A Preliminary Report on the Relationship Between Microaggressions Against Black People and Racism Among White College Students

  • Jonathan W. Kanter
  • Monnica T. Williams
  • Adam M. Kuczynski
  • Katherine E. Manbeck
  • Marlena Debreaux
  • Daniel C. Rosen
Article

Abstract

Previous efforts to understand microaggressions have surveyed stigmatized group members’ experiences of receiving microaggressions. This report presents the first attempt to measure self-reported likelihood of delivering microaggressions rather than receiving microaggressions and to explore the association between the likelihood of delivering microaggressions and racial prejudice. We conducted a cross-sectional survey of 33 black and 118 non-Hispanic white undergraduate students at a large public Southern/Midwest university. Black students reported the degree to which a series of statements would be experienced as microaggressive. White students reported their likelihood of delivering those statements and completed measures of racial prejudice. White students’ self-reported likelihood of engaging in microaggressive acts was significantly related to all measures of racial prejudice. The single item “A lot of minorities are too sensitive” was the strongest predictor of negative feelings toward black people. Results offer preliminary support that the delivery of microaggressions by white students is not simply innocuous behavior and may be indicative of broad, complex, and negative racial attitudes and explicit underlying hostility and negative feelings toward black students.

Keywords

Racism Discrimination Microaggressions Prejudice Bias Race 

Introduction

Microaggressions, a term first coined by Pierce (1970), more recently have been defined as “brief and commonplace daily verbal, behavioral, and environmental indignities, whether intentional or unintentional, that communicate hostile, derogatory, or negative racial slights and insults to the target person or group” (Sue et al. 2007, p. 273). Although these communications typically appear harmless, they are considered a form of everyday racism or discrimination (Essed 1990; Jones 1997). Sue and colleagues described nine categories of microaggressions, including (a) assumptions that a person of color is not a “true” American; (b) assumptions of lesser intelligence; (c) statements that convey color blindness or denial of the importance of race; (d) assumptions of criminality or dangerousness; (e) denial of individual racism; (f) promotion of the myth of meritocracy; (g) assumptions that one’s cultural background and communication styles are pathological; (h) being treated as a second-class citizen; and (i) having to endure environmental messages of being unwelcome or devalued.

As overt and blatant expressions of prejudice have declined over the last several decades, increasing attention has been paid to how more subtle forms of prejudice may be enacted in everyday interpersonal interactions (e.g., Dovidio and Gaertner 1986, 1998, 2000), and interest in microaggressions has been galvanized in this context (Lilienfeld 2017). Recent surveys document that African Americans report experiencing microaggressions regularly (Constantine 2007; Donovan et al. 2013; Lewis et al. 2000; Smith et al. 2007) with multiple, negative mental health consequences, including increased serious psychological distress (Chae et al. 2011), increased depression and decreased life satisfaction (Ayalon and Gum 2011), increased risk of mood and substance use disorders (Clark et al. 2015), increased anxiety (Liao et al. 2016), and increased suicide risk (O’Keefe et al. 2015). In addition, researchers have tailored the microaggression construct to other groups and have found that multiple stigmatized groups report experiencing microaggressions regularly, including lesbian, gay, bisexual, transgender, and queer (LGBTQ) individuals (Balsam et al. 2011; Nadal 2013), Asian Americans (Lin 2010; Ong et al. 2013), Latinos (Huynh 2012), women (Capodilupo et al. 2010), and others (see Sue 2010).

To date, efforts to understand microaggressions have surveyed stigmatized group members’ self-reported experiences of microaggressions (e.g., Nadal 2011) but have not attempted to assess the degree to which others engage in microaggressive behaviors, independent of the target’s self-reported experience. Although the experiential reality of group members experiencing microaggressions is foundational to the definition and conceptualization of the construct (Sue 2017), this exclusive reliance on self-reported experiences of microaggressions in research has been criticized as limiting conclusions that can be drawn from the research. Specifically, a direct focus on the psychology of those delivering microaggressions will improve our understanding of event base rates, indicate who is more or less likely to microaggress, and document the degree to which microaggressions reflect objective acts of prejudice on the part of deliverers (Lilienfeld 2017). In general, by supplementing research on target’s experiences of microaggressions with a focus on deliverers of microaggressions, the construct can be better situated within the existing literature on racism and discrimination. Such a focus also may improve efforts to develop interventions to educate those committing microaggressions to reduce the frequency of these acts.

This report presents the first exploration of microaggressions toward blacks in potential deliverers (i.e., microaggressors) and their relationship to racism in a white college student sample. Given the microaggression construct’s inherently fuzzy boundaries and ambiguous nature (Lilienfeld 2017), our approach prioritized the experiences of black students and identified potential microaggressions that were at least “possibly” racist in a specific context. We then asked white students how likely they would be to engage in these microaggressions and correlated this likelihood with several indicators of racism and prejudice. Although microaggressions are received across multiple stigmatized groups, disenfranchised identities, and intersections of identity (Sue 2010), we focused on microaggressions delivered by white college students directed toward black students. This was done for methodological simplicity and in recognition of the longstanding significance of black–white racism in the USA and on college campuses today (e.g., Devine and Elliot 1995; Dovidio and Gaertner 1986; Solórzano et al. 2000).

Method

Participants

Participants were 33 black and 118 non-Hispanic white undergraduate students at a large public Southern/Midwest university between the ages of 18–35 who completed measures online for course credit. For black students, 27 (82%) were female and the mean age was 24.89 (SD = 7.46). For white students, 71 (60%) were female and the mean age was 22.28 (SD = 4.10). The University’s Institutional Review Board approved the study.

Measures

Cultural Cognitions and Actions Survey (CCAS). To develop the CCAS, a survey measuring one’s self-reported likelihood of engaging in microaggressions, we first identified common contexts in which students of color report experiencing microaggressions and examples of these microaggressions. This involved a multimodal process including examination of the existing literature (e.g., Sue et al. 2007; Lewis et al. 2000; Smith et al. 2007) and administration of focus groups with students of color. Students were recruited from one private and two public institutions located in the Southern/Midwest and Pacific Northwest USA, for a total of six focus groups (total N = 36). Participants were provided the definition of microaggressions and asked to discuss specific incidents in their lives consistent with the definition (Debreaux et al. 2016). Students were not recruited on the basis of prior knowledge of the microaggression construct. This resulted in the development of 56 items across five scenarios involving potential black–white individual or group interactions. For example, Scenario 1 was: “A friend of yours has wanted you to meet a friend, saying they think you will like the person. You meet this person one-on-one. He turns out to be a tall, fit-looking black man who says he is a law student. He seems very smart and he has a very sophisticated vocabulary. You like his personality.” The other scenarios included: (2) interacting with a young, African American female with African-style dress and braided hair; (3) taking a diversity training workshop; (4) talking about current events (e.g., police brutality) with mixed-race friends; and (5) listening and singing along to rap music with mixed-race friends (a sixth scenario and items were developed but not analyzed for this report). See “Appendix” for the list of scenarios.

After each scenario, white participants were provided a series of potential statements one might make in that situation, including statements that would be considered microaggressive (e.g., “Did you get into school through a minority scholarship?”) and not microaggressive (e.g., “What is law school like for you?”). Respondents were asked to report how likely they would be to think or say each response (or something similar) on a five-point scale with anchors 1 (“I wouldn’t think it at all”), 2 (“I would think it but definitely wouldn’t say/do it”), 3 (“I would think it but probably not say/do it”), 4 (“I would think it, and I might say/do it”), and 5 (“I would think it and probably would say/do it”).

Changes in instructions, scaling, and slight changes to item wording were made for black respondents to explore the degree to which the items would be experienced as microaggressive by black students. They were provided the same scenarios and items and asked to rate how they would experience each item on a four-point scale with anchors 1 (“Not at all racist”), 2 (“Possibly racist”), 3 (“Somewhat racist”), and 4 (“Very racist”).

MarloweCrowne Social Desirability Scale (MCSDS; Crowne and Marlowe 1960). This 33-item scale, which has been shown to improve predictive accuracy of measurement of socially sensitive themes across many studies (Evans 1982), was used to control for the effects of socially desirable responding in analyses. The scale’s internal consistency with the white sample was α = .78.

Racial Feeling Thermometer (FT). The feeling thermometer for race asks white participants to indicate their attitudes toward blacks on the thermometer, which ranged from 0° (extremely unfavorable) to 100° (extremely favorable). Low scores on FTs are interpreted as a simple indicator of explicit prejudice (e.g., Greenwald et al. 1998; McConnell and Leibold 2001), and FTs demonstrate significant correlations with objective behavioral indicators of discrimination in meta-analyses (r’s = .13, .26, .33, .42; Talaska et al. 2008). The correlation between FT ratings and social desirability based on the MCSDS in the white sample was not significant, r = .03, p = .782.

Allophilia Scale (AS; Pittinsky et al. 2011). The AS is a 17-item scale that measures explicit positive attitudes toward outgroup members (i.e., black people in the current study) on a six-point scale from 1 (“Strongly Disagree”) to 6 (“Strongly Agree”). The AS has strong associations with old-fashioned racism and one’s likelihood of seeing a black person as an ingroup rather than outgroup member (Pittinsky et al.). The scale’s internal consistency with the white sample was α = .96, and the correlation with social desirability was not significant, r = −.03, p = .764. High scores indicate more positive attitudes toward black people.

Color-Blind Racial Attitudes Scale (CoBRAS; Neville et al. 2000) is a 20-item measure of participants’ beliefs that racial dynamics are not important and that institutional and other forms of racism do not exist. Items (e.g., “‘Race plays a major role in the type of social services [e.g., such as type of health care or day care] that people receive in the USA”) are rated on a six-point scale ranging from 1 (“Strongly agree”) to 6 (“Strongly disagree”). For the purposes of this investigation, the CoBRAS total score was used, which is related to greater levels of racial intolerance and racial prejudice against blacks and a belief that the world is just and fair (Neville et al. 2000). The scale’s internal consistency with the current white sample was α = .82, and the correlation with social desirability was significant, r = −.24, p = .011. The CoBRAS was scored such that high scores indicate more color-blind attitudes and denial of racism.

Symbolic Racism Scale 2000 (SR2K; Henry and Sears 2002). The SR2K is an eight-item, revised version of the original measure of symbolic racism which combines negative affect toward blacks with particular beliefs, such as that black people violate cherished American values like hard work and taking responsibility. The response set for the SR2K varies across items. A sample item is “How much discrimination against blacks do you feel there is in the USA today, limiting their chances to get ahead?” The scale predicts endorsement of antiblack policies such as being against interracial marriage and equal opportunity initiatives, erroneous beliefs such as that genes can tell us what race a person belongs to, and disgust toward blacks (controlling for conservative ideology; Brown et al. 2009). The scale’s internal consistency with the white sample was α = .78, and the correlation with social desirability was significant, r = −.24 p = .009.

Modern Racism Scale (MRS; McConahay 1986). The MRS is a seven-item measure of explicit contemporary prejudicial attitudes toward blacks (as opposed to “old-fashioned” or overt racism). Items are endorsed on a five-point scale from 1 (“Strongly Disagree”) to 5 (“Strongly agree”). Sample items include “Discrimination against blacks is no longer a problem in the USA” and “Over the past few years, blacks have gotten more economically than they deserve.” The scale’s internal consistency with the white sample was α = .78, and the correlation with social desirability was not significant, r = −.01, p = .947.

Dataset and Power

The current report represents a secondary analysis of a dataset generated for a larger, ongoing multi-site validation of the CCAS. As such, no a priori power calculations were employed to determine sample size for the current analyses. Average obtained power for the primary correlational analyses reported below with the white subsample was .82. The measures, dataset, and variable scoring used for these analyses are available at https://osf.io/k7dvp/.

Results

For analyses of white student’s responses, we retained 30 CCAS items with a mean rating of 2 or higher by the black students, indicating that the item was experienced as at least “possibly racist” by black respondents (this removed all 10 of the intended non-microaggressive items from the analysis and 16 others). Table 1 presents the means, standard deviations, and percentage of black respondents who evaluated each item as “possibly” racist, and “somewhat” or “very” racist, for these items. All 30 microaggressive items were evaluated as at least possibly racist by over 50% of the black respondents.
Table 1

CCAS item scores for black and white respondents and correlations with feeling thermometer

Scenario and item

Black respondents

White respondents

M

(SD)

Possibly racist (%)

Somewhat or very racist (%)

M

(SD)

Might or probably would say/do it (%)

Correlation with FT

Scenario 1

 You are smart for a black guy

3.70

(0.68)

12.1

84.8

1.39

(0.67)

00.9

−.34***

 You are a credit to your race

3.48

(0.80)

9.1

84.8

1.57

(0.93)

05.3

−.30**

 You don’t really seem like other black people

3.33

(0.89)

18.2

75.8

1.59

(0.83)

02.6

−.25*

 Did you get into school through some sort of minority scholarship?

3.27

(0.94)

15.2

75.8

1.63

(0.90)

04.4

−.29**

 You talk like a white person

3.24

(1.03)

15.2

72.7

1.64

(0.97)

05.3

−.15

 I wasn’t expecting you to be black

3.18

(0.81)

24.2

72.7

1.63

(0.82)

01.8

−.20*

 You seem more intelligent than I would have thought

3.03

(0.92)

21.2

69.7

1.48

(0.84)

03.5

−.15

 I am surprised you are a law student

2.94

(0.93)

27.3

63.6

1.46

(0.82)

03.5

−.24*

 I have other black friends

2.36

(1.03)

45.5

33.3

1.65

(0.92)

03.5

−.04

Scenario 2

 Is your hair real?

2.42

(0.94)

42.4

39.4

2.07

(1.08)

10.6

−.12

 Black women are so exotic

2.18

(1.18)

24.2

33.3

1.60

(0.89)

02.6

−.16

 Do you like spicy food?

2.12

(1.17)

18.2

36.4

1.60

(1.10)

10.6

−.00

 Can I touch your hair?

2.03

(1.03)

30.3

27.3

1.83

(1.18)

12.3

−.11

Scenario 3

 A lot of minorities are too sensitive

3.15

(0.94)

27.3

66.7

1.99

(1.18)

13.6

−.41***

 Hard work can overcome white privilege

2.64

(1.14)

33.3

45.5

2.58

(1.34)

25.4

−.13

 Black people get unfair advantages due to scholarships and affirmative action

2.59

(1.13)

24.2

48.5

2.29

(1.27)

21.1

−.18

 White privilege doesn’t really exist

2.58

(1.03)

45.5

39.4

1.91

(1.13)

10.6

−.30**

 Racism really doesn’t affect most people any more

2.21

(1.17)

27.3

33.3

1.70

(0.92)

04.4

−.23*

Scenario 4

 Tell a racial joke

3.44

(0.88)

15.2

75.8

1.49

(0.95)

07.8

−.18

 People of color are given extra unfair benefits because of their race

2.73

(1.07)

36.4

48.5

2.01

(1.19)

12.2

−.11

 I don’t understand why blacks get preferential treatment in school/jobs

2.70

(1.07)

21.2

57.6

1.92

(1.04)

07.8

−.33**

 The police have a tough job. It is not their fault if they occasionally make a mistake

2.70

(1.02)

33.3

51.5

2.53

(1.34)

26.1

−.20*

 Racism may have been a problem in the past, but it is not an important problem today

2.59

(1.16)

27.3

45.5

1.68

(0.99)

07.0

−.31**

 Racial problems in the USA are rare, isolated situations

2.48

(1.18)

33.3

39.4

1.72

(1.05)

08.7

−.19

 I am definitely not a racist. It is a problem, but it is not my problem

2.28

(1.05)

21.2

42.4

1.99

(1.27)

14.8

−.19

 All lives matter, not just black lives

2.15

(1.20)

18.2

36.4

3.40

(1.44)

51.3

−.19

 I don’t think of black people as black

2.03

(1.02)

33.3

27.3

2.70

(1.33)

30.4

.12

Scenario 5

 It’s unfair that black people can say the N-word but white people can’t.

2.67

(1.22)

18.2

54.5

1.95

(1.22)

10.4

−.27**

 Continue singing but explain that there is a difference between “nigga” and “nigger.”

2.30

(0.92)

45.5

33.3

1.65

(0.97)

06.1

−.28**

 Continue singing along, including the N-word

2.18

(1.10)

39.4

27.3

1.93

(1.08)

09.6

−.19

CCAS Cultural Cognitions and Actions Survey, FT Feeling Thermometer

* p < .05; ** p < .01; *** p < .001

Among white respondents, the 30-item total CCAS score demonstrated good internal consistency (α = .92) and items grouped by scenario varied in internal consistency, with all scenario-derived subscales at least moderately acceptable (αs = .89, .70, .79, .76, and .80 for Scenarios 1–5, respectively). There were no significant gender differences in CCAS total or subscale scores. The correlation between social desirability and the CCAS total was not significant, r = −.11, p = .258, and the correlations between social desirability and CCAS subscales were all nonsignificant.

Table 2 presents white respondents’ CCAS total and subscale scores and correlations with other measures, controlling for respondents’ social desirability scores. The total CCAS score correlated significantly with all five indicators of prejudicial feelings and attitudes toward black people. Each subscale was significantly correlated with four or more measures of racial prejudice except Scenario 2.
Table 2

White respondents’ CCAS total, scenario mean item scores, and correlations with other measures

 

M

(SD)

Correlations

FT

AS

CoBRAS

MRS

SR2K

Scenario 1

1.56

(0.64)

−.28**

−.29**

.20*

.29**

.13

Scenario 2

1.78 

(0.78)

−.19

−.17

.23*

.34***

.20

Scenario 3

2.09

(0.87)

−.33**

−.40***

.44***

.27**

.47***

Scenario 4

2.16 

(0.69)

−.29**

−.37***

.50***

.32**

.52***

Scenario 5

1.84 

(0.93)

−.29**

−.26**

.31**

.14

.27**

CCAS total

1.89 

(0.60)

−.38***

−.39***

.45***

.36***

.42***

CCAS Cultural Cognitions and Actions Survey, FT Feeling Thermometer, AS Allophilia Scale, MRS Modern Racism Scale, SR2K Symbolic Racism Scale 2000

* p < .05; ** p < .01; *** p < .001

Table 1 also presents results for individual items, including the percentage of white respondents who reported that they “might” or “probably” would say/do each item, and the correlations between individual items and FT scores. White respondents varied in endorsement of individual items, with a mean of 1.89 (SD = 0.60) across all items, suggesting that white respondents would most likely think the items but definitely not say or do them. At the item level, the mean scores of black respondents and white respondents were highly correlated, r = −.77, p < .001, suggesting that white respondents were less likely to report engaging in the microaggressions that black respondents felt were most offensive. However, the percentage of white respondents who reported that they “might” or “probably” would say/do an item varied, ranging from almost 0% (“You are smart for a black guy”) to 51.3% (“All lives matter, not just black lives”). Individual item correlations demonstrated small-to-moderate associations between individual items and FT scores. The strongest correlation with the FT was the item “A lot of minorities are too sensitive,” r = −.41, which was significant at p < .0001.

We also considered the frequencies of white respondents engaging in multiple microaggressive acts, according to their self-report. A total of 24 respondents (33%) reported that they would not say/do any of the items, 30 (28%) reported that they might or probably would say or do 1 or 2 of the items, 28 (26%) reported that they might or probably would say or do 3 or 4 of the items, and 24 (23%) reported that they might or probably would say or do 5 or more of the items. The upper range was one participant who reported that she/he “might” or “probably” would say or do 18 of the 30 CCAS items.

Discussion

To our knowledge, this report presents the first attempt to measure self-reported likelihood of delivering microaggressions by white individuals and to explore the association between the likelihood of delivering microaggressions and racial prejudice. Results suggested that likelihood of microaggressing across five common contexts is associated with several validated measures of prejudice. Specifically, white students who reported that they were more likely to microaggress were more likely to endorse color-blind, symbolic, and modern racist attitudes, report significantly less favorable attitudes toward black people on the feeling thermometer, and report significantly less positive attitudes toward black people. These findings provide empirical support that microaggressive acts are rooted in racist beliefs and feelings of deliverers, and may not be dismissed as simply subjective perceptions of the target. These findings resonate with Hudson Banks (2014), who cautioned our field that emphasizing the “perceived” nature of discrimination places an undue burden on the recipient of the discrimination to prove their experiences are valid; the current data validate the experiences of those who report being microaggressed against without requiring them to shoulder the burden of proof.

Racism is a multifaceted and complex construct, and some measures have been criticized as being confounded by inclusion of conservative ideological beliefs as indicators of racial prejudice (Lilienfeld 2017). Although research is clear that some conservative ideological beliefs are strongly associated with racial prejudice in their own right (e.g., Dhont and Hodson 2014), suggesting that inclusion of these beliefs in measures should not simply be considered a confound but a feature of the construct under investigation, a strength of the current study is the use of multiple measures of racism, including measures which are direct and pure indices of hostility and feelings toward black people independent of ideology (i.e., the racial feeling thermometer and the Allophilia Scale). Results were consistent across all measures. Overall, the current results offer preliminary support that the delivery of microaggressions by white students is not simply innocuous behavior and may be indicative of broad, complex, and negative racial attitudes and explicit underlying hostility and negative feelings toward black students.

The presentation of item-level results across black and white respondents may beg a question oft-raised in diversity workshops: “Was that a microaggression?” Although this is a question psychologists likely should avoid trying to answer (similar to an expert witness refusing to provide opinion on the state of mind of a defendant at the time a crime was committed), the item-level results do offer some important validations of the experiences of black students and microaggression researchers. For example, black individuals commonly report that they are told they are being “too sensitive” when they attempt to point out or address a microaggressive experience (e.g., Constantine 2007; Sue et al. 2009). This assertion—that the claim that one has been microaggressed against reflects “neuroticism” or “negative affectivity” rather than an objectively insulting experience—has been advanced as a critique of the validity of the microaggression research program in general (Lilienfeld 2017). Our results suggest that thinking or making the comment, “A lot of minorities are too sensitive,” which almost all black respondents felt was possibly, somewhat, or very racist, moderately correlates with hostile feelings toward black people. In other words, a white person in this sample who is more likely to deliver this utterance may be relatively higher in prejudice against black people than one is who is less likely to deliver it. The black person’s perception that the deliverer of this utterance may have hostile or negative feelings toward him/her is reasonably supported by these data, even if the deliverer’s true feelings are unknowable on a case-by-case basis. The unknowability of the deliverer’s true intentions may, in fact, contribute to the potential deleterious health effects of microaggressions, as some research indicates that ambiguous enactments of racism have higher costs on the recipient than do blatant, unambiguous enactments (Murphy et al. 2013).

This study has several limitations. First, the sample was too small and demographically homogeneous to develop the CCAS into a validated measure that would be suitable for use with other groups. Our choice to focus on white microaggressions against blacks is justified historically, by whites’ dominant positions in our society, and by epidemiological data documenting that blacks report experiencing discrimination more frequently than other major ethnic groups (Chae et al. 2011; Kessler et al. 1999). The dynamics of discrimination and privilege, however, are complex. Microaggressions may occur between any two individuals on the basis of differences in power and privilege (Sue 2010), and our results do not generalize to white racism toward other groups, such as Latinos or Asians, or to microaggressions committed by others than whites.

Geographically, respondents were undergraduate students at a large university in the Southern/Midwest USA, where prejudice toward blacks is stronger than in the West or New England (e.g., Mooney 2014). Generalizing findings to other regions, or to community or other samples, is not encouraged. Likewise, multiple ethnic and stigmatized groups report experiencing microaggressions, but the current analysis was restricted to a subset of specific microaggressions reported by black students. For example, one common microaggressive theme suggested by Sue et al. (2007) is “alien in one’s own land,” typified by the question “Where are you from?” The black respondents in the current study did not find this question to be racist, so it was not included in the final 30-item scale, but this is likely to be experienced differently by Latino and Asian Americans.

Further development of the CCAS is required, including internal issues such as exploring its factor structure and external issues such as additional concurrent validity. Because we know that much racial bias is implicit (Greenwald et al. 1998) and this bias manifests in multiple, subtle ways in interracial interactions (e.g., Dovidio et al. 2002), it is important to explore relations between the CCAS and measures of implicit bias as well as the explicit measures incorporated in this study. At the same time, it could be useful to explore the relation of the CCAS to more objective indicators of explicit prejudice (such as actual behavior). This should occur across demographically and geographically diverse samples, and an important next step in this line of inquiry would be a similar study of microaggressive behaviors against additional racial and ethnic minority groups. As with the construct of microaggressions itself, efforts to investigate the delivery of microaggressions will need to be specifically tailored to target microaggressions experienced by these other stigmatized groups.

Results suggest that it is possible to measure a self-reported likelihood to microaggress in potential deliverers of microaggressions and that this measurement can incorporate the ambiguous nature of the construct such that it is not confounded by social desirability. Results suggest that the construct of microaggressions is rightly situated within the science of racism and prejudice and contributes to our understanding of how racism is enacted in everyday interactions. The likelihood to microaggress appears related to prejudice, consistent with the experiences of those who report being on the receiving end of microaggressions. Combined with improved efforts to measure self-reported microaggressions, and the impact of these microaggressions on health and well-being, the current strategy offers promise for a multimodal approach to measurement and scientific understanding of microaggressions, how they function, and how they may be addressed and reduced.

Notes

Acknowledgments

This research was supported in part by a grant to Monnica T. Williams from the American Psychological Foundation.

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.Department of PsychologyUniversity of WashingtonSeattleUSA
  2. 2.University of ConnecticutStorrsUSA
  3. 3.University of LouisvilleLouisvilleUSA
  4. 4.Bastyr UniversityKenmoreUSA

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