State of the Science: Implicit Bias 2018-2020
State of the Science: Implicit Bias 2018-2020Xiaodan Hu, PhD & Ange-Marie Hancock, PhD | Published 02:30 p.m. ET May 22, 2024.
Cite this article (APA-7): Hu, X., & Hancock, A. M. (2024). State of the science: Introduction to implicit bias review 2018-2020. The Kirwan Institute for the Study of Race and Ethnicity. https://kirwaninstitute.osu.edu/research/state-science-introduction-implicit-bias-review-2018-2020
The Kirwan Institute has a long history of aggregating and disseminating the latest research developments regarding implicit racial bias. We remain steadfast in our commitment to rigorously curating and making this work accessible as part of our land grant mission. In honor of Kirwan’s 20th anniversary and the 10th anniversary of the first Kirwan State of the Science, we are releasing three (3) State of the Science reports simultaneously (2018, 2019, and 2020) in a new virtual format. We will chronicle research developments in three general domains: education, healthcare, and law/criminal justice over this three-year period. Prior State of the Science reports are cited and linked where applicable throughout this page.
Implicit Bias in Education: 2018
Implicit Bias in Education: 2018In 2018, implicit racial bias research in education continued its expanded attention to the impact of implicit biases on students and education policy. Our review includes nine (9) studies published in 2018. Ranging from how educators’ unconscious stereotypes may lead to the dehumanization and marginalization of youth of color, to disparities in disciplinary actions and evaluations of learning skills, these studies provide an in-depth look at the pervasiveness of implicit bias in educational settings.
In educational settings, implicit bias has been well-documented in the literature as a contributing factor to differences in teacher-student interactions (Okonofua & Eberhardt, 2015; Warikoo et al., 2016). Beyond the classroom, however, implicit racial biases potentially held by school administrators, such as principals and vice principals who are also an integral part of education systems, are rarely examined. The impacts of implicit racial biases manifest students’ mental/behavioral/health and academic outcomes, as well as aggregated racial disparities in school discipline and underrepresentation of racial and ethnic minoritized populations across various academic fields. Understanding these biases, their manifestations, and impacts, can expand our ability to creatively address the persistent challenges implicit biases present in educational contexts.
Impact on Students
According to new research published in 2018, the detrimental effects of implicit racial biases on students can be classified into two subcategories: societal and institutional devaluation and negative academic outcomes. We take each in turn.
Prior research documents the ways in which implicit bias may lead to a dehumanization process where youth of color are perceived as older, less innocent, and therefore more accountable for their actions than their White peers of the same age (Goff et al., 2014). This dehumanization process could result in reduced or absent social protection in school settings, making children of color more susceptible to punitive measures and less likely to be given chances to rectify their wrongdoings (Goff et al., 2008). Building on the earlier work of Philip Goff (2008; 2014); Matteo Forgiarini and colleagues (2011); Joshua Correll and colleagues (2002); and Walter Gilliam and colleagues (2016), Annamma and Morrison (2018) argued that young individuals of color are subjected to the negative impacts of implicit bias through dehumanization, pain minimization, and fear maximization. Citing empirical evidence, Annamma and Morrison detailed in their discussion the process by which youth of color as young as 12-years old are dehumanized while their pain may be overlooked. The outcomes can be fatal for some, as seen in the case of Tamir Rice, who was shot by Cleveland police while playing with a toy gun. Meanwhile, others may endure less direct but still damaging forms of violence by adults in authority.
The role of fear maximization and dehumanization also affects subgroups of the United States population in particular ways. Anthony Brown (2018) offered a thorough review of theological, scientific, and social science discourses where the construction of race has been shaped in relation to Black males. The impact of these biased practices, according to Brown, originates from the durable racial discourses of power that persistently portray Black males as feared and dangerous. In this way Brown also emphasizes the connections between fear maximization, dehumanization, and implicit racial bias against Black males in schools and society.
A second area of 2018 research focuses on the impact of implicit racial biases upon teachers’ evaluations of students’ learning skills. Building on the prior work of Lennard Davis’s critical disability theory (2013), Parekh and colleagues (2018) argued that it is important to examine the role of implicit racial bias in teachers’ evaluations of students’ learning skills and how it affects different communities. They suggested that critical disability theory is particularly relevant because it dissects how our society’s excessive emphasis on ability can unfairly label people, especially those from communities that often struggle with poverty and precarity. Their exploratory study of teachers’ perception of students’ learning skills across demographic and institutional factors drew data from Canada’s largest public board of education, which served approximately 246,000 students at the time of the study. The researchers examined the associations between students’ self-reported racial identity and the degree to which they were noted as having “Excellent” learning skills across achievement categories. The findings indicated that White students were typically the most likely to be given this high rating for their learning skills. On the other hand, despite being compared at similar academic levels, students self-identifying as Black were less likely to be recognized as having “Excellent” learning skills. The results imply that Black students, irrespective of their academic performance, are not perceived to embody core attributes implicitly valued by the educational system.
This 2018 study aligns with similar results found at the post-secondary level in earlier research. In a simulated setting that replicated teaching interactions involving college student participants who exhibited lower performance on a test, researchers discovered that White instructors showed stronger implicit associations favoring White individuals and harbored negative associations towards similarly situated Black individuals (Jacoby-Senghor et al., 2015). Another study examined implicit racial associations held by teachers concerning White and Arab individuals in the United States (Kumar et al., 2015). It was observed that teachers with implicit biases favoring White individuals and holding negative associations towards Arab individuals were less inclined to establish a culturally responsive classroom environment and facilitate the resolution of interethnic conflicts within the classroom.
Historically both the intention and assumption of the roles that teachers play in classrooms have been focused on teachers’ ability to promote egalitarian attitudes and foster harmony among individuals of different races. Teachers – particularly but not exclusively White teachers – have been found to play a significant role in perpetuating racial inequality that requires attention, intention, and mitigation (Ladson-Billings, 1994; Gershenson et al. 2016). Please see the Mitigation Strategies section of this report for research findings regarding successful interventions.
Systemic Impact
Having explored the intricate ways in which implicit bias can directly impact student outcomes, we now investigate how these biases further manifest in specific areas of the educational system. In the education sector, the role of implicit bias has been linked to racial disparities in school disciplinary actions. Racial disparities play a significant role in both K-12 educational outcomes like high school graduation rates and youth getting caught up in what is now commonly called the “school-to-prison pipeline.” The stakes, therefore, could not be higher for young people.
The first area of systemic implicit racial biases’ impact is school discipline. A vast amount of prior research suggests that disciplinary methods in schools affect students of color more than their peers (such as Wallace et al., 2008; Skiba et al., 2011; Hannon et al., 2013). A plethora of studies have found that certain student subgroups face a disproportionate amount of exclusionary discipline (Aud et al., 2011; Nowicki, 2018; U.S. Department of Education, Office for Civil Rights, 2015). Implicit racial bias is one of the contributing factors to this problem (Girvan et al., 2017; Goff et al., 2014), particularly under certain conditions, such as when teachers or administrators are making decisions that are ambiguous, demand fast judgement, or when they are physically or mentally drained (Kouchaki & Smith, 2014). Black students were found to be significantly more likely than White students to be labeled as troublemakers, their misbehaviors were more likely to be perceived as indicative of a pattern. Educators also showed a higher tendency to envision themselves suspending a Black student in the future compared to a White student. (Okonofua & Eberhardt, 2015). The role of implicit bias in school discipline becomes more evident when we examine the disparities for more subjective behavior infractions such as disruption, as opposed to objective infractions like theft (Skiba et al., 2011). Objective infractions are behaviorally defined and based on objective event (e.g., fighting, skipping classes) that often leaves a permanent product, whereas subjective infractions are defined vaguely and more open to subjective interpretation (e.g., defiance, disrespect; Skiba et al., 2002; Theriot & Dupper, 2010). A study of student discipline records from more than 1,800 schools unveiled that these disparities were largely due to racial differences in office discipline referrals for subjectively defined behaviors such as defiance (Girvan et al., 2017). In sum, the past 12 years of studies reveal a troubling trend of systemic unfair treatment of students of color attributable to implicit racial bias.

A second area of systemic implicit racial biases’ impact is the persistent underrepresentation of racially minority students in particular fields, including but not limited to STEM education (McGee, 2021). Two 2018 studies – one in chemical engineering and one in the humanities – explored this impact, as did a cross-disciplinary study of recommendation letters. Farrell and Minerick (2018) examined the stealth nature of implicit bias in the realm of chemical engineering education. They argued that the pervasive presence of implicit bias and stereotype threat creates an environment where educators tend to allocate their time and resources to those students they perceive as more likely to succeed. Such an environment is likely to generate self-fulfilling prophecies and to negatively impact students’ interest in a subject as well as their levels of effort. In the same vein, Holroyd and Saul (2018) provided a detailed discussion of implicit bias in the field of philosophy. The authors suggested that implicit biases might be part of the explanation for the persisting underrepresentation and marginalization of multiple groups in philosophy. For instance, Black PhD students and professional philosophers combined are merely 1.32% of philosophers in the U.S. (Botts et al., 2014). The authors further emphasized the gravity of the situation, noting how implicit biases perpetuate unjust societal structures.
The role of implicit bias is not only limited to direct interactions between educators and students, but it also permeates more indirect aspects of the education system such as recommendation letters. Letters of recommendation, often utilized to evaluate undergraduate students’ potential for success as research assistants, interns, or graduate students, can sometimes include implicit bias, thereby potentially impacting decisions and constraining opportunities for underrepresented minorities and students from non-research institutions. Houser and Lemmons (2018) employed a text analysis software to analyze 457 recommendation letters for undergraduates applying for an international research experience, aiming to identify any significant difference in the language used to depict students who were accepted versus those who were rejected. The findings indicate that recommendation letters for successful applicants depict the students’ productivity with more certainty and incorporate more student work quotes. Conversely, the letters for unsuccessful applicants contain more positive emotion and mention the students’ insight, but also include more discrepancy-associated words (e.g., should) and tentative statements (e.g., perhaps, maybe). The statistically significant results showed the White students tended to be described in relation to their cognitive ability, insightfulness, productivity, and perceptiveness while non-White students tended to be depicted in affective languages and positive emotions.
Taken together, research conducted in 2018 regarding the impact of implicit bias continues to document the deleterious effects of implicit racial bias on students of color as well as an aggregate impact that produces systemic racial disparities. Highlights from 2018 include a theoretical focus on the mechanisms of dehumanization and fear maximization directed at individuals of color. This was complemented by studies that explored the role of implicit bias in teachers’ evaluation, nuances in recommendation letters, and underrepresentation of racial and ethnic minority populations across various academic fields. These studies and critical analyses provide a more updated understanding of the scope of implicit racial bias in education, underscoring the urgency for the sector to take meaningful actions.
Implicit Bias in Education: 2020
Implicit Bias in Education: 2020We examined twelve (12) articles published in 2020 that investigated the role of implicit racial bias in educational settings. A number of studies published in 2020 further explored the extent of teachers’ implicit racial bias and its influence on their evaluation of students. Prior literature has documented the links between racial biases held by teachers and racial inequality in education outcomes (Warikoo et al., 2016). 2020 research has revealed that it is possible that even well-intentioned teachers may be unconsciously influenced by their implicit biases, which hinder them from promoting racial equity (Starck et al., 2020).
Starck and colleagues (2020) compared teachers’ implicit bias against those of other adults with similar characteristics using two national datasets. The study found that both teachers and nonteachers have similar levels of pro-White implicit racial bias, indicating that teachers’ racial attitudes largely mirror those held by the broader society. Additionally, Chin and colleagues (2020) found that teachers’ implicit biases across the nation varied by teacher gender and race. Female teachers appeared slightly less biased than non-female teachers, and teachers of color appeared to be less biased than White teachers. Overall, teachers’ adjusted bias levels were lower in counties with higher shares of Black students, echoing the role of contextual factors. When the data were analyzed at an aggregated level, counties with higher levels of implicit racial bias among teachers tended to exhibit more pronounced disparities between Black and White students in both test scores and suspension rates. This finding persists even after adjusting for a broad array of covariates at the county level. Together, these two studies showed that schools and the teachers embedded in them should not be considered as separate entities inherently capable of counteracting societal inequalities independently (Starck, 2020)
Furthermore, Quinn (2020) conducted experimental studies to assess the impact of implicit bias on teachers’ evaluations of student writing. On average, teachers showed a significant implicit association between White students and higher writing competency (Quinn, 2020). Racial bias against Black students was found when teachers scored student writing using vague rubrics. Importantly from a mitigation perspective, racial bias was not found when teachers adhered to rubrics with clearer evaluation criteria. These findings lent support to previous implicit bias research on the relationship of evaluation criteria and teacher’s racial bias (Payne & Vuletich, 2018). Quinn (2020) noted that further research should be conducted to determine the influence of bias on specific academic subjects and the nature of the student work being evaluated.
Controlling for explicit racial bias, Marcucci (2020) conducted a survey with racial priming to examine the potential impact of implicit bias on teachers’ disciplinary decision-making. The participating teachers were randomly assigned to either the African American or White condition for the vignette, which served as the racial prime. Subsequently, the teachers were presented with questions regarding their hypothetical responses to the student described in the vignette, specifically addressing disciplinary choices that encompass punitive or rehabilitative approaches. The results indicated that teachers’ implicit bias had a greater impact on punitive disciplinary decisions than on rehabilitative decisions. Counterintuitive to conventional knowledge about anti-Black implicit bias and racial inequalities in discipline, Marcucci (2020) found that teachers treated White students more harshly by making more punitive disciplinary decisions. The author cautioned against interpreting such a finding as evidence for the presence of anti-White implicit bias. Instead, Marcucci (2020) suggested that social desirability might exert a powerful influence on teachers’ decision-making processes in specific contexts. The findings indicated that teachers have the capacity to override anti-Black implicit biases when they are aware of the socially desirable quality for racial neutrality in a reflective setting such as a survey, as opposed to the pressure of a real-time disciplinary interaction. While this overriding tendency may lead to over-correcting standards for White students and lowering expectations for Black students in a harmful manner, it also demonstrated that teachers may be open to engaging in transformative de-biasing strategies. To achieve success in implicit bias mitigation, Marcucci (2020) emphasized the need of restructuring the teaching profession to reduce the cognitive and emotional stress burden on teachers and, consequently, prioritize opportunities for self-reflection.
One recent study investigated the impact of school administrators’ implicit biases on the severity of disciplinary actions (Gullo & Beachum., 2020). With a survey sample of 43 administrators from 22 schools in 7 Pennsylvania school districts, the researchers found that the administrators showed an overall pro-White preference on the Implicit Association Test for race. Discipline data at the individual student-level, including information such as student race, infraction type, disciplinary action, and the deciding administrator for the infraction, was collected from participating districts and schools. It was found that approximately 25% of the differences in discipline severity were based on student race. Most interestingly, the severity of subjective disciplinary decisions, which are not dictated by law, policy, or code, was influenced by administrators’ implicit bias. On the other hand, some of the variations in objective disciplinary decisions were attributed to student race (Gullo & Beachum, 2020). This study is one of the first to demonstrate the influence of administrators’ implicit bias on their subjective discipline decisions.
Taking the findings from Marcucci (2020) and Gullo and Beachum (2020) together, it prompts scholars to consider the multifaceted ways implicit bias manifests itself, showing that it might differ depending on the settings where educational disciplinary practices occur. Marcucci’s controlled, survey setting demonstrated that educators are able to override their implicit biases, leading to unexpected outcomes such as more punitive measures against White students. Marcucci attributed such overriding not to anti-White bias but to the influence of social desirability and a potential over-correction upon reflection. In contrast, Gullo & Beachum’s investigation into real-world disciplinary actions confirmed the persistent effect of implicit biases. Their findings showed a pro-White preference among administrators, indicating that a notable proportion of disciplinary disparity can be attributed to implicit racial bias, particularly in subjective decision-making. These findings collectively emphasize the complexity of implicit bias in educational disciplines, particularly how it impacts punitive versus rehabilitative decisions and objective versus subjective decisions. Please see the Mitigation Section for the authors’ recommended solutions.
In summary, the research from 2020 underlined the varying influence of implicit bias across different levels of educators, not just among teachers who interact with students on a daily basis, but also among school administrators who have power to enforce discipline policies or promote applicable changes to them. In our review, we have uncovered divergent ways of how implicit bias influences educators across different contexts. A highlight that stood out is the nuanced impact implicit bias could have on disciplinary practices. It is crucial to recognize that in environments where educators are conscious of scrutiny, the effect of their implicit racial bias could lead to an overcompensation in disciplinary standards for students from different racial backgrounds. On the other hand, in situations where social desirability is not of concern, implicit bias continues to be associated with disparate subjective disciplinary decisions, leading to unjust treatment of certain student populations. While teachers and administrators may have every good intention to support all students equally, their behaviors and judgments are influenced by both their own implicit bias and deeply embedded systemic biases. These findings come at a crucial time, especially considering the anticipated demographic shift in U.S. schools where the number of racial and ethnic minority students are expected to surpass that of their non-minority peers (Federal Interagency Forum on Child and Family Statistics, 2017).
Mitigating Bias in Education
Mitigating Bias in EducationStudies from 2018-2020 did not simply continue to confirm the last ten or more years of evidence, supporting a direct link between implicit racial bias and educational policies and outcomes. Many studies also proposed and/or tested mitigation strategies, which has led to a crucial debate: Should the focus be on fixing the implicit bias held by students and teachers through awareness training, or should efforts be concentrated at the policy level? Girvan and colleagues (2017) found evidence for the former, showing that when explicit guidelines are provided, individuals are more likely to make equitable decisions. However, just making each individual accountable for their biased decisions isn’t enough. Anyon and colleagues (2018) argued for the necessity of examining specific school settings as a more systemic factor that creates discrepancies in discipline. Their study showed that it is the classroom environment itself that contributes most substantially to the disciplinary disparity among students of color. Furthermore, Tate and Page (2018) raised critiques about individual level implicit bias training. They argued that we must recognize that biases are often interlinked with broader institutional and systemic structures, emphasizing the unconscious nature of implicit bias may downplay the role of White supremacy in maintaining racism. Arlo Kempf (2020) also pointed out that the implicit bias perspective may provide a corporate-friendly lens for understanding racism at the individual level, but it is not enough for disrupting racism at the institutional and structural levels. He called for the use of critical race theory and critical pedagogy as tools to deepen implicit bias intervention approaches.
Heidi Vuletich and Keith Payne (2019) highlights the importance of considering the impact of systemic factors, such as campus-specific social indicators and faculty diversity, on the stability of individual implicit biases. They delved into the critical question of whether implicit bias can be mitigated in the long-term, and if so, under what conditions. Bearing these questions in mind, they revisited a prior study which indicated that although interventions altered participants’ bias immediately after, the effects were not sustained over time (Lai et al., 2016, Study 2). To investigate whether the stability observed in implicit bias reflected persistent individual attitudes or stable environments on campus, Vuletich and Payne reanalyzed the data collected across 18 university sites by Lai and colleagues and identified three measures capturing historical and present inequalities that could potentially influence university community members today. The three measures are: 1) public display of structural inequality (evaluating whether Confederate monuments were displayed on campuses), 2) faculty diversity (a measure reflecting underrepresentation of minority faculty as a signal of institutional inequalities), and 3) campus-specific social mobility (derived from a study estimating social mobility in U.S. universities). Lai and colleagues had previously interpreted the short-lived effects of their interventions as showing that individual’s implicit biases are difficult to change. However, Vuletich and Payne’s further analyses found that the stability of individual implicit biases should be attributed to campus environments reflecting historical and present inequalities. This reinterpretation has important implications for combating discrimination as it suggests that altering the social environment may be more effective than attempting to change individual attitudes. The findings also suggested that eliminating environmental cues of inequality, like Confederate monuments, could potentially reduce overall implicit bias. Similarly, enhancing faculty diversity at universities or diversifying leadership roles within organizations may lead to sustained institutional bias changes.
As we did in the introduction, we classified mitigation strategies into three categories: students, educators, and systems. Table 1 below presents a summary of the mitigation strategies derived from our review of the implicit bias intervention literature, specifically focusing on education published between 2018 and 2020. Each strategy is hyperlinked to facilitate easier navigation for reader.
Mitigation Strategies for Students’ Implicit Biases | |
Davis (2020); | |
Behm-Morawitz &Villamil (2019); | |
Mitigating Implicit Bias Among Educators | |
Provide Voluntary Professional Development Workshops to Educators | Aguilar (2019); |
Holroyd & Saul, 2018; | |
Systemic and Policy-Oriented Mitigation Strategies | |
Gullo & Beachum’s (2020); | |
Clark-Louque & Sullivan (2020); | |
Applebaum (2019); |
Mitigation Strategies for Students’ Implicit Biases
1. Leverage the Critical Window of Early Childhood Education
Several studies suggest that early education presents a crucial window for addressing implicit bias, including five studies from our samples: two studies by Qian et al., 2019a and 2019b; Setoh et al., 2019; McCardle and Bliss, 2019; and Davis, 2020. The first study by Qian et al. (2019a) found that implicit racial bias against outgroup members was evident in Chinese participants as young as four years old and that implicit anti-Black bias remained stable across the age range from 4 to 19 years old. This finding underscored that implicit racial bias develops at a young age. Returning to Setoh and colleagues’ 2019 study, which recommended that future research should delve into the role of social experiences in shaping children’s understanding of racial categories, the authors proposed a perceptual training approach aimed at reducing children’s automatic inclination to categorize faces based on race, potentially fostering better interracial reactions. Qian et al.’s second study (2019b) did exactly that by shedding light on the development of face-related social processing. This study also offers practical strategies for mitigating implicit racial bias in young children.
Qian and colleagues (2019b) assessed the long-term impact of perceptual individuation training on reducing implicit racial bias in preschool children. The study tracked 95 Chinese preschool children across a period of 70 days. Two perceptual individuation trainings, one initial and one supplementary, were carried out to teach preschoolers to focus on distinctive facial features rather than relying on stereotypes or group attributes. Implicit racial bias was measured at five time points, including before and immediately after each training, as well as 9, 10, and 70 days after the pretest. Results revealed that perceptual individuation training effectively reduced implicit racial bias in preschool children. Specifically, this bias reduction was observed both immediately after the initial training and 70 days after the pretest. These practical approaches could be integrated into school curriculum or utilized by social workers, as suggested by McCardle and Bliss (2019), to address individual factors leading to segregation in the society.
Furthermore, in the wake of the tragic events involving George Floyd, Breonna Taylor, and Ahmaud Arbery, Thamara Davis (2020) discussed the importance of addressing diversity, fair treatment, implicit bias, and racial trauma, particularly in the context of educating young children. She argued that such news events can emotionally impact children, potentially leading to chronic stress, similar to their effects on adults. On the other hand, these events also offer opportunities to teach about privilege, racism and implicit bias. The articles we reviewed documented that children as young as four years old have exhibited implicit racial bias against outgroup members. Therefore, avoiding these topics during this critical window may have unintended consequences. Avoiding discussions on these topics, even with young children, might foster the misconception that race is a taboo topic or create a space where prejudice and bias develop. Davis contended that parents, educators and healthcare professionals should all play a role in holding discussions about implicit bias, as well as the trauma and anxiety surrounding racial violence.
2. Embrace Multicultural Education
A second mitigation strategy we identified in our review of all 33 publications between 2018 to 2020 is an embrace of multicultural education. Multiculturalism can be described as a social and intellectual movement that upholds diversity as a fundamental principle and advocates for the equitable treatment and respect of all cultural groups (APA, 2017). This approach encompasses the incorporation of educational materials and activities designed to foster multicultural awareness, such as diversity quizzes and videos on cultural sensitivity. Three studies from our sample concurred with this strategy.
Behm-Morawitz and Villamil (2019) turned our attention to the digital realm and investigated the effectiveness of innovative online diversity training in higher education. Specifically, the research examines how an online program impacts undergraduate students’ attitudes toward diversity, motivation to control prejudice, and bias reduction toward African Americans. The study discussed a comprehensive approach to assessing bias, employing both direct (self-report) and indirect measures. With the indirect measure of the Implicit Association Test (IAT) to gauge implicit bias against African Americans, the results revealed that completing the online diversity program led to decreased implicit bias and enhanced openness to diversity. Furthermore, the researchers found that lessons addressing identity, stereotyping, housing discrimination, and education discrimination are particularly effective in engaging students with intergroup-based diversity instruction. Additionally, Behm-Morawitz and Villamil noted that the classroom setting is susceptible to society’s evolving and diverse worldviews. Therefore, when drafting online diversity training programs, it is crucial to consider the polarized U.S. political climate and students’ diverse perspectives, employing strategies such as interactive language and a second person viewpoint to draw viewers into a deeper engagement with the materials being presented. McCardle and Bliss (2019) expanded on this conversation by suggesting school integration can be seen as a strategy to promote multiculturalism as well. Their study observed a direct correlation between perceived diverse experiences and reduced implicit bias. This finding indicated that school integration could provide students with more diverse life experiences, which would better equip students’ adult life in a multiracial society by allowing more opportunities to have genuine interactions with people from different racial, regional, and socioeconomic backgrounds.
Black and Li (2020) based their research on previous culture-related studies and hypothesized that cultivating multiculturalism can be a possible solution to mitigating intergroup bias problems. For instance, trainings that emphasized cultural awareness and diversity issues were found to be a useful tool for the on-the-job education of healthcare professionals to improve cultural competency (Smith, 1998), self-awareness of cultural bias (Carter et al., 2006), and reduce stigmatization (Hayes et al., 2004). Such training programs were shown to be effective on both educators and students of different ages in improving attitude to and social engagement with outgroup members of different races and ethnicities (Turner & Brown, 2008; Warring et al., 1998; Sakurai et al., 2010). In the context of this study, intervention techniques were employed to familiarize participants with educational materials centered around multiculturalism. Black and Li’s 2020 experimental study involved random assignment of 249 undergraduate students to intervention or control conditions and found that their virtual intervention strategies successfully increased multiculturalism scores among undergraduate students. Five major sets of activities were contained in the educational materials, including a diversity awareness quiz, “My Multicultural self”; cultural sensitivity scenarios; microaggression-related educational videos, cultural appropriation, and implicit bias; and scenarios illustrating advocacy and taking proactive measures against racism. The authors argued that multiculturalism may positively influence implicit and explicit cultural attitudes, perceptions, and behaviors. This positive result of intervention demonstrates the possibility of using inexpensive and time-efficient methods to address biases in student populations.
Mitigating Implicit Bias Among Educators
1. Voluntary Professional Development Workshops:
One of the more traditional ways of mitigating implicit bias at individual level is through workshops and training programs for teachers to raise awareness about implicit bias and offer tools for introspection and self-improvement. Equipping educators with the tools they need to combat implicit bias and foster equitable educational environments is a crucial tool for disrupting the harms students of color often face due to implicit racial bias in the classroom. Our review identified four (4) studies over the three-year period that focused specifically on professional development training for educators.
Educators may not consciously endorse stereotypes, but implicit racial bias is sufficient to make an individual quickly perceive youth of color, particularly males, as threatening and justify punitive measures against them (Brown, 2018; Eberhardt et al., 2004; Mendez et al., 2002; Skiba et al., 2011; Wallace et al., 2008). Therefore, it is crucial for educators to disrupt the perpetuation of dysfunctional educational ecologies by learning and understanding the racial discourses that inform implicit bias in schools (Annamma & Morrison, 2018). Aguilar (2019) explored the potential impact of mindfulness and awareness cultivation on educators’ ability to recognize and disrupt unconscious biases, leading to a reduction in opportunity gaps within educational institutions. Aguilar (2019) emphasized the importance of acknowledging the concept of race as a detrimental narrative that perpetuates inequities in education, including the belief that students from specific backgrounds possess diminished capabilities or that certain student groups are predisposed to behavioral issues. These narratives can foster implicit biases that impact educators’ interactions and support for students, thus contributing to the persistence of opportunity gaps. To address this issue, Aguilar (2019) provided an illustrative example of a mindfulness professional development session implemented in school, as a result of this session, educators were able to proactively intercept racist thoughts as they arise, enabling them to consciously choose their responses and actions.
In their study of women of color students and faculty, Robinson et al. (2019) proposed remedies such as creating new courses centered on diversity and inclusivity, establishing safe spaces for discussions on race and sensitive topics, involving faculty in sensitivity training, and forming affinity groups to address the needs of students of color. Additionally, drawing from a previous study (Jackson et al., 2014), Robinson et al. reiterated the effectiveness of diversity training in reducing stereotypes in STEM fields and fostering a more inclusive environment. Robinson and colleagues concluded that educational institutions should prioritize support programs involving mentoring to effectively recruit and retain diverse students and faculty.
Harrison-Bernard and colleagues (2020) documented the processes and results of a professional development workshop on implicit bias held at a university. The six workshops consisted of various didactic teaching modules, active participation, and discussions aimed at increasing participants’ introspection and implicit bias awareness. Pre- and post-workshop surveys were conducted to assess participants’ self-perception of knowledge and behaviors related to diversity and implicit bias. The surveys showed that participants’ knowledge of implicit bias increased significantly as a result of the workshops. Moreover, an observational study of a single 90-minute racial affinity caucusing workshop was also conducted to for educators interested in racial health disparities (Guh et al., 2020). The workshop successfully improved participants’ impression of and confidence in implementing racial affinity caucusing. Both studies effectively demonstrate that educators’ knowledge and attitudes regarding implicit bias intervention tools can be changed even in a much shorter period of time. These studies called attention to the need for effective tools to teach and remedy the impact of implicit racial bias in education.
2. Foster Empathy and Equal Expectations for All Students
Empathy-based intervention has been using in various areas of study, such as teacher-student interaction (Okonofua et al., 2016) and healthcare-related education (Batt-Rawden et al., 2013; McGuire, 2016). Research findings exemplified by the Whitford and Emerson (2019) study showcased the potential of empathy interventions to mitigate implicit bias among pre-service teachers. The authors conducted an experiment to examine whether a brief empathy-inducing intervention could reduce implicit bias among pre-service teachers who planned to work in elementary schools. This intervention required participants to read 10 instances of racism that Black students encountered. Subsequently, participants were asked to put themselves in the students' situations, express their feelings about the experiences, detail how they would react in those scenarios, describe the potential emotions of growing up in such an environment, and suggest ways to prevent similar experiences in the future. The results showed that the empathy intervention significantly decreased implicit bias among White female pre-service teachers towards Black individuals. School discipline disparities contribute to the prison pipeline for at-risk students (Skiba et al., 2014). Empathy intervention conducted in Whitford and Emerson could serve as a foundation for promoting change and addressing implicit bias in education.
In addition to the cultivation of empathy, another similar theme also surfaced from our synthesis, underscoring the imperative of fostering equal consideration for students from diverse backgrounds. Researchers have urged educators to maintain high expectations for all students, while also being vigilant about the harmful effects of stereotype threats. This is particularly crucial for fields such as STEM education and philosophy, where minority students are severely underrepresented (Haring-Smith, 2012; Holroyd & Saul, 2018; Farrell & Minerick, 2018). In their 2018 study on chemical engineering education, Farrell and Minerick drew our attention to the fact that, due to implicit biases, educators often direct their time and resources toward students they deem most likely to be successful. To combat these challenges, the authors suggested that both students and educators have responsibilities in addressing them. Students should strive to be more mature and adaptive problem-solvers, while of course fulfilling class requirements to the best of their abilities., Educators should employ as objective a grading system as possible. Furthermore, educators should acknowledge their implicit biases, pursue self-education regarding these biases, and remain cognizant of stereotype threat and its negative impacts on students. Educators also need to send consistent messages of high expectations and anticipated success to all students in the class. Importantly, educators should not perceive limited prior experience and low confidence in engineering as deficits as these are common traits for students from underrepresented groups in engineering. Instead, these characteristics should be considered as indicators of assets that may aid students in their journey to becoming engineers.
Systemic and Policy-Oriented Mitigation Strategies
1. Utilize Objective Decision-Making Standards
The objective decision-making standards approach involves the application of data-driven methodologies and explicit guidelines to identify, analyze, and address disciplinary disparities. McIntosh and colleagues (2018) deepened scholars’ engagement with the approach by testing a four-step, data-driven decision-making strategy. This method helps to identify the interactions that are susceptible to implicit bias and then tailors the environment to meet all students' needs. The first step, problem identification, involves calculating disproportionality metrics by incorporating both risk ratios and absolute rates by subgroups. The metrics will establish the baseline for monitoring progress. Next, during the problem analysis step, potential causes for the disproportionality are identified. Tools such as the School-Wide Information System (SWIS) are recommended for examination of discipline patterns such as location, time of day, and type of behavior by subgroup. The third step is plan implementation, in which existing systems are evaluated and potentially revised to better meet student needs. McIntosh et al. (2018) recommended a flexible, proactive, multi-tiered behavioral approach that incorporates explicit expectations and accommodates the needs of students, families, and the community. This approach also promotes objective discipline procedures, such as clearly defining problematic behaviors. Finally, in the plan evaluation step, the implementation of the plan is assessed through established measures, and the original disproportionality metrics are recalculated. These are then compared with the initially identified equity goals. In a case study using this approach, McIntosh et al. (2018) noted a consistent decrease in discipline disproportionality, reinforcing the effectiveness of this objective, data-driven strategy. Gullo and Beachum's 2020 study also highlighted the importance of having clear and objective policy guidelines and procedures to help reduce the racial discipline. They also emphasized the need for schools to make efforts to expand objective policies and remove the subjective nature of many disciplinary decisions when possible.
2. Replace Negative Impact Policies with Restorative Measures
Much of the research at the systemic level has focused on the alarming disparities in K-12 school discipline. School discipline disparities contribute to the school-to-prison pipeline for marginalized students (Skiba et al., 2014). Existing policies in the current education system sometimes inadvertently contribute to the disproportionately high rates of disciplinary actions against marginalized student populations. Zero Tolerance policies are one of them (Clark-Louque & Sullivan, 2020). Zero Tolerance was originally developed and introduced to public schools in an effort to make schools safer. It operates under two basic assumptions: 1) harsh disciplines will deter student misconduct, and 2) removal of students who committed the most serious offenses will benefit the school. However, these assumptions are problematic as school principals’ attitudes are subjective and can be influenced by implicit racial bias. Recently, Zero Tolerance policies have expanded to include relatively minor issues such as dress code violations, disrespect, and willful defiance, which were observed among the common infractions leading to suspension. Notably, disrespect and willful defiance are subjective concepts which, when applied, are rife with the risk of implicit racial bias influence due to their vagueness – everyone has their own understanding of respect and defiance (Girvan et al., 2017; Skiba et al., 2002; 2011). Excessive reliance on punitive forms of discipline such as suspension was directly linked to students’ tendencies to drop out of school susceptibility to being ensnared by the criminal justice system (Fergus, 2015).
At the school administration level, Clark-Louque and Sullivan (2020) discussed the disproportionate discipline consequences faced by Black girls and linked it to the implicit biases held by some school officials. They argued that these biases, which are based on stereotypes that see Black women and girls as hypersexual, sassy, conniving, or loud (Morris, 2016), distort the views of school officials towards Black girls and resulted in the disciplinary actions taken based on Zero Tolerance policies. Clark-Louque and Sullivan (2020) presented two real-life scenarios in which Black female students were suspected of using marijuana. In one scenario, the school administration followed a Zero Tolerance approach, while in the second scenario the administration adopted a restorative and equity-based partnering approach such as asking questions that allow students to express themselves and inviting students to sign up for counseling. Under the first scenario, the student involved was eventually expelled. The four students involved in the second scenario, however, were given an opportunity to meet with the school counselor and their families were notified regarding safety concerns and future possible engagement strategies. Based on their findings the researchers strongly recommended that school administrators should guard against implicit and explicit biases by adopting restorative practices and build culturally proficient partnerships with student families instead of relying heavily on Zero Tolerance practices.
Furthermore, Romero and colleagues (2020) reviewed a number of promising studies that may shed light on how to alleviate implicit bias in school discipline. Their review showed that less punitive alternatives such as restorative justice, as opposed to the Zero Tolerance approach, are gaining popularity in schools. Romero and colleagues recommended training and intervention strategies to educators, including empathetic mindset training, motivated self-regulation, and prejudice habit-breaking interventions. The researchers emphasized that mitigating implicit bias in schools requires a sustained approach that raises awareness of implicit bias and its consequences in educational settings. This calls for the inclusion of individual level implicit bias assessments coupled with careful feedback on the results and sustained professional development.
Marcucci (2020) also championed restorative measures. Her study found that implicit bias appeared to have less influence on rehabilitative disciplinary decisions compared to punitive ones. According to Marcucci (2020), restorative practices are able to compel students and educators to find novel ways of interaction, which may humanize the students and allow educators to reflect and disrupt automatic and unconscious biased thinking. Echoing Marcucci (2020)’s findings, McIntosh and colleagues further underscored this perspective with their flexible four-step behavioral approach that exemplified the restorative measures. By pinpointing “physical aggression on the playground” as a specific vulnerable decision point that increases the likelihood of implicit bias affecting discipline decision making, the research team advised educators to set clear expectations and meet the needs of students, families, and the community. This restorative approach fosters objective discipline procedures, which have resulted in a consistent decrease in disciplinary disparity over time.
3. Utilize a Holistic Approach
The first two systemic mitigation strategies lead us to a third and final strategy: using a holistic approach. By this we mean crafting approaches that include but are not limited to mitigating implicit racial bias. This approach complements individual-level interventions by addressing the broader environmental factors that contribute to implicit bias, suggesting that sustained change may require a comprehensive strategy that includes altering the social environment.
Applebaum’s critical read of implicit bias trainings is one example. In lieu of an exclusive reliance on implicit bias training, Applebaum advocated for a more comprehensive and holistic approach that attends to systemic as well as individual and intergroup factors. Another example is proposed by Rynders (2019), who provided possible legal solutions that lawyers can employ in the courtroom and within their own practice to address implicit bias. These solutions include using expert witnesses to testify about implicit bias, using data to show disproportionality, and advocating for culturally responsive teaching practices. At the end of his discussion, Rynders called for educators and advocates to acknowledge the impact of implicit bias in these disparities and integrate research-based approaches to mitigate racial biases. He also emphasized the role of attorneys in education, asserting that special education lawyers should address racial and national origin discrimination as necessary and partner with racial justice organizations to attain educational equity.
In a similar vein, Holroyd and Saul (2018) widened the discussion to include faculty hiring and professional development. They emphasized the need for proactive strategies to counter these biases in decision-making and interactions. To specifically address the entrenched issue of implicit bias in philosophy, they offered various reform suggestions, including: diversifying the subject matter taught, setting hiring criteria in advance, and reducing dependence on letters of recommendation as a key element in faculty selection.
In response to racially disproportionate expulsion rates in preschools (Meek & Gilliam, 2016), Davis and colleagues (2020) take a more systemic approach to combating implicit bias in early education. Their theoretical framework, the Infant and Early Childhood Mental Health Consultation (IECMHC), can reduce the influence of implicit bias on educators’/teachers’ disciplinary decisions. IECMHC was developed to account for the roles played by mental health consultants in building teachers’ capacities to support the healthy social-emotional development of young children. The framework underlined the power of a strong consultative alliance between teachers and consultants with expertise in infant and early childhood mental health. This consultative alliance can be built through multiple core tasks, including: asking reflective questions, creating a holding environment for others’ emotions, raising issues of race and gender, cultivating cultural awareness, and exploring contextual influences such as parenting, trauma, cultural expectations, and developmental differences. A strong consultative alliance, in turn, can contribute to increases in reflective capacity and changes in teachers’ perspective and behavior, both of which are expected to reduce the influence of implicit bias on expulsion rates. In addition to professional help, facilitated workshops for teachers and staff members have also been created and implemented.
Building on the aforementioned strategies, the final mitigation strategy we have identified focuses on transforming the campus environment as a whole. As we noted earlier, Vuletich and Payne’s (2019) findings offered us a roadmap for this transformative approach. Their findings emphasized the power of environmental cues on campus, such as Confederate monuments and level of faculty diversity, in perpetuating biases. By addressing these historical and present inequalities embedded within the campus environment, universities have the potential to significantly reduce implicit bias.
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State of the Science: Implicit Bias in Healthcare 2018-2020
State of the Science: Implicit Bias in Healthcare 2018-2020As a pervasive influence that affects social interactions across various domains, implicit bias has drawn substantial attention in healthcare research. Questions like why youth of certain racial and ethnic backgrounds more likely to be diagnosed with disruptive behaviors (Fadus et al., 2020), or why Black individuals assumed to have stronger pain tolerance than their White counterparts (Miller et al., 2020) are just a few of the questions addressed from implicit racial bias research. Whether positive or negative in valence, implicit racial bias for or against a group influences medical providers across all specialties and negatively impacts patient care (Cooper et al., 2012; Haider et al., 2011). Between 2013 and 2017 the Kirwan Institute for the Study of Race and Ethnicity published a series of reports of implicit bias literature that analyzed the scientific foundations and impacts of implicit racial bias within the healthcare system. These State of the Science reports chronicled numerous studies that documented alarming racial disparities that result from implicit biases held at both individual and institutional levels. Specifically, Kirwan’s analysis brought together empirical research illustrating the impact of implicit bias across multiple foci in healthcare, including clinical decision-making and medical education. The report series also underscored the need for further exploration of how implicit bias manifests itself and for interventions aimed at achieving equitable healthcare outcomes. This current report updates the state of science on implicit bias in the healthcare industry across three years: 2018, 2019, and 2020. Kirwan’s first implicit bias publication, State of the Science: Implicit Bias Review 2013, laid the groundwork for our subsequent reports by evaluating implicit bias in a range of professional sectors. Regarding healthcare, both the 2013 and 2014 State of the Science reports aggregated clear empirical evidence connecting implicit racial biases with racially disparate treatment decisions across various health conditions – ranging from acute coronary syndrome to HIV (Moskowitz et al., 2012; Stone & Moskowitz, 2011). Moreover, physician biases in both doctor-patient interactions and pain assessments were documented (Burgess et al., 2014; Chae et al., 2014; Sabin et al., 2009). The State of the Science reports from 2015, 2016, and 2017 added a new dimension of analysis: the role of medical schools. These three reports shared cumulative evidence from multiple studies (Gonzalez et al., 2014; White & Stubblefield-Tave, 2017; Zestcott et al., 2016), presenting a plethora of bias mitigation strategies focused on improving equitable decision-making by medical students and ultimately reducing healthcare disparities in clinical practice. These strategies, which addressed curriculum design at the institutional level and techniques like mindfulness meditation at the individual level, provided a framework for mitigating the effects of implicit bias during the early stages of a provider’s career.
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Since the publication of the landmark report, “Unequal Treatment” (Nelson, 2002), racial and ethnic treatment disparities are now one of the most widely examined topics in the field of healthcare. Three types of healthcare interactions have been consistently identified to contribute to differential treatments of patients based on race/ethnicity: provider-patient communication (see Burgess et al., 2019; Hagiwara et al., 2020; Lowe et al., 2020b), providers’ symptom assessments (see Fadus et al., 2020), and providers’ treatment recommendations (see Burgess et al., 2019; Hymel et al., 2018; Thomas, 2018). Figure 1 illustrates a series of patterns that have been observed across these dimensions. First, multiple reviews have documented that healthcare providers’ implicit biases negatively affect provider-patient communication dynamics, which in turn, can lead to lower levels of patient satisfaction with care and reduced trust in their provider (Miller et al., 2020). Patient satisfaction and trust in their provider are also well-established predictors of patients’ health-related behaviors such as adherence to treatment, follow-up visits, and future healthcare utilization (Stewart et al., 2013; Street et al., 2009). Second, suboptimal assessments of symptoms were also identified as a contributing factor to health disparities among racial and ethnic minority patients (Fadus et al., 2019; Hymel et al., 2018; Thomas, 2018). Last but not least, healthcare provider implicit bias is also associated with suboptimal treatment recommendations for racial and ethnic minority patients as compared to their White counterparts (Fadus et al., 2020; Hagiwara et al., 2020; Hymel et al., 2018; Thomas, 2018). In a similar vein, a non-trivial number of articles across the three-year period focused on the impact of implicit racial bias on patients under the age of 18, typically called pediatric patients (Fadus et al., 2020; Goodwin, 2018; Hymel et al., 2018; Johnson, 2020; Miller et al., 2020). Findings across this period revealed substantive similarities in the role of implicit racial bias between adult or pediatric cases, suggesting two important ramifications. First, such findings underscore the ongoing vulnerability of children of color in our healthcare system. Second, and perhaps even more troubling, negative childhood medical experiences may shape patients’ willingness to seek medical care later as adults (Pate et al., 1996), creating particularly challenging conditions for improving either healthy outcomes for patients themselves at the micro level or broader community health outcomes like rates of type II diabetes or infectious disease vaccination at the macro level.
In the current review, we follow the 2017 review by exploring and consolidating the research related to implicit racial bias in healthcare published between January of 2018 and December of 2020. For this industry-specific report we analyzed a total of 61 academic articles published between 2018-2020 in peer-reviewed journals. This number includes 18 published in 2018; 17 published in 2019, and 26 published in 2020. For more information about how we selected and analyzed articles, please go to our implicit bias introduction. Table 1 illustrates the variety of specialties covered across the time period. A clear variation exists with several specialties having more scholarship published in the arena than others; some specialties remain under- or unrepresented completely.
Table 1. Specialty Representation by Year 2018-2020*
*Specialties listed in alphabetical order; some articles fit multiple categories (e.g., pediatric psychiatry, surgical education)
**While COVID19 is not a formal category, we include it in anticipation of readers’ questions about the impact of the global pandemic on our analysis.
Specialty | 2018 | 2019 | 2020 | Total |
---|---|---|---|---|
Dentistry |
| 1 |
| 1 |
Emergency Medicine |
|
|
| 1 |
Family Medicine |
| 1 |
| 1 |
Medical Education | 5 | 8 | 7 | 20 |
Mental Health (Psychiatry & Psychology) | 3 |
| 1 | 4 |
Miscellaneous General Articles | 4 | 2 | 4 | 10 |
Neurology |
|
| 2 | 2 |
Nursing | 1 | 2 | 1 | 4 |
Obstetrics | 3 |
| 2 | 5 |
Oncology |
|
| 2 | 2 |
Otolaryngology |
| 1 |
| 1 |
Pediatrics | 2 | 1 | 4 | 7 |
Radiology |
|
| 1 | 1 |
Surgery (all specialties) | 1 | 2 |
| 3 |
**COVID19 |
|
| 4 | 4 |
Especially relevant for this report, although both nurses and physicians work in challenging and high-stress environments that are conducive for implicit bias activation, researchers have raised concerns that current research on implicit bias in healthcare almost exclusively focuses on physician-patient interactions, which leaves a gap for further research on nurse- and/or medical staff-patient interactions (Crandlemire, 2020; Greene et al., 2018; Schultz & Baker, 2017). We therefore attend to the broader category of “healthcare provider” in this report to encompass practicing physicians, nurses, medical staff, interns and residents.
Understanding where the science has led scholars to date is an essential stimulus for further study. Our goal is to offer an accessible summary of implicit bias research in healthcare during this three-year window and to present insights for potential future research directions, including the development of effective interventions that contribute to the ultimate goal of establishing a more equitable healthcare system for all.
Implicit Bias in Healthcare: 2018
Implicit Bias in Healthcare: 2018Kirwan’s previous State of the Science reports emphasized differential treatment of patients due to implicit bias among healthcare providers (see also Burgess et al., 2014; Chae et al., 2014; Moskowitz et al., 2012; Sabin et al., 2009). Consistent with this theme, studies published in 2018 continued to investigate the pervasiveness of implicit racial bias within healthcare systems and its adverse impacts on the quality of care as well as patient outcomes. A total of 18 articles from the year 2018 were included in the article dataset. In the following section, we examine insights here as they pertain to the manifestation of implicit bias in healthcare. Specifically, we synthesize the findings regarding the potential negative impacts of implicit racial bias on patient care, including a discussion of disparate quality of care and differential standards of medical decision-making (Goodwin, 2018). The impact of implicit bias isn't confined to general healthcare alone but extends its reach to various specialized healthcare services, each presenting unique challenges.
Our 2018 Healthcare State of the Science takes a deep dive into the question of who in the healthcare system is influenced by implicit bias. We found articles focused on healthcare providers across specialties (Maina et al., 2018; Tajeu et al., 2018); medical trainees (Backhus et al., 2019; Hernandez, 2018); and mitigation strategies. The three articles that explicitly focus on mitigation are combined with recommendations from other years into a single cumulative mitigation strategies section for the healthcare sector. Articles published in 2018 affirm the pervasiveness of implicit racial bias among providers from multiple specialties (pediatrics, obstetrics, mental health) and trainees undergoing medical education (medical students and residents). Even patients themselves (Greene et al., 2018) are susceptible to being influenced by implicit racial bias as they make decisions about their healthcare.
Impact of Healthcare Provider’s Implicit Racial Bias on Patient Care
Our data collection strategy uncovered three medical specialties that used a variety of methods (quantitative, qualitative, mixed methods and meta-analysis) to arrive at their conclusions. In this section we focus on obstetrics, pediatrics, and mental health implicit racial bias research published in 2018. We cover additional specialties in 2019 and 2020 as applicable based on the results of our data collection strategy. All three of the specialties we analyzed for 2018 acknowledged the intersection of the healthcare system with other important and relevant systems that are also grappling with significant racial disparities: the child welfare system (obstetrics and pediatrics) and the criminal justice system (mental health).
Obstetrics
Obstetrics and gynecology as a medical specialty has a particularly fraught history with explicit racial bias and discrimination, which has had a direct effect on the quality of patient care. Several articles published in 2018 allude to this broader history as well as provide evidence of ongoing implicit racial bias. Brenda Pereda and Margaret Montoya (2018) provide a broad review of the role of implicit bias and note specifically the history of non-consensual medical experimentation on enslaved women and forced sterilization of Latinas as part of the embedding of bias. In a similar vein Erin Thomas (2018)’s study of bias among lactation consultants suggests that such bias originates from larger inequalities in society and must be addressed at their root.
Through semi-structured interviews with 36 lactation consultants, Thomas (2018) documented instances of race-based discrimination against patients seeking lactation care and connected these findings to the implicit bias literature. Through an analysis of interview transcripts, the researcher identified three subthemes of implicit bias, including lower quality and less quantity of care. Thomas used actual statements given by the interviewees to show how Black and Hispanic mothers were denied proper assistance with breastfeeding because healthcare providers believed it would be a waste of resources. Similar biases toward various Asian groups were also observed, particularly those who spoke English as a second language. Thomas (2018) explicitly connected these biases to quality of care, finding that White patients received more services and less referrals to social services in lactation care compared to Black patients. This was especially prevalent in cases where a patient used drugs or showed signs of mental illness. Although the study did not directly measure implicit bias, it presented us with compelling evidence of its existence. Of special interest to our analysis, Thomas noted negative pediatric impacts of positive implicit racial bias, where White infants were at higher risk when parents displayed evidence of drug abuse or mental illness left unacknowledged by lactation consultants.
This study was accompanied in 2018 by the publication of a national study of 286 perinatal physicians by Natasha Shapiro and colleagues (2018), which used a vignette strategy to explore the role of implicit bias regarding both race and socioeconomic status. In this study, physician participants were instructed to view a vignette featuring a female patient in imminent labor. The patient's race was indicated by a photograph of either a White or Black individual, while their socioeconomic status was implied by mentioning the care is provided by either a "Private Obstetrician" for high socioeconomic status or by the "Resident OB clinic" for low socioeconomic status. After being randomly assigned to view one of the four versions of the vignette, participants were then asked about how likely they would recommend the patient for intensive care versus comfort care.
Following this choice, participants’ implicit biases were also measured through two Implicit Association Tests (IATs) focused on race and socioeconomic status respectively. The results revealed that the participating physicians demonstrated an implicit preference for White patients and those with higher socioeconomic status. However, it was found that these implicit biases did not influence the physicians' treatment decisions based on the patient's race. The researchers suggested that this could be a result of physician’s higher self-awareness of racial biases and their impact on decision-making, making them more cognizant of not letting these biases influence their recommendations. The researchers also started with a sample of 971 physicians who initially started the study; 685 physicians did not complete the entire study so there is more work to be done to understand the relationship between implicit racial bias and implicit socioeconomic bias in obstetrics. Interestingly, some prior research suggests that someone whose behavior does not necessarily reflect the biases might still be influenced by social or cultural norms in their responses to IATs Fazio & Olson (2003), which is consistent with some of the literature in medical education that points to mitigation strategies that focus on the meso- and macro-level of analysis. We take up this point in the mitigation strategies section of this report.
Pediatrics
As with obstetrics scholarship in 2018, pediatrics research published in the same year also focused on the impact of implicit biases on quality of care in both qualitative and quantitative studies. Michele Goodwin (2018)’s analysis of the Jahi McMath case, where she documented the tragic experiences of a 13-year-old girl who suffered severe complications after receiving a routine tonsillectomy, which is the second most commonly performed pediatric surgical procedure in the United States (Jaryszak et al., 2011). Goodwin cited several statements from Jahi’s family questioning whether she received the standard quality of care. While acknowledging the tragedy of McMath’s death Goodwin suggested that there are numerous social implications regarding the influence of healthcare providers’ implicit biases upon the quality of care received by patients who are members of minoritized racial groups.
In a similar vein Kent Hymel et al. (2018) conducted a cross-sectional analysis of 500 pediatric patients under three years of age with acute head injuries to examine the potential influence of implicit bias among physicians who specialize in Abusive Head Trauma (AHT). Here the researchers used the evaluation and reporting frequencies of AHT as an indirect measure of implicit racial bias. Their findings showed that racial and ethnic minority patients were evaluated and reported more frequently for suspected AHT than White (non-Hispanic) patients, which is considered an indicator of implicit racial bias in reporting standards. Similar to the Thomas (2018) study, Hymel et al. (2018) suggest “positive” implicit racial bias, like giving White parents the “benefit of the doubt,” when assessing for potential child abuse, can have negative outcomes for White non-Hispanic babies under three years old. The consequences are critical, even if they exist predominantly in lower-risk patients, because delays in AHT diagnosis have been shown to lead to re-injury or even death.
Both obstetrics and pediatrics authors suggest that having too many false positives among minoritized caregivers in AHT cases and too few positives in lactation cases are detrimental both for the young patients themselves (infants and children up to three years old) but also for the parents, who either face unwarranted referrals to child welfare services or law enforcement OR do not get adequate treatment for the drug dependence or mental health concern, leaving children at risk in either outcome.
Mental Health
Four (4) studies published in 2018 analyzed the role of implicit racial biases in mental healthcare, using a variety of empirical methods. Similar to their peers in other specialties, healthcare providers in the mental health field also may hold similar levels of implicit bias against certain patients based on their race, ethnicity, and sexual orientation (Hall et al., 2015; Merino et al., 2018; Snowden, 2003). That said, Yesinia Merino and colleagues (2018) conclude that mental health care is particularly vulnerable to the effects of an individual provider’s implicit racial bias because it heavily relies on one-on-one services where a single provider acts as the gatekeeper to care. Ivy Maina and colleagues (2018) conducted a meta-analysis to consolidate findings of 37 studies published between 1997 and 2015. Their review found that there is growing evidence suggesting that similar to the general U.S. population, a substantial number of healthcare providers across different training levels and disciplines hold implicit biases against Black, Hispanic, American Indian, and dark-skinned individuals more broadly. Maina and colleagues found that studies focused on real-world patient care yielded more consistent findings, which revealed an association between higher implicit bias and less favorable patient-provider interactions.
Merino and colleagues (2018) argued that the potential impact of negative implicit bias reaches various aspects of mental health care, encompassing not only clinical screening but also diagnosis, treatment processes, and crisis response. Furthermore, they also explored the intersection of implicit bias in mental health care and criminal justice institutions. The authors emphasized the importance of this exploration as prison systems have become one of the largest mental health providers in the U.S. (James & Glaze, 2006). In their conclusion, Merino and colleagues reiterated the need to understand how individual practitioners' implicit attitudes influence the delivery of mental health services and treatment effectiveness. Additionally, the authors also urged future investigations to not overlook how structural inequities within the mental health system could perpetuate implicit bias. The structural inequities they identified include the lack of diversity in the mental health workforce and among mental health educators, evidence-based practices that are centered on a majority-group framework, and the lack of diversity on the boards of mental health agencies (Merino et al., 2018).
While Javeed Sukhera et al. (2018b) and George Bermudez (2018) focus more on mitigation strategies, each documents the presence of implicit racial bias among mental health care providers prior to engaging in mitigation. Sukhera et al. focuses on a group of psychiatry faculty and residents, while Bermudez focuses on a group of faculty, students and administrators from various disciplines using psychoanalytic techniques of social dreaming. Analyses of their proposed mitigation strategies in connection with other research can be found in the cumulative mitigation strategies section.
Conclusion
The studies discussed in the 2018 State of the Science use a variety of methods to document the ongoing challenges presented by the role of implicit racial bias among healthcare providers and implicit racial bias’s connection to systemic barriers in the social welfare and criminal justice systems. While recommendations for mitigation are explored in a different section of this report, the articles described here offer both general and specialty-specific ideas for future research. Both Maina et al. (2018) and Thomas (2018) identified a need to move beyond a focus on physicians’ implicit bias to include other types of healthcare providers in the mental healthcare specialty, with Thomas (2018) noting the particular role that lactation consultants play with new parents of infants. To meet this need Tajeu et al. (2018) conducted a statewide study of 107 healthcare staff, which included physicians, nurses, and non-MD/RN personnel such as receptionists. The authors found that White staff members had higher implicit racial bias against Black patients than the physicians or nurses, identifying a potential gap for both further research and mitigation strategy development.
As we noted in the general introduction to the Healthcare State of the Science report, the “who” in healthcare has continued to expand beyond simply physicians. Similar to healthcare providers and non-MD/RN staff, patients can also exhibit implicit racial bias, especially when selecting their physicians, but this also remains a relatively understudied area. Jessica Greene and colleagues (2018) asked study participants to hypothetically choose from four physicians based on their performance quality information. Among the four, two physicians had top performance ratings and two had lower quality performance ratings. The study manipulated the names of the top-performing physicians to represent different races/ethnicities and genders. The findings revealed that respondents more frequently selected a physician with a typically White male name compared to the same physician with either an African American male, African American female, or Middle Eastern name. This bias was more pronounced among White respondents. Greene and colleagues cautioned that it remains unclear if this bias found in an isolated experiment setting can translate into real-world physician selection. If it does, however, it could result in racial and ethnic minority and women physicians having smaller patient panels (Ly et al., 2016). Given the increasing enrollment in health plans with limited provider networks (Polsky & Weiner, 2015) and the painfully slow but steady diversification of the medical profession, the potential influence of implicit bias in patients' choice of new physicians becomes particularly relevant.
Implicit Bias in Health/Health Care: 2019
Implicit Bias in Health/Health Care: 2019Our review of implicit racial bias research published in 2019 includes 17 articles. Whereas research in 2018 provided multiple pieces of scholarship that offered a sense of depth in particular specialties (obstetrics, pediatrics, mental health), 2019 research featured breadth across eight (8) specialties and depth in medical education (4 articles) and mitigation strategies
(10 articles). The medical education articles complement two articles published in 2018 (Abelson et al., 2018; Hernandez, 2018), which did not on their own constitute a set of findings. We therefore further dissect how implicit racial bias plays a role in patient care by exploring it in medication education in the first section and then across specialties in the following section. Mitigation articles are discussed in the cumulative mitigation strategies section of this report.
Impact of Healthcare Providers’ Implicit Racial Bias
Medical Education
No matter the industry – healthcare, education, or criminal justice – implicit racial and ethnic bias has been found to play a heightened role in cognitive functions whenever there are high stress / high cognitive load or ambiguous environments, to the point of being settled science. While many healthcare providers chide television and film representations of healthcare, there is one thing they do not contest: working as a healthcare provider is stressful and so is the training. In other words, medical trainees (e.g., medical or nursing students, interns, residents) are experiencing high cognitive loads in learning contexts which are uncertain (Johnson et al., 2016) and high stakes (medical care). So it is not surprising to learn that medical students and residents are more likely to have their preexisting implicit biases translated into explicit patient-care-related outcomes. Two longitudinal quantitative studies – one of 3,756 medical students across 49 different medical schools (Burgess et al. 2019) and one of 3,392 medical residents across various specialties – document this phenomenon. Liselotte Dyrbye and colleagues (2019) conducted a study to investigate medical residents’ implicit bias and their symptoms of burnout. A total of 3,392 non-Black participants across various specialties completed three point-in-time questionnaires: during their fourth year of medical school, as well as at the second and third years of residency. The findings showed that 45.2% and 41.3% of the sample experienced symptoms of burnout and depression, respectively. Moreover, after controlling for confounding variables such as demographics and specialty, burnout symptoms in the second year of residency were found to be positively associated with implicit racial biases a year later. Considering the widespread occurrence of burnout symptoms among medical residents and the adverse link between implicit racial bias and suboptimal care, Dyrbye et al. argued that signs of burnout could contribute to inequalities in healthcare delivery. Both medical residents and medical students form part of the essential pipeline for future healthcare providers.
Medical education research published in 2019 took two directions; exploring trainees’ existing implicit racial biases and the potential impact of such implicit biases on patient care and diversity of the pipeline, which is a critical pathway for improving the provision of culturally competent care. Both medical residents and medical students form part of the essential pipeline for future healthcare providers. Two articles looked at implicit racial bias among medical students, concluding that medical students’ implicit racial bias can have an impact on patient care.
Diana Burgess et al. (2019) collected data on political ideology and implicit bias from a sample of medical students. Using a stratified random sampling strategy, they recruited a total of 3,756 students in their first and fourth years of study from 49 medical schools. The researchers found that first-year students’ political ideology was associated with their implicit bias in year four. Specifically, a greater conservative political orientation in year one was linked to higher implicit racial bias against Black individuals in their final year of medical school. Over the duration of the study, a stronger initial conservative political ideology also predicted increased explicit attitudes toward stigmatized groups, reduced internal motivation to regulate racial prejudice, diminished levels of empathy toward patients, and decreased levels of patient-centered attitudes at a later time point. These correlations remained consistent across different medical schools and were not influenced by students' race or geographic location. Burgess and colleagues also noted that conservative ideology may align with characteristics like conscientiousness, self-control, and a sense of duty, which could potentially be utilized to improve care for marginalized populations. They did not, however, test any mitigation strategies, suggesting instead that further investigation is necessary. Second, Christine Motzkus and colleagues (2019) examined two cohorts of pre-clinical medical students enrolled in a determinants of health course, analyzing 250 deidentified essays from the course itself. More about Motzkus et al.’s findings can be found in the mitigation strategies section.
The second thread of medical education research in 2019 focused on the pipeline into medical school. Building on Abelson et al.’s 2018 study of the lack of diversity in the surgical specialty, Leah Backhus and colleagues (2019) assess problems presented by implicit racial bias and implicit gender bias. Backhus et al. found that the representation of African American surgeons at all levels of the academic hierarchy, including tenure, either remained stagnant or declined between 2003 and 2006. Additionally, retention rates were significantly higher for White assistant professors, whereas Black assistant professors had the lowest promotion rates across all specialties. Backhus et al.’s 2019 study recognized the pervasive nature of implicit racial bias throughout the recruitment and training processes for future physicians. The authors pointed out that racial and ethnic minorities in both medicine and medical education are significantly underrepresented. According to the data collected between 2014 and 2015, Black individuals comprised only 5.7% of medical students and 6.2% of general surgery residents. These figures starkly contrast with the 12.4% representation of Black individuals in the U.S. population. Similarly, despite Hispanics constituting 17.4% of the U.S. population, only 4.5% of medical students and 8.5% of general surgery residents represent this demographic (Abelson et al., 2018). Backhus and colleagues (2019) suggested such racial disparities in medical education could be partially due to implicit racial biases held by influential individuals in the system. The authors referenced a study that examined the implicit biases of 140 members of medical school admissions committees at a Midwestern university. Using the Black-White IAT, the study found that all groups of the committee exhibited levels of implicit preference for White males and faculty were shown to have the highest implicit bias scores (Capers et al., 2017). Moreover, underrepresentation of minorities in medical education at the faculty level could directly influence the recruitment, mentoring, and retention of minority students (Rodriguez et al., 2014).
Healthcare Providers
Four (4) studies, each in a different specialty (trauma care, otolaryngology, nursing, and dentistry), continued to use a broad definition of healthcare provider beyond the narrow focus on MDs (Narayan, 2019; Tajeu et al., 2018; Zebib et al., 2019). While some 2019 medical education studies emphasized the stress and ambiguity aspects of the healthcare context, another study emphasized the population context to evaluate whether racial and socioeconomic diversity would mitigate the existence of implicit racial bias in trauma care. Laura Zebib and colleagues (2019) recruited 91 participants from ten (10) healthcare professions in Miami, Florida. Their study found that trauma healthcare professionals in a multicultural city exhibited reduced levels of implicit racial and socioeconomic bias compared to the average implicit bias amount White surgeons in the U.S.
In a summary of the associations among implicit bias and patient safety as well as the quality of care, Karthik Balakrishnan & Ellis Arjmand (2019) underscored that professional healthcare providers are as susceptible as the general population to implicit social and cultural biases (Zestcott et al., 2016). Drawing on studies conducted by Plaisime et al. (2017) and Penner et al., (2016), Balakrishnan and Arjmand suggested that the implicit biases not only influence assessment made by clinicians and providers’ decision-making processes in treatment, but also affect how patients perceive their encounters with healthcare professionals, which impacts patient satisfaction and their confidence in the care received.
Mary Narayan (2019) also discussed the presence of implicit bias, suggesting that such bias influences the relationships between providers and patients, the quality of care delivered, and the psychosocial well-being of patients. Regarding the provider-patient relationship, biases may lead to perceiving Black patients as having inferior communication skills and being less warm, friendly, and team-oriented. This perception can result in decreased patient adherence, fewer return visits, and diminished trust in healthcare providers (Chapman et al., 2013). Furthermore, implicit biases may manifest as spending less time listening to Black patients and assuming that Black and Hispanic patients are less likely to adhere to treatment and cooperate compared to White patients (Zestcott et al., 2016). In terms of the quality of care, studies have shown that implicit bias influences diagnoses, treatment recommendations, the thoroughness of patient histories, and the frequency of tests ordered (FitzGerald & Hurst, 2017). Lastly, implicit biases can also affect patients' health outcomes, impacting factors such as social integration, levels of depression, and overall life satisfaction (Hall et al., 2015).
Neha Patel et al. (2019) implemented a cross-sectional survey at the University of Cagliari, Italy. Fifty-seven qualified dentists working in the endodontic department of one hospital participated in the survey. These examiner respondents were randomly assigned to review a clinical vignette featuring either a Black or White patient presenting a decayed tooth and related symptoms of irreversible pulpitis, which signals that the innermost layer of a tooth is no longer able to heal itself. Both canal treatment and extraction were viable treatment options. However, the loss of a tooth can result in compromised aesthetics, lower biting stability, and replacement options (such as fixed partial dentures or implants) may result in damage of adjacent teeth (Al-Quran et al., 2011; Saunders & Saunders, 1998). The examiner participants were tasked with assessing the likelihood that the patient’s symptoms were due to irreversible pulpits, providing their treatment recommendation, and indicating the strength of this recommendation.
Implicit racial bias held by respondents was measured using the Brief Implicit Association Test (BIAT) (Nosek et al., 2014). Across both conditions, 91.23% of the examiners participating in the study exhibited a pro-White implicit bias. Additionally, they were significantly more inclined to recommend root canal treatment for White patients and extraction for Black patients. Patel and colleagues suggested that the preference to recommend tooth extraction to Black patients might stem from assumptions about their socioeconomic status, which leads the examiners to believe that Black patients may not be able to afford root canal treatment. While this might be perceived as an empathetic gesture to avoid causing financial strain, the authors highlighted that it still reflects bias.
Conclusion
In sum these 2019 articles continue to articulate the harms that can ensue with failure to address implicit racial bias in healthcare. They complement those published in 2018 in terms of a focus on expanding scholars’ and clinical practitioners’ attention to broadening the types of healthcare providers studied, providing empirical and meta-analytical evidence of an existing problem that requires mitigation.
Implicit Bias in Health Care: 2020
Implicit Bias in Health Care: 2020The year 2020 was momentous in healthcare due to the sudden and acute onset of the COVID19 global pandemic. Our data collection strategy resulted in a total of 25 studies that were published in 2020 about implicit racial bias. Similar to our findings in 2019, the largest number of articles (11) were focused on mitigation strategies, followed by COVID19, and pediatrics. Aside from pediatrics, specialties were again represented broadly instead of deeply, with articles at either the broad cross-sectional level (Bonica et al., 2020; Chuang et al., 2020; Hagiwara et al., 2020) or as a single study in emergency medicine (Manchanda & Macias-Konstantopoulos, 2020), Neurology (Charleston et al., 2020), Obstetrics and Oncology (Lowe et al., 2020a; Lowe et al., 2020b), or Radiology (Maxfield et al., 2020). As was the case with articles published in 2018 and 2019, the findings from these studies will empower us to chart a clearer map for understanding how implicit bias may have detrimental effects on patient care, including specific dimensions like provider-patient communications, treatment recommendations, and health outcomes more broadly.
Impact of Healthcare Providers’ Implicit Racial Bias on Patient Care
Pediatrics
Although there is growing evidence of implicit bias favoring White patients over Black and Hispanic patients in general (Maina et al., 2018), most studies have used Implicit
Association Tests with adult-based race vignettes. One evolution in implicit racial bias research in 2020 was the improved utilization of age-specific IAT measures. Results from all three 2020 pediatric studies in our dataset affirm that implicit racial bias affects medical trainees (medical students and residents) as well as established physicians with little to no impact of patient age on the level of healthcare provider bias. Together these findings together draw attention to the presence of biased racial attitudes among healthcare providers toward both adult and pediatric patients, underscoring the vulnerability of children within the healthcare system.
In a review of implicit bias in pediatric physicians, Tiffani Johnson (2020) drew on two studies that compared measures by using both adult and child race vignettes to test heath care providers’ implicit bias and highlighted that children are also vulnerable to biased attitudes held by their health care providers (see also Thomas, 2018; Hymel et al., 2018). The two studies reviewed by Johnson were both conducted in the emergency department setting and examined implicit racial bias among physicians towards children. In one study, a majority of resident physicians from a pediatric emergency department showed pro-white/anti-black racial bias on both the Adult Race IAT (85%) and Child Race IAT (91%). Notably, there were no significant differences in the levels of implicit bias toward adults versus children. Prior research also affirms that levels of implicit bias did not vary based on resident demographic characteristics like gender or medical specialty when comparing pediatric resident physicians with emergency medicine residents (Johnson et al., 2016). In another study involving emergency department providers at five hospitals in the Midwest, a significant majority (84%) exhibited implicit bias favoring White children over American Indian children.
Racial and ethnic disparities in the diagnosis of disruptive behaviors have similarly received ongoing scholarly attention (Cameron & Guterman, 2007; Feisthamel & Schwartz, 2009; Mizock & Harkins, 2011). Previous studies have identified a tendency for Black and Latino youth from urban and low-income backgrounds to be overrepresented in this type of diagnosis (Cameron & Guterman, 2007). On the contrary, these same groups of minority youth are less likely than their non-Hispanic White counterparts to receive a diagnosis of ADHD (Coker et al., 2016). Facing the same group of young vulnerable patients, Matthew Fadus and colleagues (2020) presented a review that focused on disparities in the diagnosis of psychiatric disorders, specifically pertaining to oppositional defiant disorder (ODD), conduct disorder (CD), and attention-deficit/hyperactivity disorder (ADHD). Fadus et al. (2020) linked this concerning pattern to implicit biases held by clinicians, which may lead them to over-pathologize behaviors of ethnic and minorities as more disobedient and dangerous (see also Clark, 2007).
Third and finally pain-related disparities have been a longstanding concern in healthcare studies (e.g., Anderson et al., 2009; Campbell & Edwards, 2012; Green et al., 2003; Tait & Chibnall, 2014). Previous research found that providers are influenced by implicit racial bias, perceiving African Americans as having a higher pain tolerance than other racial and ethnic groups (Anderson et al., 2009). Megan Miller and colleagues (2020) assessed providers’ implicit bias in pain-related decision making in a pediatric medical setting. Their study sampled 129 medical students, and the results were consistent with the findings of previous studies, showing that the medical students assumed that African Americans had stronger pain tolerance than their White counterparts. It was also found that providers were more likely to recommend opioids for African American pediatric patients than White patients, which could lead to potentially harmful over-prescription for Black pediatric patients. These findings extended the scope of pain tolerance bias research that previously focused on acute pains, showing that providers held the same type of implicit racial bias applies when it pertains to chronic pain tolerance. These findings underscore the alarming reality that implicit racial biases in pain perception cross age ranges to include children under the age of 18.
COVID19
The COVID-19 pandemic disrupted and transformed the field of healthcare in ways that few could have imagined. As the pandemic spread across the world in 2020, it became increasingly evident that different racial and/or ethnic groups had varying COVID-related incidence and mortality rates (Wadhera et al., 2020). Our dataset included five (5) early studies that explored the impact of implicit racial bias on COVID-19 as a public health issue. Moreover, a sudden increase of stigmatizing media reports about the virus’ origins also fueled implicit and explicit biases against Asian Americans (Darling-Hammond et al., 2020). The racial implications of the murder of George Floyd (Davis-Martin, 2020) and media linkages of COVID-19 to people of Asian descent alike posed significant challenges in health care outcomes. As we illustrated in the general introduction to the State of the Science, patient-provider trust plays a direct role in health outcomes. Moreover, studies by both Burgess et al. (2019) and Bonica et al. (2020) suggest provider ideology is increasingly playing a role in both provider location (Bonica et al.) and patient care (Burgess et al.).
Using data from Project Implicit, a non-profit platform that provides IATs as a “virtual laboratory” for studying implicit social cognition on the Internet, Thomas and colleagues (2020) analyzed anti-Black bias among non-Hispanic Whites across 2,994 counties. It was estimated that high levels of implicit bias at the county-level was positively associated with high COVID-19 incidence rate among Black Americans. This study was the first to test and report the associations between county-level implicit racial bias and COVID-19 incidence and mortality rates in the United States (Thomas et al., 2020). The authors noted that further research is needed to better understand the relationship between implicit racial bias and disparities caused by an infectious rather than chronic disease.
The COVID-19 pandemic not only shed light on the detrimental effects of healthcare providers' implicit racial bias but also sparked discussions about the potential influence of implicit bias as perceived by patients in physicians. Davis-Martin (2020) chronicled their experiences as a behavioral health provider to help their patients deal with anxiety about upcoming procedures. The patient in this case experienced heightened anxiety due to the combined impact of COVID-19 and racial tensions prevalent at the time. In his expression of concern to the author, the patient talked about how he feared that the riots featured in the news might negatively affect perceptions of his racial group. Consequently, the patient felt uncomfortable disclosing this fear to his White primary care provider, worrying the quality of care he receives may be negatively impacted, stating, “What if my surgeon does a bad job because they think I hate the police or America?” This narrative offered a unique perspective from a Black patient’s point of view, showing that even the mere suspicion that one’s physician may have implicit bias is enough to alter a patient’s decision-making process, leading to hesitation in scheduling a surgery appointment with a White healthcare provider.
While African American communities were disproportionately burdened by higher COVID-19 incidence and mortality rates, the pandemic also sounded an alarm about the effects of stigmatizing media on the health and welfare of Asian Americans. On March 8, 2020, a 650% increase in Twitter retweets using the term “Chinese virus” and affiliated terms was observed.
The use of these terms had an 800% increase in conservative news media articles the following day. Darling-Hammond and colleagues (2020) analyzed data from non-Asian participants of the Project Implicit “Asian Implicit Association Test” from 2007-2020. The results showed that Implicit Americanness bias (i.e., the subconscious belief that individuals of European origins are more “American” than those of Asian origins) declined from 2007 through early 2020. The trend was reversed, however, following the explosion of use of racially stigmatizing language on media outlets. This trend reversal is consistent with the longstanding stereotype of Asian
Americans as “perpetual foreigners;" the researchers argued that it may also lead to increases in discriminatory behaviors, with adverse mental and physical outcomes for those who experience discrimination. While these articles were published early in the pandemic cycle, numerous articles have sadly documented tremendous increases in violence and discrimination against Asian Americans well beyond the healthcare sphere in the shadow of the pandemic (Chan et al., 2024).
Implicit Racial Bias Across Specialties
In 2020, new studies on differential treatment in healthcare focused more on specific types of providers and specialties. A systematic review showed that health care providers from various backgrounds and levels of training hold implicit biases against non-White individuals (Maina et al., 2018). Similar results were also found in emergency medicine and radiology in more up-to-date studies published in 2020. Examining 40 emergency medicine faculty, Cleveland Manchanda and Macias-Konstantopoulos (2020) found that 45% of their sample reported IAT results with an implicit preference for Whites. Moreover, Maxfield and colleagues (2020) examined the IAT results reported by 31 faculty participants at three academic radiology departments. The results of this study revealed that 71% of participants exhibited implicit anti-Black bias. Adding to these studies that primarily focused on physician implicit bias, Lynn Crandlemire (2020) underscored in her review of implicit bias’s impact on caring, that the majority of nurses are susceptible to implicit racial bias as well (see also Haider et al., 2015).
Previous research has also shown that implicit racial bias held by clinicians can negatively impact communication with patients, which can foster decreases in patient trust, engagement, and adherence to treatment (Zestcott et al., 2016). Chenery Lowe and colleagues (2020a, 2020b) extended this line of research to the field of genetic counseling to examine counselors’ implicit bias with mixed findings. Using Linguistic Inquiry Word Count (LIWC) and Roster Interaction Analysis System (RIAS), they examined the influence of implicit racial bias in genetic counselors’ facilitation of emotional and cognitive processing (Lowe et al, 2020a). Contradictory to the conventional findings in studies with clinicians, they did not find an association between genetic counselors’ pro-White implicit bias and their communicative behavior during sessions. The researchers suggested that it is possible that the LIWC measure was not sensitive enough to capture an implicit bias effect in counseling sessions, or the small sample size used in the study could have limited their ability to detect associations between cognitive and emotional processing and IAT scores.
Adopting a different approach to focus on counselors’ framing of information, the researchers conducted another study to investigate whether genetic counselors’ implicit racial bias affected their communication style with simulated minority clients (Lowe et al., 2020b). The study involved a sample of sixty genetic counselors, primarily consisting of females (92%) and individuals identifying as non-Hispanic/Latino White (90%). Participants completed the Race IAT assessment and engaged in simulated counseling sessions with clients (17 sessions with simulated White clients and 43 sessions with simulated African American or Hispanic Latino clients). The information framing employed by counselors in the recorded sessions was analyzed using a genetic counseling-specific adaptation of RIAS coding. The results showed that implicit racial bias may negatively impact clinicians’ communication style. Genetic counselors with higher pro-White implicit bias provided less informational individuation and made fewer facilitation and activation statements to minority clients compared to their White counterparts. It was also found that with counselors who scored higher on the IAT, minority clients asked fewer medical questions and disclosed less information (Lowe et al., 2020b). These results highlighted that the implicit racial bias held by a genetic counselor likely affects counselor-patient communication in both directions.
Conclusion
While much has been written about COVID19 and explicit bias, discrimination, and even violence, particularly against African Americans in light of George Floyd’s murder and against Asian Americans in light of the pandemic, we kept a strict focus on implicit racial bias for this 2020 analysis. For example, Thomas’ 2020 results noted that implicit bias was significant under a single circumstance, while explicit bias was consistently statistically significant. As we’ve already noted, the negative effects of implicit racial bias are real, and that is why we have kept our attention focused on them. We take up lingering questions about research impact along with those from Maina et al., 2018 and other articles in the Conclusion and Directions for Future Research section of this report.
Mitigating Implicit Racial Bias in Health/Healthcare
Mitigating Implicit Racial Bias in Health/HealthcareAs discussed in the previous sections, the influence of implicit bias is evident in both medical education and everyday healthcare practices, thereby subtly shaping the learning experiences of students and the development trajectories of healthcare professionals. Without recognition of and adequate intervention for implicit bias, individuals immersed in these systems may inadvertently promote inequitable practices. In this section, we present a compilation of articles published between 2018 and 2020 that explored strategies aimed at mitigating implicit bias within the healthcare field. A total of 30 articles were analyzed for this section; this constitutes almost half of our 61-article dataset. Table 2 lists the specialties and citations for readers seeking further specialty-specific details.
Table 2. Implicit Bias Mitigation Strategy Research 2018-2020 by Specialty
Specialty | Total Number of Articles Analyzed in this Section | Citations |
---|---|---|
Family Medicine | 1 | Sherman et al., 2019 |
Medical Education | 20 | Avant & Gillespie 2019; Backhus et al., 2019; Burgess et al., 2019; Capers et al., 2020; Caruso-Brown et al., 2019; Gatewood et al., 2019; Gonzalez et al., 2019; Hernandez 2018; McClinton & Laurencin, 2020; Motzkus et al., 2019; Muntinga et al., 2020; Onyeador et al., 2020; Perdomo et al., 2019; Sherman et al., 2019; Stone et al., 2020; Sukhera et al., 2018a; Thomas & Booth-McCoy 2020; Tsai & Michaelson, 2020 |
Mental Health | 2 | Bermudez, 2018; Fadus et al., 2019 |
Neurology | 1 | Charleston & Spears, 2020 |
Nursing | 4 | Alspach 2018; Crandlemire, 2020; Gatewood et al., 2019; Narayan, 2019 |
Obstetrics / Gynecology | 1 | Pereda & Montoya, 2018 |
Oncology | 1 | Graboyes et al., 2020 |
Otolaryngology | 1 | Balakrishnan & Arjmand 2019 |
Palliative Care | 1 | Chuang et al., 2020 |
Pediatrics | 1 | Fadus et al., 2019 |
Pharmacy | 1 | Avant & Gillespie 2019 |
Surgery | 1 | Backhus et al., 2019 |
These interventions cover various career stages, from medical student education and residency program matching to professional development for healthcare providers and medical school faculty retention. Ranging from widely practiced awareness training to examinations of the medical school environment, these strategies address individual, institutional, and systemic factors. Consistent with our other 2018-2020 State of the Science Reports, we define individual-level factors as those factors that influence individuals’ likelihood to cognitively but unconsciously rely on implicit racial bias – including but not limited to previously established influences as cognitive load (fatigue, stress, burnout) and ambiguous decision / decision complexity. While these factors are influenced by the situation, individuals experience them individually. We define institutional factors as factors that shape the context at the meso-level, like at the level of the entire medical or nursing school, or across an entire specialty nationally. Finally, we define systemic factors as the set of factors that transcend or intersect with healthcare. For example, cultural and historical stereotypes are not usually unique to the healthcare system. Similarly, while the child welfare or criminal justice system intersects with the U.S. healthcare system, they are not synonymous with the healthcare system. We organize this section accordingly. Table 3 presents a summary of the mitigation strategies derived from our review of healthcare-specific strategies discussed among the articles we analyzed. Each strategy is hyperlinked to facilitate easier navigation for readers.
Table 3. Mitigation Strategies Discussed in Healthcare Implicit Racial Bias Research, 2018-2020
Strategy | Citations |
---|---|
Individual Strategy 1: Awareness Intervention | Alspach, 2018; Avant & Gillespie, 2018; Backhus et al., 2019; Balakrishnan & Arjmand, 2019; Motzkus et al., 2019; Sherman et al., 2019; Sukhera et al., 2018a; White et al., 2018 |
Individual Strategy 2: Adopt Evidence-Based Mitigation Techniques | Backhus et al., 2019; Balakrishnan & Arjmand, 2019; Bermudez 2018; Narayan, 2019 |
Individual Strategy 3: Design Interventions with Resistance in Mind | Alspach, 2018; Backhus et al., 2019; Gatewood, 2019; Gonzalez et al., 2019; Sukhera et al., 2018b |
Institutional Strategy 1: Incorporate Advances in Curriculum Development | Bermudez, 2018; Burgess et al., 2019; Fadus et al., 2019; Hernandez, 2018; Motzkus et al., 2019; Stone et al., 2020; Tsai & Michaelson, 2020 |
Institutional Strategy 2: Pilot Novel Curricula | McClinton & Laurencin 2020; Perdomo et al., 2019; Thomas & Booth-McCoy, 2020 |
Institutional Strategy 3: Adopt a Nuanced Approach to Structural Racism | Backhus et al., 2019; Capers et al., 2020; Chuang et al., 2020; Fadus et al., 2019; Graboyes et al., 2020; Onyeador et al., 2020 |
Given the wide variation in frequency of specialties addressed, we explicitly avoid presenting conclusions that are specific to particular specialties. Our goal in reviewing these intervention strategies is to explore evidence-based strategies to counter the different ways implicit racial bias plays a role in the provision of healthcare. We hope that the application of these interventions contributes to a more equitable and effective healthcare system.
Individual Strategy #1: Awareness Intervention
Our review of implicit bias interventions in the healthcare domain identified eight (8) articles that specifically discussed the awareness intervention strategy. Awareness intervention strategies typically focus on empowering individuals to understand and acknowledge the role of implicit racial bias in healthcare, and, where applicable, in their provision of care to patients.
Across the articles the strategy is broken down into two steps:
Raising awareness about implicit bias itself.
Reflecting on one’s own implicit biases and how they might manifest within the professional environment.
The effectiveness of awareness intervention strategies can vary (Balakrishnan & Arjmand, 2019) based on a variety of factors (Alspach, 2018; Sukhera et al., 2018a). Healthcare research published between 2018-2020 and analyzed here concur that inclusion and intentional design of the second step, reflection, is essential to a more successful awareness intervention strategy (Alspach, 2018; Backhus et al., 2019; Motzkus et al., 2019). Specifically, scholars have empirically demonstrated that early interventions (e.g. year 1 of medical school) that include documenting reflections through writing (Avant & Gillespie, 2019; Motzkus et al., 2019), reflection upon an individual’s own culture and the extant culture of medicine they study/work in (White III et al., 2018), and sustained awareness intervention efforts (Backhus et al. 2019; see also Onyeador et al., 2020 and Alspach, 2018 for further rationales regarding longitudinal studies of impact) can have statistically significant impacts. Studies of this strategy involved professional students (Avant & Gillespie 2019; Motzkus et al., 2019; White et al. 2018) as well as medical residents and faculty (Sherman et al., 2019).
Individual Strategy #2: Adopt Evidence-Based Mitigation Strategies
Three (3) studies focus attention on practices providers should engage in consciously to thwart unconscious bias. Prior research indicated that practices like group-based debriefing could facilitate a transformation of how students reflect upon their experiences (Teal et al., 2010) and support those who feel less at ease in addressing race or ethnicity-related issues in group settings (Littleford et al., 2005; see also Burgess et al. 2019).
Among the “debiasing” strategies outlined for implicit bias mitigation, Balakrishnan and Arjmand (2019) specifically suggested perspective-taking and counter stereotypical examples as crucial factors in addressing implicit bias among healthcare providers. The authors maintained that implicit biases not only affect interactions between providers and patients but also influence the dynamics among providers themselves. A nursing education review by Narayan (2019) echoed this suggestion. Citing the advice from the Joint Commission, Narayan contended that healthcare providers should employ emotional regulation, partnership building, and perspective taking during clinical encounters to mitigate biases. Furthermore, alongside partnership building and perspective taking, the recommendations also included addressing bias through counter stereotypic imaging, individuation, enhancing opportunities for intergroup contact, and stereotype replacement.
Additionally, research on implicit bias intervention strategies expanded to incorporate an examination of different agents in the interactions affected by implicit bias. Moving away from a focus on providers, Bermudez (2018) applied social dreaming theory and the social dreaming matrix in group therapy settings. He argued that this approach provides a “container” for processing and healing racial trauma due to implicit bias. Focusing on the receivers' perspective, this psychoanalytic approach aims to a) address the impact of implicit bias on individuals, and b) facilitate their healing process in groups.
Individual Strategy #3: Design Interventions with Resistance in Mind
Research published in 2018-2020 cautioned against thinking that the awareness strategy is sufficient or without pitfalls (Backhus et al. 2019; Alspach 2018; Sukhera et al., 2018a). While awareness interventions can help participants uncover their own implicit biases, they can also trigger resistance and denial (Gonzalez et al., 2019). Our review identified five (5) articles that discussed these reactions and provided strategies and insights for mitigating potential negative responses to awareness interventions. Resistance manifests in various ways, including: questioning the validity of tests like IATs (Gatewood et al., 2019); anticipating negative emotions when acknowledging one’s own bias, especially when disclosing it publicly (Gonzalez et al., 2019); subtle discouragement of open discussion about implicit bias related to racial and ethnic subgroups (Gonzalez et al., 2019); and frustration stemming from the conflicts between one’s professional ideals and their susceptibility to implicit bias (Sukhera et al., 2018b).
The IAT can be used in distinct and complementary ways; curriculum designers and educators must consider the premise behind the test, and potential reactions from learners, and have a plan in place to address such reactions prior to delivering instruction. Gatewood and colleagues’ 2019 study of nursing students illustrated why clarity about the role and effectiveness of the IAT is instrumental in mitigation. Sukhera and colleagues (2018b) also affirmed the importance of IAT role clarity.
Although the evaluation of the session at the aggregated level was positive, some students expressed doubts regarding the legitimacy of the IAT test. Specifically, they raised doubts that the test appeared to have measured dexterity instead of bias. Gatewood and team (2019) acknowledged this skepticism and further substantiated this finding with similar concerns voiced in previous research (Gonzalez et al., 2014). These concerns may stem from a lack of full grasp of the IAT test’s critical design, particularly regarding the counterbalance for the order of two groupings of response targets. The main IAT question is which response mapping participants find easier to use, instead of simply assessing the error rate, which could be interpreted as a sign of dexterity. Gatewood et al. (2019) suggested that future studies should explore participants' confidence in the accuracy of the IAT and their ability to engage in self-reflection at different levels of learning.
Two qualitative studies looked at more individual-level responses to test results. Gonzalez et al.’s (2019) study of medical students and Sukhera et al.’s (2018b) study of medical faculty and residents both found shame and fear of public disclosure of implicit bias were barriers that fostered resistance to implicit bias instruction. Sukhera et al.’s study also revealed the dissonance. The study recruited 21 healthcare faculty and resident participants and had them take the IAT related to mental illness. Afterwards, participants were asked to draw a picture about their experience with the IAT. Using grounded theory, a methodology that involves the construction of hypotheses and theories through the collecting and analysis of data by inductive reasoning, the researchers analyzed the responses and found that the participants experienced tensions between an idealized professional identity that aspires to be unbiased and an actual identity that was susceptible to implicit bias. The participants described their process of reconciling these tensions, which involved acknowledging the existence of implicit bias while actively working towards self-improvement. To manage implicit bias, the participants emphasized the importance of relationships, including communicating their experiences with others and potentially seeking guidance from faculty mentors. Sukhera and colleagues (2018b) concluded that adopting a mindset of self-improvement while acknowledging personal limitations could serve as a model for addressing implicit bias among healthcare professionals. These strategies, combined with peer group discussion (see Sherman et al. 2019; Tsai & Michelson, 2020) may foster better uptake of mitigation efforts by anticipating and addressing resistance with intentionality up front.
Only an environment that avoids triggering defensiveness or denial can help an individual better process feedback received during awareness exercises, thereby effectively reducing implicit bias. Alspach (2018) emphasized that awareness exercises should be conducted in a non-threatening environment where one’s biases can be privately discovered. It is equally important to know that stereotyping is common for most of us. The articles associated with this strategy emphasize the importance of addressing potential resistance as a primary concern when designing and implementing awareness-based implicit bias intervention training.
Institutional Strategy #1: Incorporate Advances in Curriculum Development
Neither implicit racial biases nor attempts to address them function in a vacuum. Curriculum, whether formal or informal, plays a pivotal role in shaping students' awareness and their capacity to challenge their own biases. A variety of articles (7) from our review of literature from 2018 to 2020 were concerned with this theme. While relatively little is known about the percentage of medical education programs that have begun to implement these trainings and what their training curricula entail, Tsai and Michelson (2020) conducted one of the first studies aimed at answering these questions, using a nation-wide survey of 64 pediatric residency program directors. Their results revealed that 63% of the surveyed programs were already delivering some form of training to mitigate implicit bias. The survey respondents also identified a number of perceived barriers to implementation. Time constraints were often reported as the biggest challenge when adding more materials to an already intense program (Tsai & Michelson, 2020). These findings highlighted the need for more theoretically sound, evidence-based, and time efficient implicit bias intervention training models and curricula. From single course designs to more systematic intervention models for curriculum implementation, these articles explore diverse pieces of the puzzle, like strategies for screening vignettes used in curriculum materials and the factors impacting specific groups’ receptivity to a curriculum design.
Echoing van Ryn et al., (2015), Hernandez (2018), Burgess et al. (2019) and Motzkus et al. (2019) all found that medical students enter medical school and become habituated to norms and practices that can often reinforce rather than mitigate implicit racial bias, with serious implications for patient care. For example, Burgess and colleagues (2019) found lower levels of patient empathy among their strongly conservative respondents at the 4th year versus the 1st year of medical school, suggesting a role for medical school norms beyond individuals’ ideologies. Hernandez suggested leaders harness the opportunity to change institutional norms to mitigate implicit bias among students by assessing the formal and informal curricula, and the so called “hidden curriculum,” which are transmitted through structural and cultural factors such as methods of evaluation and colloquialisms.
Several studies focus attention on practices providers should engage in consciously to thwart unconscious racial bias. Bermudez (2018) applied social dreaming theory and the social dreaming matrix in sessions with students, faculty, and staff. In documenting his experiments from these psychotherapy workshops Bermudez concluded that the social dreaming matrix offered a distinctive chance for participants to perceive the struggles of others with implicit bias and racial trauma as if they were their own. Through this reflection and meaning creation process, a collective psychoanalytic path is formed, leading to an improved and proactive social and moral imagination that may intervene against the negative effects of implicit racial bias.
In a similar vein multiple studies (Burgess et al., 2019; Fadus et al., 2019; Stone et al., 2020) provided evidence that a tailored approach beyond the standard approach to race in curriculum and course design is important. In light of their findings, Burgess et al. (2019) suggests designing course content that resonates with more conservative individuals within curricula that might focus on values such as respect for authority and in-group loyalty and using influential figures in the medical profession as the source of communication. Fadus et al. (2019) suggests a nuanced approach that doesn’t rely solely on a patient’s appearance to infer racial or cultural identity but strives to obtain additional relevant information like cultural or immigrant backgrounds that help providers develop a comprehensive understanding of the factors that shape the values, attitudes and symptomatology among patients from diverse backgrounds. Specifically, the educational experience can raise awareness regarding common disparities by race that exist in healthcare settings, such as the disproportionate administration of higher doses of anti-psychotics to Black men that cannot be solely explained by clinical severity (Walkup et al., 2000). These curricular innovations aim to help medical students to grasp the implications of cognitive errors such as confirmation bias and framing, which may perpetuate misunderstanding of racial and ethnic minority patients.
Due to prevailing stereotypes that often characterize Hispanic/Latinx patients as medically noncompliant (Sabin et al., 2009), Jeff Stone and colleagues (2020) conducted a study comparing implicit racial bias levels of first-year medical students from different racial and ethnic backgrounds toward Hispanics before and after two active learning workshops. The workshops covered topics such as the psychological mechanisms of intergroup bias, and the effects of implicit bias on patient care. Then, the students completed a series of activities to learn how to control their implicit bias when interacting with patients. Prior to the workshops, assessment revealed that both the majority and nontarget minority groups held considerable levels of implicit stereotypes regarding Hispanics, but the target minority group did not. After completing the workshops, the majority group showed a significant decrease in implicit bias, but this change was not found in the nontarget minority group. The main findings from this study are two-fold. First, it showed that both proactive and reactive strategies are effective in mitigating implicit bias in medical students. According to Stone and colleagues (2020), activating beliefs or “stereotypes” to categorize patients can be helpful in diagnosing and treating patients using epidemiology and clinical case studies. Thus, as opposed to promoting a strategy focusing on negating automatic associations, it may be more effective to train medical students on proactive and reactive strategies to make the switch from category-based practice to individual-based processing when interacting with patients from stigmatized groups. The second contribution of this study was to demonstrate that not all ethnic and racial minority individuals respond the same way when learning to control implicit bias. This finding led to the recommendation highlighted by the authors that tailoring may be necessary in designing the materials and activities for implicit bias intervention curriculum. It involves not only customizing the context of the materials to match the scenarios and research findings to specific doctor-patient interactions, but also culturally tailoring the materials and activities for medical students of different ethnic and racial minority groups.
Institutional Strategy #2: Pilot Novel Curricula
Three (3) studies offered curricular interventions that can be piloted systematically at the department or school (e.g., medical school, nursing school, or pharmacy school) level. The ability of an individual to consistently adopt and uphold a trauma-informed approach is contingent upon their own well-being. For this reason, the studies discussed here acknowledge and incorporate individual strategy insights when designing their institutional strategy.
The Trauma-Informed Medical Education (TIME) model was proposed to foster awareness that medical students and trainees can experience trauma from an environment imbued with implicit bias and to advocate for new practices in medical education. Authors Aneesa McClinton and Cato Laurencin (2020) argued that the prevalence of implicit bias in patient-provider interactions and its impact on learners’ experiences (see, e.g., Green 2018; Backhus et al. 2018; Capers et al. 2017; Rodriguez et al. 2014) necessitates a set of curricular principles aimed at establishing a supportive environment (Ravi & Little, 2017). Since identifying individuals who have experienced trauma can be challenging in the context of institutions, trauma-informed principles can be implemented as a universal precautionary measure (see also Kuehn, 2020). In so doing, the TIME approach does not rely on individual disclosures of the specific trauma endured (therefore avoiding privacy policy issues). Instead, it operates on a set of principles aimed at establishing a supportive environment (Ravi & Little, 2017). Similar to Stone et al.’s (2020) attention to proactive and reactive strategies used in clinical settings, the TIME model proposes four Rs for medical student training in implicit bias mitigation at both the individual and institutional levels: realize, recognize, respond and resist (McClinton & Laurencin, 2020).
While the TIME model has focused on medical students and trainees, the Health Equity Rounds (HER) model is aimed at faculty and practitioners across various training levels and disciplines engaging in conversations about how racism and implicit bias directly affect patient care. Joanna Perdomo and colleagues (2019) developed HER in a pediatrics department and empowered medical residents to design and later advise on curriculum development. Participants in this longitudinal, case-based curriculum included attending physicians, fellows, residents, and medical students from departments such as pediatrics and family medicine. HER sessions were held quarterly during dedicated time for departmental case conferences. Incorporating the curriculum into regularly offered case conferences can address a concern about fitting implicit racial bias into a crowded curriculum (Tsai & Michaelson 2020). The cases used in HER sessions were selected from real provider-patient interaction scenarios submitted by residents and faculty. In addition to a wide coverage of topics spanning from contraceptive counseling to Williams syndrome, these cases were also curated to focus on issues connected to implicit bias and racism to foster interdisciplinary, cross-rank conversations instead of complex medical details that might create barriers to understanding. The authors employed a variety of evidence based individual strategy techniques to enhance case presentation, including perspective taking and individuation practice based on imagery exercises. Moreover, the curriculum incorporated different methods, including reflection essays, share out loud, and think-pair-share, to encourage the participants to practice the learned techniques. Survey feedback about HER sessions indicated that HER helped them gain awareness, motivation, and tools to reflect on their implicit biases, which subsequently benefited their clinical practices. Their findings also echoed some findings we discussed at the individual level, suggesting that tailored approaches could be combined with HER curriculum for maximal impact.
Third and finally, Billy Thomas and Amber Booth-McCoy (2020) proposed a theoretical model for reducing the impact of implicit bias with descriptions of eight longitudinal stages. The first six stages include: 1) awareness of implicit biases, 2) an increase in knowledge about the science of implicit bias, 3) acknowledgement and acceptance of implicit biases and their effect on behavior and patient outcomes, 4) intentional behavioral change by self-reflection and perspective taking, 5) direct application of strategies promoting behavioral changes, 6) affirmation of behavioral change through positive feedback. These six process stages are thought to lead to a pair of final result stages: 7) actual mitigation of implicit biases through behavioral change and 8) improved patient-provider relationships and better health outcomes and equity. Along with this theoretical model, Thomas and Booth-McCoy (2020) also reviewed four intervention strategies and their outcomes. They suggested that medical schools should adopt mandatory implicit association tests and provide cultural humility training as a curriculum change. In this way, medical students can learn to care for minority and underserved communities through experience.
Institutional Strategy 3: Adopt a Nuanced Institutional Approach to Structural Racism
Just as patients should not be treated as if race is a one-size-fits-all shaper of health outcomes, neither should providers or students be assumed to benefit from one-size-fits-all training (see also Burgess et al. 2019). Similarly, while structural racism is pervasive it does not operate uniformly or identically in all contexts.
Several articles acknowledged small but persistent effects among factors that could be assumed to play a bigger role. Moving protocols away from emphasizing implicit bias training in isolation can provide additional impact on reducing racial disparities. An equitable and effective healthcare environment can be constructed at multiple layers, including incorporating counter stereotypical examples in educational materials, enhancing interracial contact in the physical environment through diversifying the rank of faculty and tapping into the racial and socioeconomic diversity of the city where the medical institute is embedded.
Acculturation should also be a part of medical curricular design (including additional education and training in interview skills) to ensure that students and trainees are using unbiased instruments in an unbiased way, ultimately contributing to a more equitable and effective treatment. For example, Fadus et al. (2019) suggested that psychiatric providers enhance their culturally informed interview techniques, utilize existing tools with cultural sensitivity (see also Lewis-Fernández et al., 2020) and improve their structural competency to better recognize the implications of socioeconomic factors on psychiatric disorder symptoms. In a similar vein, Quinn Capers and colleagues (2020) also emphasized the importance of real patient interactions in medical education. They proposed that teaching hospitals should encourage regularly recurring gatherings of health providers to review incidents in which bias or racism is suspected to have occurred.
Residency interviews are another hurdle where implicit racial bias can manifest itself (Backhus et al., 2019). This analysis referenced a study indicating that a large proportion of medical students encounter potentially discriminatory questions during their residency match interviews (Santen et al., 2010). Backhus et al. (2019) suggested that one way to mitigate this issue is to design standardized interview questions tailored to what trainees may experience at the residency program, rather than utilizing unstructured interview formats. The authors also noted that implementing a scoring system to evaluate the interviewee's responses to these questions could further enhance the standardized interview process's effectiveness. The collective evidence presented by Backhus and colleagues (2019) emphasized the need for establishing initiatives at the institutional level to address implicit racial bias in admission and enhancing support for minority faculty members in academic medicine, thereby fostering the growth of minority medical students.
At the institutional level of implicit bias mitigation, Ivuoma Onyeador and colleagues (2020) examined the influence of three medical school factors, including interracial contact, medical school environment, and diversity training (for both implicit and explicit racial bias) during medical residency. Using a 6-year longitudinal dataset, they found that the quality of contact predicted a very small but consistent reduction in implicit bias. However, racial climate, modeling of bias, and length of diversity training did not consistently lower implicit bias. These results provided valuable insight into the long-term effects of implicit bias mitigation trainings in medical education and highlighted the importance of encouraging interracial contact at the institutional level.
Healthcare continues to present unique opportunities for evidence-based research to mitigate implicit racial biases. For example, implicit bias can influence how medical practitioners allocate healthcare resources, potentially contributing to disparities among patients of different racial and ethnic backgrounds. Evan Graboyes and colleagues (2020) discussed strategies to address this issue in head and neck cancer care delivery, specifically in how surgical cases are prioritized. Previously, it has been suggested that a "color-blind" decision-aid prioritization system, which excludes race information from the decision-making process, could help rectify unequal treatment of racial and ethnic minority patients. Graboyes et al. (2020) cautioned against this simplistic approach because, even after removing race/ethnicity data, clinical stage and comorbidity severity would still have a role in this prioritization scheme. As African American and Hispanic/Latino patients are more likely to have comorbidities and present with advanced stages of diseases, implementing a decision-aid prioritization system solely focused on maximizing benefits based on comorbidity and disease stage could inadvertently perpetuate bias against these patients. Therefore, a comprehensive approach is necessary to mitigate bias and ensure equitable treatment for all patients. Graboyes and colleagues suggested a possible solution to this problem, which is developing a prioritization scheme that incorporates evidence-based, data-driven weights based on patient populations and local or regional prevalence of the relevant diseases. Another solution could be to develop a framework that prioritizes racial and ethnic minorities based on ethical principles, such as giving priority to those who are worse off (Graboyes et al., 2020). Although the optimal solution has yet to be determined, Graboyes and colleagues’ discussion emphasized the need for objective and metric-based decision aid/intervention tools to address disparities associated with implicit racial biases. Graboyes and colleagues’ recommendation for such tools concurs with findings in the 2018 Sate of the Science. Hymel et al. (2018) recommended that future attention needs to be devoted to developing validated and evidence based AHT screening tools in order to reduce the potential negative impact of implicit racial and ethnic bias in AHT diagnosis and evaluation.
While many authors in our three-year dataset focused on infant and pediatric contexts, one publication stood out for its development of a novel end-of-life tool. Elizabeth Chuang and colleagues (2020) developed a novel tool on the basis of the Race IAT to measure provider’s implicit bias in end-of-life (EOL) care. Through literature review, the researchers identified an initial pool of words used in EOL care that fit under two categories: comfort-oriented or aggressive. Clinicians in the specialties that treat serious illness were invited to rate and rank the words included in the initial pool. Words that were consistently sorted and ranked as representative of the two target categories were chosen as attributes in the novel EOL-IAT. Participants were instructed to categorize these words with two response keys, representing counterbalanced pairings of race (Black/White) and attributes (comfort/aggressive). This tool was piloted online through ProjectImplicit® and yielded promising results for practical application. This study represented an effort in customizing tools for accessing implicit biases held by providers of different specialties. It serves as a reminder for us that providers' implicit bias may not be as straightforward as associating White people with the attribute of "good" and
Black people with “bad”. Instead, it can manifest in ways specific to the care of the specialty. For example, in EOL care, it may be more critical to determine if providers tend to associate White patients with the attribute of “comfort”, while exhibiting a stronger tendency to associate “aggressive” with Black patients.
Conclusion & Directions for Future Research
Conclusion & Directions for Future ResearchFrom racial disparities in specific areas of patient care and the repercussions of the COVID-19 pandemic, to the unfair interactions among providers as well as among medical students themselves, 61 articles published over a three-year period between 2018 and 2020 documented the tangible consequences of these biases. While acknowledging the existence of the issues posed by implicit bias is a start, effectively addressing it in the field of healthcare requires actionable and diverse strategies. Emerging research findings from our review underscored the need for intervention methods that combine the best of what we know at the individual level about how to mitigate the impact of implicit racial bias with evidence-based institutional interventions tailored to the diverse population of healthcare providers and trainees. Moreover, it continues to be necessary to develop a deeper understanding of how implicit bias operates at the individual and institutional levels. The healthcare domain’s collective commitment to dismantling these biases is vital, as it enhances the chance of every patient receiving unbiased and compassionate care, while also affording equitable opportunities to those providing services in the healthcare system. If 2020 taught us anything, it is that no country or community can be completely isolated from the healthcare challenges faced by others.
Even though decades of implicit racial bias research have continued to confirm the negative impact of bias in 2018-2020 there remain areas where research conclusions are unsettled, providing new directions for research. Sukhera et al.’s (2018a) review of healthcare education studies that use the IAT found that the IAT is often used in two ways: as a metric to evaluate the success of an educational activity or as a tool to promote awareness while triggering discussion and reflection. The IAT can be used in distinct and complementary ways; curriculum designers and educators must consider the premise for using the test, anticipate potential reactions from learners, and have a plan in place to address such reactions prior to delivering instruction. For example, when the goal of implicit bias intervention is to improve provider communication behaviors, Hagiwara et al., (2019) raised concerns about the limitations of the existing patient provider communication coding systems, such as the Roter Interaction Analysis System (RIAS) and the Four Habits Coding Scheme. They noted that these systems fail to consistently include an assessment of nonverbal or paraverbal behaviors, which are often associated with the manifestation of implicit bias. To address these shortcomings, the authors recommended that more research should be aimed towards identifying specific provider communication behaviors that may reflect provider implicit racial bias, with a special focus of integrating minority patient perspectives. By gathering narratives from minority patients, researchers can identify nonverbal and paraverbal cues that are consistent with implicit racial bias and then develop coding systems to recognize discrete and quantifiable communications for providers to address.
Notably, Maina et al.’s 2018 review indicated that the research on the impact of providers’ implicit bias on patient care and outcomes had mixed results. When it comes to mitigation efforts, their review found only two intervention studies that investigated methods to reduce implicit bias among healthcare providers, with only one study demonstrating a post-intervention reduction in implicit bias. The authors also highlighted several limitations among the reviewed studies, including the use of convenience samples, low response rates, overreliance on vignettes instead of real-world measures, limited ability to infer causality due to cross-sectional study designs, and an excessive focus on physicians’ implicit racial bias rather than that of other types of healthcare providers. While the latter limitation has been addressed by multiple studies in our dataset, the opportunities for both empirical (additional evidence-based findings) and methodological innovations (development of more precise and successful tools to study implicit racial bias) in this line of scholarship remain. We hope these areas for future research will be addressed across many healthcare specialties, reducing disparities and producing better medical outcomes in the years to come.
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