Unpacking Intention and Behavior: Explaining Contact Tracing App Adoption and Hesitancy in the United States

要旨

COVID-19 has demonstrated the importance of digital contact tracing apps in reducing the spread of disease. Despite people widely expressing interest in using contact tracing apps, actual installation rates have been low in many parts of the world. Prior studies suggest that decisions to use these apps are largely shaped by pandemic beliefs, social influences, perceived benefits and harms, and other factors. However, there is a gap in understanding what factors motivate intention, but not subsequent behavior of actual adoption. Reporting on a survey of 290 U.S. residents, we disentangle the intention-behavior gap by investigating factors associated with installing a contact tracing app from those associated with intending to install, but not actually installing. Our results suggest that social norms can be leveraged to span the intention-behavior gap, and that a privacy paradox may influence people's adoption decisions. We present recommendations for technologies that enlist individuals to address collective challenges.

受賞
Honorable Mention
著者
Jack Jamieson
NTT, Keihanna, Japan
Daniel A.. Epstein
University of California, Irvine, Irvine, California, United States
Yunan Chen
University of California Irvine, Irvine, California, United States
Naomi Yamashita
NTT, Keihanna, Japan
論文URL

https://dl.acm.org/doi/abs/10.1145/3491102.3501963

動画

会議: CHI 2022

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2022.acm.org/)

セッション: COVID Technologies

290
5 件の発表
2022-05-05 18:00:00
2022-05-05 19:15:00