Research has shown that mental health problems in general and in adolescents in particular, are associated with one’s racial and ethnic affiliation. Specifically, having a minority status is a predictor of an increased risk for diverse types of mental illness and psychological problems (Becares & Nazroo, 2013; Eilbracht, Gonneke, Wigman, van Dorsselaer, & Vollebergh, 2015; Flink et al., 2013; Lee & Liechty, 2015; Schofield et al., 2016). An explanation for this is offered by the minority stress model, which was originally developed by Meyer (2003) in relation to lesbian, gay and bisexual populations to explain factors associated with stressors and coping mechanisms and their impact on mental health outcomes (Meyer, Schwartz, & Frost, 2008). This model posits that members of minority groups are exposed to unique distal and proximal stressors. Distal stressors include societal and institutional racism, which is manifested in stigma, hostile ostracizing and prejudicial attitude, and discrimination (Brittian et al., 2015; Chen, Szalacha, & Menon, 2014; Cokley et al., 2017; Schmitt, Branscombe, Postmes, & Garcia, 2014; Williams & Mohammed, 2013). These stressors are internalized by the individual to add a proximal source of stress. Outcomes of this stress can include impairment of one’s self image, sense of self-worth, and sense of control (Paradies et al., 1990). These detrimental effects exist across various minority groups (Forrest-Bank & Cuellar, 2018).

Contrary to blunt and direct racism, microaggressions denote behavioral, verbal and visual subtle slights, insults, and mistreatments that convey negative stereotypes about one’s race, ethnicity, gender, religion, sexuality, or ability (Pierce, 1970). Common forms of microaggressions include invisibility, minimization, stereotypes, being asked to represent one’s entire group, exoticization, infantilization, racist humor, and color blindness (Sue et al., 2007; Wong, Schrager, Holloway, Meyer, & Kipke, 2014a; Wong, Derthick, David, Saw, & Okazaki, 2014b). It can be intentional or unintentional, ambiguous and hidden in everyday interactions; yet the detrimental effects are pervasive and cumulative (Sue et al., 2007). Studies have found that encountering racial microaggressions can be psychologically and physically draining, generating stress and poor mental health outcomes (Nadal, Griffin, Wong, Hamit, & Rasmus, 2014; Sue et al., 2007; Wong et al., 2014b).

Exposure to racism and microaggressions vary according to the community in which members of minority groups reside, especially its level of ethnic density. Ethnic density refers to the relationship between the size of the minority and majority groups in a given area. The ethnic density hypothesis posits that it is the experience at the local rather than national level that is critical (Halpern, 1993). Consequently, one’s experience is shaped by the ethnic composition of the immediate environment in which one grows up and lives and whether it includes a significant presence of one’s own group.

The effects of ethnic density depend on its specific nature. Racial/ethnic minorities residing in predominantly majority group areas where their own ethnic group comprises a small proportion of the population—i.e. low ethnic density—are at a higher risk for mental health problems (Bonnar & McCarthy, 2012). Conversely, living in a medium diversity environment (Flink et al., 2013) or among members of their own ethnic group—i.e. medium or high ethnic density—worked as a buffer against negative influences related to minority affiliation (Morgan, Charalambides, Hutchinson, & Murray, 2010; O’Donoghue et al., 2015; Veling et al., 2008). For example, attending predominately minority schools was identified as a protective factor against negative effects of racism on mental health (Scott, Wallander, & Cameron, 2015). Similar findings were documented relative to second generation adolescents (Eilbracht et al., 2015).

While most studies did not specify the proportion of minorities in the various levels of density, some studies presented some information regarding the calculation of ethnic density or diversity index (e.g. Flink et al., 2013). For example, in a study in a remote, rural county in Northern New York, which was viewed as low density, 2.4% of the population was Black, 1.1% American Indian/Alaskan Native, 2.0% Hispanic/Latino, .9% Asian American, and .9% multi-racial (Bonnar & McCarthy, 2012). Another study (O’Donoghue et al., 2015) obtained census data to determine the level of ethnic density based on the proportion of first generation immigrants residing in the area and the proportion of the population with at least one parent who was a migrant but no data were presented as to which proportions were considered low or high density.

Findings regarding the ethnic density hypothesis have been mixed. Most studies found empirical support for it regarding immigrant as well as non-immigrant populations (Shaw et al., 2012) whereas other studies did not (e.g. Schrier et al., 2014). Protective effects of living among ethnically similar others were documented regarding diverse mental health issues (El-Sayed, Tracy, Scarborough, & Galea, 2011; Neeleman & Wessely, 1999; Neeleman, Wilson-Jones, & Wessely, 2001; Shaw et al., 2012). For example, lower rates of depressive symptoms and of mortality were reported in African Americans in homogenous neighborhood than in their counterparts in heterogeneous neighborhoods (English, Lambert, Evans, & Zonderman, 2014; Fang & Madhavan, 1998; Hunt, Wise, Jipguep, Cozier, & Rosenberg, 2007). Similarly, an increase in own-group ethnic density was associated with reduced psychosis incidence among Black Africans in East London (Kirkbride, Jones Ullrich, & Coid, 2014). Finally, Black students attending mostly white colleges were particularly prone to detrimental effects of minority status stress (McClain et al., 2016).

Some studies found partial or no support for the ethnic density hypothesis. For example, while a systematic review of studies that examined the effects of ethnic density on mental health found that overall the prevalence of psychotic disorders in ethnic minorities was higher in low ethnic density areas, some ethnic groups (e.g. Pakistani, Chinese, Caribbean) had inverse or no associations with ethnic density (Bosqui, Hoy, & Shannon, 2014). Ethnic density (or perhaps—racial density) was protective for blacks of lower socioeconomic groups, but not for those who were better-off economically (Bécares, Nazroo, & Jackson, 2014). Contrary to other studies, Choi, Kim, & Lee (2016) found negative effect of immigrant enclaves on immigrants’ mental health. Specifically, older recent immigrants who live in the counties with high ethnic density were most vulnerable to mental health symptoms.

An explanation offered for the effects of ethnic density on mental health, was that in low-density settings, with a relatively large percentage of the majority group, ethnic minorities are made more aware of their minority status and are more exposed to racism, discrimination, prejudiced attitudes, and microaggressions. Conversely, those who live in communities with a high concentration of their own ethnic group experience lower levels of exposure to racism and microaggressions (Flink et al., 2013). Because microaggressions and discrimination are associated with mental health (Nadal et al., 2014; Sue et al., 2007; Wong et al., 2014b), the latter have less negative mental health outcomes than the former. Additional support for this explanation was provided by Gieling, Vollebergh, & van Dorsselaer (2010) who found that school ethnic density affected both perceived discrimination and mental health. Similarly, minority young adults reported experiencing racial and ethnic discrimination as they were exposed to more diversity when enrolling in college than they were accustomed to beforehand (Forrest-Bank & Cuellar, 2018).

In addition, high density neighborhoods offer stronger social ties and social cohesion, yielding better emotional support and sense of belonging (Rios, Aiken, & Zautra, 2012), access to mental health care (Termorshuizen, Braam, & Ameijden, 2015) and to culturally sensitive services (Lee & Liechty, 2015; Whitley, Prince, McKenzie, & Stewart, 2006). Specifically, ethnic identity and social support emerged as factors that moderate the relationships between exposure to discrimination and mental health outcomes (Brittian et al., 2015; Forrest-Bank & Cuellar, 2018; Ong, Phinney, & Dennis, 2006).

Ethnic identity is a multi-dimensional dynamic construct that develops in a complex process over one’s lifetime and includes cognitive, affective, and behavioral aspects. It reflects the part of self-perception that relies on affiliation with a particular group, the significance of this affiliation and its associated sense of belonging (Phinney & Ong, 2007). A critical dimension of ethnic identity is ethnic pride versus shame. Ethnic pride represents a sense of attachment to one’s ethnic group and positive emotions and attitudes towards it, as well as interest in the group’s culture, history, and customs of the group (Anderson, 2016). Ethnic shame connotes a negative attitude towards one’s affiliation and its manifestations such as a difference in appearance, accent, having a “foreign” name and speaking a “foreign” language in public, food, cultural norms and values, which are viewed as incompatible with those of the dominant majority culture (Lauret, 2016; Napholz, 2000). It is a form of feeling as an outsider due to one’s ethnic heritage (Anderson, 2016).

Findings regarding the effects of ethnic identity on mental health were inconsistent. Numerous studies found that ethnic identity, specifically ethnic pride, is a strong predictor of better mental health outcomes, psychological wellbeing and resilience (Smith & Silva, 2011). It is associated with positive self-esteem and life satisfaction (Anderson, 2016), academic, social and psychological outcomes (Hernández, Conger, Robins, Bacher, & Widaman, 2014), decreased internalizing and externalizing problems such as depression, substance abuse, risky sexual behavior and aggression (Abu-Rayya, 2006; Jones & Neblett, 2016). Other studies (Ajibade, Hook, Utsey, Davis, & Van Tongeren, 2016; Vera et al., 2011) found that ethnic identity moderated the relation between perceived discrimination and wellbeing. However, the evidence varied across different minority groups: While ethnic racial identity was generally beneficial for African American adolescents’ psychosocial, academic, and health risk outcomes, the evidence was rather mixed for Latino and American Indian youth (Rivas-Drake, Seaton, Markstrom, Quintana, Syed, & Lee, 2014; Rivas-Drake, Syed, Umaña-Taylor, Markstrom, French, Schwartz, Lee 2014).

It was suggested that ethnic identity may intervene in the relationships between racial microaggressions and psychological wellbeing. While racial microaggressions may have damaging impacts on the psychological wellbeing of racial and ethnic minorities, it may also elicit stronger ethnic identity that serves as a protective factor against such negative effects (Forrest-Bank & Cuellar, 2018).

Social support and undermining Social support includes the provision of instrumental, informational, material and emotional resources by others. Numerous studies have shown that social support has a protective role in youths’ psychological wellbeing and mental health in the context of life change stresses (Kong & You, 2013; Malkoç & Yalçin, 2015; Taylor, 2015). Social support from family, peers and school can moderate the outcomes of negative social exposure by providing the individual with the experience of being cared and loved, esteemed and valued (Arslan, 2018). Consequently, individuals with high level of social support have higher level of wellbeing, are coping better and have a higher probability of being resilient (e.g. Kong & You, 2013; Malkoç & Yalçin, 2015). Thus, support from and connection to social networks can buffer adverse influences of racism and of other types of minority stressors on individuals’ mental health and protect their psychological wellbeing (Harding et al., 2015; Linnabery, Stuhlmacher, & Towler, 2014; Scott et al. 2015; Wong et al., 2014a). Intrafamilial support, particularly from extended family members has been recognized as an important resource during stressful times such as immigration, initial adjustment to college and post incarceration (Adelman, 1988; Reid, Holt, Bowman, Espelage, & Green, 2016; Wallace et al., 2016). Specifically relevant to the current study is that familial social support explained the relationship between intragroup marginalization and thriving (Llamas & Consoli, 2012). In contrast, family undermining was associated with a plethora of psychological distress, internalizing and adolescents’ externalizing problems and increased symptoms (Schuster, Kessler, & Aseltine, 1990; Soler, Caldwell, Córdova, Harper, & Bauermeister, 2018; Taylor, 2015).

The current study examined the ethnic density hypothesis among Palestinian Israelis as well as the mediating/moderating effect of perceived microaggression, family support/undermining and ethnic pride/shame. Palestinian Israelis are the largest minority group comprising about 20% of the population (Israel Central Bureau of Statistics, 2017). Close to 80% of this population group are Muslims, 10% Christians and 10% Druze (Ghanem & Mustafa, 2011). The Palestinian Israeli population is young with about 41% of children and adolescents below the age of 15. The vast majority lives in towns and villages that are exclusively Arab, whereas about 10% live in mixed cities such as Akka (Acre), Haifa, Ramla, Jaffa, Lydda and Ramla, where they are a minority (Ghanem & Mustafa, 2011). Palestinian Israeli families, including extended families (hamulas), tend to live in the same village or town. The few studies that examined the relationship between ethnic density and well-being focused on non-white populations in western cultures. In addition, the theoretical model suggested and examined in this paper was never tested. Thus, this study may expand and provide more nuanced understanding of the role of ethnic density, perceived microaggressions and risk and resilience buffers in shaping the mental health of minority adolescents.

Hypotheses

  1. 1.

    Adolescents who live in a high ethnic density environment will have lower scores in the psychological distress scale.

  2. 2.

    Perceived microaggressions will mediate the relationships between ethnic density and adolescents’ mental health as measured by psychological distress.

  3. 3.

    Family support and ethnic pride will moderate the relationships between perceived microaggressions and adolescents’ mental health; the higher the support and ethnic pride, the weaker the relationship between perceived microaggressions and psychological distress.

  4. 4.

    Family undermining and ethnic shame will moderate the relationships between perceived microaggressions and adolescents’ mental health; the higher the undermining and shame, the stronger the relationship between microaggressions and psychological distress

The study’s theoretical model is presented in Fig. 1.

Fig. 1
figure 1

Study’s theoretical model

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Method

Sample and Sampling

The study’s target population was adolescents in grades 10 to 12. The sample was recruited via Israeli public schools that allowed access. Altogether, it comprised 21 schools from all over the country. This geographic dispersion may be important, as Palestinian Israelis are not a uniform society, and geographic differences may reflect some of the internal heterogeneity among them. Data were collected from 777 students. Almost two-thirds (64.9%) of the sample were girls; their mean age was 15.93 (SD = 1.06). In their attitude to religion, 52.2% described themselves as religious (observant), 5.2% as secular, and 42.6% as “traditional” (i.e. religiously observant and following religious laws and traditions but less so than the observant). The majority (59.8%) perceive their family social economic status as good or very good, 31.8% as average, and 8.3% as bad or very bad.

Measures

Ethnic density Respondents were asked a single question indicating the homogeneity or heterogeneity of the town in which they reside. Specifically, they were to choose one of eight options regarding the composition of their community: mixed (Jews, Muslims, Christians and others); Muslims, Druze, Bedouin and Christians (no-Jews); almost exclusively Bedouin, or Muslim or Christians or Druze or Jewish; other. The eight original categories were grouped into three: 1 = the most heterogeneous community (comprising Jews, Moslems, Christians, and others); 2 = heterogeneous Arab populations (comprising Palestinians, Arabs, Moslems, Christians, and others); 3 = homogeneous, same ethno-religious group. A higher score indicates living in a relatively homogeneous ethnic density environment. It is worth mentioning here that 17% of the subjects described their town as heterogeneous (Arabs and Jews), 8% as a mixed Arab community, and 77% as a rather homogeneous.

Psychological distress The construct was measured by K-6 that was developed as a unidimensional measure, sensitive to nonspecific psychological distress (Kessler et al., 2002). It taps six indicators of anxiety and depression (e.g., irritability, despair, depression). Respondents were asked to state how often they experienced each of the indicators in the past month, from 1 = not at all to 5 = all the time. Reliability (internal consistency as measured by Cronbach’s alpha) was α = .86. As suggested by Kessler et al. (2010), scores were calculated as the sum of the responses, so that the higher the score, the more severe the psychological distress.

Perceived microaggressions were assessed by the Racial Microaggressions Scale (RMAS) developed by Torres-Harding, Andrade and Romero Diaz (2012). The original measure includes 32 items in six factors. For the purpose of this study, only three factors were included, whereas the other three factors were omitted because of cultural (e.g. sexuality) and contextual (e.g. foreign/not belonging and environmental invalidation) irrelevance to the target population. The adapted version of the RMAS was left at 22 items. The measure categories include the following: Invisibility (8 items; e.g., I am ignored in school environments because of my race); Criminality (4 items; e.g., others assume I will behave aggressively because of my race); Low-Achieving/Undesirable Culture (10 items; e.g., others suggest that my racial heritage is dysfunctional or undesirable). Respondents were asked to indicate on a 4-point Likert scale (1 = Never, 2 = Rarely, 3 = Sometimes, 4 = Often) how frequently they were exposed to each type of microaggressions within the past year. Confirmatory factor analysis did not confirm the three-factor structure, χ2 (206, N = 777) = 1040.27, p < .0001; TLI = .86, CFI = .88, RMSEA = .07. Subsequently, a principal components analysis was performed and showed that all the 22 items were highly loaded on a single factor, with loadings ranging from .42 to .77 and median loading of .61. Therefore, a single score of perceived microaggressions was calculated, as done, for example, by O’Keefe et al. (2014). The scale’s reliability was α = .92. The score was calculated based on the items’ mean; higher score indicates perceived exposure to more microaggressions.

Family support and undermining were assessed by a questionnaire developed by Abbey, Abramis, and Caplan (1985). It consists of eight items tapping perceived family support (e.g., my family cares for me as a person) and five items tapping perceived family undermining (e.g., my family acts in an unpleasant or angry manner toward me). Items were rated on a 5-point Likert-type scale (1 = not at all, 5 = a great deal). In this study, scales’ reliabilities were α = .83 for family support and α = .82 for family undermining. Scores were calculated as the mean of the items comprising each of the scales; the higher the score, the more family support or more undermining perceived by the respondents.

Ethnic Pride and shame were measured by seven items phrased based on the literature on ethnic identity (Lauret, 2016; Napholz, 2000; Phinney & Ong, 2007). Participants were asked to indicate how proud (3 items, e.g., I am happy that I am a member of the group I belong to), and how ashamed they are with their ethnicity (4 items, e.g., I am ashamed of my ethnic group). Responses were rated on a 5-point Likert-type scale (1 = not at all, 5 = a great deal). Reliabilities obtained were α = .86 for pride and α = .77 for shame. Scores were calculated as the mean of the items comprising each of the scales; the higher the score, the more proud or ashamed the respondents were.

Demographic covariates Demographic information collected included age, gender (0 = male, 1 = female), perceived socioeconomic status (1 = very poor to 5 = very good), and religiosity (1 = very religious to 5 = secular).

Procedure

An Arabic self-administered questionnaire was distributed with the assistance of graduate and post-doctoral students to a convenience sample of high school students across the country. Permission was obtained from Israel’s Ministry of Education and from Tel Aviv University’s ethics committee. Parents had the option to object to their child’s engagement. Any student in a participating class who was willing and able to complete the questionnaire was eligible. The students signed a consent form, prior to filling out the questionnaire.

Analyses

Descriptive statistics (means and standard deviations) of the research variables, as well as their intercorrelations, were computed using SAS software, Version 9.4. The model in Fig. 1 was assessed using Structural Equation Modeling with Mplus software Version 8 (Muthén & Muthén, 1998–2012). Ethnic density was used in the model as an observed variable. The other research constructs were specified as latent variables, each measured, using the accepted approach of parceling (Bandalos, 2002), by four indicators defined as random fourths of the scale items.

There were missing values in the data: the minimal covariance coverage in the variance–covariance matrix used in the analyses was .89. To take advantage of all the available data, the model was fit using full-information maximum likelihood estimation with robust standard errors (Little & Rubin, 2003). Following recommendations of Hu and Bentler (1999), fit indexes of two types are reported: the Tucker-Lewis index (TLI) and the Comparative Fit Index (CFI), and two indexes of misfit: root mean-square error of approximation (RMSEA) and standardized root mean-square residual (SRMR). NNFI and CFI close to or above .95, combined with RMSEA below .06 and SRMR below .08, are considered indicative of acceptable fit. After a significant moderation effect was demonstrated in the model, a follow-up simple slopes analysis was performed using the PROCESS tool for SPSS software developed by Hayes (2012, Model 14).

Results

Means and Zero-Order Correlations

As ethnic density had only three levels, Spearman rank correlations were used for this variable; product moment correlations were calculated for all other variables. As presented in Table 1, there were no significant relationships between ethnic density and the ultimate dependent variable psychological distress. Ethnic density was negatively correlated with perceived microaggressions (rs = − .14, p < .001), with family undermining (rs = − .14, p < .001) and with ethnic shame (rs = − .11, p < .01). Perceived microaggressions were positively correlated with psychological distress (r = .21, p < .001), as well as with family undermining (r = .13, p < .001) and ethnic shame (r = .09, p < .05). In addition to perceived microaggressions, psychological distress was also positively correlated with family undermining (r = .34, p < .001) and with ethnic shame (r = .17, p < .001), but negatively correlated with family support (r = − .17, p < .001) and with ethnic pride (r = − .14, p < .001).

Table 1 Distribution and intercorrelationsa of research variables
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As the first stage of the main analyses, the measurement model was tested. It yielded acceptable results: χ2 (215, N = 777) = 635.55, p < .001, TLI = . 5, CFI = . 96, SRMR = .05, RMSEA = .05 (90% CI .046; .055). These results provide support for the validity of the factor structure in the model and specifically, for the validity of discriminating between the constructs of family support versus family undermining and ethnic pride versus ethnic shame.

Testing the Structural Model

Next, the research hypotheses were tested within a structural model. To the theoretical model depicted in Fig. 1, that included random terms of the four effects moderating the relation between perceived microaggressions and psychological distress, paths leading from control variables (gender, SES, religiosity) to each of the content variables were added. The Loglikelihood index of the model was − 25471.14, Akaike information coefficient (AIC) was 51,148.28, and Bayesian information coefficient (BIC) was 51,627.79. Insignificant paths were omitted from the model, emitted by control variables and the analysis was re-run. This modification did not change the model fit significantly (Loglikelihood = − 25,480.44, AIC = 51,150.87, and BIC = 51,593.14). The results are presented in Fig. 2. Omitted from the figure are paths connecting the control and the content variables, they are presented in Table 2.

Fig. 2
figure 2

Path model of moderated mediation effects of ethnic density upon psychological distress with standardized parameters. Note The solid lines indicate paths statistically significant at p < .05. The dotted lines indicate nonsignificant paths

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Table 2 Standardized path parameters linking background and research variables
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We hypothesized that (1) adolescents who live in a high ethnic density environment will have lower scores in the psychological distress scale. As seen in Fig. 2, this hypothesis was not sustained: no statistically significant relation was found between these two variables.

We further hypothesized (2) that perceived microaggressions will mediate the relationships between ethnic density and adolescents’ mental health as measured by psychological distress. Consistently with the hypothesis, there was a low, but statistically significant negative effect of ethnic density upon perceived microaggressions (β = − .14, p < .001) and a significant positive effect of perceived microagressions upon psychological distress (β = .32, p < .001). In view of these moderate effects, the indirect effect of ethnic density upon psychological distress (mediated by perceived microaggressions), was tested and found to be weak (β = .03), but statistically significant (p = .002).

Our next hypothesis (3) stated that family support and ethnic pride will moderate the relationships between perceived microaggressions and adolescents’ mental health; the higher the support and ethnic pride, the weaker the relationship between perceived microaggressions and psychological distress. As seen in Fig. 1, this hypothesis received partial support: Only family support moderated the relationship between perceived microaggressions and psychological distress (β = − .14, p < .001). As indicated by the negative sign of the moderation coefficient, the moderation was a buffering effect: the higher the support, the weaker was the relationship between perceived microaggressions and psychological distress. Indeed, in a follow-up simple slopes analysis of the moderated mediation it was found that the indirect effect was the strongest at a low level of family support (− 1SD, B = .36, p < .001), mild at the average level of family support (B = .22, p < .001), and non-significant at a high level of support (B = .09, p = .07).

Finally, we hypothesized (4) that family undermining and ethnic shame will moderate the relationships between perceived microaggressions and adolescents’ mental health; the higher the undermining and shame, the stronger the relationship between microaggressions and psychological distress. The data did not support this hypothesis: neither moderating effect was statistically significant.

In addition, family undermining exhibited a main effect upon psychological distress (β = .28, p < .001). As can be seen in Table 2, two of the three covariates are significantly correlated with the some of the research variables: perceived family social economic status and gender. Those who perceive their family social economic status as higher report less exposure to microaggressions, as well as to family undermining. They also report more family support. Compared to the boys, the girls in the sample report more family support and ethnic pride, and less exposure to microaggressions, to family undermining and to ethnic shame. But, they also report more psychological distress. Overall, the research model explained 24% of the variance in psychological distress.

Discussion

This study examined a mediated and moderated model of the relationship between ethnic density and psychological distress in Palestinian Israeli adolescents. The means and standard deviations of the study’s variables indicate reported low exposure to microaggressions, moderate family support and somewhat low family undermining. They also show high ethnic pride, low ethnic shame, and moderate psychological distress.

The correlations among the variables suggest complex relationships among them. As expected, ethnic density was negatively correlated with perceived microaggressions (although this effect was rather low), which were positively correlated with psychological distress. However, contrary to expectation, ethnic density was not significantly associated with psychological distress. The finding that ethnic density is not correlated with psychological distress disagrees with the findings of some previous studies (Bonnar & McCarthy 2012; Flink et al., 2013; O’Donoghue et al., 2015). However, studies have already shown that the relationship between ethnic density and mental health is not uniform across ethnic groups and may be affected by experiences in settlement and personal history (Bécares, Nazroo, & Jackson, 2014). Furthermore, previous research demonstrated that while the risk of psychological distress increased with ethnic heterogeneity, this was explained by neighborhood and individual socioeconomic factors and native origin, such that the negative impact was mostly in low socioeconomic contexts (Johnson-Singh, Rostila, Ponce De Leon, Forsell, & Engström, 2018). This finding in the current study may be either due to the economic status of the respondents (who described it as average or high), or due to the limited variance of the economic status variable.

The finding that girls report a little more family support and ethnic pride and less exposure to microaggressions, family undermining, and ethnic shame, may be explained by the nature of relationships and attitudes towards girls and boys in the Palestinian Israeli community. Girls are more sheltered than boys and are expected to honor family and cultural norms and traditions (Al-Krenawi, 2000; Barakat, 1993). They are also not encouraged to engage or hangout in heterogeneous environments, thus this may explain the finding about their less exposure to microaggressions. These cultural mechanisms may also offer an explanation to the finding that girls reported slightly higher psychological distress than boys. The Palestinians in Israel are going through a transition from a traditional patriarchal society to a more open and western society (Khalaila & Litwin, 2012), to which adolescents are exposed. This may create a dissonance between adolescents’ desire to keep the family traditional norms and values and engaging in more western behaviors. This is more so for girls who are more sheltered compared to the boys. The resulting conflict may lead to more psychological distress. With this, the finding that girls are more psychologically distressed than boys is consistent with previous findings (see, for example, Drapeau et al., 2010; Joiner Jr. & Blalock, 1995).

As for the tested model, the findings only partially supported the hypotheses depicted in the theoretical model. As hypothesized, the findings showed a mediating effect of perceived microaggressions between ethnic density and psychological distress, and this mediation effect was conditioned by family support. The mediation effect is congruent with minority stress theory and with former empirical findings that individuals in low ethnic density environment are exposed to direct and indirect racism more than those who live in high ethnic density environment (Flink et al., 2013). Thus, perceived microaggressions is a mechanism that explains how ethnic density is related to psychological distress. This means that while ethnic density is not directly related to psychological distress, it does have an indirect effect through perceived microaggressions.

The finding that the mediating effects of perceived microaggressions on the relationship between ethnic density and psychological distress was strongest at a low level of family support means that low family support is a risk factor for psychological distress. This finding is supported by the literature that emphasizes the vital role of social support in general and family support in particular (Reid et al., 2016; Wallace et al. 2016).

The hypothesized moderating effects of ethnic shame and pride and of family undermining on the relationships between perceived microaggressions and psychological distress were not supported by the data. This finding adds to previous research, which yielded mixed evidence regarding the buffering effects of ethnic identity on mental health (Que-Lam, Devos, & Goldberg, 2014). A meta-analysis of studies that examined the moderating effects of group identification on the relationships among perceived discrimination and both mental and physical health, found that most studies (71%) showed no moderating effect of identification on the relationship between perceived discrimination and mental health whereas only 18% of the analyses were consistent with a buffering hypothesis (Pascoe & Smart Richman, 2009).

While the findings failed to support a moderating effect of family undermining, they did show that it had a direct effect on psychological distress. Although not the focus of this paper, it is important to underscore the damaging power of family undermining. This negative effect was also reported in previous studies that documented an association between family social undermining and psychological distress in disadvantaged population groups such as young gay and lesbians across different family types (Soler et al., 2018) and low income African American adolescents and their mothers (Taylor, 2015).

Study Limitations, Suggested Future Studies, and Contributions

The main limitation of the study is the non-representative nature of the sample. As mentioned in the Method section, data were collected from schools whose principals were willing to cooperate. This yielded a biased sample with relation to gender and socio- economic status. The proportion of girls and of students who perceive their family economic status as above average is higher in the sample than their proportion in the Israeli population (Israel Central Bureau of Statistics, 2017). In addition, while previous studies about racial/ethnic minorities in general and Palestinian Israelis in particular reported high exposure to everyday racism and microaggressions (Avihu, 2016), this was not the case in the current study. Although the latter difference may well be explained by differences in study population and design (the Avihu study was a small scale, qualitative study of adult professionals), these biases raise the question about the generalizability of the findings. Thus, conclusions should be drawn with caution.

Its limitations notwithstanding, the findings have implications for theory, research, and practice. In terms of theory, the findings confirm the role of perceived microaggressions as an explanatory mechanism of psychological distress, the importance of family support as a buffer to psychological distress, and the toll that exposure to family undermining entails on psychological wellbeing.

In terms of research, to the best knowledge of the authors, this study is the first to test a mediating/moderating model exploring the relationships between ethnic density and psychological distress among Palestinian Israeli adolescents. Further studies are needed, however, to better understand the complex relationships among the study’s variables. It is thus recommended to replicate the study with a representative sample, in Israel and elsewhere, and to include adolescents who dropped out and those who study outside of the state high-school system.

In terms of practice, the findings have several implications. Social work, as a profession, is guided by the ideas of promoting social inclusion rather than segregation of populations (Gamble, 2012). With this, the price of integration in terms of exposure to microaggressions is evident from the current and other studies’ findings (Sheppard, 2006). The question emerged how to increase integration among populations without the price of mental health for the underprivileged minority group. One possible solution, as suggested by other researches (Flink et al. 2013; O’Donoghue et al., 2015), is to monitor the ratios of majority and minority groups residing in given neighborhoods. Taking into account the limited feasibility of such interventions, it may be more practical and pragmatic to focus on educational and social interventions and policies for minimizing manifestations of microaggressions, enhancing family support, and shedding light on the ramifications of family undermining. Social workers and other helping professionals can and should have a role in promoting these interventions and policies.