user should know that their information is being used to verify that they are quarantining, and that it will be deleted, say, after their quarantine period ends.
In our paper, we make several other suggestions for the future design of information-tracking solutions that can potentially ease people's concerns and grow their user base. We plan to evaluate the effectiveness of these suggestions in future studies.
What sets your work apart from previous research in this area?
Past studies focused primarily on contact tracing apps. We looked at a broader range of solutions that require different kinds of personal information — location data, selfies, phone numbers and more — and have different tracking goals.
Our qualitative approach also enabled us to gain a deeper understanding of the process people undergo when deciding whether to use a given solution. What factors do they consider? How do they relate to one another? And how do these things promote or hinder usage?
"COVID-19 Information-Tracking Solutions: A Qualitative Investigation of the Factors Influencing People's Adoption Intention" was co-authored by Yue Huang, Borke Obada-Obieh and Konstantin Beznosov of UBC's Department of Electrical and Computer Engineering, Elissa M. Redmiles of the Max Planck Institute for Software Systems and Satya Lokam of Microsoft Research.
Photo by Mika Baumeister on Unsplash
