Camellia Zakaria
University of Massachusetts Amherst, Amherst, Massachusetts, United States
Digital contact tracing can limit the spread of infectious diseases. Nevertheless, barriers remain to attain sufficient adoption. In this study, we investigate how willingness to participate in contact tracing is affected by two critical factors: the modes of data collection and the type of data collected. We conducted a scenario-based survey study among 220 respondents in the United States (U.S.) to understand their perceptions about contact tracing associated with automated and manual contact tracing methods. The findings indicate a promising use of smartphones and a combination of public health officials and medical health records as information sources. Through a quantitative analysis, we describe how different modalities and individual demographic factors may affect user compliance when participants are asked to provide four key information pieces for contact tracing.
https://dl.acm.org/doi/abs/10.1145/3491102.3517595
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2022.acm.org/)