摘要：Objectives. We assessed implicit and explicit bias against both Latinos and African Americans among experienced primary care providers (PCPs) and community members (CMs) in the same geographic area. Methods. Two hundred ten PCPs and 190 CMs from 3 health care organizations in the Denver, Colorado, metropolitan area completed Implicit Association Tests and self-report measures of implicit and explicit bias, respectively. Results. With a 60% participation rate, the PCPs demonstrated substantial implicit bias against both Latinos and African Americans, but this was no different from CMs. Explicit bias was largely absent in both groups. Adjustment for background characteristics showed the PCPs had slightly weaker ethnic/racial bias than CMs. Conclusions. This research provided the first evidence of implicit bias against Latinos in health care, as well as confirming previous findings of implicit bias against African Americans. Lack of substantive differences in bias between the experienced PCPs and CMs suggested a wider societal problem. At the same time, the wide range of implicit bias suggested that bias in health care is neither uniform nor inevitable, and important lessons might be learned from providers who do not exhibit bias. Significant ethnic/racial disparities in health care and health outcomes show remarkable consistency across illnesses and health care services in the United States. 1,2 Reduction of these disparities and their associated excess morbidity and mortality is a major goal for quality improvement. 3–6 A 2003 report by the Institute of Medicine crystallized long-standing concerns that provider attitudes are part of the problem, concluding that “bias, stereotyping, prejudice, and clinical uncertainty on the part of healthcare providers” likely play a role in the continuation of health disparities. 7 (p12) For present purposes, bias can be defined as the negative evaluation of one group and its members relative to another. Such an evaluation can be expressed explicitly (e.g., “I don’t want to work with Latinos”) or more implicitly (e.g., negative nonverbal behavior). Explicit bias also differs from implicit bias in terms of the underlying process. Explicit bias requires that the person is aware of the evaluation, believes that evaluation to be correct in some manner, and has the time and motivation to act on it in the current situation. 8–10 Accordingly, explicit bias is measured by asking individuals to report on their own feelings and beliefs. Such measures show that explicit bias against ethnic/racial groups has declined significantly over the past 50 years and is now unacceptable in general society. 11 Implicit bias, by contrast, operates in an unintentional and even unconscious manner. 8–10,12 Activated by situational cues (e.g., a person’s skin color), implicit bias can quickly and unknowingly exert its influence on perception, memory, and behavior. 10,13–17 Self-report is therefore not a good measure of implicit bias. This form of bias is instead measured by sophisticated instruments that have been developed for this purpose, the most common being the Implicit Association Test (IAT). 18,19 These instruments reveal that, unlike the decline in explicit bias, implicit bias appears to be common and persistent. 20–22 To better understand how implicit bias may affect clinical outcomes, consider the example of an implicitly biased physician who wrongly perceives that an African American patient with uncontrolled hypertension is uncooperative and unlikely to adhere to a more intensive treatment regimen. Unaware of the distortions introduced by bias, the physician may not intensify treatment appropriately. Furthermore, the physician may demonstrate bias in unconsciously negative behavior (e.g., in facial expression, body language, and voice tone), making the patient uncomfortable and hesitant to engage in honest dialogue. In this manner, implicit bias may hamper the flow of information and weaken the patient’s resolve to follow treatment recommendations. 23–28 Six studies directly measured ethnic/racial biases among health care providers, all focused on bias against African Americans. 29–34 Five of these studies found evidence that providers had implicit bias against African Americans to varying degrees, whereas explicit bias against the same group was low to nonexistent. 35 Although the number of studies is not high, the evidence has been generally consistent in suggesting that implicit, but not explicit, ethnic/racial bias exists in health care settings. This conclusion is circumscribed, however, by limitations of the research. 35 First, ethnic/racial bias in health care has not yet been assessed with regard to groups other than African Americans. Of particular concern in this regard is the lack of research on bias against Latinos, who constitute the largest and fastest-growing minority group in the United States, 36 and who also experience a disproportionate burden of poor health outcomes. 1,2 Second, all but 1 of the studies were conducted with relatively young and inexperienced providers (residents and students). It is therefore unknown how experienced providers might respond. Third and finally, nearly all of the studies had very low (e.g., 26%) or unknown response rates, again calling into question the representativeness of the results. 35 In this study, we hypothesized that primary care providers (PCPs) would demonstrate, on average, a substantial level of implicit bias (Cohen’s d ≥ 0.50) against Latinos and against African Americans; that PCPs would demonstrate little explicit bias (Cohen’s d ≤ 0.50) against either group; and that PCPs and community members (CMs) would not differ in implicit or explicit ethnic/racial bias.
