Concealed within the construct of racial prejudice is the often-disregarded issue of colorism. Colorism is the process of discrimination that privileges light skin and Eurocentric features over dark skin and Afrocentric features (Harris, 2008; Hunter, 2005). Researchers suggest that African Americans (AAs) of all skin tones are subject to inequity, unfair criticism, and second-class citizenship merely because they are African American. The discrimination’s intensity, frequency, and outcomes, however, differ dramatically by skin tone (Hunter, 2007). And while AAs with lighter skin can face intragroup discrimination, research has found little evidence for light skin disadvantage. Rather, darker skin has been associated with disadvantages across socioeconomic and health domains, and even associated with higher body mass index and more stressful life events (Moore et al., 2020). As noted by Hochschild and Weaver (2007), people with darker complexions suffer from both primary and secondary marginalization, receiving adverse treatment because of their race (primary) and because of their skin tone (secondary). While colorism is a subcategory of racism when considering out-group discrimination, it exists independently of racism in the context of intragroup biases. The primary focus of this study is to better understand intragroup colorism within the AA community.

History of Colorism

In the USA, Anglo beauty standards have roots in European colonialism and slavery (Hunter, 2007). During this time, enslaved Africans who emulated whiteness culturally, ideologically, economically, and aesthetically were rewarded and given preferential treatment. A skin tone hierarchy was developed on the plantation (Bennett, 2007), and enslaved individuals with lighter skin received opportunities and resources that were otherwise unreachable to those with darker skin. Following slavery, the considerable social, educational, and economic advantages of black people with lighter skin gave them an irrefutably vast head start compared to other black folks (Bodenhorn & Ruebeck, 2007). Due to this skin tone privilege, these men and women with lighter skin were the first to become early business owners, clergy, teachers, and leaders in the early AA community.

Currently, research has found that people with light skin tend to have higher socioeconomic status (Hill, 2000; Hughes & Hertel, 1990), complete more years of formal education (Hunter, 2002), reside in better neighborhoods (Hunter, 2007), marry higher status people (Hochschild & Weaver, 2007; Hughes & Hertel, 1990), have less punitive relationships with the criminal justice system (Hochschild & Weaver, 2007; Viglione et al., 2011), and are viewed as more intelligent than those with darker skin (Hannon, 2014). Hannon (2015), for example, found that white interviewers saw black people with lighter skin as more intelligent than black people with darker skin even though they had the same educational achievement, vocabularies, and test scores. Uzogara and colleagues (2014) examined the perception of skin tone discrimination among a sample of AA males from 1995 and the second sample of AA males from 2003. It was found that men with medium skin tones perceived the least discrimination, while men with light and dark skin perceived more in-group discrimination. In another study, perceived in-group discrimination based on skin color was associated with worse physical health outcomes among African Americans (Monk, 2021).

While the impact of colorism has been relatively consistent across studies, the intersection of colorism and sexism may serve as a caveat to the notion that darker skin is always worse. That is, the rigid beauty standard that ties lightness to attractiveness and success for AA women (Hunter, 2005) is not always active among AA men. With less stringent standards of attractiveness, men with darker skin may not experience the same level of distress faced by women with darker skin (Keith, 2009), or as many limitations because of their darker skin tone. There is also evidence that the impact of colorism may vary by gender.

Gendered Colorism

Researchers have proposed that the effects of skin tone discrimination are more amplified in the lives of AA women (Hall, 2017; Maxwell et al., 2016). Given the research on the societal objectification of women, and a woman’s tendency to equate physical attractiveness with existential value (Calogero et al., 2011), the belief that gender may moderate the effects of skin tone discrimination among AAs is theoretically supported. These proposed discrepancies have gradually led to more empirical work designed to understand the intersection between gender and skin color (Hill, 2002).

Gendered colorism in the AA community is seen in a variety of contexts. For example, while the media put forth depictions of AA women who have light skin or who are racially ambiguous, this is not the case for men, who seem to have an easier time escaping the oppression of colorism through various entertainment and sports industries. Rappers with darker skin discriminate against black women based on color in their lyrics and music videos, polarizing perceptions of women but not men (Maxwell et al., 2016). Hill (2002) found that AAs perceive “fair” skin tone as a feminine characteristic. In this study, skin tone strongly influenced the attractiveness ratings assigned to black women, but this association was significantly weaker for men.

Thompson and Keith (2001) examined the relationship between colorism and psychological well-being and found that skin color predicted self-esteem scores for AA women but not men (Thompson & Keith, 2001). Skin color further predicted perceived self-efficacy for AA men but not women. These differences may indicate that skin color operates differently for men than women, not only in how they are treated but also in how they feel about themselves.

To understand how skin color satisfaction differs across complexion, Maxwell and colleagues (2015) evaluated the relationship between gender, self-reported skin color, skin color satisfaction, and the private regard aspect of racial identity. There were no significant differences between skin color and skin color satisfaction. However, very few participants considered themselves “dark” or “very dark,” and the researchers suspect that social desirability may have influenced the absence of a significant finding. Thus, the color satisfaction scores may be misleading. However, they found that internalized racism, or the endorsement of negative race-related stereotypes, was associated with lower skin color satisfaction.

Theoretical Framework

Three theories, namely social learning theory (Bandura, 1977), social identity theory (Tajfel et al., 1979), and intersectionality theory (Crenshaw, 1989), are helpful for understanding how African Americans intake, process, internalize, and reproduce colorist attitudes and behaviors. Research in social psychology demonstrates the importance of the social environment on learned attitudes and behavior (Bandura et al., 1961). According to social learning theory, children learn behavior through observing influential role models, like parents, teachers, and peers (Bandura, 1977). It is therefore plausible that African American youth learn attitudes about skin tone from people in their environment, and this information becomes and internalized and reproduced over time.

To further understand the motivation for acting out colorist behaviors, we can explore the notions of in-group and out-group belongingness, and personal and social identities. According to Tajfel and colleagues (1979), the groups for which people belong are an important source of pride and self-esteem (1979). Therefore, people’s beliefs and behaviors are shaped not just by their unique characteristics, but also by their sense of belonging to a particular group. One fundamental premise of social identity theory (Tajfel et al., 1979) is that members of the same group will seek to find negative aspects of an out-group, thus boosting their own self-image. Therefore, it is not uncommon for people to favor fellow in-group members and neglect or even discriminate against people from various out-groups (Volz et al., 2009). Regarding colorism, this concept is clearly recognized in the polarization of the lighter and darker skin tones (e.g., team light skin vs. team dark skin).

Lastly, it is important to consider an intersectional understanding of the colorism given its multifaceted nature. Intersectionality, a theory coined by Crenshaw (1989) describes the way in which people’s social identities overlap (Steinmetz, 2020). Instead of talking about race inequality separate from inequalities based in other areas (gender, class, sexuality, ability, etc.), Crenshaw (1989) encourages deeper exploration into how these identities intersect with one another. Furthermore, she stresses that the experience of intersectionality is greater than just the sum of its parts, and that intersectionality is made up of the intertwined lived experiences of one’s entire being. Given the gendered nature of colorism, the current study sought to better understand differences in the psychological consequences for men and women who experience colorism.

Purpose of the Present Study

The purpose of this research was three-fold: (1) to better understand the psychological effects of intragroup colorism, (2) to better understand how colorism differs between AA men and women, and (3) to explore the role of internalized racism, skin color satisfaction, and implicit skin tone preferences.

We hypothesized that men and women would explicitly prefer lighter skin tones over darker skin, with men’s preference significantly lighter than women’s. It was also predicted that men would have an implicit preference for the lighter two skin tones as evidenced by results on the IATs. We further predicted that as skin color preference became lighter, colorism would increase for men but not women. We predicted that dissonant skin tone preference, defined as the absolute value of the difference between one’s skin color and the skin color they prefer, would be associated with colorism, internalized racism, and psychological distress. We predicted that skin color dissatisfaction, colorism, and internalized racism would all be positively correlated with psychological distress, and that internalized racism, skin color satisfaction, and colorism would all uniquely predict each other. We hypothesized that as skin tone became darker, perceived discrimination would increase for women. Lastly, we predicted that as perceived discrimination from European and African Americans increased, psychological distress would increase and that perceived discrimination from African Americans would have a greater impact on psychological distress.

Method

Sample

The American University institutional review board approved the study. Participants were recruited online from Amazon’s Mechanical Turk (MTurk) and gave informed consent before participating. Participants identified as AA and were at least 18 years old. The study recruited 90 female and 86 male participants. There were 69 male and 56 female participants excluded from the study due to disqualifications based on inclusion criteria or failure to meet implicit measure latency standards. Participant ages ranged from 21 to 67. Regarding education, most participants identified as having a bachelor’s degree (44% and 52% of women and men respectively). Regarding income, the majority of men reported an annual income range between 42 and 62 K (36%) and the majority of women reported an annual income range between 21 and 41 K (29%). Regarding marital status, most participants identified as single, 59% and 52% of women and men respectively. Regarding skin color, most participants self-identified as having medium skin tone, 63% and 71% of women and men respectively.

Instruments

The In-Group Colorism Scale (ICS), developed by Harvey and colleagues (2014), was used to assess colorist beliefs and behaviors. The measure assesses the degree to which skin tone variation is important across five domains: Self-Concept, Affiliation, Attraction, Impression Formation, and Upward Mobility. The ICS was proven to have both good reliability and good structural validity (Harvey et al., 2017). The current study sought to understand colorism behaviors related to interpersonal relationships, so the Self-Concept subscale was removed. There were four subscales containing four items each. Items were rated on a 7-point Likert scale, ranging from 1 (strongly disagree) to 7 (strongly agree). The original Affiliation and Attraction subscales yielded good internal consistency as indicated by coefficient alphas, 0.80 and 0.81 respectively. The original Impression Formation scale yielded acceptable reliability as indicated by a coefficient alpha of 0.73, and the Upward Mobility scale yielded excellent reliability as indicated by a coefficient alpha of 0.90. For women of the current study, the Affiliation (α = 0.832) and Attraction (α = 0.826) subscales yielded good reliability. The Impression Formation (α = 0.912) and Upward Mobility (α = 0.926) subscales yielded excellent reliability. For male participants, the Affiliation (α = 0.810), Attraction (α = 0.871), and Impression Formation (α = 0.863) subscales yielded good reliability. The Upward Mobility (α = 0.935) subscale yielded excellent reliability.

The Brief Symptom Inventory—18 (BSI-18) is the shortened form of the BSI-53 and has been validated with AA populations. It contains three 6-item scales in the areas of somatization, depression, and anxiety (Derogatis, 2000). The questionnaire asked participants to indicate the degree of discomfort they experienced from each symptom over the last week. Answers on the 5-point Likert scale ranged from 0 (none at all) to 4 (Extreme). The current study removed the somatization subscale, and psychological well-being was based on depression and anxiety elevations independently. For women in the current study, both the depression (α = 0.92) and anxiety (α = 0.93) subscales yielded excellent reliability. For male participants, both the depression (α = 0.88) and the anxiety (α = 0.89) subscales yielded good reliability.

The Internalized Racial Oppression Scale (IROS; Bailey et al., 2011a, b) is a 36-item instrument that measures how much racial oppression is internalized and replicated by African Americans. The IROS utilizes a 5-point Likert scale that ranges from 1 (strongly disagree) to 5 (strongly agree). There were originally five subscales which reflected the different dimensions of internalized racial oppression: Belief in the Biased Representation of History (BRH), Devaluation of the African Worldview and Motifs (DAW), Alteration of Physical Appearance (APA), Internalization of Negative Stereotypes (INS), and Hair Change (HC). Although five subscales initially, their research supported an adequate model fit of a four-factor model (Bailey et al., 2011a, b); therefore, the DAW subscale was removed in the current study. Mean subscale scores were used to calculate a total scale score with higher scores indicating more internalized racial oppression. The original alpha coefficients for the four subscales of the IROS were as follows: BRH = 0.83, APA = 0.77, INS = 0.79, and HC = 0.77. For women in the current study, alpha coefficients were as follows: BRH = 0.66, APA = 0.83, INS = 0.87, and HC = 0.63. For men in the current study, alpha coefficients were as follows: BRH α = 0.34, APA α = 0.88, INS α = 0.88, and HC α = 0.23.

Two questions adapted from previous research (Uzogara et al., 2014) assessed how respondents appraised their skin tone as either an advantage, a disadvantage, or irrelevant during interactions with other AAs (in-group) as well as EAs (out-group). The in-group appraisal read: “Because of the shade of your skin tone, other AAs treat me: 1. A lot better; 2. Somewhat better; 3. No different; 4. Somewhat worse; or 5. A lot worse than other AAs?” The out-group appraisal read similarly, with “European Americans” replacing “African Americans.”

A 12-tone skin color pallet was used for participants to select the shade closest to their skin tone. Tones 1–4 were classified as light tones, 5–7 were classified as medium skin tones, and 8–12 were classified as dark skin tones. Using the same 12-tone skin color pallet, participants identified which skin color they had dated most and which skin tone they found most attractive.

Skin color satisfaction was measured using an adapted and shortened scale derived from three items from past research (Maxwell et al., 2015). The first item was derived from the Skin Color Questionnaire (Bond & Cash, 1992), and the second and third items were derived from the Skin Color Satisfaction Scale (Falconer & Neville, 2000). This brief 3-item scale measured color satisfaction (rated from 1 “extremely dissatisfied” to 9 “extremely satisfied”), color satisfaction compared to family members, and color satisfaction compared to AAs in general (both latter items rated from 1 “strongly disagree” to 9 “strongly agree”). The mean scores were summed and averaged, with higher scores indicating more satisfaction with skin color. Cronbach’s alpha for the original SCSS was 0.71. Cronbach’s alpha for the original 3-item scale developed by Maxwell and colleagues was 0.87. The alpha for the 3-item scale used in the current study was good for women (α = 0.88) and men (α = 0.83).

The Implicit Association Test (Greenwald et al., 1998) was used to assess implicit attitudes toward skin tone. Participants sorted a series of words and pictures into two attribute categories labeled “attractive” and “unattractive.” There was a total of six IATs, three taken by women and three taken by men. The IATs for women featured male faces, and the IAT for men featured female faces. Each set of IATs assessed the preference of two different skin tones: light vs. dark, light vs. medium, and dark vs. medium. For the IATs featuring female faces, the “attractive” attribute words were Pretty, Beautiful, Gorgeous, and Stunning. For the IATs featuring male faces, the “attractive” attribute words were Handsome, Good-looking, Striking, and Gorgeous. The “unattractive” attribute words for both sets of IATs were Ugly, Hideous, Repulsive, and Unpleasant. At the end of the task, a d-score was produced where higher values represented stronger associations between concepts. While the IAT has been used in many studies, this tool has never been used to look at the proposed research questions.

At times results from implicit tests are not consistent with results on explicit measures. It is important to understand that while implicit measures can provide users and researchers with important information, such a tool is mainly supplementary to explicit measures. Feedback from the IAT should be used as an educational device to provoke thinking about implicit bias and how it may influence how they interact with the world. As Brian Nosek, an IAT developer, said, “[The IAT] is not as malleable as mood and not as reliable as a personality trait. It’s in between the two–a blend of both a trait and a state characteristic” (Azar, 2008).

Design

A within-subjects design was used to gather survey data, and a between-subjects design was used for the implicit association tests. Participants were informed that participation was voluntary and electronically consented before participating. The study implemented descriptive statistics, correlations, and regression analyses. For occasional missing data in the questionnaires, data were replaced with the average score for the subject on a particular scale.

Results

Participant demographic information is shown in Table 1. Demographic information is categorized by gender and includes the frequencies of sex, sexual orientation, education, income range, and marital status indicated. Chi-square analysis indicated no association between participants’ sex and any of the other demographic information collected.

Table 1 Demographic information
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Explicit Skin Tone Preference

Participants rated the skin color they found most attractive and the skin color they had dated most in the past using a 12-tone skin color pallet. Regarding attractiveness, men’s average rating was 5.55 and women’s was 6.61, both corresponding to medium skin tone preference. Regarding dating history, men’s average rating was 5.66 and women’s was 6.51, both corresponding to medium skin tone. An independent-samples t test compared the means of these two groups. Levene’s Test for Equality of Variances indicated equal variances should be assumed. The t test revealed a significant difference between the means of men and women for both the skin tone they found most attractive (t =  − 2.545, *p = 0.012) and the skin tone they had dated most in the past (t =  − 2.244, *p = 0.026). Therefore, while both men and women preferred medium skin tone, men preferred a lighter medium compared to women. Cohen’s d was used to examine the effect sizes of the mean scores. The effect sizes were small for skin tone dated (Cohen’s d = 0.34) and for skin tone attracted (Cohen’s d = 0.38). The first hypothesis was supported.

Implicit Preference for Skin Tone

Implicit preference for skin tone was measured using three IATs which compared preferences for Light v Medium (LvM), Light v Dark (LvD), and Medium v Dark (MvD) skin tones. Statistical analyses revealed the LvM data came from a normal distribution for men and women (p = 0.720 and 0.143, respectively). Likewise, the LvD data came from a normal distribution for men and women (p = 0.513 and 0.227, respectively). The MvD data from men came from a normal distribution (p = 0.134), but the MvD data from women did not (p = 0.049). Even still, violations of normality on F and t tests usually do not impact validity as long as the sample size exceeds 30 or, even better, 50 (Pituch & Stevens, 2016). The current study exceeded these parameters, and the data was used as-is for subsequent analyses.

The built-in cutoff points for d-scores indicate various levels of implicit bias; however, cutoff scores are arbitrary and not based in research (Blanton & Jaccard, 2006). Therefore, the current study looked at the mean d-scores and tested whether they were significantly different from zero (zero indicated little to no preference).

A one-sample t test on the LvM IAT revealed that the average d-score for female participants (µ = 0.003) was not significantly different from zero, indicating little to no implicit preference when choosing between AA men with light and medium skin tones. Alternatively, the average d-score for male participants (µ = 0.142) was significantly different than zero, indicating that, on average, male participants preferred AA women with light skin over AA women with medium skin tones.

On the LvD IAT, the average d-score for female participants (µ = 0.076) was not significantly different from zero, indicating little to no implicit preference when choosing between AA men with light or dark skin. Alternatively, the average d-score for male participants (µ = 0.187) was significantly different than zero, indicating that, on average, male participants preferred AA women with light skin over AA women with dark skin.

On the MvD IAT, the average d-scores for both male (µ = 0.242) and female (µ = 0.191) participants were significantly different from 0, indicating that, on average, both groups had a preference for AAs with medium skin over AAs with dark skin. An independent-samples t test showed that these means were not significantly different from one another (t = 0.839, p = 0.402), indicating the strength of the preference was similar for men and women. Overall, the second hypothesis was partially supported.

Colorism and Dissonant Skin Color Preference

As men’s preference for lighter skin increased, as evidenced by the skin tone they had dated, colorism increased (r(88) =  − 0.283, p < 0.01). As men’s preference for lighter skin increased, as evidenced by to whom they reported being most attracted, colorism also increased (r(88) =  − 0.350, p < 0.001). These relationships did not exist for women.

Results indicated no relationship between skin color dissonance and skin color satisfaction, internalized racism, colorism, and psychological distress.

Skin Color Satisfaction, Colorism, Internalized Racism, and Psychological Distress

For women, as skin color satisfaction decreased, anxiety (r(88) =  − 0.527, ***p < 0.001) and depression (r(88) =  − 0.496, ***p < 0.001) increased. As colorism increased, anxiety (r(88) = 0.543, ***p < 0.001) and depression (r(88) = 0.531, ***p < 0.001) increased. As internalized racism increased, anxiety (r(88) = 0.435, ***p < 0.001) and depression (r(88) = 0.408, ***p < 0.001) increased. For men, as skin color satisfaction decreased, depression (r(84) =  − 0.363, ***p < 0.001) increased, but not anxiety. As colorism increased, anxiety (r(84) = 0.267, *p < 0.05) increased, but not depression. As internalized racism increased, anxiety (r(84) = 0.225, *p < 0.05) and depression (r(84) = 0.237, *p < 0.05) increased.

For women, as internalized racism increased, colorism increased (r(88) = 0.614, ***p < 0.001), skin color satisfaction decreased (r(88) =  − 0.526, ***p < 0.001), and anxiety (r(88) = 0.435, ***p < 0.001) and depression (r(88) = 0.408, ***p < 0.001) increased. Similarly for men, as internalized racism increased, colorism increased (r(84) = 0.720, ***p < 0.001), skin color satisfaction decreased (r(84) =  − 0.478, ***p < 0.001), and anxiety (r(84) = 0.225, *p < 0.05) and depression (r(84) = 0.237, *p < 0.05) increased.

Using the Fisher r-to-z transformation, the strength of men’s and women’s correlations was compared to one another. The positive correlation between internalized racism and colorism was stronger among men. The negative correlation between internalized racism and skin color satisfaction was stronger among men. Alternatively, the positive correlation between internalized racism and anxiety and depression was stronger among women.

Three hierarchical regressions were conducted to understand better the relationships between internalized racism, skin color satisfaction, and colorism. Each of the three constructs rotated as the outcome variable (y) while the other two hierarchically predicted it in the regression analysis. Figure 1 illustrates the gender differences.

Fig. 1
figure 1

Unique variance explained by gender

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In the first hierarchical regression for women, colorism explained 38% of the variance (R2 = 0.38, F = 53.28, ***p < 0.001) and skin color satisfaction explained 7% of the variance (R2 = 0.07, F = 35.56, ***p < 0.001) in internalized racism. For men, colorism explained 52% of the variance (R2 = 0.52, F = 90.60, ***p < 0.001) and skin color satisfaction explained 5% of the variance (R2 = 0.05, F = 54.28, **p < 0.01) in internalized racism.

The second hierarchical regression for women showed that internalized racism explained 28% of the variance (R2 = 0.28, F = 33.62, ***p < 0.001) and colorism explained 3% of the variance (R2 = 0.03, F = 19.58, *p = 0.05) in skin color satisfaction. For men, while internalized racism explained 23% of the variance in skin color satisfaction (R2 = 0.23, F = 24.94, **p < 0.01), the unique variance explained by colorism was not statistically significant.

The third hierarchical regression for women showed that internalized racism explained 38% of the variance (R2 = 0.38, F = 53.28, ***p < 0.001) and skin color satisfaction explained 3% of the variance (R2 = 0.03, F = 29.77, *p < 0.05) in colorism. For men, while internalized racism explained 52% of the variance in colorism (R2 = 0.52, F = 90.60, ***p < 0.001), the unique variance explained by skin color satisfaction was not statistically significant. Overall, the fourth hypothesis was partially supported.

Skin Color and Perceived Discrimination

There was a positive relationship between women’s skin tone and perceived discrimination from EAs (r(88) = 0.385, ***p < 0.001), but not from other AAs. There was not a significant relationship between men’s skin tone and perceived discrimination from EAs or AAs. Hypothesis five was partially supported.

Perceived Discrimination and Psychological Distress

Statistical analysis found no relationship between perceived discrimination from EAs and psychological distress for women or men. Alternatively, analyses revealed a relationship between perceived discrimination from other AAs and psychological distress, but just for women. More specifically, as women’s perceived discrimination from other AAs increased, anxiety (r(88) = 0.209, *p < 0.05) and depression (r(88) = 0.208, *p < 0.05) increased for women. The sixth hypothesis was partially supported.

Discussion

The purpose of this study was to examine the unique ways in which colorism affects the psychological well-being of African American men and women. Explicitly, both men and women indicated medium skin tone preference regarding their ratings for who they found most attractive and who they mainly dated. Statistical analysis revealed a significant difference between the preferences for men and women, with men showing a preference for a lighter shade of medium skin compared to women. Cohen’s d was used to examine the effect sizes of the mean scores associated with the skin pallets. Results indicated that the effect sizes were small when comparing men’s and women’s skin tone dated and skin tone attracted averages. While statistically significant, the difference between men’s and women’s average preferences on the 12-tone pallet showed little variability to the naked eye and may or may not have true meaning for real-life experiences. Still, on a scale where two pallets offer little difference visually, men went with a pallet that numerically indicated a lighter medium than women. Perhaps it would not be socially acceptable for AA men to explicitly desire AA women with lighter skin, and to select a more socially desirable palate, men chose the “lightest” tone that still appeared within the medium range of skin tones. In this scenario, AA men understand the issue of colorism, and in their strive to be culturally “woke” they adapt their choices to appear less biased. For women, preference for medium skin may have been an attempt to convey that socially, it is acceptable to prefer any range of skin tones among AA men. These hypotheses are in light of the implicit preference biases explained below.

Implicitly, we found that AA men always preferred the lighter two skin tones when pitted in contrast to one another, whereas women mostly showed no clear preferences. Women did, however, show an implicit preference for medium over dark skin. Therefore, while AA men’s responses were accurately predicted, the predictions regarding women (that they would implicitly show no preference in any IAT condition) were not fully supported. Women’s lack of preference for light over medium and light over dark skin tone may indicate that women find AA men of varying skin colors desirable. If so, this may be the consequence of AA men’s skin tones (across the spectrum) being associated with good and attractive attributes in mainstream society. The same does not hold for women who are more likely to be selected for media spotlight and regarded as beautiful if they have light skin tones. Even with the progressive strides to bring attention to the issue of colorism, women of darker skin tones continue to be portrayed with certain undesirable traits in movies, video games, TV shows, and advisements (Rotondo, 2020). It was surprising, however, when women implicitly preferred medium over dark skin tones without showing any other implicit preferences. This unexpected result may have something to do with AA women preferring medium skin in specific contexts. Perhaps one of those contexts is when these women self-identify as having medium skin tones themselves (as did the majority of women in this study). Future research should explore potential factors that impact these implicit preferences.

Statistical analyses revealed that the more AA men preferred lighter skin, the more colorist beliefs and behaviors they endorsed, and this was not the case for women. The importance of this finding lies within real-life implications of how we distinguish between harmless and harmful romantic preferences. It is common for individuals to disguise their colorist views (both conscious and subconscious) as preferences. Therefore, men may report they are simply more attracted to lighter skin and that their attraction has nothing to do with colorism; however, this finding suggests otherwise. The same relationship did not exist among women and may indicate that women date across the skin color spectrum, and when they have a skin color preference, they do not hold bias toward the other groups. In sum, preference for lighter skin among men is related to colorism.

The study further predicted that skin color dissonance, defined as the absolute value of the difference between one’s own skin color and the skin color they prefer, would positively correlate with skin color dissatisfaction, internalized racism, colorism, and psychological distress. Statistical analyses did not support this prediction. A closer examination of participant’s dissonant scores, which range from zero (no dissonance) to 11 (most dissonant), revealed the average score of dissonance was very low for women (µ = 2.33) and men (µ = 1.94). The low dissonance scores make sense given that most participants identified as having medium skin tones, and the majority also reported preferring medium skin tones. The lack of dissonance among the present sample likely contributed to this finding. Future research should explore these relations further.

The study found several variables associated with psychological distress. For instance, the more men and women disliked their skin color, the more they experienced depression, and women also experienced increased anxiety. The more men and women embraced colorist beliefs and behaviors, the more they experienced anxiety, and women also experienced more depression. The more men and women internalized racist views of AAs, the more they experienced anxiety and depression. Overall, women experienced both anxiety and depression in each association, whereas the emotional response from men varied. It is not entirely clear what mechanisms are responsible for men’s variable results, and future research should seek to better understand men’s stress responses toward these concepts.

Men’s and women’s behavioral and attitudinal responses to internalized racism also demonstrated gender differences. For example, as internalized racism increased, (a) colorism increased, (b) skin color satisfaction decreased, and (c) anxiety and depression increased for women. The same held true for men. As their internalized racism increased, (a) colorism increased, (b) skin color satisfaction decreased, and (c) anxiety and depression increased. The strengths of the correlations were compared and showed that the positive relationship between internalized racism and colorism was stronger in men, as was the negative relationship between internalized racism and skin color satisfaction. Alternatively, the positive relationship between internalized racism and anxiety and depression was stronger in women. It seems that the endorsement of negative AA stereotypes may have a more significant emotional effect on black women. In contrast, internalized racism may affect black men’s internal and external views on skin color. Subsequent analysis in future research may clarify the impact of these factors on mental health by considering other ways these constructs relate to one another.

The relational interlinks of internalized racism, colorism, and skin color satisfaction were explored and results indicated several ways in which each uniquely predicted the others. Internalized racism and colorism predicted the same percentage of variance in each other for both men and women. Perhaps the internalization of racist views toward AAs and colorist beliefs and behaviors toward the AA population touches on similar aspects of dislike for the AA community as a whole. The desire for proximity to whiteness among those who have internalized racist stereotypes is like those who discriminate within their own race because of skin color. Results also indicated colorism and skin color satisfaction predicted the same percentage of variance in each other for both men and women, and these levels of variance were much less compared to the other combinations of hierarchical regressions involving the three variables. Specifically, they both explained just 3% of the variance in each other for women, and their unique contributions to the variances of each other were not significant for men. It is not entirely surprising that skin color satisfaction plays a minor role in colorist beliefs and vice versa. Colorism is not isolated or polarized to one skin tone; instead, it affects individuals across the vast range of AA pigmentation. For both men and women, skin color satisfaction predicted far less of the variance in internalized racism than vice versa. Perhaps one can like or dislike their own skin color for a multitude of reasons, but still hold on to positive beliefs about African Americans, whereas when they have internalized negative views of AA, that dislike is more prone to trickle into their views of themselves. Overall, these results indicate the relationship between colorism, internalized racism, and skin color satisfaction is multifaceted, and more interactions between these variables should be explored in future research.

Other study findings revealed that as women’s skin color became darker, they perceived more discrimination from EAs, but not AAs. The subsequent analysis showed that as women’s skin became darker, their anxiety increased. None of these relations was significant among men. Again, there is a gender discrepancy between the experiences of men and women, furthering the notion that colorism and gender go hand in hand. Further illustrating gender differences, as women’s perceived discrimination from other AAs increased, so did their anxiety and depression. It appears that AA women do not necessarily feel judged by other AAs because of their skin color; however, when they do feel judged by other community members because of their skin color, it results in increased psychological distress. It may be that the experience of negative judgment from EAs, while unfortunate, is commonplace for many AAs and does not directly impact their emotional well-being. On the other hand, at least for AA women, when they feel judged within their own community because of their skin color, it is particularly harmful, which leads to increased anxiety and depression. This finding suggests that the impact of in-group discrimination may be more damaging than out-group discrimination. It is unclear what buffers the impact of intragroup-based discrimination or what mechanisms protect AA men from some of these effects.

Conclusion

In summary, the interplay between colorism, psychological well-being, internalized racism, skin color satisfaction, and skin color preference has yet to be adequately explored. The results from this clearly show evidence of colorism for African American men and women. It indicates that the society as a whole, and African Americans in particular, need to work on their self-perception regarding skin color. Providing community-wide information about the existence and impact of colorism would be a good first step. There should also be an intervention designed to eliminate colorism in the African American community.

This is particularly important for African American women given that we found the effect of colorism to be notably more substantial and harmful for women. In addition to facing the hardship of racism, AA women are keenly aware that men prefer them less as their skin color darkens. Ultimately, it is incumbent upon AA men and women to work together to combat the effects of colorism. But to do so will require a better understanding of the complicated role played by internalized racism. Only with a deeper examination of these constructs and progressive societal strides to dismantle racism can we begin to understand and address the psychology of African Americans in general, and African American women in particular.

Authors’ Note

It should be noted that the majority of participants reported having medium skin tone. Consequently, the lack of diversity of skin tones meant that more specific analyses pertaining to individual’s skin tones could not be conducted. Future research should consider more ways to gather skin tone information from individuals. Such methods may include having a more comprehensive range of skin tone choice options, recruiting participants who identify as having a specific skin tone, or measuring participant’s skin tones in person.