Racial Discrimination and Relationship Outcomes: A Meta-Analysis

Abstract

Although racial discrimination is clearly connected to poor health, and relationships are connected to good health, little research has examined the link between racial discrimination and relationships. Thus, we conducted a meta-analysis of studies that examine the relation between racial discrimination and relationship outcomes. Of the 36 articles including 113 effect sizes, we found a small association of racial discrimination to poor relationship outcomes, r = −.095, 95% CI [−.141, −.049]. Subgroup analyses suggest racial discrimination is related to higher negative relationship outcomes, lower positive relationship outcomes, and is unrelated to social support. The overall association was moderated by study quality, study design, and proportion of Black participants. This meta-analysis highlights the need to consider whether racial discrimination has a causal impact on relationships, and, if so, how to harness relationships to buffer the negative health effects of discrimination. Future research should examine mechanisms explaining the link between racial discrimination and relationship outcomes.

Keywords

meta-analysis discrimination relationships social support stress

There is a well-established literature linking racial discrimination to poor mental and physical health (Allen et al., 2019; Carter et al., 2017; Lee et al., 2020; Paradies et al., 2015), but much less research has examined the link between discrimination and relationship outcomes despite the fact that relationships promote health and buffer the effects of stress on health. The purpose of this paper is to undertake a meta-analytic review of the literature linking racial discrimination to relationship outcomes.

It is important to understand how racial discrimination affects the quality of relationships because relationships have established links with good health. For example, meta-analyses have shown that greater marital quality is related to better health (Robles et al., 2014), and social support is related to lower levels of systemic inflammation (Uchino et al., 2018) and improved sleep outcomes (Kent de Grey et al., 2018). A quantitative synthesis of 60 meta-analyses on social support and psychological adjustment also revealed a positive association (Zell & Stockus, 2024). Relationships not only have a direct benefit to health but also buffer the adverse effects of stress on health (Cohen & Wills, 1985). For these reasons, it is important to understand the effects of discrimination on relationships.

There are a number of theories that could shed light on the association of discrimination to relationship outcomes. One possibility is that discrimination has an adverse effect on relationships because it is a stressor that causes strain for the relationship. This is in line with the theory of stress spillover, which posits that stressors external to the relationship deplete self-regulatory resources needed to maintain positive relationship behaviors (Buck & Neff, 2012). Relationship behaviors are critical to the Family Stress Model (Conger et al., 1990), which suggests that external stressors negatively impact relationships via the quality of social interactions (Conger et al., 1990). Specifically, economic stressors have been shown to increase hostile interactions and undermine warm and supportive interactions among White married couples (Conger et al., 1990; Conger, 2025). These findings have been partly replicated in a study of African American couples (Cutrona et al., 2003). In that study, financial strain predicted lower marital quality but did not predict observed warm or hostile interactions. Living in a disadvantaged neighborhood predicted lower warmth but did not predict hostility and, surprisingly, predicted higher marital quality.

Similarly, the Vulnerability-Stress-Adaptation Model suggests that external stressors affect the quality of close relationships via their effects on the nature of social interactions (Karney & Bradbury, 1995). However, those effects could be negative or positive, partly determined by the enduring vulnerabilities of the individual (e.g., sociodemographic or personality traits). In a study of African American couples, religiosity served as an enduring resource and low education served as an enduring vulnerability to the effects of financial stress on relationship outcomes (Cutrona et al., 2011).

These theories, however, may be limited in understanding the effect of racial discrimination on relationships because there are aspects of racial discrimination that distinguish it from other stressors. First, racial discrimination is not a single stressor but a collection of stressors that affect all aspects of life for racial minoritized populations (Williams, 2018). Racial discrimination can take many different forms, ranging from being denied housing to being socially excluded, due to a physical characteristic that is uncontrollable and unconcealable. Second, this physical characteristic is often viewed by others to be a defining characteristic of the person. That is, racial discrimination is tied to a personal characteristic of the self (i.e., ethnic-racial identity), which may exacerbate the impact of the stressor (Williams et al., 2020). Third, compared to some other stressors, racial discrimination is unavoidable, and the pervasiveness of this stressor may make it more likely that the person internalizes others’ negative perceptions, which can further negatively affect health (Sosoo et al., 2020). According to minority stress theory, racial discrimination consists of both external and internal processes (Meyer, 2003). Discriminatory events are external to the individual, but there are additional sources of stress that are more internal to the individual—specifically, hypervigilance about one’s social environment and internalization of discrimination. For these reasons, it is not clear whether the predictions from the foundational relationship theories on stress generalize to discrimination.

There is also the possibility that the effect of discrimination on relationships can be thought of in a way that differentiates it from the stress literature. There is reason to believe that discrimination could have benefits to relationships. Experiences of discrimination may increase cohesion and connection as well as provide opportunities for support exchanges. Families and close relationship partners can provide support to one another to cope with discrimination in a way that the larger society cannot (Murry et al., 2001). Some researchers have suggested that facing discrimination is a common stressor that draws Black and Brown communities together (Cortland et al., 2017). One study of African Americans distinguished between two kinds of stress—financial strain and racial discrimination—and found evidence that financial strain was associated with providing less support to partners, but racial discrimination was associated with providing more support to partners (Clavél et al., 2017). Because discrimination is an uncontrollable stressor unrelated to the relationship, it may be seen as an issue that neither member of the couple has the ability to influence, allowing for couple members to provide support to one another causing the relationship to grow stronger.

Despite this reasoning, a systematic review of the link between racial discrimination and relationship outcomes among African American couples concluded that racial discrimination not only undermined positive relationship outcomes (e.g., marital satisfaction) but also was related to increased negative relationship outcomes (e.g., conflict) (Rice et al., 2023). One study demonstrated that discrimination exacerbated the link of stressful life events to poor relationship outcomes (Murry et al., 2001). To address this issue more completely, we conducted a meta-analytic review of the literature on racial discrimination and relationship outcomes to quantify the relation, evaluate links to distinct relationship outcomes, examine moderator variables, and extend the work beyond African Americans to all minoritized group and beyond romantic relationships to all adult dyadic relationships. We then discuss the findings in terms of the foundational relationship theories presented here.

The Present Study

We undertook a meta-analysis to examine the relation between racial discrimination and a set of relationship outcomes, specifically positive outcomes (e.g., marital satisfaction, relationship quality), negative outcomes (e.g., conflict, strain), and social support. We thought it was important to distinguish between positive and negative relationship outcomes, as there is evidence that the negative aspects of relationships have stronger effects on health than the positive aspects (e.g., Helgeson et al., 2014). We distinguished social support from positive relationship outcomes, such as marital quality and relationship satisfaction, because the latter reflect very general characteristics of a relationship that may be based on behaviors, cognitions and/or feelings, whereas social support references a specific transactional process (i.e., one person provides a resource to another person) that may or may not impact relationship quality. It is also the case that social support reflects a sizeable and distinct literature (Uchino et al., 2018). It is possible that discrimination has differing effects across these three categories of relationship outcomes. Finally, there may be moderator variables that influence the relation of discrimination to relationship outcomes, such as gender or age, as suggested by the Vulnerability-Stress-Adaptation Model (Karney & Bradbury, 1995). Racial discrimination may be more strongly linked to relationship outcomes for men compared to women because men may be less likely than women to share stressful experiences and seek social support (Lindsey & Marcell, 2012). Racial discrimination may be less strongly related to relationship outcomes for older individuals than younger individuals because older individuals may have habituated to discrimination. In fact, one study showed that older adults reported less discrimination than younger adults (Bergeron et al., 2020). To address these questions, we identified articles that examined racial discrimination and one of the three previously mentioned relationship outcomes quantitatively in samples of non-White groups.

Method

Author Positionality

Because we recognize that all of the authors have their own experiences, biases, and perspectives on the world, we feel it is important that we share our identities. Two of us are White, two are Asian, one is Mexican American, and one is biracially Black and White. Three of us identify as female, one as male, and one as nonbinary. Because a major focus of this meta-analysis is race, we acknowledge that our identities may have shaped the literature that we selected to review (including inclusion and exclusion criteria), the moderators that we chose to examine, the way we coded relationship quality, and our interpretation of the data. In an attempt to avoid these kinds of bias, we worked collaboratively to develop the meta-analysis procedures and to consider a variety of data interpretations.

Search Strategy and Study Selection

We conducted searches through PsycINFO, Academic Search Main Edition, Social Sciences Citation Index, and PubMed using a combination of terms assessing racial discrimination, race, and relationship outcomes. Because PsycINFO includes dissertations, we were able to include unpublished work, providing an opportunity to examine publication bias. Additionally, in an attempt to capture unpublished work, we requested articles from researchers in relevant fields via respective mailing lists, but we received no responses. Further details about our search strategy, including our exact search string, are included in the Supplementary Materials. Initial searches were conducted in June 2024 and updated before the meta-analysis was run in February 2025.

Articles were entered into Covidence (Veritas Health Innovation, 2024), a systematic review software, where duplicated articles were removed, yielding 2,403 reports. Two coders (ZK and LM) screened titles and abstracts, with disagreements resolved by consensus meetings that included the last author. Reports were excluded based on the following criteria: (1) the sample was fully under the age of 18 years; (2) the article was not written in English; (3) the source of discrimination was from the relationship of interest (e.g., racial discrimination from a spouse), (4) the relationship outcome was not specific to one person (e.g., social support measured through perceptions of availability in support network); (5) the sample consisted exclusively of White participants. Additionally, the article was only eligible for the meta-analysis if it made clear that the source of discrimination was related to race/ethnicity; thus, articles where the source of discrimination was ambiguous were not included. While the experience of racial discrimination can vary across racial groups, the nature of racial discrimination for White participants is fundamentally distinct from the racial/ethnic discrimination experienced by underrepresented groups. An exception to this criterion was made for White participants in interracial relationships; if the discrimination they faced was specifically due to their interracial relationship, these participants were retained in the sample. When multiple studies reported the same association based on the same sample, only one effect size was retained to avoid duplication. In these cases, we selected the estimate from the study that provided effect sizes that were more precise or more readily convertible to the target Pearson’s r.

As depicted in Figure 1, after abstract and title screening, 114 reports proceeded to full text review. Of these, 40 reports met the eligibility criteria described above, but two were excluded due to insufficient statistics for effect size calculation, and two were excluded due to presenting data from samples we had already collected data from as described above. Thus, the final count of reports was 36.

Data Extraction

The data, codebook, and coding scheme are available at https://osf.io/tdvwj. Two coders (ZK and LH) extracted methodological characteristics, including the racial discrimination measure, timeframe of discrimination recalled, source of racial discrimination, relationship outcome measure, type of relationship outcome (positive, negative, or social support), and design (cross-sectional, longitudinal, or prospective), as well as sample characteristics, including mean age, mean relationship length, relationship type (i.e., married, cohabiting, dating, family, and friend), gender, race/ethnicity, and percentage who achieved college or higher. A list of the studies included in the meta-analysis and their methodological characteristics is shown in Table 1. Inter-rater reliability for each of these variables was good (all AC1’s > .80, except for college percentage: AC1 = 0.45), and disagreements were resolved via consensus meetings.

Table 1.

Summary of Study Characteristics

Article	Article type	Racial discrimination measure	Relationship outcome measure	Sample source	Design	Sample size	Mean age	Female %	Race of sample
Adesogan et al. (2022)	Published	Racism and life experiences scale	Quality of marriage index	Community	Cross-sectional	250	45.12	51.6%	100% Black
Baptist et al. (2019)	Published	Everyday discrimination scale, everyday discrimination scale adapted for couples	Couple satisfaction index, relationship maintenance strategies - openness subscale	Online	Cross-sectional	356	31.86	47.8%	100% Black
Barr et al. (2023)	Published	Modified schedule of racist events	Marital satisfaction and happiness scale (2 items)	Community	Cross-sectional	814	23.5	50%	100% Black
Barton et al. (2018)	Published	Racism and life experiences scale	Quality of marriage index, relationship confidence scale (4 items; Stanley et al., 1994)	Community	Prospective, contemporaneous	297	38.25	50%	100% Black
Brown et al. (2023)	Published	Perceived ethnic discrimination questionnaire	Perceived relationship quality component inventory - satisfaction subscale	College	Cross-sectional, longitudinal, prospective	86	20.69	77%	59.3% Black, 40.7% Latino/a
Caselli and Machia (2022)	Published	Everyday discrimination scale adapted for couples	Investment model scale - commitment subscale, investment model scale - satisfaction subscale, inclusion of the other in the self scale	Online	Experimental	78	34.25	64.4%	100% White
Clavél et al. (2017)	Published	Modified schedule of racist events	Marital satisfaction and happiness scale (2 items), social provisions scale	Community	Cross-sectional, longitudinal	326	39.31	50%	100% Black
Decker (2022)	Dissertation	Perceived ethnic discrimination questionnaire-community version - past week discrimination subscale	Social relationships inventory	Online	Cross-sectional	146	30.54	50%	100% Black
Edmond et al. (2014)	Published	Modified schedule of racist events	Relationship distress scale (4 items; Cui et al., 2005), best friend distress scale (1 item)	Community	Cross-sectional	637	21	56.5%	100% Black
Ferrill (2020)	Dissertation	Index of race-related stress - Brief version	Support in intimate relationships rating scale - revised, positive-negative relationship quality scale - positive subscale	Community	Cross-sectional	203	46	66.7%	100% Black
Galick (2013)	Dissertation	Discrimination scale (10 items; McNeilly et al., 1996)	Relational support scale (15 items), marital stability index (Booth et al., 1983)	Community	Cross-sectional	1164	34.95	50%	100% Black
Genç and Su (2022)	Published	Discrimination scale (6 items; Trail et al., 2012)	Couple satisfaction index	Online	Cross-sectional	356	29.71	50%	100% Black
Grewal (2005)	Dissertation	Index of race-related stress - Brief version	Dyadic adjustment scale	Community	Cross-sectional	28	39	0%	55.6% Black, 11.1% Latino/a, 27.8% Asian
Henderson et al. (2024)	Published	Everyday discrimination scale	Marital support scale (3 items), marital strain scale (4 items)	Community	Cross-sectional	560	64.6	50%	100% Black
Jenkins et al. (2020)	Published	Experiences of discrimination scale	Domains of marriage scale	Community	Cross-sectional, longitudinal, prospective	336	42.16	50%	100% Black
Kelley and Helgeson (2025)	Published	Racial discrimination scale (21 items; Nadal, 2011; Torres-Harding et al., 2012)	Partner support (4-items; Helgeson et al., 2014), negative interactions (4-items; Helgeson et al., 2014), positive emotional responsiveness (4-items; Fekete et al., 2007), negative emotional responsiveness (4-items; Fekete et al., 2007)	Online	Cross-sectional	138	37.5	100%	100% Black
Kerr et al. (2018)	Published	Everyday discrimination scale, racism and life experiences scale	Relationship satisfaction scale (1 item)	Community	Cross-sectional	203	27	0%	100% Black
Killoren et al. (2020)	Published	Global discrimination subscale (5-items; Whitbeck et al., 2001)	Relationship maintenance behaviors scale, marital instability index	Online	Cross-sectional	283	25.37	42.4%	100% Latino/a
Lavner et al. (2018)	Published	Racism and life experiences scale	Quality of marriage index, marital status index - instability subscale	Community	Cross-sectional	688	38.19	50%	100% Black
Lei et al. (2024)	Published	Schedule of racist events	Partner support scale (3-items)	Community	Longitudinal	286	59.29	100%	100% Black
Leslie & Letiecq (2004)	Published	Perceived racial discrimination scale (Krieger, 1990)	Personal relationship scale - love subscale, personal relationship scale - Ambivalence subscale	Community	Cross-sectional	76	36.6	50%	100% Black
McNeil Smith et al. (2020)	Published	Experiences of discrimination scale	Racism specific support scale (1 item)	Community	Cross-sectional	974	39.05	50%	100% Black
McNeil et al. (2014)	Published	Experiences of discrimination scale	Spousal specific support scales	Community	Cross-sectional	974		50%	100% Black
MIDUS Wave 2	Other	Everyday discrimination scale, lifetime discrimination scale	Relationship quality measure (1 item), instability scale (2 items), partner strain scale (6 items), partner support scale (6 items)	Community	Cross-sectional	208	42.96	50.4%	5.3% Black, 94.7% Latino/a
Murdock and Wood (2022)	Published	Everyday discrimination scale	Positive and negative semantic differential questionnaire - positive subscale, positive and negative semantic differential questionnaire - negative subscale, dyadic coping inventory - partner support, dyadic coping inventory - negative	Community	Cross-sectional	90	38.03	74.2%	100% Black
Murry et al. (2008)	Published	Modified schedule of racist events	Marital satisfaction and happiness scale (2 items), marital instability index, relationship warmth scale (Conger & Elder, 1994)	Community	Cross-sectional	361	39	100%	100% Black
Murry et al. (2001)	Published	Modified schedule of racist events	Marital instability index, marital satisfaction and happiness scale (2 items)	Community	Cross-sectional	386	35	100%	100% Black
Ogan et al. (2024)	Published	Global discrimination subscale (5-items; Whitbeck et al., 2001)	Relational uncertainty scale, marital instability index	Online	Cross-sectional	937	25.32	60.2%	100% Latino
Ong et al. (2022)	Published	Racism and life experiences scales - daily life experience	Perceived relationship quality components inventory	Community	Daily diary	196	35.9	50%	100% Black
Perry et al. (2024)	Published	Discrimination scale (4 items)	Relationship commitment scale (4 items; Stanley et al., 2002)	Community	Cross-sectional	480	26.4	50%	100% Black
Riina and McHale (2010)	Published	Experiences of discrimination scale	Relationships questionnaire - conflict subscale	Community	Cross-sectional	312	43.25	50%	100% Black
Sun et al. (2020)	Published	Workplace racial bias scale - institutional discrimination subscale	Relationships questionnaire	Community	Cross-sectional, longitudinal, prospective	328	41.82	50%	100% Black
Takeda (2017)	Dissertation	The subtle and Blatant racism scale for Asian americans, LGBT people of color microaggression scale - racism in LGBTQ communities	MSPSS - subscale for mother, MSPSS - subscale for father, MSPSS - subscale for significant other	Online	Cross-sectional	442	27.84	46.3%	100% Asian
Weber et al. (2024)	Published	Schedule of racist events	Couple satisfaction index, commitment inventory (4 items; Stanley & Markman, 1992), partner support scale (3 items; Surjadi et al., 2011)	Community	Cross-sectional, longitudinal, prospective	93	24.1	100%	100% Black
Williams and Baptist (2023)	Published	Everyday discrimination scale adapted for couples	Communication danger signs scale, couple satisfaction index, relationship maintenance strategies - openness subscale	Online	Cross-sectional	420	31.69	50%	100% Black
Williamson (2011)	Dissertation	Perceived racism scale - public realm subscale	Investment model scale - commitment subscale, actual perceived partner responsiveness scale (3 items; Reis et al., 2018), perceived relationship quality component inventory - intimacy subscale	Online	Cross-sectional	104	31.55	56.7%	100% Black

Three coders (ZK, PL, and LH) extracted sample size and relevant statistics, with Pearson’s correlation (r) as the target effect size. The exception is when only regression analyses were available, for which we extracted the number of predictors and the regression coefficients, which were transformed into partial r. Effect sizes for negative relationship outcomes were reverse coded, so that across relationship outcomes, a positive association meant racial discrimination was associated with better relationship outcomes, and a negative association meant racial discrimination was associated with worse relationship outcomes. Inter-rater reliability for effect size extraction also was good (all AC1’s > .80), and disagreements were resolved via consensus meetings.

Finally, two coders (MT and VH) independently assessed study quality using a 9-item coding scheme (see Supplementary Materials) covering three domains: quality of the discrimination measurement (susceptibility to recall bias, validity, reliability), quality of relationship outcome measurement (susceptibility to recall bias, validity, reliability), whether the discrimination and relationship measure were confounded in some way (i.e., relationship outcome was about feeling supported in the context of discrimination), and soundness of the design/analytical approach (representativeness of sample, sample size justification). Study quality coding is the only situation in which we did not calculate inter-rater reliability because discrepancies were resolved by deferring to the rater with the greater expertise (MT is experienced in the discrimination literature, and VH is experienced in the relationships literature). Thus, disagreements were resolved via consensus meetings, where measurement decisions were deferred to the author who had the requisite expertise.

The following variables were examined as moderators of the link of discrimination on outcomes: proportion of women in the sample, mean age, study quality, year of publication, sample source (online vs. community), design (prospective vs. cross-sectional), mean relationship length, mean education, and proportion of married participants. Because the only race that was widely represented across studies was African American, we examined race by calculating the proportion of participants who were African American. As it turned out, African Americans either comprised the entire sample (100%) or a very small proportion of the sample (5.3% or less) with the exception of two studies that included 59.3% and 55.6% African American. For analytic purposes, we examined race moderation by creating a dichotomous variable—low (0-5.3%) vs. high (100%)—excluding the two studies with proportions that fell between the extremes. We intended to examine nature of relationship as a moderator, but 93% of the effect sizes were based on romantic partners. Thus, there were too few other kinds of partners to examine this variable as a moderator.

Analytic Approach

All of the analyses were pre-registered: https://osf.io/2m394. Following conventions (Borenstein et al., 2009), Pearson’s r was converted into Fisher’s Z for analyses, and results were then transformed back to Pearson’s r for interpretation. Some studies (n = 25, 74%) included multiple relevant discrimination measures (e.g., Everyday Discrimination Scale and Racism and Life Experiences Scale) and/or relationship outcomes (e.g., Quality of Marriage Index and Marriage Instability Scale), resulting in multiple effect sizes per study, which violates the independence assumption of traditional random effects models. Following best-practice recommendations, we conducted random effects models with robust variance estimation to account for within-study dependencies (Tipton, 2015; Tipton et al., 2023; Tipton & Pustejovsky, 2015). In addition, we also applied small-sample corrections to control for Type 1 error rates, such that unreliable results, defined as the Satterthwaite degrees of freedom (df) below 4, were not interpreted (Tipton, 2015).

Furthermore, when raw effect sizes were not reported, we extracted adjusted effect sizes (i.e., derived from models that included additional predictors such as age), resulting in a minority of adjusted effect sizes (k = 30, 19%). Preliminary analyses showed no significant difference in magnitude (b = −.02, SE = .04, p = .567) or heterogeneity, based on overlapping 95% confidence intervals of τ² (raw: [.0079, .0219]; adjusted: [.0017, .0247]). Accordingly, adjusted and raw effect sizes were pooled in analyses, with effect size type (adjusted vs. raw) included as a binary covariate (Aloe et al., 2016).

Analyses were conducted in two phases. First, we estimated the overall effect size for the association between discrimination and relationship outcomes, along with heterogeneity statistics (I² and τ²). We then conducted two sets of sensitivity analyses: (1) We computed the estimated overall effect size when additionally accounting for study quality; (2) We examined whether estimates were robust to influential outliers (defined by significantly large studentized deleted residuals) and publication bias using the precision-effect test (PET; effect size’s precision as a moderator; published vs. non-published (i.e., dissertations, public data) studies as a moderator). In the second phase, we conducted moderator analyses to test whether the association between discrimination and relationship outcome differed by the extracted methodological and sample characteristics described above. Moderators were tested in separate models, and sensitivity analyses repeated moderator analyses controlling for study quality. All analyses were conducted using R packages robumeta (Fisher & Tipton, 2015) and metafor (Viechtbauer, 2010).

Results

Overall Association Between Racial Discrimination and Relationship Outcomes

There was a small overall association between racial discrimination and poorer relationship outcomes (r = −.095, 95% CI [−.141, −.049], p = .002) while accounting for whether effect sizes were raw or adjusted (b = −.061, 95% CI [−.154, .033], p = .175). Furthermore, substantial heterogeneity was observed. I², a relative measure of heterogeneity, suggested that 80.84% of the total variance was attributable to between-study differences, whereas τ², an absolute estimate of heterogeneity, was estimated at .018, corresponding to a standard deviation (τ) of .13 in true effect sizes on the Pearson’s r scale.

Outcome-Specific Analyses

Subgroup analyses were conducted for the three categories of relationship outcomes (i.e., negative, positive, and social support). Racial discrimination was associated with lower positive outcomes (r = −.113, 95% CI [−.172, −.052], p = .005) and higher negative relationship outcomes (r = −.146, 95% CI [−.250, −.039], p = .024), but racial discrimination was not related to social support outcomes (r = .012, 95% CI [−.361, .382], p = .850). These relations are shown in Figures 2 –4. Differences across outcome types were formally tested by examining type of outcome as a moderator. As shown in Figure 6(A), effect sizes for social support (reference) differed significantly from those of positive outcomes (b = −.154, 95% CI [−.218, −.090], p < .001) and negative outcomes (b = −.251, 95% CI [−.346, −.157], p < .001). Specifically, discrimination was most strongly related to greater negative outcomes (predicted r = −.205), was modestly related to less positive outcomes (predicted r = −.108), and was not related to social support (predicted r = .046).

Sensitivity Analyses

We conducted a series of sensitivity analyses to evaluate the robustness of the synthesized association. First, the association was recomputed controlling for study quality. The overall association remained significant (r = −.109, 95% CI [−.168, −.050], p = .003), suggesting this result is not driven by lower quality methodology. Second, we assessed whether this association was robust to influential outliers and publication bias. After removing influential outliers (n = 5), the overall association remained significant (r = −.095, 95% CI [−.139, −.050], p = .001). Third, we evaluated potential publication bias. A funnel plot displaying effect sizes plotted against their precision is shown in Figure 5. A small degree of asymmetry was observed: there were fewer small-sample studies showing negative effect sizes and fewer large-sample studies showing positive effect sizes. Nonetheless, PET indicated that precision was not a significant predictor of effect size magnitude (b = .241, 95% CI [−1.385, 1.867], p = .752). Additionally, an effect-coded predictor assessing published vs. non-published literature indicated that publication status was not a significant predictor of the effect size (b = .071, 95% CI [−0.068, 0.210], p = .269). Thus, neither test yielded a significant result, suggesting a lack of strong evidence for publication bias.

Furthermore, we conducted these sensitivity analyses on the three outcome subgroup analyses, and the aforementioned results were unaffected. After controlling for study quality, relationship outcome remained a significant moderator (social support versus positive: b = −.145, 95% CI [−.211, −.078], p < .001; social support versus negative: b = −.238, 95% CI [−.324, −.151], p < .001; positive versus negative: b = −.097, 95% CI [−.178, −.017], p = .020).

Moderator Analyses by Methodological and Sample Characteristics

Due to an insufficient number of studies examining moderators within the three outcomes, we examined how the overall association between racial discrimination and relationship outcomes differed by methodological and sample characteristics of studies. As a few studies utilized the same sample, demographic and methodological characteristics are summarized in Table 2 by study and by sample, and individual moderator analyses are summarized in Table 3. Study quality significantly moderated the relation between racial discrimination and relationship outcomes (b = −.019, 95% CI [−0.037, −0.0003], p = .047), such that the association was more negative in higher quality studies (1 SD above the mean; r = −.224, 95% CI [−.049, −.410]), but was not significant in lower quality studies (1 SD below the mean; r = −.155, 95% CI [−.318, .016]). This moderation is shown in Figure 6(B). There was no moderation by published year of study (b = .0002, 95% CI [−.007, .007], p = .956) or sample source (community vs. online; b = −.091, 95% CI [−.218, .035], p = .147).

Table 2.

Mean (SD) and Frequency (%) of Demographic and Methodological Characteristics by Sample and Study

		Sample	Study
Age		36.1 (10.3)	36.6 (10.2)
Relationship length		9.3 (6.5)	9.0 (6.2)
Year		2018.3 (5.8)	2017.6 (5.8)
Relationship type	Positive	67 (59.3%)	42 (56%)
	Negative	25 (22.1%)	17 (22.7%)
	Social support	21 (18.6%)	16 (21.3%)
Design	Cross-sectional	98 (86.7)	52 (74.3%)
	Longitudinal	11 (9.7%)	10 (14.3%)
	Prospective	10 (9.6%)	5 (7.1%)
	Daily diary	2 (1.8%)	2 (2.9%)
	Contemporaneous	2 (1.8%)	1 (1.4%)
Sample source	Community	77 (68.1%)	39 (69.6%)
	Online	32 (28.3%)	15 (26.8%)
	College	4 (3.5%)	2 (3.6%)
Gender Breakdown	Wholly female	35 (31.0%)	19 (33.9%)
	Wholly male	22 (19.5%)	16 (28.6%)
	Heterogeneous	56 (49.6%)	21 (37.5%)
Race Breakdown	Wholly Black	85 (75.2%)	46 (82.1%)
	Wholly Asian	6 (5.3%)	1 (1.8%)
	Wholly Latino	4 (3.5%)	3 (5.4%)
	Heterogeneous	18 (15.9%)	6 (10.7%)

Table 3.

Meta-Regression by Study Characteristics (Moderator Variables)

	b	CI	p
Study quality	−.019	−.037, −.0003	.047
Published year	.0002	−.007, .007	.956
Sample source
Intercept	−.075	−.114, −.035	.001
Online (vs. Community)	−.091	−.218, .035	.147
Design
Intercept	−.130	−.194, −.067	.006
Prospective (vs. Cross-sectional)	.167	.058, .276	.009
Mean age	.003	−.0003, .006	.068
Mean relationship length	−.079	.196, .037	.142
Mean education	−.001	−.006, .005	.837
Proportion of married participants	−.027	−.117, .062	.538
Proportion of female participants
Intercept	−.118	−.182, −.055	.002
Moderate (vs. Low)	.049	−.032, 129	.129
High (vs. Low)	.020	−.087, .126	.127
Proportion of Black participants
Intercept	−.264	−.418, −.110	.005
High (vs. Low)	.177	.021, .332	.032
Relationship outcomes
Intercept	.046	−.021, .113	.162
Positive (vs. Social support)	−.154	−.218, −.090	<.001
Negative (vs. Social support)	−.251	−.346, −.157	<.001

Note. Individual moderator analyses were conducted for each variable. Continuous variables were mean-centered, and categorical variables were dummy-coded with the reference group in parentheses.

Next, we tested study design (cross-sectional vs. prospective) as a moderator. Because all prospective studies in this meta-analysis only included positive outcomes, we limited the test of this moderator to studies that examined positive relationship outcomes. Study design was a significant moderator (b = .167, 95% CI [.058, .276], p = .009), such that there was a negative association for cross-sectional studies (predicted r = −.047), but there was no association for prospective studies (predicted r = .037), shown in Figure 6(C). After controlling for study quality, study design remained a significant moderator for the positive relationship outcome studies (cross-sectional vs. prospective; b = .152, 95% CI [.035, .270], p = .018).

We then examined how the association between racial discrimination and relationship outcomes differed by sample characteristics. There was no moderation by mean age of sample (b = .003, 95% CI [−.0003, .006], p = .068), mean relationship length of sample (b = −.079, 95% CI [−.196, .037], p = .142), mean education of sample (b = −.0006, 95% CI [−.006, .005], p = .837), proportion of married participants in sample (b = −.027, 95% CI [−.117, .062], p = .538), or proportion of females in sample (categorized as low [<25%], medium [25–75%], and high [>75%]; low vs. medium: b =. 020, 95% CI [−.087, . 126], p = .707; low vs. high: b = .049, 95% CI [−.032, .129], p = .224); medium vs. high: b = .029, 95% CI [−.070, .128], p = .556). However, as shown in Figure 6(D), there was moderation by sample’s proportion of Black participants (low [0% to 5.3%] vs. high [100%]; b = .177, 95% CI [.021, .332], p = .032). The association between racial discrimination and relationship outcomes was stronger when there was a low proportion of Black participants (predicted r = −.258, 95% CI [−.109, −.396, p = .002) but weaker (yet still significant) when the sample was composed of entirely Black participants (predicted r = −.087, 95% CI [−.043, 0.131, p = .001). After controlling for study quality, proportion of Black participants remained a significant moderator (b = .148, 95% CI [.005, .291], p = .043).

Discussion

The goal of the present study was to examine the relation between racial discrimination and relationship outcomes. We found that racial discrimination is related to worse relationship outcomes. This finding is consistent with the Family Stress Model (Conger et al., 1990) as well as stress spillover theory—the idea that external stress depletes self-regulatory resources, which causes that stress to spill over into the relationship, leading to negative relationship outcomes (Buck & Neff, 2012).

This finding is particularly troublesome because racial discrimination is a stressor that negatively impacts the health of racially minoritized individuals (Carter et al., 2017), and relationships are ordinarily considered to be resources that people can use to combat stressful events. Instead of relationships buffering the negative impact of racial discrimination on health, these relationships might serve to exacerbate the effect of racial discrimination on health—or at least not be as strong of a buffer as possible. Alternatively, relationships might be a pathway by which racial discrimination adversely affects health.

The results suggest three directions for future research. First, researchers should conduct experimental studies to ensure that it is racial discrimination that is adversely affecting relationships, as the majority of research in this area is correlational and cross-sectional. The fact that the few prospective studies in this area did not observe a relation makes this future direction particularly imperative.

Second, to the extent a causal relation does exist, researchers should explicate the process by which discrimination adversely affects relationships. Is stress spillover the explanation? Are people who face racial discrimination feeling depleted such that they cannot serve to be suitable resources for their loved ones? One of the studies included in this review showed that perceived stress partly explained the link between discrimination and poor relationship quality (Kerr et al., 2018). Both the Family Stress Model and the Vulnerability-Stress-Adaptation Model emphasize the role of social interactions in the connection between stress and relationship outcomes (Conger et al., 1990; Karney & Bradbury, 1995). Discrimination may reduce the frequency of warm interactions and increase hostile and angry interactions (Rice et al., 2023). Rather than drawing couple members closer together, discrimination may lead to a focus on the self and managing one’s own affect. There could be an affective pathway, such that experiencing discrimination leads to negative affect (either anger or sadness), which then inspires relationship conflict. One study showed that dysregulation of emotions and inflammation explained the link of discrimination to relationship strain (Doyle & Molix, 2014). However, the cross-sectional nature of that study makes it unclear whether these variables are mediators of the link between discrimination and relationship strain or potential outcomes from relationship strain.

Other future directions include intervention work that aims to equip racially minoritized individuals and couples with coping skills that enable them to use their relationship as a resource rather than a hindrance. Finally, researchers should recognize that it is not only personal experiences of discrimination that may affect relationships, but that structural discrimination affects the availability of relationship partners and the economic resources to maintain relationships (Kerr et al., 2018).

All of these future research directions should take note that racial discrimination was more strongly linked to negative relationship outcomes than positive relationship outcomes or social support. Thus, racial discrimination may be more likely to lead to conflict in relationships and hostile interactions than to undermine support exchanges or relationship quality. Consistent with stress spillover theory (Buck & Neff, 2012), discrimination may lead to a depletion of self-regulatory resources, which then leads one to engage in negative behavior toward the partner or to interpret the partner’s neutral behavior in a negative way. If that is the case, interventions attempting to ameliorate the effect of racial discrimination on relationships should focus on reducing the strain brought on by racial discrimination as opposed to increasing or maintaining support in the face of racial discrimination. It is also worth noting that effects were stronger for the general positive relationship outcomes than the specific construct of social support. This finding may reflect the fact that positive relationship outcomes are general perceptions and broad constructs that are likely affected by many factors, which can include conflict and difficulties, whereas social support is typically linked to specific behaviors. The null effect for support could be due to the combination of discrimination increasing some supportive behaviors and undermining others. With additional research in this area, other moderators of the effect of discrimination on support could be detected.

Additionally, we found that several methodological factors affected the relation between racial discrimination and relationship outcomes—specifically, study quality, study design, and the proportion of Black participants. The relation between racial discrimination and relationship outcomes was stronger among studies that had a higher study quality, increasing our confidence in the overall finding. The primary contributors to study quality had to do with the validity and reliability of the racial discrimination and relationship outcome measures. This finding shows how important it is for researchers to use well-established, reliable measures instead of developing their own measures or drastically modifying existing measures. The study quality measure also included how representative of the population the sample was. Thus, we emphasize the need to conduct high-quality research on this topic, as low-quality research may not capture how racial discrimination impacts the lives of racially minoritized individuals.

We also found that study design moderated the association between racial discrimination and relationship outcomes, such that the few studies with a prospective design did not find a significant association. There are a couple of explanations for this finding. First, it may be that the impact of racial discrimination on relationship outcomes diminishes over time. Individuals could cope with racial discrimination in a way that allows them to overcome negative effects on relationships. Second, only five studies provided data to examine racial discrimination and relationship outcomes prospectively, so the conclusions we draw are limited. Two of the studies examined racial discrimination and relationship outcomes 6–8 weeks later, whereas the other three examined the association 9–12 months later. Yet, all five studies found non-significant prospective associations, so time elapsed since the discrimination event—whether weeks or months—did not appear to affect the relation. The effect of racial discrimination on relationship outcomes may be more immediate, potentially fading within days or even hours. An ecological momentary assessment design or daily diary design might shed light on this issue. Only one such daily diary study has been conducted and is included in this meta-analysis: Ong et al. (2022) found that although there was no direct correlation between racial discrimination and relationship quality, partner’s negative affect reactivity to daily racial discrimination was related to worsened relationship quality for the individual. Finally, it is important to point out that there is a methodological confound with the prospective studies. All of the prospective studies only examined positive relationship outcomes—the set of outcomes for which the overall relation was smaller. In sum, the current literature does not allow us to be conclusive about the impact of study design on the link of discrimination to relationship outcomes. Future prospective studies that measure a variety of relationship outcomes and that vary in length of follow-up are needed to shed light on this issue.

The racial composition of the sample also moderated the association between racial discrimination and relationship outcomes, such that studies that included only a small proportion of Black participants found a stronger association than studies that consisted of all Black participants. However, this finding is qualified by the fact that this comparison is between studies that have very few Black participants to studies that have 100% Black participants, so we do not know the results of studies that had a more varied racial composition. The weaker finding for the Black only samples suggests that the relationships of Black people may be more resilient to the effects of discrimination compared to the relationships of other racial minorities. In the United States, Black people have a long history of facing discrimination, which may have led them to bond together as a group in a way that enables them to use their relationships more effectively in the context of discrimination. There is evidence that African Americans and Afro-Caribbeans face more racial discrimination in the United States than other ethnic minority groups (Ayalon & Gum, 2011; Gong et al., 2017). However, there is also some evidence that the link of discriminatory experiences to health may be weaker for African Americans than other groups (Ayalon & Gum, 2011; Bergeron et al., 2020). African Americans may have habituated to the effects of discrimination or have greater social and cultural resources at their disposal to buffer the effects of discrimination (Ayalon & Gum, 2011). Compared to Latino/a and Asian samples, African Americans and Afro-Caribbeans have the strongest ethnic-racial identity (Gong et al., 2017), which has been shown to bolster self-esteem (Sellers et al., 1998) and could buffer against experiences with racial discrimination. That is, African Americans may have a form of cultural resilience or ethnic-racial socialization in which people learn about their racial and/or ethnic group and how to cope with discrimination (Anderson & Stevenson, 2019; Neblett, 2023). Prior work has found that Black and African American families engage in the highest rates of this kind of socialization to contend with bias by emphasizing cultural heritage as a form of strength upon which they can rely (Hall et al., 2025).

Relationship partners in the Black community may also be more understanding of the stress that racial discrimination causes (Rice et al., 2023). However, there are drawbacks to this shared cultural understanding. A shared cultural understanding helps to foster communication and promote empathy, but it also leads to the distress associated with knowing relationship partners are subject to their own experiences of discrimination (Awosan & Hardy, 2017). Importantly, there was still a significant association between discrimination and relationship outcomes even among samples with a high proportion of Black participants, so we do not want to conclude that racial discrimination does not affect the relationships of Black people. It is important for future work to experimentally test whether race alters the effect of discrimination on relationship outcomes and to include samples that have varied and sufficient representations of multiple racial groups rather than rely on correlational work that is skewed in its representation of race.

Before concluding, we note several limitations of this meta-analysis. First, the literature on this topic is not large. Second, our moderation by race/ethnicity was based on study-level comparisons; yet, race is an individual-level variable, and a more rigorous test would involve recruiting individuals from diverse racial backgrounds to formally examine whether the link between discrimination and relationship outcomes differs across groups. Third, it is important to note that the overall effect size was small, and there were a number of moderator variables. Thus, future research should be conducted to identify the specific groups or specific conditions under which racial discrimination is most likely to have a negative impact on relationships. Fourth, studies in this meta-analysis generally did not control for general stress to isolate the unique effects of racial discrimination on relationship outcomes. While there is evidence to suggest that the association between racial discrimination and relationship outcomes persists after controlling for general stress and financial stress (e.g., Kerr et al., 2018), the practice of controlling for other stressors was uncommon in the articles included in this review. Finally, none of the studies included in this meta-analysis were experimental, and the majority were correlational. Thus, we cannot infer causality from this body of work. While it makes more intuitive sense that racial discrimination would affect relationships than that relationships would affect discrimination, there is the potential for third variables such as negative affect to influence the association between discrimination and poor relationship outcomes. Additional longitudinal work is needed in this area. Intensive longitudinal designs would enable a more fine-grained analysis of the causal directions between discriminatory experiences and relationship outcomes.

Despite these limitations, there were a number of strengths associated with this meta-analysis. We were able to examine the association of racial discrimination to specific kinds of relationship outcomes and to focus specifically on race and ethnicity. In addition, we were able to leverage recent advances in meta-analytic statistical modeling to include multiple effect sizes from a study, rather than choosing to extract a single effect size or averaging effect sizes, which allowed for the retention of heterogeneity for moderator analysis. It is also important to note that we included unpublished studies in this review.

In conclusion, we found a small but significant association between racial discrimination and poorer relationship outcomes. This association highlights the need to take the relationships of racially minoritized individuals into account when studying population health inequality. Although relationships may be a resource in ameliorating the negative health effects of racial discrimination, if racial discrimination is negatively impacting the relationship, the relationship cannot be utilized as a resource to its fullest capacity. Ultimately, more research must be conducted on this association to understand the mechanisms that explain the relation and the conditions that exacerbate and ameliorate the relation.

Supplemental Material

Supplemental Material - Racial Discrimination and Relationship Outcomes: A Meta-Analysis

Supplemental Material for Racial Discrimination and Relationship Outcomes: A Meta-Analysis by Zane Kelley, Phoebe H. Lam, Letian Huang, Michael A. Trujillo, Lilly McLeod, Vicki S. Helgeson in Journal of Social and Personal Relationships

Footnotes

Acknowledgements

We would like to thank Dr. Susanne Ferber for her comments on a previous version of this manuscript.

ORCID iDs

Zane Kelley

Phoebe H. Lam

Letian Huang

Michael A. Trujillo

Lilly McLeod

Vicki S. Helgeson

Ethical Considerations

Ethical approval was not required for this research.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was funded by a Dietrich Honors Fellowship provided by the Dietrich College of Humanities and Social Sciences at Carnegie Mellon University. This research was also funded by the Ireland Award provided by the George and Elisabeth Ireland family through the Carnegie Mellon University Department of Psychology.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data and accompanying files are available at .

Open Science Statement

As part of IARR’s encouragement of open research practices, the authors have provided the following information: This research was pre-registered. The aspects of the research that were pre-registered were statistics extraction, study quality coding, and data analysis. The registration was submitted to: https://osf.io/2m394/. The data used in the research can be publicly posted. The data can be obtained at: . The materials used in the research can be publicly posted. The materials can be obtained at https://osf.io/tdvwj.

Supplemental Material

Supplemental material for this article is available online.

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