Dissertation/Thesis Abstract

Causal and predictive relationships among race, implicit racial bias, and simulated treatment recommendations
by Charles, Laurine T., Ph.D., Capella University, 2009, 197; 3380481
Abstract (Summary)

This study applied social unconscious theory to measure the relationships among race, implicit racial bias, and treatment recommendations to ascertain whether they might suggest a potential link to race-based health disparities. Seventy medical residents participated in a causal comparative research design that measured effects of the independent variables medical resident race, medical resident implicit racial bias as measured by the Implicit Association Test (IAT), and patient race on treatment recommendations made in a simulated clinical vignette. Analysis included a 2x2x2 factorial analysis of variance (ANOVA) for main and interaction effects, and binary logistic regression analyses. IAT scores (F = 2.582, α = .024) and patient race ( F = 26.56, α = .000) demonstrated significant main effects on the number of treatment recommendations. Medical residents with negative implicit racial bias recommended significantly fewer treatments ( = 3.2) than did medical residents with positive implicit racial bias ( = 5.28). Simulated Black patients received significantly fewer ( = 3.247) treatments than did simulated White patients ( = 5.280). The odds of White patients receiving the full complement of treatments were 102 (α = .000) times that for Black patients. The odds of receiving all treatments were 4.846 (α = .005) for each one unit increase in IAT score. The odds of receiving fewer than the mean number of treatments was 1941 (α = .002) greater in medical residents with negative implicit racial bias than in medical residents with positive implicit racial bias. Black patients were 5.389 times more likely than were White patients to receive fewer than the mean number of treatments (α = .005). These findings have significant implications. Physicians should be encouraged to examine personal biases for effects on cross-cultural decision-making. Educators should incorporate the IAT into the curriculum to provide students opportunities to understand how bias might affect clinical decisions. Future research testing larger numbers of racial and ethnic participants, and investigating the effects of systems factors on the application of race and implicit racial bias in the clinical setting will be informative. Developing methods to moderate the effects of implicit racial bias and interventions to improve clinical decision-making can ultimately reduce race- and bias-based health disparities.

Indexing (document details)
Advisor: Worthington, Michael T.
Commitee: Hurd, Debra, Moore, Julia
School: Capella University
Department: School of Human Services
School Location: United States -- Minnesota
Source: DAI-B 70/12, Dissertation Abstracts International
Subjects: Social psychology, Public health, Sociology
Keywords: Clinical decision making, Cross cultural communication, Health disparities, Implicit association test, Implicit racial bias
Publication Number: 3380481
ISBN: 978-1-109-51426-1
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