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Applied Racial/Ethnic Healthcare Disparities Research Using Implicit Measures.
Hagiwara, Nao; Dovidio, John F; Stone, Jeff; Penner, Louis A.
Afiliação
  • Hagiwara N; Virginia Commonwealth University.
  • Dovidio JF; Yale University.
  • Stone J; University of Arizona.
  • Penner LA; Wayne State University/Karmanos Cancer Institute.
Soc Cogn ; 38(Suppl): s68-s97, 2020 Nov.
Article em En | MEDLINE | ID: mdl-34103783
ABSTRACT
Many healthcare disparities studies use the Implicit Association Test (IAT) to assess bias. Despite ongoing controversy around the IAT, its use has enabled researchers to reliably document an association between provider implicit prejudice and provider-to-patient communication (provider communication behaviors and patient reactions to them). Success in documenting such associations is likely due to the outcomes studied, study settings, and data structure unique to racial/ethnic healthcare disparities research. In contrast, there has been little evidence supporting the role of providers' implicit bias in treatment recommendations. Researchers are encouraged to use multiple implicit measures to further investigate how, why, and under what circumstances providers' implicit bias predicts provider-to-patient communication and treatment recommendations. Such efforts will contribute to the advancement of both basic social psychology/social cognition research and applied health disparities research a better understanding of implicit social cognition and a more comprehensive identification of the sources of widespread racial/ethnic healthcare disparities, respectively.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Guideline / Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Guideline / Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article