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Abstract

The present study provides preliminary evidence for validity of the Multidimensional Inventory of Cultural Stress (MICS), a measure of cultural stress developed to expand existing conceptualizations of cultural stress. The participants were 309 Hispanic/Latine adolescents (60.2% female; M_age= 15.30 years). Exploratory structural equation modeling (ESEM) revealed a four-factor solution: exclusionary political climate (i.e., perception of anti-immigrant and xenophobic rhetoric), Spanish criticism (i.e., experiences of being criticized for Spanish proficiency), within-group discrimination (i.e., experiences of being bullied/discriminated against for being too enculturated), and language brokering (i.e., experiences with having to translate for parents). Moreover, whereas exclusionary political climate was positively associated with alcohol use and symptoms of anxiety, Spanish criticism was negatively associated with self-esteem and positively associated with symptoms of depression and anxiety. These findings expand our current conceptualization of cultural stress and provide further guidance regarding how cultural stress impacts adjustment.

Keywords

cultural stress acculturative stress Hispanic language brokering within-group discrimination

Significance of the Scholarship to the Public

This study identifies the ways in which Hispanic adolescents experience cultural stress and presents a new survey measure to assess cultural stress, the Multidimensional Inventory of Cultural Stressors (MICS). This study shows that the MICS represents a simple, standardized way to identify Hispanic adolescents who are experiencing cultural stress. Moreover, this study further highlights cultural stress as a challenge among Hispanic adolescents.

Cultural stressors have been associated with alcohol and other drug use (e.g., Cano et al., 2015; Meca et al., 2019), mental health outcomes (e.g., Schwartz et al., 2015), and antisocial and deviant behavior (e.g., Smokowski & Bacallao, 2011) among Hispanic/Latino/a/e/x (HL) adolescents. Although many HL adolescents engage in adaptive mechanisms to manage or cope with cultural stressors (Carlo et al., 2022; Christophe et al., 2019), cultural stress has been highlighted as playing a key role in observed health disparities within immigrant populations. Broadly, cultural stress represents a constellation of unique stressors rooted in racism, colorism, xenophobia, and the challenge of navigating one’s heritage and the United States (U.S.) culture simultaneously (Meca & Schwartz, 2024). Despite this burgeoning area of research focused on the detrimental impact of cultural stressors, a key challenge has been the lack of a clear conceptualization of cultural stress. Indeed, although Cano et al. (2015) and Schwartz et al. (2015) conceptualized cultural stress as consisting of three components (i.e., perceived discrimination, bicultural stress, and negative context of reception), the broader literature has identified a variety of unique stressors that may qualify as cultural stressors (e.g., language brokering). Therefore, it is imperative to further refine the operationalization of cultural stress (Meca & Schwartz, 2024). Addressing this gap, and building on previously published qualitative work (Vos et al., 2021), the current study developed and provided evidence for the validity of a new measure of cultural stress that further expands on existing conceptualizations of cultural stress.

Conceptualizing Cultural Stress

Cultural stress theory (CST) defines cultural stress as a “collection of stressors rooted in the need to navigate both multiple cultural streams and a context that is often marked by racism, colorism, xenophobia, and a widespread framing of immigrants as real and/or existential threats to the destination society” (Meca & Schwartz, 2024, pp. 2–3). Although cultural stress has been broadly defined as a multidimensional construct, research drawing on CST has largely operationalized cultural stress using three distinct stressors: perceived discrimination (Sawyer et al., 2012), negative context of reception (Schwartz et al., 2014), and bicultural stress (Romero & Van Campen, 2011). Perceived discrimination refers to perceived experiences of unfair or differential treatment (e.g., being treated unfairly for having an accent; Sawyer et al., 2012). Negative context of reception refers to the degree to which adolescents feel unwelcome in their receiving context (e.g., perception of being unwelcome; Schwartz et al., 2014). Finally, bicultural stress refers to stressors associated with pressures to adopt the majority culture while also maintaining the heritage culture (e.g., brokering between American and Hispanic ways of behaving; Torres et al., 2012).

Despite the focus on these cultural stressors, the broader literature has identified a variety of additional unique stressors experienced by HL adolescents, including immigration-related stress and acculturation-gap stress (Cervantes et al., 2012), language brokering (see Weisskirch, 2017 for a collection of reviews), and within-group discrimination (Basáñez et al., 2019). Immigration-related stress refers to stressors associated with the process of immigration and includes fears of deportation and “homesickness” (Cervantes et al., 2012). Acculturation-gap stress refers to stressors associated with clashes between adolescents’ and their parents’ cultural norms and values (Cervantes et al., 2012). Language brokering occurs when adolescents are tasked with serving as linguistic intermediaries between their parents and members of U.S. mainstream culture (Morales & Hanson, 2014), and can represent a cultural stressor, particularly when adolescents are placed in a position where they must translate important family-related information, such as legal documents or healthcare information (Kam & Lazarevic, 2014). Within-group discrimination represents discrimination from members within the HL community (Basáñez et al., 2019) based on generational status, country of origin, language proficiency, or skin color (Córdova & Cervantes, 2010). Recent qualitative work (Vos et al., 2021) also has highlighted the impact of an exclusionary political climate. Although anti-immigrant and xenophobic rhetoric is not a new phenomenon within the U.S., HL populations have been increasingly scapegoated for economic and social problems (Castañeda, 2019). These perceptions, and the xenophobic beliefs that underlie them, have increased perceptions of fear among HL adolescents (Callister et al., 2019).

Current Measures of Cultural Stress

Paralleling the variability in the various manifestations of cultural stress, researchers have produced numerous measures, each capturing a specific or narrow facet of cultural stress (e.g., language brokering, intragroup marginalization, negative context of reception, etc.). Exceptions to this are the Bicultural Stress Scale (BSS; Romero & Roberts, 2003) and the adolescent version of the Hispanic Stress Inventory (HSI-A; Cervantes et al., 2012), which each capture multiple facets of cultural stress. The BSS is a 20-item scale developed to assess family-related cultural stressors, discrimination, monolingual stressors (i.e., issues related to language), and peer pressure to conform to one’s ethnic group. That said, the BSS does not capture perceived context of reception, acculturative stressors (e.g., pressures to acculturate and resist acculturation), and stressors rooted in language brokering. Moreover, as a result of limited psychometric work, the BSS has primarily been treated as a total score and masks the unique variance between its subscales. Although the HSI-A has undergone more rigorous psychometric evaluations, it includes several noncultural stress subscales (e.g., family economic stress, community and gang violence stress) and, like the BSS, does not assess stressors rooted in perception of context of reception, language brokering, and acculturative stress. Moreover, the HSI-A is a large instrument (71-items), making it difficult to integrate into large epidemiological studies. In sum, the BSS’s inability to capture some cultural stressors and the HSI-A’s length prohibit the ability to capture cultural stress in an efficient way. As such, there is a clear need for the development of a new brief measure of cultural stress that can speak to the lived experiences of HL adolescents today and is structured with multidimensional subscales incorporating various cultural stressors that can assess multiple cultural streams and a context that is often marked by racism, colorism, and xenophobia.

The Current Study

Addressing this gap, the present study was guided by two primary objectives. The first objective was to establish the factor structure of the MICS. The MICS was developed by the investigative team, in collaboration with an advisory board, using themes extracted from prior qualitative work (Vos et al., 2021) and from the existing literature on cultural stress to generate items that capture a breadth of cultural stressors that have not been traditionally included in current conceptualizations (Cano et al., 2015; Salas-Wright & Schwartz, 2019). Based on the item generation process, we hypothesized the MICS would represent a multidimensional measure capturing key stressors previously identified, including language brokering, differential acculturation, exclusionary political climate, within-group discrimination, and discrimination from White Americans (see Table S1 in Supplemental Materials). The second objective of this study was to examine the links between these measures of cultural stress and youth adjustment (i.e., self-esteem, symptoms of depression, symptoms of anxiety, and alcohol use). Given past research has found different dimensions of cultural stress to differentially predict youth adjustment (e.g., Meca et al., 2019), we expected one or more of the extracted dimensions of cultural stress to be negatively associated with self-esteem and positively associated with symptoms of depression and anxiety and alcohol use.

Method

Participants and Procedures

The present study utilized data from a multiphase mixed-methods study among HL adolescents in Miami and Los Angeles. For all phases, study eligibility criteria included: (a) self-reporting or identifying as HL and (b) being born, or having at least one parent born, in a Spanish speaking country in the Caribbean, Mexico, Central America, or South America.

During the first phase, as described by Vos et al. (2021), 34 HL adolescents (70.6% girls, n = 24) were recruited from two different high schools in Los Angeles and Miami and participated in six focus groups (three focus group per site, two in Spanish) conducted between November 2018 and April 2018. Participants were first- (n = 18, 52.9%) and second-generation (n = 16, 47.1%), primarily of either Mexican (n = 10, 29.4%) or Cuban heritage (n = 9, 26.5%), recruited either by high school guidance counselors (i.e., Miami site) or through classrooms identified by school administrators (i.e., Los Angeles site).

Focus groups lasted approximately 40−90 minutes each and were audio recorded with written and verbal parental consent and youth assent. The focus group consisted of questions, developed in consultation with a team of experts on HL development and cultural stress, across seven domains: belongingness, family dynamics, language, discrimination and xenophobia, migration issues, future plans, and emotional coping developed to capture acculturation-gap stress, acculturative stress, and bicultural stress (i.e., the belonginess, language, and family dynamics domains), discrimination and negative context of reception (i.e., discrimination and xenophobia domain), and immigration-related stress (i.e., migration issues domain). Upon completion, participants were compensated $15 for their time. The focus group findings were used to generate items for the MICS scale (described below), and 11 students were recruited to participate in cognitive interviews.

The third and final phase of the study, which is the primary stage of focus for the current paper, consisted of a quantitative study conducted during the Spring and Summer of 2020 via an online survey. Participants were recruited from two high schools in Los Angeles and one in Miami. Electronic informed parental consent and youth assent were obtained prior to participation. Although our initial goal was to recruit 600 adolescents, due to challenges with COVID-19, the final sample consisted of 309 HL adolescents (60.2% female, n = 186; M_age = 15.30 years, SD = 0.76 years, range = 14−17 years) residing in Miami (n = 110, 35.6%) and Los Angeles (n = 199, 64.4%) who participated in a quantitative study. The sample was primarily composed of second-generation immigrants (n = 171, 55.3%) and first-generation immigrants (n = 63, 20.4%), with the reminding 24.3% (n = 75) consisting of third-generation or greater. Participants were largely of Mexican (n = 174, 56.3%), Cuban (n = 82, 26.5%), Central American (Salvadoran, Honduran, Nicaraguan, and Guatemalan; n = 35, 11.3%), or other Latin American (n = 18, 5.9%) origin. The sample included 10th (n = 154, 49.8%), 11th (n = 93, 30.1%), 9th (n = 58, 18.8%), 12th (n = 2, .7%) grade students, and two participants who did not indicate grade level. The survey consisted of demographics, cultural stress items from the earlier study phases described above, acculturation, substance use, and mental health. All measures were translated into Spanish using a two-step translation process (Sireci et al., 2006). Adolescents received a $15 gift card for their participation. All study procedures were approved by the Institutional Review Boards at the participating universities.

Item Generation

Thematic analysis of the focus groups conducted during the first phase of the study, as reported by Vos et al. (2021), identified 4 themes: perceived discrimination from other HLs (in-group discrimination), perceived discrimination from non-HL groups (out-group discrimination), internalization of stressors and discrimination experienced by participants’ parents, and the current U.S. political rhetoric surrounding immigration. These themes were then presented to the Advisory Panel, which consisted of a group of scholars, who had been previously identified by the investigative team for their extensive expertise in HL youth and families, prevention and intervention efforts, cultural stress, and measurement. Along with the investigators, through iterative discussions, an initial set of 63 items corresponding to five distinct domains (i.e., language brokering, differential acculturation, exclusionary political climate, within-group discrimination, and discrimination from White Americans) were developed. Whereas exclusionary political climate, within-group discrimination, and discrimination from White Americans emerged as direct outgrowths from the themes extracted during the initial focus group, language brokering (i.e., stress rooted in a need to serve as both a linguistic and cultural intermediary by translating or interpreting cultural practices) and differential acculturation (i.e., stressors associated with clashes between adolescents’ and their parents’ cultural norms and values) emerged as nuanced discussion during the iterative process that built on understanding of HL family dynamics and sentiments relayed by youth regarding stressors rooted in interacting with their parents.

Next, 11 students were recruited to participate in cognitive interviews to determine how participants comprehend and interpret materials presented to them (Willis, 2006). Students first reviewed all the questions generated by the research team and circled or marked questions they found confusing or hard to answer. After the students completed their review, a research team member facilitated a discussion about the questions. Students suggested that the response scale for all the questions should be identical and thought that the survey should read “Hispanic/Latino” since they found neither term inclusive. Students strongly resonated with questions that asked about “not feeling Hispanic enough” or “not feeling American enough” in addition to questions asking about translating for their parents. Regarding questions tapping into the larger political climate, participants recommended framing these questions more generally, so that they gauge political climate and attitudes versus specific policies and politicians. Subsequently, the items for the MICS were edited in accordance with the suggestions and revised so they could be rated on a 5-point Likert-type response scale ranging from 1 (strongly disagree) to 5 (strongly agree). “Hispanic/Latino” was added in lieu of “Hispanic” and questions regarding the first Trump administration and the 2016 election were edited to ask about the “political situation” and politicians more generally.

Measures

Symptoms of Depression

Symptoms of depression were assessed utilizing the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10; Andresen et al., 1994). The CESD-10 is a 10-item scale that assesses adolescents’ depressive symptoms during the week prior to assessment (sample item: “I felt sad this week”). Response choices were on a 4-point Likert-type scale ranging from 0 (rarely or none of the time) to 3 (almost all the time). The CES-D has been translated into Spanish and used frequently with HL individuals (e.g., Todorova et al., 2010), with studies supporting the psychometric validity of this measure for using with HL populations (e.g., Gonzáles et al., 2017). The Cronbach’s alpha of the CESD-10 in the present study was .87.

Symptoms of Anxiety

Symptoms of anxiety were assessed utilizing the General Anxiety Disorder-7 (GAD-7; Spitzer et al., 2006). The GAD-7 consists of 7-items that ask participants to indicate the degree to which they experience symptoms of anxiety within the last 2 weeks (sample item: “Worrying too much about different things”). Similar to the CES-D, the GAD-7 has been previously utilized in Spanish, and prior research supported the psychometric validity of using this measure with HL populations (e.g., Mills et al., 2014). Items were rated on a 4-point Likert-type scale ranging from 0 (not at all) to 3 (nearly every day). The Cronbach’s alpha of the GAD-7 in the present study was .92.

Self-Esteem

Self-esteem was assessed using the 10-item Rosenberg (1965) Self-Esteem Scale (sample item: “On the whole, I am satisfied with myself”). This scale has been previously utilized in Spanish, and prior research supported the psychometric validity of using this measure with HL populations (e.g., Martín-Albo et al., 2007). Items were rated on a 5-point Likert-type scale ranging from 1 (strongly agree) to 5 (strongly disagree). The Cronbach’s alpha of the Rosenberg Self-Esteem Scale score in the present study was .88.

Alcohol Use

Alcohol use was assessed using the National Institute on Alcohol Abuse and Alcoholism/American Academy of Pediatrics Brief Alcohol Use Screener (National Institute on Alcohol Abuse and Alcoholism, 2011). The two-item Alcohol Use Screener items ask about (a) friends’ alcohol use and (b) adolescents’ own personal alcohol use frequency. In the present study, we utilized adolescents’ own personal alcohol use frequency (i.e., “In the past year, on how many days have you had more than a few sips of beer, wine, or any drink containing alcohol?”).

Statistical Analyses

The analysis proceeded in two steps and was conducted in Mplus v8.7 (Muthén & Muthén, 1998–2017) using a robust maximum likelihood estimator. Model fit was evaluated using the comparative fit index (CFI), the root mean square error of approximation (RMSEA), and the standardized root mean square residual (SRMR). According to values suggested by Little (2013), good fit was represented as CFI ≥ .95, RMSEA ≤ .06, and SRMR ≤ .06. Although reported, we did not use the χ² value to gauge model fit because it tests a null hypothesis of perfect fit, which is rarely plausible with large samples or complex models (Davey & Savla, 2010). Missing data at baseline was minimal (1.6–12.0%) and handled utilizing full information maximum likelihood, which is appropriate given the small amount of missing data and the fact that data was missing completely at random according to Little’s missing completely at random test, χ²(2203) = 2062.790, p = .984 (Schafer & Graham, 2002).

Although the initial aim was to conduct an exploratory factor analysis (EFA) with the first half of the sample, and a confirmatory factor analysis with the second half of the sample, due to challenges with recruiting participants during the early stages of COVID-19, recruitment was limited. As such, in the first step, we established the factor structure for the MICS utilizing exploratory structural equation modeling (ESEM; Muthén & Muthén, 1998–2017). ESEM represents an integration of confirmatory factor analysis and EFA and an oblique geomin rotation to minimize factor complexity by reducing cross-loadings and increasing interfactor correlations (Marsh et al., 2014). Like EFA, ESEM allows items to load freely on all factors (Asparouhov & Muthén, 2009). To determine the optimal number of factors, we compared 1- to 7-factor models using the Δχ² difference test, ΔCFI (>.010), and ΔRMSEA (>.010) criteria to determine significant change in model fit (Asparouhov & Muthén, 2009). Specifically, we determined a model to be an improvement if two or more of these criteria indicated a significant improvement in model fit. Simulation studies have shown that power for EFA increases as the item-to-factor ratio and magnitude of factor loadings increases, and 80% power can be achieved even with samples sizes as small as 250 (de Winter et al., 2009; MacCallum et al., 1999), particularly when primary factor loadings are above .60 (Wolf et al., 2013). Towards that end, to ensure that the factors we extracted would be robust, items were only retained if their factor loadings were above .60 (Brown, 2015).

Next, we sought to provide initial evidence for concurrent validity by exploring the association of each extracted factor with self-esteem, symptoms of depression and anxiety, and alcohol use. Because alcohol use represented a count variable, we used Poisson regression, where the unstandardized regression coefficient can be converted into an incidence rate ratio (IRR). which reflects the multiplicative increase in the expected count of the outcome variable with each one-unit increase of a predictor variable. However, because models utilizing count variables require numerical integration, which is incompatible with ESEM, factor scores were saved back into the dataset and treated as observed scores.

Results

Establishing the Factor Structure of the MICS

As shown in Table 1, the initial ESEM models provided support for a 6-factor structure, as it was a significant improvement upon the 5-factor model, Δχ²(58) = 129.922, p < .001, ΔRMSEA = .001, ΔCFI = .011, but was not significantly different from the 7-factor model, Δχ²(57) = 75.654, p = .050, ΔRMSEA = .002, ΔCFI = .004. That said, the 6-factor model was associated with poor-to-good model fit, χ²(1590) = 2866.279, p < .001, RMSEA = .051, CFI = .851, SRMR = .039. Moreover, closer examination of the factor loadings indicated several items did not meaningfully load |> .60| on to any particular factor and two factors with 2 or fewer salient loadings. As a next step, we sought to identify items that were consistently loading poorly across the 3- to 6-factor model. Of the initial 63 items, 32 items were identified as failing to meaningfully load to any factor, and as a result, were dropped, and the ESEM models were estimated anew.

Table 1.

Model Fit Across Exploratory Structural Equation Models (ESEM)

Model	χ²(df)	Δχ²(df)	RMSEA	ΔRSMEA	CFI	ΔCFI	SRMR
First iteration
1-Factor	6390.475(1890)^*		0.088		0.474		0.113
2-Factor	4432.358(1828)^*	1744.594(62)^*	0.068	.020	0.696	.222	0.069
3-Factor	3605.201(1767)^*	718.748(61)^*	0.058	.010	0.785	.089	0.053
4-Factor	3380.783(1707)^*	163.546(60)^*	0.057	.001	0.805	.020	0.046
5-Factor	3021.600(1648)^*	386.977(59)^*	0.052	.005	0.840	.035	0.041
6-Factor	2866.279(1590)^*	129.922(58)^*	0.051	.001	0.851	.011	0.039
7-Factor	2845.983(1533)^*	75.654(57)^*	0.053	−.002	0.847	−.004	0.037
Second iteration
1-Factor	2900.254(434)^*		0.136		0.469		0.168
2-Factor	1542.584(404)^*	1502.809(30)^*	0.096	.040	0.755	.286	0.087
3-Factor	941.348(375)^*	516.760(29)^*	0.070	.026	0.878	.123	0.044
4-Factor	751.092(347)^*	154.262(28)^*	0.062	.008	0.913	.035	0.033
5-Factor	587.063(320)^*	129.491(27)^*	0.052	.010	0.942	.029	0.029
6-Factor	523.684(294)^*	55.112(26)^*	0.051	.001	0.951	.009	0.025
7-Factor	460.670(269)^*	54.179(25)^*	0.048	.003	0.959	.008	0.021
Third iteration
1-Factor	2078.754(275)^*		0.146		0.537		0.159
2-Factor	1028.647(251)^*	1038.220(24)^*	0.101	.045	0.800	.263	0.086
3-Factor	654.266(228)^*	307.993(23)^*	0.078	.023	0.891	.091	0.043
4-Factor	500.193(206)^*	132.528(22)^*	0.068	.010	0.924	.033	0.030
5-Factor	329.908(185)^*	141.355(21)^*	0.051	.017	0.963	.039	0.024
6-Factor	254.008(165)^*	67.692(20)^*	0.042	.009	0.977	.014	0.019
7-Factor	195.851(146)^*	48.618(19)^*	0.033	.009	0.987	.010	0.016
Fourth iteration
1-Factor	1937.217(252)^*		0.148		0.547		0.160
2-Factor	968.198(229)^*	941.041(23)^*	0.103	.045	0.801	.254	0.087
3-Factor	598.506(207)^*	303.695(22)^*	0.079	.024	0.895	.094	0.043
4-Factor	441.542(186)^*	136.126(21)^*	0.067	.012	0.931	.036	0.028
5-Factor	270.909(166)^*	142.307(20)^*	0.045	.022	0.972	.041	0.021
6-Factor	219.867(147)^*	43.619(19)^*	0.040	.005	0.980	.008	0.018
7-Factor	—	—	—	—	—	—	—

Note. * p < .001.

Upon estimating the new ESEM model, and as reported in Table 1, fit indices provided support for a 5-factor structure, as it was a significant improvement upon the 4-factor model, Δχ²(27) = 129.491, p < .001, ΔRMSEA = .010, ΔCFI = .029, but was not significantly different from the 6-factor model, Δχ²(26) = 55.112, p = .001, ΔRMSEA = .001, ΔCFI = .009. However, closer examination indicated several items did not meaningfully load |> .60| on to any one particular factor, and one factor had no meaningful loadings. Paralleling the process before, we identified 6 items that were consistently poorly loading across the 3- to 5-factor model. These items were subsequently dropped, and the ESEM was estimated a third time. As indicated in Table 1, model fit provided evidence for a 6-factor structure, but two factors had no items with a meaningful loading. Although no items were found to consistently function poorly across the viable factor solutions (4-, 5-, and 6-factor models), one item was found to not meaningfully load in the 4-factor and 6-factor.

Subsequently, the fourth iteration of the ESEM model supported a 5-factor structure, but once again, one factor did not have any items with meaningful loadings. Given that the 4-factor model was associated with adequate-to-good model fit, χ²(186) = 441.542, p < .001, RMSEA = .067, CFI = .931, SRMR = .028, and all items had significant and meaningful factor loadings and all factors consisted of three or more items, the 4-factor model was put forth as the championed model. It is worth noting, modification indices suggested a residual correlation between item 56 (“I have to go to important appointments with my parents to translate for them”) and 61 (“I spend a lot of time going places with my parents to translate for them”). To improve model fit, and ensure a simple factor structure, item 56, which had the lowest loading onto its respective factor, was dropped. The final 4-factor model was associated with good model fit, χ²(167) = 289.85, p < .001, RMSEA = .049, CFI = .964, SRMR = .024.

The standardized factor loadings are reported in Table 2. All items loaded on to a primary factor above the recommended threshold (i.e., |.6|). Moreover, although all items were allowed to cross-load, cross-loadings were below |.3|, with one exception. Specifically, item 3, “I have been criticized by other Hispanics/Latinos because of the way I speak Spanish,” which primarily loaded onto the Spanish criticism factor (λ = .632), had a cross loading of .326 with within-group discrimination. Although there has been some inconsistency regarding the suggested cut-off scores for cross-loading items, the cross-loading may indicate a complex factor structure (Sass & Schmitt, 2010). However, to avoid a two-item factor, item 3 was retained in the model.

Table 2.

Standardized Factor Loadings for Final Championed Model

Item	Wording	Exclusionary political climate	Language brokering	Within-group discrimination	Spanish criticism
Item 4	I think our current president is a threat to Hispanics/Latinos.	0.694	−0.169	−0.044	0.028
Item 6	With the current political situation, I have felt more fearful.	0.668	−0.005	0.007	0.085
Item 10	Tougher immigration laws make me afraid for my or my family’s future in this country.	0.772	0.115	0.024	−0.138
Item 16	Hearing politicians or people in the media say bad things about immigrants makes me feel upset or angry.	0.749	−0.105	−0.002	0.021
Item 18	With the current political situation, I think students are more afraid about what may happen to them or their families.	0.669	0.137	0.023	0.071
Item 22	I am worried what the end of DACA and other protections would do to my family or friends.	0.707	0.155	0.049	0.001
Item 43	I worry about attacks against Hispanic/Latinos.	0.744	−0.005	0.007	0.027
Item 27	I am worried that people I love will be deported.	0.810	0.064	0.010	−0.128
Item 17	When my family members go to the doctor, I often go with them to help them understand what the doctor is saying.	0.111	0.624	−0.001	0.005
Item 23	I have to help my parents fill out forms in English.	0.001	0.891	0.037	−0.079
Item 28	I have to help my parents read documents in English.	−0.057	0.964	0.028	−0.011
Item 34	I feel like I’m responsible for helping my parents understand things in English.	0.087	0.838	−0.012	0.012
Item 39	I worry that I will translate something wrong or explain it to my parents wrong.	0.237	0.626	−0.124	0.220
Item 44	My parents rely on me to translate things from English to Spanish.	−0.013	0.857	−0.024	−0.065
Item 61	I spend a lot of time going places with my parents to translate for them.	0.117	0.679	0.073	−0.002
Item 2	Other Hispanics/Latinos often make fun of me because of the country my family is from.	−0.097	0.191	0.623	0.104
Item 21	Other Hispanics/Latinos have called me insulting names, like reffee or arrow-thrower.	0.074	−0.030	0.648	−0.106
Item 31	Other Hispanics/Latinos often tell me I’m too Hispanic/Latino or not American enough.	0.004	0.150	0.680	−0.010
Item 32	I have been bullied at school by other Hispanic/Latino kids because of my skin color.	0.126	−0.051	0.604	0.043
Item 37	I have been bullied at school by other Hispanic/Latino kids because of the country me or my family is from.	0.061	−0.082	0.713	−0.004
Item 3	I have been criticized by other Hispanics/Latinos because of the way I speak Spanish.	−0.071	0.052	0.326	0.632
Item 15	I feel uncomfortable speaking Spanish around other Hispanics/Latinos because it is not my first language.	0.028	−0.251	−0.015	0.688
Item 36	Other Hispanics/Latinos criticize me for not speaking Spanish well enough.	0.152	−0.033	0.185	0.635

Note. Factor loadings in bold are those above the |> .60| threshold identified as meaningful in prior research (Brown, 2015).

Items loading on the first factor largely reflected fear and concerns associated with deportation and the broader political context. This subscale taps into the youth’s perception of anti-immigrant and xenophobic rhetoric that have pervaded political discourse and social media (e.g., Castañeda, 2019). This first factor was labeled exclusionary political climate. The second factor largely reflected experiences with youth having to translate for their parents. Consistent with the broader literature (e.g., Weisskirch, 2017), this factor was labeled language brokering. Items loading onto the third factor were items from the within-group discrimination theme, reflecting experiences of being bullied and discriminated against by other HL youth on basis of nationality, skin color, or for being too enculturated. For this reason, this factor was labeled within-group discrimination. Lastly, a second factor stemming from the within-group discrimination items emerged but primarily reflected experience of youth in which they felt criticized for their low Spanish proficiency. For this reason, this last factor was labeled Spanish criticism. Table 3 presents intra-factor correlations as well as McDonald’s (1999) Omega coefficient, an indicator of composite reliability similar to Cronbach’s Alpha, for each factor.

Table 3.

Intrafactor Correlations and McDonald’s Omega

Cultural stressors	1	2	3	Ω
1. Exclusionary political climate				.900
2. Language brokering	.450			.920
3. Within-group discrimination	.261	.125		.829
4. Spanish criticism	.242	−.171	.229	.774

Note. Ω = McDonald’s Omega.

Evidence for Concurrent Validity

Next, to provide evidence for concurrent validity, we examined the relationship between the extracted cultural stressors and symptoms of depression and anxiety, self-esteem, and alcohol use. We controlled for age, gender, and nativity. As indicated in Table 4 and shown in Figure 1, Spanish criticism was negatively associated with self-esteem (β = −.230, p = .001) and positively associated with both symptoms of depression (β = .205, p = .004) and anxiety (β = .228, p = .001). Exclusionary political climate was positively associated with both alcohol use (IRR = 2.232, p = .003) and symptoms of anxiety (β = .169, p = .009).

Table 4.

Path Estimates for Criterion Validity Model

Outcome	Cultural stress factor	Estimate	p value	95% CI
Alcohol use	Exclusionary political climate	2.232	.003	1.320 to 3.777
	Language brokering	1.1445	.438	0.813 to 1.611
	Within-group discrimination	1.209	.371	0.798 to 1.833
	Spanish criticism	1.327	.251	0.818 to 2.153
Self-esteem	Exclusionary political climate	−0.088	.221	−0.229 to 0.053
	Language brokering	−0.128	.076	−0.268 to 0.013
	Within-group discrimination	−0.083	.155	−0.197 to 0.031
	Spanish criticism	−0.230	.001	−0.362 to −0.097
Symptoms of depression	Exclusionary political climate	0.111	.141	−0.037 to 0.260
	Language brokering	0.077	.292	−0.066 to 0.221
	Within-group discrimination	0.104	.113	−0.025 to 0.233
	Spanish criticism	0.205	.004	0.065 to 0.346
	Exclusionary political climate	0.169	.009	0.043 to 0.296
	Language brokering	−0.010	.888	−0.143 to 0.124
	Within-group discrimination	0.118	.054	−0.002 to 0.238
	Spanish criticism	0.228	.001	0.100 to 0.357

Notes. Estimates for Alcohol Use represent Incident Rate Ratios (IRR) whereas estimates for all other variables are standardized path estimates.

Figure 1.

Path Estimates for Criterion Validity Model

Discussion

Despite this burgeoning research on cultural stress, scholars have called for greater attention to capture a wider breadth of cultural stressors and challenges pertinent to HL youth (Meca & Schwartz, 2024), particularly in light of recent increases in anti-immigrant and xenophobic rhetoric (e.g., Castañeda, 2019). Towards this end, the current study utilized themes extracted from recently published qualitative work (Vos et al., 2021), feedback from an advisory panel of experts in HL youth and cultural stress, and cognitive interviews in order to develop the MICS and capture a wider breadth of cultural stress experiences rooted in anti-immigrant, xenophobic rhetoric and acculturative stressors. As a whole, the current study provided initial evidence for the validity of the MICS.

Factor Structure of the MIC

Based on psychometric analysis, the final measure consisted of 23 items and a 4-factor structure consisting of exclusionary political climate (i.e., youth’s perception of anti-immigrant and xenophobic rhetoric that has pervaded politics and social media), Spanish criticism (i.e., in which they felt criticized for their low Spanish proficiency), within-group discrimination (i.e., experiences of being bullied and discriminated against by other HL youth for being too enculturated), and language brokering (i.e., experiences with having to translate for parents). Moreover, these cultural stressors uniquely accounted for variance in several indicators of psychosocial functioning, in theoretically consistent ways, thus providing preliminary evidence for concurrent validity.

Consistent with Vos et al.’s (2021) work, several items were generated capturing the increasingly prevalent exclusionary political climate. The fact that these items both emerged as key factors and were retained speaks to the degree to which the broader sociopolitical context represents a unique stressor, over and above other cultural stressors. As previously noted, HL populations have been increasingly blamed for economic and social problems (e.g., Castañeda, 2019). Because HL populations have perceived increases in experiences of discrimination (Callister et al., 2019) and higher anxiety surrounding immigration policy following the 2016 presidential election (Eskenazi et al., 2019), the emergence of this factor was not surprising. Perceptions of xenophobia and fear of deportations are on the rise and, since the first Trump administration, have been at the highest point in recent history among HL youth and adults (Roche et al., 2018). With the start of the second Trump administration in 2025, which have made mass detainment and deportation (American Immigration Counsel, 2026), and the abolishment of birthright citizenship (Exec. Order No. 14, 160, 2025) core priorities, items capturing an exclusionary political climate may become even more relevant. Exclusionary political climate differs from negative context of reception in that, whereas negative context of reception focuses more on perceived hindrance to opportunities or social economic mobility, exclusionary political climate focuses more on fear, anxiety, or lack of perceived safety tied to the specific political rhetoric and climate. This may be more developmentally appropriate for youth in high school, who are not actively contending with entering the workforce or other life milestones.

Although items were originally generated to capture within-group discrimination broadly, items corresponding to within-group discrimination split into two factors: Spanish criticism and within-group discrimination. As a whole, Spanish criticism represented experiences in which HL youth were judged regarding their low Spanish language competency. This cultural stressor is highly consistent with the broader literature on bicultural stress (Romero & Van Campen, 2011), which included monolingual-based stressors rooted in the pressure to maintain one’s cultural heritage (Torres et al., 2012). Consistent with the initial qualitative findings (Vos et al., 2021), experiencing Spanish criticisms may serve as a form of in-group identity threat as it may serve to invalidate people’s own identification with their heritage culture. Informed by social identity theory (Tajfel, 1981), Branscombe et al. (1999) posited that experiences that invalidate one’s status as a group member can pose a threat to one’s personal identity. Consistently, prior research has shown that HL youth encounter experiences in which their American identity is denied (e.g., Kiang et al., 2019). Findings from the current study additionally highlight the ways in which identity threats can originate from the within-group and threaten ones’ ethnic-racial identity. Future research should explore other forms of within-group pressures that may compromise HL youth’s ties to their heritage culture.

Items that reflected discrimination based on skin color, nationality, and acculturative orientation grouped together, largely reflecting within-group discrimination as conceptualized by prior work (Basáñez et al., 2019). The emergence of the within-group discrimination factor highlights that HL youth may hold xenophobic beliefs about other HLs based on country of origin, immigrant generation status, or skin color (Basáñez et al., 2019; Chavez-Dueñas et al., 2014). Indeed, prior research has found that more established (e.g., U.S.-born, longer-term immigrant) HL youth may disparage more recent immigrants (e.g., Córdova & Cervantes, 2010). It is important to note however, as emphasized by Córdova and Cervantes (2010), within-group discrimination is rooted in a sociopolitical hierarchy established during the colonization of indigenous peoples. Both in-group identity threats and within group discrimination are dimensions of intragroup marginalization, or the perceived rejection by people of one’s own ethnic group (Castillo et al., 2007). Intragroup marginalization is subversive to building a sense of belonging and sense of self.

The final factor that emerged within the psychometric analysis was language brokering, referring to experiences with youth having to translate for their parents (Tse, 1995). The emergence of this factor is consistent with the broader literature on language brokering (see Weisskirch, 2017, for a collection of reviews). Language brokers themselves report both positive and negative feelings (López et al., 2019). Although some language brokers report a greater sense of responsibility for their families (e.g., Martinez et al., 2009), some youth find the experience of language brokering to be stressful, particularly when the situation is beyond their language capabilities or tied to the well-being of the family, such as translating medical information or legal documents (Anguiano, 2018). In the context of the language brokering subscale, the highest loading item specified a sense of responsibility on behalf of the youth for the welfare of their parents. As such, this factor may be indicative of language brokering that may detrimentally impact family dynamics, as youth are forced to take on adult roles, potentially resulting in parentification (Burton et al., 2018; Roche et al., 2014).

It is worth noting that although the full 63-item battery contained items that tapped into discrimination from the majority group, despite our hypothesis, it did not emerge as a factor within our psychometric analysis. This is particularly surprising given the extensive wealth of research that has documented the detrimental impact of discrimination (e.g., Sawyer et al., 2012). Because this study was conducted in predominantly HL communities among adolescents who attended primarily HL schools, it is possible that the adolescents typically interacted with other HLs in their daily lives and had fewer opportunities to experience discrimination from White people or other ethnic-racial groups. Indeed, research indicates that, in terms of HL individuals’ experiences, ethnic enclaves may be qualitatively different from other types of communities (e.g., Portes & Rumbaut, 2014). Alternatively, these findings may indicate the importance of examining the source of discrimination, wherein in-group discrimination may be more disruptive to identity formation than outgroup discrimination. Future studies in more heterogeneous communities might find more evidence of discrimination from White people or other ethnic-racial groups.

Similarly, and despite the extensive research on acculturation or intergenerational gaps (for review, see Lui, 2015), items capturing acculturation gaps did not make it to the final measure. It is possible the lack of cohesion of these items stemmed from the specific sociohistorical context of this data. Indeed, as noted by Vos et al. (2021), participants not only noted a fear of their parents being deported based on the sociopolitical conversation spearheaded by the Trump administration at the time, but they had concerns for their parents’ well-being and indicated they felt pressure to help their parents. As a result, acculturation gaps may not have been a particularly salient stressor at the time, resulting in items failing to coalesce into a singular factor. Concurrently, it is worth noting the data collected for this study in particular occurred during the COVID-19 pandemic. It is possible that during this period, HL youth’s experiences with their caregivers were much more diverse and heterogenous while home schooling, which perhaps gave caregivers a greater window into the lives of their adolescent children. Alternatively, youth may have fallen into family habits and were therefore less likely to be influenced by their friends and peers at school to gravitate towards U.S. culture. Future research is necessary to replicate these findings and determine whether acculturation-gap represents a distinct cultural stressor. Regardless, the lack of discrimination and acculturation-gap subscale does limit the capacity of the MICS to fully capture an important element of cultural stress and suggest the need for the MICS to be utilized in conjuncture with other established measures of discrimination. Despite this, the MICS makes an important contribution by extending our operationalization of cultural stress to include relevant to sociopolitical threats and stressors rooted in within-group dynamics.

Unique Effects of Cultural Stress on Psychosocial Functioning

Some important findings emerged vis-à-vis the associations of the various forms of cultural stress factors and psychosocial functioning. To begin with, Spanish criticisms were positively associated with symptoms of anxiety and depression and negatively associated with self-esteem. This finding is highly consistent with the broader literature on identity denial experiences that have largely focused on others’ rejection of one’s identity as American (e.g., Kiang et al., 2019). Indeed, identity denial experiences and microaggressions have been found to have harmful downstream effects on psychological health among Asians and Latinos (e.g., Nadal et al., 2014). These findings may also be understood within the context of a social identity theory (Tajfel & Turner, 2004). In this context, Spanish criticism likely serves as a within-group identity threat that may undermine the degree to which HL youth are able to maintain ties to their cultural heritage. Given the critical role that ethnic-racial identity plays in psychosocial functioning (for a comprehensive review, see Meca et al., 2023), invalidation of one’s heritage-cultural identity is likely to be particularly disturbing to one’s personal identity (Meca et al., 2022), and therefore to one’s overall functioning.

Political climate was positively associated with both alcohol use and symptoms of anxiety. These findings are consistent with recent research emphasizing the detrimental impact of the broader political rhetoric and policy on HL well-being (e.g., Eskenazi et al., 2019; Wray-Lake et al., 2018). Exclusionary political climate, in particular, represents a stressor rooted in the broader macro-level of youth’s ecology, and as a result, it is far removed from youth’s direct capacity to impact or respond to the situation. As shown by Vos et al. (2021), youth indicated they felt helplessness and feelings of being stuck in limbo waiting on residency status updates. For example, in response to fears about their parents’ deportation, youth said “Like for example, if immigration takes them away from me, what am I supposed to do? What are my parents supposed to do? Yeah” (Vos et al., 2021, p. 225). As such, it is not surprising that this stressor was particularly associated with higher symptoms of anxiety. Moreover, for these youth, alcohol use may serve as a way by which they cope with these feelings of anxiety and the feelings of helplessness they feel in the context of this specific stressor.

Surprisingly, neither language brokering nor within-group discrimination were significantly associated with psychosocial functioning. It is possible that these stressors operate in more indirect ways. Language brokering has been found to be positively associated with alcohol and marijuana use through family-based acculturative stress (e.g., Kam & Lazarevic, 2014). Alternatively, other factors may mitigate the association between language brokering or within-group discrimination with psychosocial functioning. Based on Lazarus and Folkman’s (1984) transactional model of stress and coping, stressors may be either reduced or amplified based on one’s coping strategies in the face of said adversity. As such, coping strategies or other factors may play important roles in moderating the association between these stressors and psychosocial functioning. Additionally, although the present study utilized a wide breadth of outcomes, it is possible that language brokering or within-group discrimination impacted youths’ functioning in other domains of psychosocial functioning, such as academic or interpersonal functioning.

Limitations and Future Directions

The present results should be considered in light of several limitations. First, as previously noted, because of the COVID-19 pandemic, recruitment was changed from in-person to virtual—creating unique challenges that led to a smaller than anticipated sample; this may have limited our capacity to detect significant associations between cultural stressors and psychosocial functioning. Moreover, the smaller than expected sample size made it impossible to examine measurement invariance across gender, nativity, and site—all of which represent key social positionality variables that are likely to impact both the prevalence of specific cultural stressors and their associations with adjustment (Meca & Schwartz, 2024). Future research, with larger samples, is necessary to confirm the identified factor structure for the MICS and establish measurement invariance. Second, and building on this limitation, it is important to contextualize the findings within the specific sociohistorical setting. Data were collected towards the end of the first Trump administration, during COVID-19, and before the death of George Floyd and Breonna Taylor and the subsequent Black Lives Matter protests. Although the final items, including those that capture the exclusionary political climate, largely represent concerns that are not tied to a specific administration, it is unclear whether our findings will replicate in different political climates.

Third, the cross-sectional nature of this study not only prevented us from establishing longitudinal measurement invariance but also limited our capacity to provide evidence for predictive validity. As such, future longitudinal research is necessary to ensure the meaning and interpretation of items included in the MICS do not vary as a function of time and to establish the predictive nature of the observed findings. Fourth, although the multisite design of the current study represents an important strength, it is nonetheless important to note that both Los Angeles and Miami have large HL populations and represent well established contexts of reception for HL youth. As such, results may have been different in other cities or in “new receiving communities,” where many HL immigrants are settling and where local and state policies may be less apt to accommodate immigrant populations or more greatly impacted by anti-immigrant attitudes (Kiang et al., 2011). Lastly, given recent research focused on how HL adolescents manage or cope with discrimination (Carlo et al., 2022; Christophe et al., 2019), future work should focus on how HL adapt and cope with the specific stressors identified within the MICS (i.e., exclusionary political climate, language brokering, within-group discrimination, and Spanish criticism).

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

Despite these and other limitations, the present findings have important implications for practice, advocacy, education and training, and research. Indeed, for practice, the MICS may serve as a particularly useful instrument for administering to HL adolescents to ascertain the degree to which they are experiencing cultural stressors. Given our findings, and those of prior studies (e.g., Cano et al., 2015; Schwartz et al., 2015) highlighting the detrimental impact of cultural stressors on HL adolescents, participants reporting high cultural stress, particularly high levels of exclusionary political climate, language brokering, and Spanish criticism may be at risk for maladjustment. Although the MICS is not designed to be diagnostic, at the very least, the MICS can serve as a useful starting point for discussion between counselors and HL adolescents to understand the cultural stressors they are experiencing and identify healthy coping strategies (Carlo et al., 2022). Furthermore, given the particular negative impact of exclusionary political climate on substance use and anxiety, regardless of whether counselors utilize the MICS, the current findings highlight the need for counselors to be mindful of the broader sociopolitical context and the potential impact it may be playing in the lives of HL adolescents.

For advocacy, these findings have at least two potential implications. First, by placing words to the specific cultural stressors experienced by HL adolescents, the present findings can serve as a starting point for developing a lexicon around cultural stress that could be leveraged to increase awareness of relevant stressors experienced by the community. Given that several of the stressors were rooted in within-group dynamics, there are substantive opportunities through advocacy and community engagement to address these stressors. Secondly, our findings highlight the need for work at the structural level to turn down the broader exclusionary socio-political rhetoric. Advocacy rooted on humanizing the experiences of HL immigrants and children of immigrants may serve as a start point, although such work may be particularly difficult within the current political climate and its “anti-Diversity, Equity, and Inclusion (DEI) agenda” (Ng et al., 2025). In the context of education and training, the MICS may serve as a useful way by which educators can introduce aspiring therapists to CST (Meca & Schwartz, 2024) and stressors specific to the experiences of HL populations. Special attention can be given to HL therapists to ensure they themselves do not propagate within-group forms of cultural stress against HL clients.

Finally, and not surprisingly, our findings have the greatest implications for research moving forward. Indeed, given that the key focus of this study was on developing a new tool to assess cultural stress in a matter more aligned with CST, the current study will lead to new avenues of research focused on a more comprehensive and multidimensional operationalization of cultural stress, a key avenue of future research (Meca & Schwartz, 2024). As outlined above, future work is necessary to confirm the factor structure for the MICS and establish measurement invariance.

Conclusion

In conclusion, the present study introduces a new cultural stress scale that can complement existing cultural stress measures among HL youth. We identified subscales that are not currently assessed within existing measures—language brokering, exclusionary political climate, and two distinct forms of within-group cultural stress dimensions (discrimination and Spanish criticism). The subscales that we identified directly stem from HL adolescents’ perceptions of cultural stress and hold the potential to predict behavioral and mental health outcomes within this population. We hope that our scale will find use alongside existing measures.

Supplemental Material

Supplemental Material - Development of the Multidimensional Inventory of Cultural Stress Measure for Hispanic/Latine Adolescents

Supplemental Material for Development of the Multidimensional Inventory of Cultural Stress Measure for Hispanic/Latine Adolescents by Alan Meca, Saskia R. Vos, Ingrid Zeledon, Jennifer B. Unger, Daniel W. Soto, Ryan Lee, Pablo Montero-Zamora, Maria Duque, Beyhan Ertanir, Eric C. Brown, Seth J. Schwartz in The Counseling Psychologist.

Footnotes

ORCID iDs

Alan Meca

Beyhan Ertanir

Seth J. Schwartz

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by National Institute of Child Health and Human Development, HD095636.

Supplemental Material

Supplemental material for this article is available online.

Notes

Author Biographies

Alan Meca, PhD, is an associate professor of psychology at the University of Texas at San Antonio. His research interests include identity development across a variety of domains (e.g., ethnic-racial identity, parental identity, military identity, etc.) and acculturation processes among immigrant populations.

Saskia R. Vos, PhD, MPH, is a former researcher at the University of Miami Miller School of Medicine. Her research interests include trauma, immigration, and the epidemiology of suicide and homicide in the United States. She has published over 15 scholarly articles and presented work at multiple national conferences.

Ingrid Zeledon, PhD, is a former researcher at the University of Southern California. Her research interests have included (1) Needs assessment of opioid substance use disorder services available in American Indian Alaska Native (AIAN) tribes throughout California, (2) understanding how to empower Latina women diagnosed with breast cancer, and (3) studying the association of cultural and immigration-related stressors on mental health in Hispanic/Latinx youth.

Jennifer B. Unger, PhD, is a professor of population and public health sciences at the University of Southern California Keck School of Medicine. Her research focuses on the psychological, social, and cultural influences on health-risk and health-protective behaviors among diverse populations. She has conducted longitudinal studies of acculturation, cultural stress, and substance use among Hispanic adolescents, highlighting the role of discrimination in health-risk behaviors.

Daniel W. Soto, EdD, MPH, is an assistant professor at the University of Southern California, Keck School of Medicine. He directs the Center for Population Health (CPH). He has over 20 years of population-based health behavior research experience and seven years of curriculum design and teaching experience with graduate and undergraduate programs in public health. Dr. Soto has led research and evaluation efforts on several longitudinal and cross-sectional studies of acculturation, mental health, diabetes prevention, substance use, addressing health disparities, preventing the spread of infectious disease, and tobacco control.

Ryan Lee, MPH, is a project manager for the University of Southern California, Department of Population and Public Health Sciences. He has over five years of experience successfully managing over 10 federal, state, and foundation funded research and evaluation studies that focus on stress and acculturation, mental health, substance use prevention and tobacco control, infectious disease prevention, and addressing health disparities. He currently manages two National Institutes of Health (NIH) funded research projects that focus on substance use prevention among communities of color.

Pablo Montero-Zamora, PhD, is an assistant professor at the University of Texas at Austin, College of Education. His research focuses on how contextual and familial factors influence substance use and mental health, particularly among Latino populations. Specifically, he examines how cultural stressors (e.g., discrimination), migration, and social norms shape family dynamics, including family conflict, resulting in both antisocial and prosocial behaviors among parents and youth. By examining these etiological associations and their potential variations across different population subgroups, his research aims to inform the development, implementation, and evaluation of culturally adapted, evidence-based interventions.

Maria Duque, PhD, is a behavioral scientist whose research resides at the intersection of positive psychology, intergroup processes, and political behavior. Much of her work centers on the ways human beings thrive will navigating global social complexities (e.g., mass migration, climate change, and political divide), and how mental health outcomes change when the sociocultural context shifts from “me and you” to “us and them”.

Beyhan Ertanir, PhD, is a post-doctoral researcher at the School of Education of the University of Applied Sciences and Arts Northwestern Switzerland. She received her PhD in Psychology from Heidelberg University, Germany, in 2020. Beyhan is passionate about understanding and promoting the positive development of children and adolescents of immigrant and multilingual backgrounds using various quantitative research methods. Her current research aims to shed light on the interplay between acculturative and developmental tasks and the mental health of minority youth.

Eric C. Brown, PhD, is a professor in the University of Miami’s Department of Public Health Sciences at the Miller School of Medicine, where he directs the PhD program in Prevention Science and Community Health. He is principal investigator of the Prevention Education and Research in Latin America (PERLA) lab, which focuses on the adaptation, dissemination, and implementation of preventive interventions for youth alcohol, tobacco, and other drug (ATOD) use in Latino/a youth populations. Dr. Brown’s specific interests center around the application of advanced research methods to measure ATOD risk and protective factors, and to evaluate the implementation and effectiveness of preventive interventions in the region.

Seth J. Schwartz, PhD, is a professor of kinesiology, health education, and educational psychology at the University of Texas at Austin. His research focuses on identity, immigration, acculturation, cultural stress, and crisis migration. He has authored more than 450 scholarly publications and has been principal investigator on 9 federally funded grant awards.

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