{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T15:24:42Z","timestamp":1767713082351,"version":"3.41.0"},"reference-count":38,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2020,11,17]],"date-time":"2020-11-17T00:00:00Z","timestamp":1605571200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Digit. Gov.: Res. Pract."],"published-print":{"date-parts":[[2021,1,31]]},"abstract":"<jats:p>The COVID-19 pandemic spread across the world in late 2019 and early 2020. As the pandemic spread, technologists joined forces with public health officials to develop apps to support COVID-19 response. Yet, for these technological solutions to benefit public health, users must be willing to adopt these apps. This article details a framework of inputs to a user\u2019s decision to adopt a COVID-19 contact-tracing app or other COVID-19 technology along four major axes: technology benefits, solution accuracy, privacy considerations, and mobile-related costs. This framework is empirically validated via both the literature and a demographically-representative survey of 1,000 Americans.<\/jats:p>","DOI":"10.1145\/3428093","type":"journal-article","created":{"date-parts":[[2020,10,30]],"date-time":"2020-10-30T17:09:25Z","timestamp":1604077765000},"page":"1-12","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":43,"title":["User Concerns &amp; Tradeoffs in Technology-facilitated COVID-19 Response"],"prefix":"10.1145","volume":"2","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3930-8128","authenticated-orcid":false,"given":"Elissa M.","family":"Redmiles","sequence":"first","affiliation":[{"name":"Microsoft Research 8 Max Planck Institute for Software Systems, Germany"}]}],"member":"320","published-online":{"date-parts":[[2020,11,17]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Dan Frakes Nick Guy and Kevin Purdy. 2020. 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Dhillon , and Anne Liu . 2015 . Introduction of mobile health tools to support ebola surveillance and contact tracing in guinea. Global Health: Sci . Pract. 3 , 4 (2015), 646 -- 659 . Jilian A. Sacks, Elizabeth Zehe, Cindil Redick, Alhoussaine Bah, Kai Cowger, Mamady Camara, Aboubacar Diallo, Abdel Nasser Iro Gigo, Ranu S. Dhillon, and Anne Liu. 2015. Introduction of mobile health tools to support ebola surveillance and contact tracing in guinea. Global Health: Sci. Pract. 3, 4 (2015), 646--659.","journal-title":"Pract."},{"key":"e_1_2_1_32_1","unstructured":"Nina McMurry Sarah Kreps Baobao Zhang. 2020. Contact-tracing apps face serious adoption obstacles. Brookings. Retrieved from https:\/\/www.brookings.edu\/techstream\/contact-tracing-apps-face-serious-adoption-obstacles\/.  Nina McMurry Sarah Kreps Baobao Zhang. 2020. Contact-tracing apps face serious adoption obstacles. Brookings. 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Arxiv Preprint Arxiv:2006.10933 (2020)."},{"key":"e_1_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1080\/0960085X.2020.1784046"},{"key":"e_1_2_1_37_1","volume-title":"et\u00a0al","author":"Troncoso Carmela","year":"2020","unstructured":"Carmela Troncoso , Mathias Payer , Jean-Pierre Hubaux , Marcel Salath\u00e9 , James Larus , Edouard Bugnion , Wouter Lueks , Theresa Stadler , Apostolos Pyrgelis , Daniele Antonioli , et\u00a0al . 2020 . Decentralized Privacy-Preserving Proximity Tracing. Technical Report. \u00c9cole polytechnique f\u00e9d\u00e9rale de Lausanne . Carmela Troncoso, Mathias Payer, Jean-Pierre Hubaux, Marcel Salath\u00e9, James Larus, Edouard Bugnion, Wouter Lueks, Theresa Stadler, Apostolos Pyrgelis, Daniele Antonioli, et\u00a0al. 2020. Decentralized Privacy-Preserving Proximity Tracing. Technical Report. \u00c9cole polytechnique f\u00e9d\u00e9rale de Lausanne."},{"key":"e_1_2_1_38_1","unstructured":"Kelsey Waddill. 2020. Payers Assist States in Contact Tracing Despite Consumer Distrust. Retrieved from https:\/\/healthpayerintelligence.com\/news\/payers-assist-states-in-contact-tracing-despite-consumer-distrust.  Kelsey Waddill. 2020. Payers Assist States in Contact Tracing Despite Consumer Distrust. Retrieved from https:\/\/healthpayerintelligence.com\/news\/payers-assist-states-in-contact-tracing-despite-consumer-distrust."}],"container-title":["Digital Government: Research and Practice"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3428093","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3428093","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T21:24:23Z","timestamp":1750195463000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3428093"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,17]]},"references-count":38,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1,31]]}},"alternative-id":["10.1145\/3428093"],"URL":"https:\/\/doi.org\/10.1145\/3428093","relation":{},"ISSN":["2691-199X","2639-0175"],"issn-type":[{"type":"print","value":"2691-199X"},{"type":"electronic","value":"2639-0175"}],"subject":[],"published":{"date-parts":[[2020,11,17]]},"assertion":[{"value":"2020-07-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2020-10-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2020-11-17","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}