A Meta-Analysis of the Relationship Between Internalized Racial Oppression and Health-Related Outcomes

Internalized racism and negative mental health outcomes

The concept of internalized racism has received increased empirical attention in relation to mental health outcomes with specific consideration given to experiences of anxiety, depression, self-esteem, and psychological distress. To date, empirical research has produced fairly consistent findings to suggest a strong correlation between internalized racism and adverse mental health outcomes, that is, irrespective of differences in instrumentation, participant demographics, and sample sizes. For example, Wester, Vogel, Wei, and McLain (2006) found internalized racism, as measured by both the Miseducation and Self-Hatred subscales of the CRIS (Vandiver et al., 2000), to be directly correlated with the Anxiety subscale of the Brief Symptom Inventory (Derogatis & Melisaratos, 1983) among a sample of 130 African American male participants. However, this correlation was stronger for the Self-Hatred subscale (r = .34) than it was for the Miseducation subscale (r = .13).

A similar pattern of results was found by Worrell, Mendoza-Denton, Telesford, Simmons, and Martin (2011) among a sample of 340 African American students attending a research university with a smaller correlation between Anxiety and Miseducation (r = .002) than with Self-Hatred (r = .30). More recent findings measuring internalized racism with the CMS among 431 Black African men in Ghana continued to support a relation between anxiety and internalized racism with subscale correlations ranging from r = .12 (Physical Characteristics subscale) to r = .32 (Colonial Debt subscale; Utsey, Abrams, Opare-Henak, Bolden, & Williams, 2014). Thus, research findings on the association between internalized racism and anxiety have indicated a significant correlation with differences in effect sizes based on internalized racism measurement.

Similarly, research findings have also suggested a significant correlation between internalized racism and experiences of depression, the strength of which have also been found to vary with regard to internalized racism measurement. Specifically, correlations between a score on depression, as measured by the Brief Symptom Inventory and the Center for Epidemiologic Studies Depression Scale (CES-D Scale; Radloff, 1977), and Miseducation ranged from r = .06–.26 and from r = .31–.45 with Self-Hatred (Elion, Wang, Slaney, & French, 2012; Jones, Cross, & DeFour, 2007; Simpson, 2008; Wester, et al., 2006; Worrel et al., 2011). Findings with the Colonial Mentality Scale have also indicated significant associations between internalized racism and depression (CES-D and Mood and Anxiety Symptom Questionnaire [MASQ]; Watson et al., 1995) with CMS subscale correlations ranging from r = .09 (within-group discrimination; Utsey et al., 2014) among 431 Black Africans in Ghana to .52 (cultural shame; David, 2010) among 118 Asian American adults. This pattern of results is also consistent with investigations of the link between internalized racism, self-esteem, and collective self-esteem. Empirical findings suggest a large correlation between internalized racism (Self-Hatred) and self-esteem measured by the Rosenberg Self-Esteem Scale with significant negative correlations ranging from r = -.34 to -.46 when using the CRIS Self-Hatred subscale (Elion et al., 2012; Flowers, Levesque, & Fischer, 2011; Jones et al., 2007; and Szymanski & Gupta, 2009). Significant associations were also found with subscales of the Colonial Mentality Scale and self-esteem ranging from -.02 (Within-group Discrimination) to -.35 (Colonial Debt) and collective self-esteem (Collective Self-Esteem Scale [CSES]; Luhtanen & Crocker, 1992) ranging from -.19 (Within-group Discrimination) to -.32 (Colonial Debt; David, 2010; Utsey et al., 2014) among Black Africans and Asian Americans.

More recently, researchers have begun to investigate moderating variables in the relation between internalized racism and negative mental health outcomes. Mouzon and McLean (2017) examined the moderating roles of ethnicity/nativity and mastery (sense of self-control over life circumstances) between internalized racism and depressive symptoms and psychological distress among African American and Caribbean Blacks . Results of this study indicated a positive relation between internalized racism and depressive symptoms and psychological distress among all Black subgroups and that nativity and mastery significantly moderated the relations such that being foreign-born and perceiving higher degrees of mastery were protective against the mental health costs of higher levels of internalized racism. James (2017) also investigated internalized racism and major depressive disorder among a nationally representative sample of 3,570 African American adults and results indicated that self-esteem and ethnic identity, individually moderated the relation between internalized racism and major depressive disorder. Specifically, results indicated that when internalized racism was high, higher levels of self-esteem were protective against having experienced a past-year major depressive disorder as measured by the World Mental Health Composite International Diagnostic Interview (WMH-CIDI). This pattern of results across empirical investigations in the link between internalized racism and negative mental health outcomes indicates a general trend of significant association between variables, yet with a degree of variability potentially attributable to factors such as internalized racism instrumentation and other moderating variables, this association warrants further clarification through the systematic study of meta-analysis.

Internalized racism and negative physical health outcomes

Compared to research examining the associations between internalized racism and negative mental health outcomes, research on associations between internalized racism and negative physical health outcomes has garnered limited, yet growing, empirical attention. To date, internalized racism has been studied in relation to body mass index and obesity, cardiovascular variables (e.g., diastolic blood pressure, systolic blood pressure, hypertension, and history of cardiovascular disease), diabetic factors (e.g., glucose level and insulin resistance), and general health (e.g., self-reported health and maladaptive eating behaviors). This body of research has, on whole, provided evidence for significant relations between internalized racism and health outcomes albeit with relatively smaller effect sizes. Tull et al. (1999) found significant direct correlations between scores on the NAD and obesity (r = .134) and hypertension (r = .048).

These findings were supported by more recent findings of significant correlations between NAD scores and body mass index (Tull, Cort, Gwebu, & Gwebu, 2007; Tull, Sheu, Butler & Cornelious, 2005), and waist circumference (Cort, Gwebu, Tull, Cox, & Modise, 2013; Tull et al., 2007; Tull et al., 2005). Still further studies have demonstrated gender differences among the significant correlations with fasting glucose, diastolic blood pressure, and systolic blood pressure, with greater effect sizes for female participants (Tull et al., 2007). Significant direct correlations have also been observed with negative physical health outcomes (Mousavi, 2006) and maladaptive eating behaviors (Flowers, Levesque, & Fischer, 2011) when measuring internalized racism with the Miseducation and Self-Hatred subscales of the CRIS. These findings mirror research examining the association between internalized racism and negative mental health outcomes suggesting a greater association when examining Self-Hatred in comparison to Miseducation.

Because internalized racism has been operationalized in many different ways, we explored the moderating role of internalized racism measurement type. Furthermore, since several studies (n = 11) contained the same two subscales of the CRIS (i.e., Miseducation and Self-Hatred subscales) and three studies singularly utilized the CRIS Self-Hatred subscale (Szymanski & Gupta, 2009; Szymanski & Obiri, 2011; Szymanski & Stewart, 2010), these three CRIS subscale types served as a second moderator.

Gender

Gender was chosen as a moderator variable due to higher prevalence rates of depression among women as compared with men and because of the potentially cumulative effect of multiple oppressions on health among Women of Color (Carr, Szymanski, Taha, West, & Kaslow, 2014). Furthermore, according to a minority stress model (Meyer, 1995, 2003), the combination of multiple oppressed identities (e.g., race and gender) may create excess stress with potential impact on mental health outcomes. Given this potential, gender was considered as an important moderator.

Sample setting

Sample setting (i.e., samples drawn from universities, medical centers, and online platforms) was included as a moderator because this sampling variable may influence the degree to which internalized racism may be related to adverse outcomes. It was expected that samples collected from a university setting may differ from those collected in a community mental health clinic (i.e., clinical vs. nonclinical samples), reflecting the relatively higher or lower prevalence of mental health problems. That is, internalized racism is expected to have a weaker relationship to mental health problems in samples where mental health problems occur less frequently and with lower severity.

Country of sample

Country of sample (i.e., United States vs. international samples) was selected as a moderator because we expected the unique history of race and/or racism within each country to be salient to the development and functioning of internalized racism. For example, racism experienced within the United States or South Africa may differ from experiences of racism in postabolition Brazil, where legal race-based segregation has never been imposed (Marx, 1998). Furthermore, racism experienced in a country where the racial majority is White (e.g., United States) may be experienced differently in other countries where Blacks are the racial majority (e.g., South Africa; Statistics South Africa, 2014; U.S. Census Bureau, 2017). Past research has supported the notion of varied impact of internalized racism by country of origin (Mouzon & McLean, 2017). For example, Molina and James (2016) examined internalized racism and major depressive disorder among African American and Afro-Caribbean adults. They found that internalized racism was associated with decreased incidence of major depressive disorder among Afro-Caribbean adults, but not among African Americans.

Sampling method

Sampling method (i.e., convenience sampling or random sampling) was included as a moderator because the method in which participants are gathered can influence results by introducing unexpected and/or uncontrolled factors. For example, in a convenience sample, participants may be from the same geographical area or be of similar socioeconomic statuses or racial and/or ethnic backgrounds which may bias the sample in one way or another (Emerson, 2015). Given the potential for bias related to sampling method, it seemed to be an important moderating variable to consider.

Publication type and year

Publication type (i.e., journal or dissertation) was included as an additional assessment of publication bias. Our goal was to conduct an extensive review of the literature, thus we included both peer-reviewed publications as well as doctoral-level student dissertations. Additionally, publication year was included, given the possible influence that changes in the sociopolitical climate, regarding race, may affect how internalized racism relates to adverse outcomes.

Search Strategy

The literature search for this meta-analysis was conducted in English, and included peer-reviewed published articles and dissertations from the earliest time available in specified databases to the end of March 2015. Studies that were theoretical, qualitative, or missing relevant statistical information were excluded. The majority of articles were identified through an online search. The search covered the following databases and electronic collections: PsycINFO, PsycARTICLES, SAGE Journals, the NIH, TRACE, OhioLINK, and ProQuest (for dissertations). Studies were considered relevant to the meta-analysis if they contained empirical data examining the relationship of internalized racism and racial oppression, to psychological and physiological health outcomes among People of Color. Key terms used in these searches related to internalized racism, racial identity and oppression (e.g., racism, perceived stress, racial identity, internalized racism, internalized oppression, coping) as it related to any aspect of mental and physical health (e.g., quality of life, psychological well-being, psychological distress, psychological adjustment, psychological health, depression, distress, colonial mentality, body fat, health outcomes). The risk of confirmation bias is present in this review as the phrases used were leading in nature, which may have resulted in only supportive research being found. However, that being said, disproving research would likely have appeared in our searches, leading us to believe that this risk is minimal at most.

This search yielded a total of 790 published studies, which were then limited to 452 studies based on content relevance. From the 452 studies, 381 studies were excluded for being either conceptual pieces, qualitative, or for missing relevant statistical information. The criteria were based on studies that included a measure of internalized racial oppression and either a measure of physical or psychological functioning. Of the remaining 71 studies, 42 studies were excluded that pertained only to racial identity, ethnic identity, or racial socialization. Subsequently 29 studies were included in the final analysis.

Effect Size

The primary index of the effect size used in the current meta-analysis was Pearson Product Moment Correlation Coefficients (r), representing the relationships between internalized racism and health outcomes. We used Cohen’s (1988) benchmarks to judge the magnitude of correlations: r values between .1 and .3 were considered small, r values between .3 and .5 were medium, and r values greater than .50 were large. Heterogeneity in effect sizes were tested with Q statistic in which a p-value less than .05 indicated significant between-study variation in effect sizes (Borenstein, Hedges, Higgins, & Rothstein, 2009). The I² measure was used to capture the percentage of true heterogeneity to total variance across the observed effect sizes (Borenstein et al., 2009). For studies that included effect sizes based on regression analysis (Chae et al., 2014), odds ratio (Butler, Tull, Chambers & Taylor, 2002; Chae, Lincoln, Adler, & Syme, 2010; Tull et al., 1999), chi-square correlation (Cort et al., 2013), or provided group means, standard deviations, and confidence intervals (Tull et al., 2005), we transformed these effect sizes into correlation coefficients using methods outlined by Borenstein et al. (2009). Furthermore, in order to address the nonnormality of correlation coefficients (Hedges & Olkin, 1985), correlation coefficients were first transformed to Fisher’s z via z_i = .5*ln (1 + r_i / 1 – r_i), where ln is the natural logarithm which has a conditional variance of v _i = 1 / (n_i – 3) where n_i is the sample size (Borenstein et al., 2009). As described in Borenstein et al. (2009), all of the estimates (e.g., means and 95% confidence intervals) computed based on Fisher’s z scale were then back-transformed to the r metric via r(z_i) = (e^2zi – 1) / (e^2zi + 1), so that they could be interpreted as common correlation coefficients.

Statistical Analyses

Data were analyzed using meta-analytic techniques as described in Hedges and Olkin (1985) and Cooper et al. (2009). An overall analysis was conducted to synthesize the relation between internalized racism and outcomes, including both negative mental and physical health outcomes. A moderator analysis was then conducted to examine whether there were significant differences in how internalized racism corresponded to the two different types of outcomes (i.e., negative mental health outcomes and negative physical health outcomes). Additional moderator analyses identified whether or not the relation between internalized racism and health outcomes differed by (a) type of measure used to capture internalized racism (CMS, CRIS, NAD, and Racial Identity Attitude Scale [RIAS, Parham & Helms, 1981]), (b) gender of sample (male or female), (c) sample setting (university, hospital, online), (d) sampling method (convenience or random), (e) country of sample (United States or international), (f) publication type (journal article or dissertation), and (g) publication year. We used a more conservative alpha level of .01, instead of .05, to account for the multiple moderation analyses performed.

The random-effects model was used in the overall analysis and mixed-effects models with predictors were used in the moderator analyses because these models assume that effect sizes vary beyond what would be expected from sampling error (Raudenbush, 2009) as our intention was to generalize our findings beyond the population of studies represented in the sample (Quintana & Minami, 2006). Additional variability beyond sampling error was calculated using the Restricted Maximum Likelihood Estimation method. For the mixed-effects models with categorical moderators, the additional uncertainty was computed within each level of the categorical moderator. By allowing the population parameters to vary across studies, the random-effects and mixed-effects models reduce the probability of committing a Type I error (Borenstein et al., 2009; Hedges & Vevea, 1998). Finally, to examine whether the overall relationship between internalized racism and health outcomes varied by publication year, we used meta-regression. All statistical analyses were conducted using R software.

Dependency

In instances where there were two effect sizes that captured the relationship between internalized racism and health outcomes within the same sample, we aggregated the effect sizes so that each sample had only one effect size. This process eliminated the issue of dependency, wherein a sample may contain multiple dependent (based on the same sample) effect sizes (Borenstein et al., 2009). For example, in the overall analysis between internalized racism and health outcomes, we averaged the effect size between internalized racism and negative mental health outcomes and internalized racism and negative physical health outcomes to produce one overall effect size for internalized racism and health outcomes. Similarly, in studies where there were two effect sizes for internalized racism and negative mental health outcomes because there were two indices of negative mental health outcomes used (such as anxiety and depression found in Utsey et al., 2014), we averaged these effect sizes to produce one effect size for internalized racism and negative mental health outcomes.

Description of Studies

There were a total of 32 independent samples from 29 studies (24 published studies and 5 dissertations). Three published studies provided data for males and females separately, and thus were treated as separate samples. The included studies were published or defended between 1999 and 2015. Of the 32 samples, 30 were based on primary data that the author(s) collected, and two were based on secondary data (Chae et al., 2010; Tull et al., 2005).

Sample sizes varied from 40 to 1,216 (M = 199, SD = 121), yielding a total of 6,367 participants included in the current meta-analysis. The mean age of participants ranged from 14 to 82 years old (M_age = 30, SD = 12). Among the 32 independent samples, two were exclusively focused on children or adolescents under the mean age of 18 years old and the remaining were based on adults. Of the total number of participants, females (women or girls) represented 55% (n = 3,502), while males (men or boys) represented 45% (n = 2,865). The participants’ racial and/or ethnic backgrounds included 91.61% African American (n = 5,858), 2.54% Asian American (n = 159), 4.28% Latina/o Americans (n = 274), 1.17% Biracial (n = 76), and 0.36% did not report race and/or ethnicity (n = 25).

Publication Bias

Although we included both published studies and dissertations in our meta-analysis, as a safeguard we assessed whether publication bias was likely to be problematic in our sample of studies using the funnel plot method and Egger’s regression test of the intercept (Sutton, 2009). The results of both methods indicated that publication bias was unlikely with our sample of studies. Examination of the funnel plot showed that effect sizes were distributed symmetrically around the mean effect size suggesting that publication bias was not likely present. The Egger’s regression test of intercept was found to be nonsignificant, t(30) = 1.74, p = .073, indicating no potential threat due to publication bias in our sample of total studies. Such results provided us with additional confidence for generalizing our statistical findings given that there is no potential threat due to publication censoring.

Relationship Between Internalized Racism and Health Outcomes

Figure 1 displays results from statistical analyses examining the relationships among internalized racism and health outcomes, including both mental and physical. The results indicated that the link between internalized racism and outcomes is small and statistically significant (r = .21, SE = .02, p < .001, 95% CI [.17, .25]) with significant heterogeneity among effect sizes (Q_Error[31] = 99.57, p < .001) warranting additional moderator analyses to account for this unexplained variation. This result indicated that internalized racism is significantly and positively related to negative health outcomes, suggesting that an individual who reported greater internalized racism also reported experiencing more negative health outcomes. The results of the moderator analysis indicated that this relationship significantly differed by types of negative health outcomes (Q_B[1] = 18.67, p < .001; Q_Error[32] = 50.78, p < .001), where B indicates between-studies. The estimated correlation for negative mental health outcomes (r = .26, SE = .02, p < .001, 95% CI [.22, .30]) was significantly higher than for negative physical health outcomes (r = .11, SE = .03, p < .001, 95% CI [.06, .17]) and both correlations were small in magnitude

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Figure 1.

Forest plot of study effect sizes.

Examination of Study Characteristics for Moderation Effects

Table 1 displays the full results from the statistical analyses examining whether the relationship between internalized racism and overall health outcomes varied by internalized racism measurement, gender of sample, sample setting, sampling method, country of sample, publication type, and publication year.

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Table 1.

Summary of Main Effect and Moderation Effects

Variable	Q	k	r	SE	LL	UL
Main effect
Overall effect	QTotal(21) = 99.57***; I2 = 63%	32	.21***	.02	.16	.25
Moderation effects
Health outcome	QBetween(1) = 18.67***; I2 = 35%
Negative physical health		12	.11***	.03	.06	.16
Negative mental health		20	.26***	.02	.22	.30
Measurement type	QBetween(3) = 24.80***
CMS		2	.27***	.06	.15	.37
CRIS		14	.24***	.02	.20	.27
NAD		11	.11***	.02	.06	.15
RIAS		2	.36***	.08	.22	.48
CRIS subscales	QBetween(1) = 63.83***
Miseducation		11	.10***	.02	.06	.15
Self-hatred		14	.33***	.02	.30	.37
Gender	QBetween(1) = .33; I2 = 63%
Male		8	.15**	.05	.06	.23
Female		13	.18***	.04	.11	.25
Publication type	QBetween(1) = .01; I2 = 64%
Journal		27	.21***	.02	.16	.25
Dissertation		5	.21**	.07	.08	.34
Sample setting	QBetween(2) = .46; I2 = 27%
University		11	.25***	.03	.20	.30
Medical center		4	.23***	.06	.12	.33
Online		2	.21**	.06	.08	.32
Sampling method	QBetween(1) = 9.31**; I2 = 48%
Convenience sampling		26	.23***	.02	.19	.27
Random survey		6	.09*	.04	.003	.17
Country	QBetween(1) = 8.76**; I2 = 60%
United States		22	.24***	.03	.20	.29
International		10	.12**	.04	.04	.19

Note. I² = Percentage of true heterogeneity to total observed variation; CMS = Colonial Mentality Scale; CRIS = Cross Racial Identity Scale; NAD = Nadanolitization Scale; RIAS = Racial Identity Attitude Scale.

*

p < .05. **p < .01. ***p < .001.

Limitations

Research on the psychological and physical correlates of internalized racism is a developing area, which has gained more attention within the past two decades. In the current study, we examined the relationships between internalized racism and negative mental and physical health outcomes within the empirical literature through the year 2015. It should be noted that additional measures of internalized racism are not reflected within the study as they had not yet been developed (e.g., Appropriated Racial Oppression Scale [AROS; Campón & Carter, 2015], Internalized Racism in Asian Americans Scale [IRAAS; Choi, Israel, & Maeda, 2017]) or because no studies had yet used the scale in relation to the outcome variables of focus (e.g., the Internalized Racial Oppression Scale [IROS; Bailey, Chung, Williams, Singh, & Terrell, 2011]). These instruments, which have been developed both for specific populations (i.e., IROS for Black individuals, IRAAS for Asian Americans), and for use across racial groups (i.e., AROS) provide additional tools for further research in this area.

The participants included within the present study were primarily Black African and African Americans (92%) and may not fully reflect the nature of the relationship between internalized racism and negative physical or mental health outcomes among POC from other racial and/or ethnic backgrounds. Because each racial group has its own complex history within the United States, it stands to reason that the experience of internalized racism may also possess unique characteristics across racial groups and that the strength of the associations between internalized racism and health might vary based on racial group membership. Although findings from recent studies of internalized racism within Asian American (Choi et al., 2017) and multiracial (Gale & Pieterse, 2017) samples have indicated similar relations between internalized racism and health variables as the present study, findings from the current study are most appropriately generalized to Black African and African American individuals. Additionally, although country of sample was found to be a significant moderator, it should be noted that the individual countries included have differing current and historical contexts of race and racism. This heterogeneity in the operationalization of the variable complicates interpretation of the significant finding and further research is needed to better understand how the relationships between internalized racism, health, and mental health in the United States compare to specific individual countries and/or regions internationally.

Implications for Practice, Advocacy, Education/Training, and Research

The results of our study hold multiple implications for practice, advocacy, education/training, and research. Results indicate that for POC living in a racially stratified society, mental and physical health disparities are related to the internalization of negative racial stereotypes embedded within dominant White culture. Internalized racism may contribute to poor health outcomes through mental health symptoms of depression or anxiety, as well as limiting one’s expectations for one’s own abilities to engage in healthy behavior based on their racial group membership. As such, psychologists and other mental health providers are encouraged to assess the level and salience of internalized racism within their clinical populations, as this topic may represent an important area for clinical focus. Clinicians may choose to formally assess internalized racism via the scales identified in this meta-analysis or through included questions during initial interviews as clients’ negative views about their own racial group membership may be contributing factors to presenting problems such as low self-esteem, depression, and anxiety. Finally, although we did not test hypotheses regarding the potential causal link between internalized racism and these mental health problems, it may be reasoned that interventions targeted to lower internalized racism are likely to raise collective self-esteem and have ripple effects to other areas of clinical focus (Utsey et al., 2014). As such, mental health clinicians can include a focus on healthy racial identity development when working with POC as a targeted intervention on internalized racism (Taylor, 1990).

Through the lens of engagement in social justice and advocacy, if internalized racism is understood as a psychological response to a proximal pathway (i.e., racial discrimination, historical trauma, macro racial stressors) ultimately stemming from basic determinants of health (e.g., institutional and cultural racism; Williams & Mohammed, 2013), it follows that action is required not only at the individual level of remediation, but also at the institutional, cultural, and societal level to prevent further harm. Psychologists may then consider joining with individuals and systems involved in the development and revision of policies acting to dismember supports to systems of racial oppression, that ultimately lead to great costs to the health and mental health of POC, and the resulting strains on mental health care systems.

The results of the present study also suggest that psychologists-in-training are likely to benefit from didactic focus on connections between racial-cultural experiences such as systemic, cultural, and internalized racism and their associations to negative mental health outcomes. This training would aid psychologist trainees in their conceptualization of mental health problems among POC and treatment planning for clients presenting with elevated rates of internalized racism which may be associated with other aspects of their presenting problems. Faculty and supervisors involved in the training of psychologists and other mental health providers can bring attention to the issue of internalized racism in conceptualization and intervention planning in clinical work.

The integration of this material into practice, advocacy, and education/training would benefit from additional research. Further scholarship in this area may facilitate a more nuanced understanding of the relation between internalized racism and negative health outcomes among POC and guide intervention among mental and physical health providers in their work with racial minority communities. Further research examining the role of internalized racism among other racial minority groups is warranted and can be facilitated by use of recently developed measures outlined previously. This line of research would also allow future meta-analyses to compare the internalized racism-health link across different racial and ethnic groups.

As aforementioned, our findings suggest a potential need for adaption or revision of current measures of internalized racism given the inconsistency in findings across measurement type. Further investigations into the functioning of differing and more recent operationalizations of internalized racism not included in the present study (i.e., IRAAS, IROS, AROS) may provide greater clarity on discrepancies in results based on internalized racism measurement. This research may also indicate whether revisions or adaptations to existing scales are warranted, help to further refine understanding of the construct of internalized racism, and provide data on the applicability of various measures of internalized racial oppression for different groups or purposes. Differences in the strength of association between operationalizations of internalized racism and negative mental health and health outcomes may also suggest that some aspects of internalized racism represent greater vulnerabilities to health and mental health of POC and thus may be of specific special interest to future researchers.