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10.1371/journal.pone.0244827

http://scihub22266oqcxt.onion/10.1371/journal.pone.0244827
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33481841!7822556!33481841
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suck abstract from ncbi


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pmid33481841      PLoS+One 2021 ; 16 (1): e0244827
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  • The acceptability and uptake of smartphone tracking for COVID-19 in Australia #MMPMID33481841
  • Garrett PM; White JP; Lewandowsky S; Kashima Y; Perfors A; Little DR; Geard N; Mitchell L; Tomko M; Dennis S
  • PLoS One 2021[]; 16 (1): e0244827 PMID33481841show ga
  • In response to the COVID-19 pandemic, many Governments are instituting mobile tracking technologies to perform rapid contact tracing. However, these technologies are only effective if the public is willing to use them, implying that their perceived public health benefits must outweigh personal concerns over privacy and security. The Australian federal government recently launched the 'COVIDSafe' app, designed to anonymously register nearby contacts. If a contact later identifies as infected with COVID-19, health department officials can rapidly followup with their registered contacts to stop the virus' spread. The current study assessed attitudes towards three tracking technologies (telecommunication network tracking, a government app, and Apple and Google's Bluetooth exposure notification system) in two representative samples of the Australian public prior to the launch of COVIDSafe. We compared these attitudes to usage of the COVIDSafe app after its launch in a further two representative samples of the Australian public. Using Bayesian methods, we find widespread acceptance for all tracking technologies, however, observe a large intention-behaviour gap between people's stated attitudes and actual uptake of the COVIDSafe app. We consider the policy implications of these results for Australia and the world at large.
  • |*Mobile Applications[MESH]
  • |*Smartphone[MESH]
  • |Adult[MESH]
  • |Aged[MESH]
  • |Attitude to Health[MESH]
  • |Australia/epidemiology[MESH]
  • |Bayes Theorem[MESH]
  • |COVID-19/*epidemiology[MESH]
  • |Contact Tracing/*methods[MESH]
  • |Female[MESH]
  • |Humans[MESH]
  • |Intention[MESH]
  • |Male[MESH]


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