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Behavioural barriers to COVID-19 testing in Australia
Carissa Bonner; Carys Batcup; Julie Ayre; Kristen Pickles; Rachael Dodd; Tessa Copp; Samuel Cornell; Erin Cvejic; Thomas Dakin; Jennifer Isautier; Brooke Nickel; Kirsten J McCaffery.
Afiliação
  • Carissa Bonner; University of Sydney
  • Carys Batcup; University of Sydney
  • Julie Ayre; University of Sydney
  • Kristen Pickles; University of Sydney
  • Rachael Dodd; University of Sydney
  • Tessa Copp; University of Sydney
  • Samuel Cornell; University of Sydney
  • Erin Cvejic; University of Sydney
  • Thomas Dakin; University of Sydney
  • Jennifer Isautier; University of Sydney
  • Brooke Nickel; University of Sydney
  • Kirsten J McCaffery; University of Sydney
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20201236
ABSTRACT
BackgroundThe current suppression strategy for COVID-19 in Australia is dependent on people getting tested and self-isolating while they have COVID-19 symptoms. However, there is very little research on the behaviours and behavioural barriers involved in getting tested, both in Australia and worldwide, despite there being some evidence that these barriers do exist. MethodsThe Sydney Health Literacy Lab (SHeLL) has been conducting a national longitudinal survey in Australia since April 2020. A list of testing barriers was included in Wave 3 in June 2020 (n=1369), along with intentions to test and self-isolate if symptomatic. Open responses were also collected. The test barriers identified were categorised using the COM-B framework. ResultsOnly 49% of people strongly agreed they would get tested if they had COVID-19 symptoms, but most people agreed to some extent that they would get tested (96%). The most common barriers selected from the list provided were that testing is painful (11%), not knowing how to get tested (7%), and worry about getting infected at the testing centre (5%). Many participants (10%) indicated other reasons, and open responses included many additional barriers to testing than those provided in the initial list. These covered all components of the COM-B model. ConclusionWe identified a wide range of barriers using both quantitative and qualitative methods, which need to be addressed in order to increase COVID-19 testing behaviour.
Licença
cc_by_nc_nd
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Estudo observacional / Estudo prognóstico / Pesquisa qualitativa Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Estudo observacional / Estudo prognóstico / Pesquisa qualitativa Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
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