How Good is Good Enough? Quantifying the Impact of Benefits, Accuracy, and Privacy on Willingness to Adopt COVID-19 Decision Aids

Gabriel Kaptchuk, Daniel G. Goldstein, Eszter Hargittai, Jake M. Hofman, Elissa M. Redmiles

DTRAP — 2022

DOI Link

BibTeX

@article{DBLP:journals/dtrap/KaptchukGHHR22,
  author = {Kaptchuk, Gabriel and Goldstein, Daniel G. and Hargittai, Eszter and Hofman, Jake M. and Redmiles, Elissa M.},
  title = {How Good is Good Enough? Quantifying the Impact of Benefits, Accuracy,
                    and Privacy on Willingness to Adopt {COVID-19} Decision Aids},
  journal = {{DTRAP}},
  volume = {3},
  number = {3},
  pages = {27:1--27:18},
  year = {2022},
  url = {https://doi.org/10.1145/3488307},
  doi = {10.1145/3488307},
  timestamp = {Sun, 19 Jan 2025 00:00:00 +0100},
  biburl = {https://dblp.org/rec/journals/dtrap/KaptchukGHHR22.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}