2021
DOI: 10.1016/j.socscimed.2021.114077
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Associations of regional racial attitudes with chronic illness in the United States

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Cited by 8 publications
(7 citation statements)
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“…When scores are aggregated regionally, the IAT has been found to be a potent predictor of health outcomes (Gran-Ruaz et al, in press). Anti-Black bias as measured by the BW-IAT among White residents predicts heart failure, cancer, stroke, and poor birth outcomes among Black residents, above and beyond the effects of explicit bias (Orchard & Price, 2017; Splan et al, 2021). One hypothesis for this finding is that health care workers in these regions have biases that affect the quality of care they provide Black residents.…”
Section: Bw-iat As a Valid Measure Of Implicit Bias In Policementioning
confidence: 99%
“…When scores are aggregated regionally, the IAT has been found to be a potent predictor of health outcomes (Gran-Ruaz et al, in press). Anti-Black bias as measured by the BW-IAT among White residents predicts heart failure, cancer, stroke, and poor birth outcomes among Black residents, above and beyond the effects of explicit bias (Orchard & Price, 2017; Splan et al, 2021). One hypothesis for this finding is that health care workers in these regions have biases that affect the quality of care they provide Black residents.…”
Section: Bw-iat As a Valid Measure Of Implicit Bias In Policementioning
confidence: 99%
“…However, in a 2019 validation paper, Hehman et al (2019) found high convergent validity when comparing state-level implicit and explicit racial bias data from Project Implicit with racially charged Google searches and nationally representative racial attitude data from the Pew Research Center. Others have shown robust associations between aggregate racial bias data from Project Implicit and a range of important health and social inequities, including COVID-19 mortality rates [34], chronic disease [35,60], adverse birth outcomes [33], and racial inequities in income [39,61], police killings [62], and school discipline practices [63]. Thus, the Project Implicit data likely provide a valid measure of area-level racial attitudes, despite self-selection of the sample.…”
Section: Discussionmentioning
confidence: 99%
“…The predictive validity of IATs has also been documented, including related to health care and health outcomes (Greenwald et al, 2009; Nosek et al, 2007). For example, research has found a relationship between physicians' implicit bias and their clinical decision making for Black patients, as well as poorer health outcomes among BIPOC when they live in regions and states higher in implicit racism (Green et al, 2007; Splan et al, 2021; Zestcott et al, 2021).…”
Section: Methodsmentioning
confidence: 99%