Abstract Path analysis was used to assess direct and mediating relationships of an a priori mediation model. Data were collected from 210 black, Hispanic/Latino, and Asian undergraduate college students. Authors found that microaggression was positively associated with ethnic identity. Microaggression had a significant positive association with psychological distress but no other direct relationships with the outcome variables. Ethnic identity was negatively associated with psychological distress but positively associated with self-esteem and academic self-efficacy. A positive effect was found between ethnic identity and substance abuse. Ethnic identity mediated the effect of microaggression on psychological distress. Moreover, including ethnic identity in the equation revealed that microaggression has a positive effect on self-esteem and academic self-efficacy through participants’ reported degree of ethnic identity. The results suggest that racial microaggressions have damaging impacts on the emotional health of racial and ethnic minority young adults. However, microaggressive experiences may also elicit stronger ethnic identity, which appears to serve as a protective factor to the negative influence of microaggression on psychological well-being. Post hoc exploratory multigroup analysis revealed some differential findings for each group. The article concludes with a discussion of the implications for social work practice, education, and research. Young adults who enroll in college often become exposed to increased and different racial and ethnic diversity than they were previously accustomed to, which is likely to stimulate growth in ethnic identity (Brittian et al., 2015). Unfortunately, numerous research investigations have found that racial and ethnic minority college students tend to report that they experience racial discrimination (Hwang & Goto, 2008; Solorzano, Ceja, & Yosso, 2000; Utsey, Ponterotto, Reynolds, & Cancelli, 2000). In addition, there is substantial evidence demonstrating inverse relationships between racial discrimination and indicators of emotional well-being (Chen, Szalacha, & Menon, 2014; Hwang & Goto, 2008; Utsey et al., 2000) and behavioral health (Borrell, Jacobs, Williams, Pletcher, & Houston, 2007; Gibbons et al., 2012; Park, Schwartz, Lee, Kim, & Rodriguez, 2013). Although exposure to racial discrimination has been established as a causal factor for negative outcomes of behavioral and emotional well-being among people from racial and ethnic minority groups (Pascoe & Smart Richman, 2009; Pieterse, Todd, Neville, & Carter, 2012), much less is understood about the processes and dynamics by which the impacts occur, or the specific forms of racial discrimination involved (Pascoe & Smart Richman, 2009; Williams & Mohammed, 2009). There is a critical need for research that elucidates the mechanisms by which racial discrimination contributes to compromised psychological well-being among racial and ethnic minority young adults. It is hard to imagine a social work role that would not be better equipped to serve vulnerable populations by understanding how racial discrimination influences behavioral and emotional health, and what factors could promote resilience and interrupt those processes. Furthermore, this issue is a matter of public health and social justice and aligns with the social work grand challenge to eradicate health inequities set forth by the American Academy of Social Work and Social Welfare (Walters et al., 2016). Many experts agree that racial microaggression may be a particularly harmful form of discrimination due to the complex and stressful dynamics involved (Noh, Kaspar, & Wickrama, 2007; Sue et al., 2007). Conversely, there is considerable evidence that ethnic identity tends to have strong positive relationships with indicators of health and well-being. In fact, research has found that ethnic identity often plays a protective role against impacts of discrimination (Brittian et al., 2015; Pascoe & Smart Richman, 2009). However, the research is inconclusive about the nature of the relationship between racial discrimination and ethnic identity (Branscombe, Schmitt, & Harvey, 1999; Sellers & Shelton, 2003), and whether or not ethnic identity is a protective factor against the impacts of racial discrimination on indicators of psychological well-being (Brittian et al., 2015; Pascoe & Smart Richman, 2009). In addition, little research specifically measured the relationship between discrimination in the form of microaggression and indicators of well-being such as psychological distress, self-esteem, self-efficacy, and substance abuse, and very little research has been conducted to examine ethnic identity in the pathway between microaggression and these indicators. Furthermore, since every racial and ethnic group in the United States has unique qualities and histories of oppression, there might be variations in the mechanisms involved in how perceived discrimination influences psychological well-being (Brittian et al., 2015). We used cross-sectional data from a sample of 210 racial and ethnic minority undergraduate college students to examine the extent to which racial discrimination in the form of microaggression, and ethnic identity, predict participants’ psychological distress, self-esteem, academic self-efficacy, and substance abuse. Moreover, indirect effects of ethnic identity on the influence that experiences of racial microaggression had on psychological well-being were also assessed. In addition, we explored the relationships among the variables in each of the three racial and ethnic groups in the sample: Asian, Latino/Hispanic, and black. Racial and Ethnic Microaggression A paradox exists in the United States between social norms of racial equality and justice and the persistence of racism and discrimination. In other words, even though most people express that they are opposed to racism, and racial discrimination is prohibited by law, racial discrimination and inequities persist across all major social institutions (Wise, 2013). To illustrate, racial and ethnic minority groups are disproportionately represented in official indicators of poverty (DeNavas-Walt & Proctor, 2014), and racial disparities are found in housing, lending, and residential segregation (Shapiro, Meschede, & Osoro, 2013); employment (A. B. Smith, Craver, & Turner, 2011); education (Gregory, Skiba, & Noguera, 2010); health care (Pascoe & Smart Richman, 2009; Smedley & Smedley, 2005); and the criminal justice system (Stevenson, 2011). Racism in the United States can be defined as the system of oppression that categorizes people into groups based on skin color and stratifies the groups in a hierarchy according to an ideology of inferiority such that white people at the top are afforded preference and privilege and everyone else assumes reduced status (Bonilla-Silva, 1996). The concept of race operates as though it is based on biological differences. However, race in modern U.S. culture is socially constructed according to skin color; in reality there is very little biological difference that distinguishes one racial group from another. In fact, each racial group represents a conglomeration of numerous ethnic backgrounds. For example, consider that the racial categories of “Hispanic/Latino” or “Asian” refer to numerous different ethnic backgrounds as well as a range of extent of acculturation into U.S. culture. Racial discrimination can be understood as the unequal and unfair restriction by judgment or action of people due to their race (Krieger, 1999). In effect, racism is perpetuated and reinforced through racial discrimination. Ahmed, Mohammed, and Williams (2007) explained that racial discrimination functions at many levels. It is institutionalized such that racial and ethnic minority groups are more likely to live in poverty and residential environments that present exposure to risk factors for compromised health and well-being. Racial discrimination occurs systemically such that people from racial and ethnic minority groups have reduced access to resources like affordable housing and health care. In addition, racial discrimination occurs at the individual level where people are recipients of racist attitudes and discriminatory behaviors. Sometimes racial discrimination occurs as major traumatic events that are violent or aggressive and relay overt messages of hatred. In modern culture, however, racial discrimination is more likely to occur as small acts of discrimination called racial microaggressions. The term “racial microaggressions” was first coined by psychiatrist Chester Pierce in 1970 to refer to insults and slights containing negative stereotypes that are frequently experienced by people from racial and ethnic minority groups in their everyday lives. Microaggression may occur through interpersonal exchanges or through environmental messages (Sue et al., 2007). Although microaggressions may be manifested by verbal or physical actions intended to inflict harm (Sue et al., 2007), much of the time they occur as subtle insults toward people of color that are automatic, nonverbal, and unintended in nature (Solorzano et al., 2000; Sue et al., 2007). Experts have noted that these subtle occurrences of discrimination are harder to interpret, creating situations in which recipients are confused about the intent and how to best respond. The complexity of the dynamics involved may cause more psychological distress than blatant forms of discrimination (Noh et al., 2007; Sue, 2010). Perceived Racial and Ethnic Discrimination and Psychological Well-Being There is unequivocal evidence that racial discrimination plays a significant role as a determinant of psychological well-being on people of color in the United States (Paradies, 2006; Williams & Mohammed, 2009). For example, a review of research from population studies found that discrimination consistently was associated with detrimental mental health indicators including increased depression and anxiety and lower happiness, life satisfaction, and self-esteem (Williams, Neighbors, & Jackson, 2003). Substance use has also been found to be affected by experiences of perceived discrimination (Borrell et al., 2007; Gibbons, Gerrard, Cleveland, Wills, & Brody, 2004). In addition, negative association to belief in one’s academic competence has also been substantiated (Wong, Eccles, & Sameroff, 2003). The negative influence of racial discrimination on psychological well-being has been demonstrated across samples of various racial and ethnic groups and appears to have similar effects across groups (Chou, Asnaani, & Hofmann, 2012; Pascoe & Smart Richman, 2009). Ethnic Identity and Psychological Well-Being Ethnic identity is defined as the part of an individual’s self-concept that comes from membership in a social group (or groups) combined with the value and emotional significance attached to that membership (Phinney, 1990; Tajfel, 1981). An individual’s ethnic identity develops over the life course. Adolescence usually marks the most intensive period of ethnic identity development, but growth often continues into young adulthood and beyond (Phinney & Ong, 2007). The formation of ethnic identity has been described as a complex process that involves an ongoing exchange between the internal view one has of oneself with the external perceptions others possess based on race and ethnicity (Nagel, 1994). Phinney and Ong (2007) explained that ethnic identity is achieved over time through a complex process involving an interaction between exposure to experiences and various choices and actions made by individuals. The conceptualization of ethnic identity is complex and involves many dimensions. For example, self-categorization, or identifying with a particular group or groups, in itself is one facet of the concept. Perhaps the most important dimensions of ethnic identity involve affective qualities, or the sense of belonging people have toward their ethnic groups, including aspects like the extent to which a person feels attachment, pride, and commitment associated with that identification. Also important, however, are the active processes people take to explore their ethnic identities and participate in ethnic-oriented events, such as reading information about ethnicity relevant to them, seeking experiences with people from specific ethnic groups, and participating in cultural rituals. Ethnic identity has been consistently found to be important to people across all ethnic groups (Phinney, 1992). A substantial body of research demonstrates a positive relationship between ethnic identity and psychological well-being in samples of adolescents and young adults (T. B. Smith & Silva, 2011). Nagel (1994) asserted that ethnic identity is somewhat fluid, a construction of the specific social context, and thus varies depending on the situation. People often choose which part of their identity to present or which label to ascribe themselves based on what seems most favorable to them in the particular moment, combined with the categories available in that particular moment (Nagel, 1994). It is interesting to consider from this perspective how ethnic identity might also be influenced by experiences of racial discrimination. Many scholars have suggested that ethnic identity functions as a protective factor that enables individuals to be resilient in response to discrimination (Brittian et al., 2015; Umaña-Taylor & Updegraff, 2007). In other words, due to the strong positive influence ethnic identity has on psychological well-being, it is likely that higher levels of ethnic identity might reduce the negative impacts of racial discrimination on psychological well-being. A substantial body of research has investigated the potential protective role of ethnic identity as a moderating, or buffering, influence on the relationship between discrimination and psychological well-being. The findings have been mixed. Pascoe and Smart Richman (2009) reported findings from a systematic analysis of studies on the impacts of racial discrimination on health showing that the buffering effect was not substantiated in 71% of the effects of this relationship. However, the study also revealed that 18% of the analyses found a positive buffering effect such that ethnic identity was related to a decreased impact of perceived discrimination on negative indicators of psychological well-being including depressive symptomatology (Jones, Cross, & DeFour, 2007; Lee, 2005; Mossakowski, 2003), well-being (Lee, 2003, 2005), self-esteem (Romero & Roberts, 2003), and perceived stress (Sellers, Caldwell, Schmeelk-Cone, & Zimmerman, 2003). To confuse matters even further, 12% of the analyses found that higher levels of ethnic identity led to more negative impacts in the relationship between racial discrimination and mental health including self-esteem (McCoy & Major, 2003), well-being (Sellers, Copeland-Linder, Martin, & Lewis, 2006), perceived stress (Sellers et al., 2006), and depression (McCoy & Major, 2003; Noh, Beiser, Kaspar, Hou, & Rummens, 1999; Sellers et al., 2006). These mixed findings point to the importance of continued efforts to better explain the relationships among these variables. A much smaller number of research investigations have modeled ethnic identity’s potential protective effect as a mediating variable instead and found that perceived discrimination had indirect positive relationships with favorable impacts to psychological indicators (negative emotions and self-esteem) through ethnic identity (Armenta & Hunt, 2009; Branscombe et al., 1999; Brittian et al., 2015; Umaña-Taylor & Updegraff, 2007). It may even be that when people from racial and ethnic minority groups experience discrimination, a heightened sense of ethnic identity is triggered and results in enhanced psychological well-being (Branscombe et al., 1999; Brittian et al., 2015). Branscombe and colleagues (1999) called this effect “rejection identification.” The mediating relationship of ethnic identity between discrimination and psychological well-being may help explain differential development of resilience to racial discrimination that the buffering hypothesis does not account for. Racial and Ethnic Group Differences Results from meta-analysis have strongly suggested that there are no differences in the extent to which racial discrimination negatively affects psychological well-being for various racial and ethnic groups including Asian, Hispanic, black, Native American, and white (Pascoe & Smart Richman, 2009). However, as Brittian and colleagues (2015) pointed out, the experiences of racial discrimination and ethnic identity may be very different for each racial and ethnic group. The mechanisms by which racial microaggression influences psychological well-being might also vary across racial and ethnic groups. The Current Study The current study aimed to contribute to what is understood about how racial discrimination influences psychological well-being by conducting a path analysis of a model that hypothesized that ethnic identity would mediate a relationship between racial microaggression and outcomes of psychological distress, self-esteem, academic self-efficacy, and substance abuse. Although the data are cross-sectional, causal relationships are hypothesized with the intent to see how well the findings support the model and inform further research investigations. We posited that individuals’ ethnic identity would be strengthened by experiencing microaggression. We also expected findings to support the hypothesis that racial microaggression has a detrimental relationship with psychological well-being (that is, psychological distress, self-esteem, academic efficacy, and substance abuse), whereas ethnic identity has a beneficial one. As a secondary objective of the study, we conducted a multigroup test of the path analysis to explore the potential for variation in the results across racial and ethnic groups. Method Sampling and Data Collection Cross-sectional data were collected using a Web-based survey from young adults enrolled in an urban public college in the western United States. Participants were 210 black, Latino/Hispanic, and Asian undergraduate students (ages 18 to 35 years). The college is publically funded. Approximately 40% of the students were recipients of Pell Grants or veterans benefits. The student body of the college was racially and ethnically diverse (white 63%, Latino/Hispanic 18%, black or African American 6%, Asian 4%, American Indian or Alaskan Native students 1%, two or more races 3%, and other/unknown 5%). Fifty-four percent of undergraduate students were female and 46% were male. The current study included all black, Hispanic/Latino, and Asian participants. An e-mail address dedicated to the study and a Listserv of all student e-mail addresses enabled the invitation to the anonymous survey to be sent to all prospective participants at once. Participants proceeded to the survey only after completing informed consent. All aspects of the protocol were approved through the institutional review board before proceeding with the data collection. Measures Self-report standardized scales were used to measure six distinct constructs: racial microaggression, ethnic identity, psychological distress, self-esteem, academic self-efficacy, and substance abuse. Racial Microaggression Racial microaggression was operationalized by 28 ordinal indicators (α = .88) from the Revised 28-Item Racial and Ethnic Microaggressions Scale (Forrest-Bank, Jenson, & Trecartin, 2015). Prior factor analysis has validated the use of the scale across racial groups (Forrest-Bank et al., 2015). The original instrument contained 45 items and was developed by Nadal (2011) based on the microaggression taxonomy developed by Sue (2010). Participants are asked to think about their experience with race and then respond to each item indicating how many times they had experienced the event in the past six months. There are six response choices ranging from not at all to five or more times. The 28 items were summed then divided by the number of items used to create it to establish a composite variable, with higher scores indicative of more microaggression experienced (M = 3.89). Ethnic Identity Ethnic identity was operationalized by the summation of 12 ordinal indicators (α = .91) from Phinney’s (1992) Multigroup Ethnic Identity Measure (MEIM). Respondents were asked to choose the responses that best fit how they felt about each of the 12 items on a four-point scale ranging from 1 = strongly agree to 5 = strongly disagree. The scale contains five questions representing both affective and cognitive–behavioral components of ethnic identity search. Reliability of the 12-item scale has been demonstrated previously with a wide range of age groups and ethnicities (Roberts et al., 1999). The 12 items were summed to create a summative variable, with higher scores indicating greater ethnic identity (M = 35.61). Substance Abuse Substance abuse was measured with the CRAFFT (Knight et al., 1999), a six-item instrument used to screen for potential alcohol or drug abuse in adolescents and young adults. CRAFFT is an acronym using the first letters of the key words in the six questions. For example, the letter “C” represents the question, “Have you ever ridden in a CAR driven by someone (including yourself) who was ‘high’ or had been using alcohol or drugs?" Substance abuse was represented by the summation of six dichotomous indicators representing whether or not the items were true for them (α = .76). Items were summed to create a single summative variable in which higher scores represent the participant endorsing more symptoms associated with substance use disorders (M = 1.61). The CRAFFT has demonstrated criterion validity in identifying adolescents with substance abuse and dependence (Knight, Sherritt, Shrier, Harris, & Chang, 2002). Based on recommendations from the instrument developers, endorsement of two or more indicators is likely to predict a substance use disorder (Knight, Sherritt, Harris, Gates, & Chang, 2003). Psychological Distress Psychological distress was operationalized by the summation of 10 ordinal items used in the National Survey of Black Americans (Brown et al., 2000). Items in the scale measured symptoms of depression and anxiety. For example, symptoms included “downhearted and blue” and “restless and upset.” Respondents were asked to respond to the prompt, “During the past month, how much of the time did you feel . . .” on a four-point scale with 1 = none of the time, 2 = some of the time, 3 = most of the time, and 4 = all of the time. This scale was derived from research done by renowned innovator and expert in health outcome measurement John Ware and the Rand Corporation on the Mental Health Inventory (Ware, Davies-Avery, & Donald, 1978; Ware, Johnston, Davies, & Brook, 1979). The scale demonstrated strong reliability in the current study (α = .92). Higher scores on this variable represent more symptoms of psychological distress (M = 21.03). Self-esteem The Rosenberg Self-Esteem Scale (Rosenberg, 1965) is an extensively validated 10-item scale consisting of both positive and negative feelings about the self-value and worth (α = .88). Items are answered using a four-point Likert scale ranging from 1 = strongly agree to 4 = strongly disagree. Higher scores on this variable are indicative of higher levels of self-esteem (M = 32.51). Academic Self-Efficacy Academic self-efficacy was measured by summing seven items from the College Self-Efficacy Instrument (Solberg, O’Brien, Villareal, Kennel, & Davis, 1993). The scale demonstrated strong reliability (α = .86). This instrument assesses college students’ sense of confidence in their ability to manage tasks related to course completion that are integral to college participation, such as “do well on your exams” and “manage time effectively.” For example, one question reads, “How confident are you that you could successfully complete the following tasks?” The response choices range from 0 = not at all confident to 10 = extremely confident. Higher scores indicate higher levels of academic self-efficacy (M = 51.96). Data Analysis SPSS (Version 22) was used to generate descriptive, frequency, and percentage information for the variables used in analyses. Mplus (Version 7) (Muthén & Muthén, 2012) was used to perform path analyses to determine the extent to which microaggression, directly and through ethnic identity, affects psychological distress, self-esteem, academic self-efficacy, and substance abuse. Path analysis was the analytic strategy used for the current study for several reasons. First, unlike standard ordinary least squares (OLS) regression, it allowed for us to assess whether ethnic identity mediates the relationships between microaggression and indicators of psychological well-being. Although structural equation modeling was considered, parameter estimation would have been inadequate given the sample size. That is, the number of parameters to be estimated via a structural model would have far exceeded that recommended by current practice (Kline, 2015). Therefore path analysis using summative scales of measures that have demonstrated strong psychometric properties in past research (as discussed in the Measures section) was used. Model fit statistics were not reported as only observed indicators were analyzed within the path model and thus perfect measurement of observed indicators is assumed (Muthén & Muthén, 2012). Total direct and indirect effects were also estimated to identify paths within the model that further explained the role ethnic identity might play in mediating the effects of microaggression on outcomes of interest. Unstandardized (B) and standardized (StdYX) estimates are reported. The StdYX output option in Mplus (Version 7) was used to produce standardized coefficients, with the objective of standardizing the parameter estimates within the model and their standard errors. This option uses the variances of all variables in the model for standardization (Muthén & Muthén, 2012). A total of 213 cases of data were included for analysis. Of these, three participants had missing data on all variables included in analyses and were therefore excluded using listwise deletion, leaving a final sample size of 210. Missing data analysis of the final sample revealed that approximately 95% had available data on all variables of interest. Mean comparison methods (t test and analysis of variance) were used to compare scores on outcome variables across age, gender, ethnicity, and survey completion (that is, whether the participant had data on all items of the survey). These analyses revealed no patterns of missingness in the data. Therefore, it was assumed that data were missing at random (Little, 1988; Little & Rubin, 1989) and estimates reported in the analysis were generated using full information maximum likelihood imputation for missing values (Muthén & Muthén, 2012). Results The sample ranged in age from 18 to 35 years (M = 23.74) and was primarily female (63.8%). Moreover, 34.7% of the sample reported their race or ethnicity as being Asian, 31.5% Latino or Hispanic, 33.5% black, and 0.5% Native American. The mean time (in years) participants had spent in college was 3.22. Descriptive information for the sample can be found in Table 1. Table 1: Sample Demographics (N = 213) M (SD) n (%) Age 23.74 (4.11) 18–23 114 53.5 24–29 68 31.9 30–35 27 12.6 Gender Male 77 36.2 Female 136 63.8 Race or ethnicity Asian 74 34.7 Latino/Hispanic 67 31.5 Black 71 33.5 Native American 1 .5 M (SD) n (%) Age 23.74 (4.11) 18–23 114 53.5 24–29 68 31.9 30–35 27 12.6 Gender Male 77 36.2 Female 136 63.8 Race or ethnicity Asian 74 34.7 Latino/Hispanic 67 31.5 Black 71 33.5 Native American 1 .5 Path Analysis with the Whole Sample The findings of the a priori path analysis model with the whole study sample are reported in Table 2. As expected, we found that microaggression was positively associated with ethnic identity. As predicted, microaggression had a significant positive association with psychological distress but no other direct relationships with the outcome variables. As expected, ethnic identity was negatively associated with psychological distress, but positively associated with self-esteem and academic self-efficacy. We did not anticipate that the effect found between ethnic identity and substance abuse would be positive. Findings supported our central hypothesis that ethnic identity would mediate the relationship between racial microaggression and outcomes of psychological well-being. Ethnic identity significantly mediated the effect of microaggression on psychological distress. Moreover, including ethnic identity in the equation revealed that microaggression has a positive effect on self-esteem and academic self-efficacy via participants’ reported degree of ethnic identity. Table 2: Results of Path Analyses (N = 210) B 95% CI StdYX 95% CI Microaggression → ethnic identity .52*** .22, .81 .23*** .10, .36 Microaggression → substance abuse –.04 –.11, .02 –.09 –.22, .04 Microaggression → psychological distress .33** .08, .58 .18** .04, .32 Microaggression → self-esteem –.12 –.34, .09 –.07 –.20, .05 Microaggression → academic self-efficacy –.09 –.56, .37 –.02 –.17, .11 Ethnic identity → substance abuse .03* .00, .06 .14* .00, .28 Ethnic identity → psychological distress –.19** –.30, –.08 –.23*** –.37, –.10 Ethnic identity → self-esteem .26*** .16, .36 .35*** .22, .47 Ethnic identity → academic self-efficacy .31*** .09, .52 .20** .06, .34 Microaggression → ethnic identity → substance abuse .01 –.02, .03 .03 –.04, .07 Microaggression → ethnic identity → psychological distress –.10* –.18, –.02 –.05* –.10, –.01 Microaggression → ethnic identity → self-esteem .13** .04, .23 .08** .02, .13 Microaggression → ethnic identity → academic self-efficacy .16* .01, .30 .04* .00, .09 B 95% CI StdYX 95% CI Microaggression → ethnic identity .52*** .22, .81 .23*** .10, .36 Microaggression → substance abuse –.04 –.11, .02 –.09 –.22, .04 Microaggression → psychological distress .33** .08, .58 .18** .04, .32 Microaggression → self-esteem –.12 –.34, .09 –.07 –.20, .05 Microaggression → academic self-efficacy –.09 –.56, .37 –.02 –.17, .11 Ethnic identity → substance abuse .03* .00, .06 .14* .00, .28 Ethnic identity → psychological distress –.19** –.30, –.08 –.23*** –.37, –.10 Ethnic identity → self-esteem .26*** .16, .36 .35*** .22, .47 Ethnic identity → academic self-efficacy .31*** .09, .52 .20** .06, .34 Microaggression → ethnic identity → substance abuse .01 –.02, .03 .03 –.04, .07 Microaggression → ethnic identity → psychological distress –.10* –.18, –.02 –.05* –.10, –.01 Microaggression → ethnic identity → self-esteem .13** .04, .23 .08** .02, .13 Microaggression → ethnic identity → academic self-efficacy .16* .01, .30 .04* .00, .09 Notes: CI = confidence interval, StdYX = standardized covariance using the variances of y and x. *p ≤ .05. **p ≤ .01. ***p ≤ .001. There are a number of additional notable correlations among the outcome variables. First, psychological distress was significantly negatively correlated with self-esteem (r = –.38; 95% confidence interval [CI] [–.50, –.26]; p < .001) and academic self-efficacy (r = –.26; 95% CI [–.39, –.12]; p < .001). In addition, self-esteem and academic self-efficacy were significantly positively correlated (r = .33; 95% CI [.21, .46]; p < .001). There were no significant correlations between substance abuse and psychological distress, self-esteem, or academic self-efficacy. Multigroup Path Analysis A multigroup test of the path analysis was conducted to explore the potential for variation in the effects across the Asian, Latino/Hispanic, and black groups while recognizing the limitations for interpretation given the subsample sizes (Kline, 2015). The significant results of the multigroup analysis are reported here. The single Native American participant was not included in this part of the analysis. See Figure 1 for the findings of the path analysis depicted for the whole sample and each of the subgroups. Figure 1: View largeDownload slide Results of Path Analysis for Whole Sample and Each Racial or Ethnic Group Note: *p ≤ .05. **p ≤ .01. ***p ≤ .001. Figure 1: View largeDownload slide Results of Path Analysis for Whole Sample and Each Racial or Ethnic Group Note: *p ≤ .05. **p ≤ .01. ***p ≤ .001. For the Asian subgroup (n = 74), ethnic identity was positively associated with self-esteem (StdYX = .35; 95% CI [.14, .55]; p < .001) and academic self-efficacy (StdYX = .29; 95% CI [.07, .51]; p < .01). Within this group, there was a significant negative correlation between psychological distress and self-esteem (r = –.31; 95% CI [–.52, –.10]; p < .01), a negative correlation between psychological distress and academic self-efficacy (r = –.27; 95% CI [–.48, –.05]; p < .05), and a positive correlation between self-esteem and academic self-efficacy (r = .36; 95% CI [.16, .57]; p < .001). For the Latino/Hispanic subgroup (n = 67), microaggression experienced was positively associated with ethnic identity (StdYX = .29; 95% CI [.07, .51]; p < .01). Among Latino/Hispanic participants, ethnic identity was negatively associated with psychological distress (StdYX = –.33; 95% CI [–.56, –.11]; p < .01) and positively associated with self-esteem (StdYX = .37; 95% CI [.15, .59]; p < .01). Microaggression was positively associated with psychological distress (StdYX = .26; 95% CI [.03, .49]; p < .05) and negatively associated with self-esteem (StdYX = –.22; 95% CI [–.45, –.00]; p < .05). Within this group, there was a negative correlation between psychological distress and self-esteem (r = –.58; 95% CI [–.74, –.42]; p < .001) and a negative correlation between psychological distress and academic self-efficacy (r = –.27; 95% CI [–.50, –.04]; p < .05). Ethnic identity had a significant mediating effect on the relationship between microaggression and self-esteem among Latino/Hispanic participants (StdYX = .11; 95% CI [.02, .21]; p < .05). For the black subgroup (n = 71), ethnic identity was negatively associated with psychological distress (StdYX = –.34; 95% CI [–.56, –.12]; p < .01) and positively associated with self-esteem (StdYX = .30; 95% CI [.06, .53]; p < .05). Microaggression was positively associated with psychological distress (StdYX = .29; 95% CI [.06, .52]; p < .05). Within this group, there was a negative correlation between psychological distress and self-esteem (r = –.31; 95% CI [–.54, –.09]; p < .01) and a positive correlation between self-esteem and academic self-efficacy (r = .26; 95% CI [.01, .50]; p < .05). Discussion The current study contributes to the literature that seeks to understand the relationship between racial discrimination and psychological well-being among young adult college students. Specifically, the study applied path analysis to observe whether ethnic identity has a protective effect on the negative influence of racial microaggression on substance abuse, psychological distress, self-esteem, and academic self-efficacy. Congruent with the research literature, our findings suggest that subtle forms of discrimination can have a damaging impact on the emotional health of racial and ethnic minority young adults. In addition, ethnic identity had a beneficial effect on the relationship between racial discrimination and all of the outcomes of psychological well-being except substance abuse. In fact, ethnic identity reversed the negative direct effect of racial microaggression on psychological well-being and resulted in positive associations instead. It is clear from these findings that ethnic identity has a critically positive role in emotional well-being and can serve as a protective factor to the negative effects of microaggression on psychological well-being. Said differently, those young adults who have more developed ethnic identity may experience fewer psychologically detrimental effects when exposed to racial microaggression. The positive effect of microaggression on ethnic identity that was found in this pathway supports the proposition of the rejection-identification model (Branscombe et al., 1999), which says that awareness and preparedness for racial discrimination can heighten individuals’ ethnic group identification. This effect cannot be observed in the context of the relationship between discrimination and psychological well-being through traditional OLS interaction analysis and appears to provide crucial insight into the dynamics involved in developing resilience to racial microaggression. Interestingly, substance abuse had opposite relationships than expected with both racial microaggression and ethnic identity. Ethnic identity was positively and significantly related to substance abuse, and racial microaggression found a nonsignificant negative relationship that was also reversed when the interaction with ethnic identity was tested. In addition, substance abuse was not correlated with the other outcome indicators of psychological well-being. The differential findings may lie in that substance abuse is a behavioral indicator, whereas the other indicators of psychological well-being measure more internal states. A possible explanation might be that substance abuse was measured using CRAFFT, an instrument designed as a screening tool to assess the likelihood of substance abuse, rather than as a summed measure of extent of substance abuse. Another possible explanation may concern social relationships that foster substance use among college students. Some of the dimensions of ethnic identity explicitly measured with MEIM (Phinney, 1992) have to do with spending time with people from one’s own ethnic group. It may be that substance use is increased in social contexts, and people with higher levels of ethnic identity are more likely to engage in social contexts. Future investigations of the relationships among racial microaggression, ethnic identity, and substance use and abuse might benefit from assessing for contextual information about substance use as well as for specific substances and frequency of use, in addition to using instruments that use diagnostic indication of abuse. Racial and Ethnic Group Differences A post hoc multigroup analysis was conducted to explore how the relationships in the model differed as a function of racial and ethnic group. No hypotheses were asserted about what specifically might be different between the groups, and path analysis is optimally conducted with larger sample sizes, so specific interpretation of the variation in the findings should be drawn cautiously. The results of the multigroup analysis suggest that there were substantial differences for each group, though the directionality of all of the relationships was similar for all of the groups (except that ethnic identity and substance abuse found zero effect in the Latino/Hispanic group). Figure 1 provides a helpful visual reference for how the findings for each of the groups differed from the analysis with the whole sample, as well as how they compare with each other. Interestingly, there was considerable variation in which relationships were significant for each group; however, only one relationship appeared in the multigroup analysis that was not found in the whole sample. This exception was that microaggression was significantly related to self-esteem in the Latino/Hispanic and not in either of the other subgroup findings. The relationship between microaggression and ethnic identity was not significant in the Asian and black subsamples, but was in the Latino/Hispanic subsample. Microaggression was not significantly related to psychological distress in the Asian group, but was in the Latino/Hispanic and black groups. The positive significant effect between ethnic identity and substance abuse in the whole sample was not found in any of the subgroups and was nonexistent in the Latino/Hispanic group. Ethnic identity was significantly related to self-esteem in all the subgroups, to psychological distress in both the Latino/Hispanic and black groups but not the Asian group, and to academic self-efficacy only in the Asian group. Also noteworthy is that the correlations among the outcome variables of psychological distress, self-esteem, and academic self-efficacy were all significantly related to each other in all of the subsamples, but no significant relationship was found between psychological distress and academic self-efficacy for the black group. Only one of the mediation effects that was significant in the subgroup analysis was observed in the multigroup analysis. That significant mediation was found for the self-esteem outcome for the Latino/Hispanic group. There appear to be some substantial differences among racial and ethnic subgroups that were obscured within the bigger study sample. These differences are much more difficult to compare across different research investigations, pointing to recommendations for future research involving large-scale multigroup comparison. Many researchers have suggested that it is important to study specific racial and ethnic groups separately because every group has unique experiences, and every group is composed of numerous ethnicities and wide variation in culture (Mossakowski, 2003). In addition, the social context is likely to influence variations in discriminatory experiences and opportunities for cultural participation, as are factors like how long people have been in the United States and how much they have acculturated (Yip, Gee, & Takeuchi, 2008). At least as important to consider is the unique historical oppression of each group in the United States and how that shapes the meaning for what race, ethnicity, and discrimination mean in their lives. Some researchers have also implicated different dimensions of ethnic identity to explain variations among these relationships (Brittian et al., 2013). Implications Although there are inherent limitations in the study’s use of cross-sectional data to test hypothesized causal relationships, and in sample sizes that are smaller than optimal for multigroup comparison, the study offers some important insights and points to a number of implications for social work practice, research, and education. Social workers aligned to eradicate health inequalities strive to reveal and combat forces of oppression that influence life trajectories (Walters et al., 2016). Racial and ethnic minority young adult college students enrolled in a public college, such as those in our study, may have faced and overcome considerable disadvantage earlier in their lives. For example, some may have experienced financial hardship, exposure to risk factors for behavioral and emotional problems, or racial discrimination. College should contribute to their pathways toward positive development, psychological well-being, and equal opportunity—not contribute further to disparities. Practitioners should include assessment of client experiences concerning racial discrimination, particularly in the form of racial microaggressions, and ethnic identity in developing case conceptualizations. These assessments can help practitioners work with clients to recognize the role racial discrimination may have in their compromised well-being as well as the strength of ethnic identity in fostering resilience to the harmful impacts of racial discrimination. It seems that effective intervention might lie in a balance between raising awareness of how to manage microaggressive experiences when they arise while creating opportunities for young adults to strengthen their ethnic identity, for example through participating in cultural activities germane to their ethnicities. It is also critical to recognize how microaggression may occur within clinical settings and even unintentionally from social workers themselves. Social workers’ unawareness of microaggressions that clients are exposed to in agencies and within therapeutic dyads can be harmful to clients and undermine the therapeutic alliance. Social workers are encouraged to intentionally assess and address common microaggressions that might be occurring within their practices. In addition, social work education should include instruction about microaggression to help students understand how racism is perpetuated and explicitly teach about the importance of discrimination and ethnic identity in influencing well-being among racial and ethnic minority groups. Prevention and intervention measures specifically aimed toward ameliorating the negative impacts of racial and ethnic discrimination among college students might include universal strategies that combat stereotypes and promote open discussions about race and the importance of ending subtle and overt forms of discrimination. In addition, the findings highlight the importance of providing opportunities like clubs and physical space for students to gather with other students with similar ethnic backgrounds to promote ethnic identity development. Furthermore, colleges and universities should be encouraged to strive for inclusive messages that do not marginalize racial and ethnic minority students and do promote and celebrate the range of diversity represented on campus. Social work researchers should further explore the relationships among the variables that were identified in this article. This might be done using a larger and more representative sample of young adults, and sampling and longitudinal methods that allow for inferring causality between discussed constructs, as well as studies focused on the role of ethnic identity as it mediates the effects of microaggression on psychological well-being over time. In any case, a better understanding of how ethnic identity is protective against the negative effects of microaggression on psychological well-being in young adults can help inform mental health care practice and education to better serve racial and ethnic minority young adults. Conclusion This study contributes to growing evidence that ethnic identity acts as a protective factor against the harmful impacts of racial discrimination on psychological well-being among racial and ethnic minority college students. Specifically, this study assessed the extent to which racial discrimination in the form of microaggression, and ethnic identity, predict participants’ psychological distress, self-esteem, academic self-efficacy, and substance abuse. The findings point to the value in measuring racial discrimination in the form of specific microaggressions in continued pursuit of understanding the relationships among these variables. The findings also highlight the critical importance of ethnic identity in the psychological well-being of racial and ethnic minority young adults. Differential findings between racial and ethnic groups suggest that research should be specifically targeted to inform practice with specific groups. 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