What do We Know About Acculturation? A Measurement Invariance Examination of Acculturation Domains Between Asian and Latinx Populations

Abstract

Objectives:

Acculturation has emerged as a key variable in racial/ethnic minorities and immigrant research. Although findings generally conclude acculturation leads to adverse outcomes (e.g., risk behaviors), scholars often find contradicting results. This increased attention to the core definitional questions about what acculturation is and how it should be measured, specifically across different racial/ethnic groups.

Methods:

This study examined the measurement invariance using Multigroup Confirmatory Factor Analysis (MG-CFA) by comparing three common domains of acculturation measures across Asian and Hispanic populations (i.e., Ethnic Identification, Language Proficiency and Preference, and Acculturative Stress) using the National Latino and Asian American Study (NLAAS).

Results:

A total sample of 4,649 (n_Latinx=2,554 and n_Asian=2,095) was used. The results suggested that aspects of ethnic identification and acculturative stress measures significantly varied between groups. For example, Latinxs had higher factor loadings in certain Acculturative Stress items related to government and legal status. In contrast, Asians had higher factor loadings in an item related to Ethnic Identification.

Conclusions:

The results suggested that aspects of acculturation do not necessarily measure the same way across all populations; researchers/clinicians should consider racial/ethnic specific scales when using acculturation related measures. Future research should test universal acculturation scales across other ethnic subgroups and include more complex acculturation measures like cultural values and norms.

The enactment of Immigration and Nationality Act of 1965 enabled an influx of non-European immigrants, largely from Latin America, Asia, Africa, the Caribbean, and the Middle East, into the United States (Schwartz et al., 2010). Scholars recognized the unique challenges and difficulties Latin and Asian immigrants face which are different than earlier generations of immigrants of European decent (Xie & Greenman, 2005). Thus, immigration-related factors such as acculturation have emerged as a key variable in ethnic minority research. This increased attention to acculturation has been accompanied by core definitional questions about what acculturation is and how it functions. In earlier research, while sociologists viewed acculturation as a process of irreversible accommodation and eventual assimilation into the host culture group (Gordon, 1964), anthropologists described acculturation as a process of interactivity between cultures (Redfield et al., 1936). Both anthropologists and sociologists defined acculturation as a process that occurs at the group/population level (Barnett, 1954). More recently, psychologists have focused on individual differences or within-group heterogeneity. For example, Berry (2003) proposed acculturation as a two separate processes framework: 1) maintenance of the original culture and 2) development of relationships with the new culture; acculturation involves adoption of values, attitudes, and behaviors of the host society.

Ethnic Identification

Phinney (1990) suggests that Ethnic Identity is an aspect of acculturation that focuses on the subjective sense of belonging to the culture. Early empirical studies on acculturation and ethnic identity suggest that acculturating individuals are more likely to forget or surrender their ethnic traditions (Berry & Annis, 1974). In recent years, scholars have begun to view the acceptance of one culture and the abandonment of the other as two separate practices and can co-occur (Berry, 1990). This two-dimensional process recognizes the need to address two major aspects of sense of belonging within the context of the new and original cultures (e.g., preserving one’s heritage culture and the adaptation of the host society) and can be both secure or undeveloped concurrently (Phinney et al., 2001).

English Language Proficiency and Preference

Like Ethnic Identification, the view on the acquisition of a second language can differ depending on how one views the acculturation process (i.e., linear vs. multi-dimensions). Under a linear continuum view, learning the language of the host society occurs at the expense of the native language and culture (Schumann, 1990). On the other hand, others have argued that one does not necessarily suffer any language loss when acquiring a new language (i.e., bilingualism), which aligns with the two-dimensional process approach described by Berry (1990) and Phinney (2001). In general, language proficiency and preference are acculturation behavioral indicators and found to be valid measures of acculturation (Hunt et al., 2004) and explain a large proportion of variance in acculturation (Coronado et al., 2005).

Acculturative Stress

Acculturative Stress is a stress reaction associated with the process of acculturation; it is rooted in the intercultural contact between the individual and the host society (Berry, 2006). In a unidimensional approach to acculturation, acculturative stress is viewed as stressors specifically pertain to the immigrant experience and the level of acculturation is inversely correlated with the degree of acculturative stress (Caplan, 2007). Others have described acculturative stress as a related but distinct construct from acculturation. For example, a study found that level of acculturation did not correspond to the level of acculturative stress (Hovey & King, 1996). Similarly, the bi-dimensional perspective views acculturative stress as a construct that encompasses other facets of the immigrant experience such as discrimination and loss of cultural values that extend beyond generation post immigration (Caplan, 2007).

Group Differences in Acculturation

Literature suggests that acculturation may differ between Latinx and Asian Americans due to factors such as socioeconomic status and the context of reception by the host country (Portes & Rumbaut, 2006). For example, Asian immigrants are portrayed as “model minority” due to their good socioeconomic standing (Wong et al., 1998) while many Latinx migrants are low-wage workers with minimal human capital (Portes & Zhou, 1993). It has been reported that Latinx Americans have higher poverty (15.7%) and lower college graduation (18.8%) rates compared to Asian Americans’ 7.3% and 58.1%, respectively (Creamer, 2020; U.S. Census Bureau, 2020). Exemplified by the recent unethical and unlawful practice of the Immigration and Customs Enforcement (ICE), Latinx Americans are also more likely to be targets of harmful immigration policies and discrimination (Tran et al., 2010). Consequently, many Latinx Americans may be more likely to remain isolated from the larger U.S. culture and become less acculturated than Asian Americans. Studies have confirmed that Latinx Americans experienced higher stress levels associated with acculturation than Asian Americans (Kimbro et al., 2014).

There does not seem to be a census on Ethnic Identification group differences across the two populations. For example, studies have found that Asian and Latinx adolescents both showed similar levels of ethnic identity (Hsiao & Wittig, 2008) while others have found Asian students have lower ethnic identity scores than their Latinx counterparts (Phinney & Alipuria, 1990). It has also been suggested that Southeastern Asian refugees tend to maintain a stronger ethnic orientation compared to Latinx immigrants (Wong-Rieger & Quintana, 1987) which implies patterns could be sample or context-specific.

Acculturation and Health/Mental Health

A large body of literature has been devoted to explaining the existing relationship between acculturation and health, particularly in Hispanic Americans (Lara et al., 2005; Thomson & Hoffman-Goetz, 2009) and Asian Americans (Suinn, 2010). Furthermore, contemporary theories suggested that the link between acculturation and mental health outcome is likely mediated by other variables (Organista et al., 2003) such as acculturative stress (Hwang & Ting, 2008). Due to its complexity, acculturation research often yields inconsistent findings in relation to health outcomes (Castro, 2007). For example, studies have shown that acculturation is associated with either higher (Moscicki et al., 1989), lower (González et al., 2001), or no difference (Cuellar & Roberts, 1997) in depression risk among Latinx population. Similarly, among Asian Americans, acculturation has been associated with better (Chou et al., 2010), worse (Acevedo-Garcia et al., 2010), and no difference (John et al., 2012) in self-rated health. These inconsistencies call into question how acculturation is measured.

How is Acculturation Measured?

It is important to note that the operational definition of acculturation can dictate the direction and magnitude of its effect. The operationalization and measurement of the acculturation process are often viewed as problematic (Thomson & Hoffman-Goetz, 2009) and what has changed as a result of acculturation has been challenging to pinpoint. The most commonly referenced domains have included language use and other cultural behaviors (Szapocznik et al., 1980), values and attitudes (Berry et al., 2006), and ethnic/heritage identity (Phinney & Ong, 2007). Generally, acculturation measures employ various methodological approaches, including scale and non-scale (Choi et al., 2008). Numerous standard scales have been developed to assess various domains and dimensions of acculturation. For example, the Ethnic Identity Scale (Umaña-Taylor et al., 2004) is often used to measure ethnic identification while others focus on aspects of acculturation specific to the population.

Non-scales use proxy measures and they are widely used as indicators of acculturation in population studies like public health (Lara et al., 2005; Thomson & Hoffman-Goetz, 2009). Non-scales typically use a singular or a combination of indicators such as language, place of birth/immigration status, and age at immigration/length of residence to assess the dimensions of acculturation. Although they are quick and convenient (Lara et al., 2005) and psychometrically sound (Marin, 1992), non-scales do not always directly measure elements in attitudes or behaviors which limit the utility of the information (Thomson & Hoffman-Goetz, 2009).

Importance of Examining Racial/Ethnic Differences

Research has highlighted the importance of tailoring scale items and structure by examining differences across racial/ethnic groups and interpreting scores based on individuals’ cultures and backgrounds (Trent et al., 2013). Failing to consider systematic variations due to cultural and racial/ethnic differences (e.g., response pattern and symptom expression) can lead to inaccurate and misleading conclusions (Lambert et al., 2004). Thus, some researchers suggested that for certain groups, we should pay attention to the particular cultural elements specific to the groups (Rogler et al., 1991). As a result, many acculturation instruments are available specific for different racial/ethnic populations.

Examining Measurement Invariance

Measurement Invariance (MI) can mathematically explain measurement equivalence across groups to obtain accurate comparisons. MI requires the association between the items/test scores (i.e., the raw scores from the instrument) and the latent factors to be independent of group membership (e.g., ethnicity) or measurement occasion (time; Mellenbergh, 1989). If MI is not present in the instrument, the comparison of the raw scores is almost as if we are comparing apples to oranges, and subsequent analyses will become meaningless. Thus, measures must meet specific criteria in order for researchers to have confidence in any analyses dealing with group comparison. For these reasons, adequately examining MI in acculturation across ethnic subgroups is needed due to the erroneous research interest.

The construct Acculturation has been plagued by conceptual vagueness and too many definitions in the literature and the lack of understanding of how acculturation is measured across ethnic groups has limited research findings. The purpose of this study is to examine the MI in three commonly used acculturation domains (i.e., Ethnic Identification, Language Proficiency and Preference, and Acculturative Stress) across Asian and Latinx American samples.

Method

Participants

The National Latino and Asian American Study (NLAAS) is a nationally representative household survey of Latinx and Asian Americans that collected psychiatric information, environmental and sociocultural factors and experiences (Heeringa et al., 2004). The NLAAS used a multi-stage national area probability sampling with special supplements for adults of Puerto Rican, Cuban, Chinese, Filipino, and Vietnamese national origin. A final NLAAS sample of 2,554 Latinx and 2,095 Asian Americans were recruited and a detailed description can be found in the parent study (Heeringa et al., 2004).

Measures

Acculturation domains were examined at the level of latent variables, which correct for measurement error and indicator-specific influences. A description of the three latent constructs is in the following: Ethnic identification. Ethnic identification is a four items measure adapted from the National Comorbidity Survey-Replication (Crengle et al., 2012; Vega et al., 1998) to measure how closely the respondent identified with other people of the same racial/ethnic background, how much time they would choose to spend with others of the same racial/ethnic group, and cultural commitment to one’s racial/ethnic group, with values ranging. Higher scores indicate higher identification with individual’s ethnic/racial group.

English proficiency and preference.

English language proficiency is assessed using three items adapted from the Cultural Identity Scales for Latino Adolescents (Felix-Ortiz et al., 1994) intended to measure self-evaluated proficiency in speaking, reading, and writing English. English language preference includes three items – two questions ask, “What language do you speak with most of your [family/friends]?” and a third question asks, “In what language do you think?” Higher scores indicate higher proficiency and preference for English.

Acculturative Stress.

The Acculturative Stress scale, adapted from the Mexican American Prevalence and Services Survey (Vega et al., 1998) and the Occupational/Emotional Stress subscale of the Hispanic Stress Inventory (Cervantes et al., 1991), is a nine items scale used to assess legal stress, discrimination, and language barrier. Higher scores indicate higher stress related to acculturation.

Analysis

Confirmatory Factor Analysis (CFA).

Stata 14 (Stata, 2015) was used to examine CFA for each domain. Maximum likelihood estimation was used to fit the model and assess model fit. Model fit was evaluated using different fit indices, including χ²/df ratio (Bryant & Yarnold, 1995), the root mean square error of approximation (RMSEA; Steiger, 1990), standardized root mean residual (SRMR; Bentler, 1990), comparative fit index (CFI; Bentler, 1990), and the Tucker–Lewis index (TLI; Tucker & Lewis, 1973). Low values (<.10 for moderate fit, <.06 for good fit) are desired for RSMEA and SRMR, while high values (>.90 good; >.95 excellent) are desired for the CFI and TLI (Tucker & Lewis, 1973).

Multigroup Confirmatory Factor Analysis (MG-CFA).

Following steps outlined in Brown (2006), MG-CFA was used to determine if measurements were invariant across the Asian and Latinx samples. The procedure involved analyzing separate input matrices specific to each group and placing constraints on various parameters (i.e., factor loadings, intercepts, residuals, etc.). MG-CFA began with conducting simple CFAs using separated Asian and Latino subsamples to compare the adequate fit of each group. Then the analyses used the two populations simultaneously with constraints: Model 1) all parameters free (Configural Invariance); Model 2) loadings are invariant (Metric Invariance); Model 3 loadings & intercepts are invariant (Strong/Scalar Invariance); and Model 4) loadings, intercepts & residuals are invariant (Strict Invariance). A description of each model can be found in Gregorich (2006). A reduction of more than .01 in CFI (ΔCFI > .01) is deemed to be a significantly poorer fit (Cheung & Rensvold, 2002). Change of CFI was used as a benchmark because it is less susceptible to confounding influences from large sample sizes (Bentler, 1990), while chi-square tests are sensitive to sample size (Brown, 2014). It is also notable that it is rare for all items to evidence measurement invariance at all levels, particularly in cross-cultural psychometric research (Cheung & Rensvold, 1999). In this case, partial invariance was conducted in order to allow item(s) to vary across groups in order to determine which item(s) cause poor model fit.

Results

Basic descriptive statistics and reliability coefficients were calculated (Table 1). The Asian sample reported more English Proficiency and Preference (p < .001; d = .267) while the Latinx sample reported more Acculturative Stress (p < .001; d = . 277). Reliabilities were also examined and stratified by subgroups. While Language Proficiency and Preference (Cronbach_Asian’s α = .93 and Cronbach_Latinx’s α = .95) and Ethnic Identification (Cronbach_Asian’s α = .70 and Cronbach_Latinx’s α = .60) displayed moderate and high reliability across both Asian and Latinx samples, Acculturative Stress (Cronbach_Asian’s α = .58 and Cronbach_Latinx’s α = .69) displayed less than ideal threshold at α = .70 (Nunnally & Bernstein, 1994).

Table 1.

Descriptive statistics and reliabilities for Asian (N = 2,095) and Latinx (N = 2,554) samples.

		Asian Sample						Latinx Sample
		M	SD	Range	ɑ			M	SD	Range	ɑ
Ethnic identification	All	12.31	2.47	4 to 16	0.70		All	12.33	2.34	4 to 16	0.60
	Vietnamese	13.67	2.36	4 to 16	0.68		Cuban	12.87	2.25	5 to 16	0.59
	Filipino	11.88	2.33	5 to 16	0.65		Puerto Rican	12.14	2.21	4 to 16	0.54
	Chinese	12.31	2.47	4 to 16	0.70		Mexican	12.25	2.27	5 to 16	0.58
	Asian Others	11.90	2.45	4 to 16	0.70		Hispanic Others	12.08	2.56	4 to 16	0.66
English proficiency and preference	All	15.80	6.41	6 to 27	0.93		All	13.97	7.18	6 to 27	0.95
	Vietnamese	11.81	5.39	6 to 27	0.92		Cuban	12.15	6.71	6 to 27	0.95
	Filipino	20.07	4.75	6 to 27	0.85		Puerto Rican	16.73	6.45	6 to 27	0.93
	Chinese	15.80	6.41	6 to 27	0.93		Mexican	13.78	7.52	6 to 27	0.96
	Asian Others	18.68	5.10	6 to 27	0.86		Hispanic Others	13.94	7.08	6 to 27	0.95
Acculturative Stress	All	3.46	2.55	1 to 13	0.58		All	4.22	2.88	1 to 13	0.69
	Vietnamese	3.62	2.51	1 to 10	0.56		Cuban	3.92	2.58	1 to 11	0.63
	Filipino	2.67	2.10	1 to 11	0.55		Puerto Rican	3.01	2.27	1 to 10	0.60
	Chinese	3.46	2.55	1 to 13	0.62		Mexican	4.92	3.31	1 to 13	0.76
	Asian Others	3.50	2.55	1 to 11	0.59		Hispanic Others	4.30	2.69	1 to 12	0.59

Standardized factor loadings of the items were provided in Table 2 for context. Fit indexes and sample sizes for all CFA and multigroup models were presented in Table 3. While fit indexes indicated good to excellent fit in Ethnic Identification and English Proficiency and Preference (e.g., TLI and CFI were all >.95 across both groups), Acculturative Stress did not meet the moderate threshold for both populations (RMSEA_Asian = .120 and .RMSEA_Latinx = 122). There were also differences in terms of fit indices between groups. For example, RMSEA for both Ethnic Identification and English Proficiency and Preference were shown to be good fits for the Asian sample (0.057 and 0.070, respectively). However, the same fit indices for the Latinx sample were worse (RMSEA_{Ethnic Identification} = 0.070 and RMSEA_{English Proficiency and Preference} = 0.105).

Table 2.

Standardized factor loadings for Asian (N = 2,095) and Latinx (N = 2,554) samples.

			Factor Loading
Construct	Item	Item Content	Asian	Latinx	All
Ethnic identification	EI1	Identify with others of same racial/ethnic descent	0.73	0.73	0.73
	EI2	Feel close in your ideas/feelings w/ppl of same racial descent	0.80	0.86	0.83
	EI3	Amountt time would like to spend w/ppl of same racial/ethnic group	0.59	0.55	0.57
	EI4	Importance for same racial/ethnic group to marry within group	0.43	0.20	0.29
English proficiency and preference	EP&P1	How well do you speak English	0.93	0.95	0.94
	EP&P2	How well do you read English	0.97	0.98	0.98
	EP&P3	How well write English	0.95	0.96	0.96
	EP&P4	Language spoken with friends	0.86	0.92	0.90
	EP&P5	Language spoken with family	0.78	0.80	0.79
	EP&P6	Language in which you think	0.91	0.93	0.91
Acculturative Stress	AS1	Felt guilty about leaving family/friends in country of origin	0.22	0.29	0.27
	AS2	Same respect in US as in country of origin	0.37	0.25	0.31
	AS3	Limited contact with family and friends	0.23	0.37	0.33
	AS4	Interaction hard due to difficulty with English language	0.61	0.49	0.55
	AS5	Treated badly due to poor/accented English	0.69	0.59	0.60
	AS6	Difficult to find work due to Latino/Asian descent	0.66	0.66	0.66
	AS7	Questioned about legal status	0.13	0.42	0.32
	AS8	Think might be deported if go to social/government agency	0.15	0.51	0.40
	AS9	Avoid health service due to INS	0.16	0.51	0.41

Table 3.

CFA and MGCFA model fit statistics.

	Model	χ2	df	χ2/df	RMSEA	90% CI	SRMR	TLI	CFI	△CFI
Ethnic identification	All	37.570	2	18.79	0.062	[0.046, 0.080]	0.022	0.972	0.991	--
	Asian	15.560	2	7.78	0.057	[0.033, 0.085]	0.019	0.978	0.993	--
	Latinx	27.040	2	13.52	0.070	[0.048, 0.095]	0.026	0.963	0.988	--
	Configural	42.604	4	10.65	0.065	[0.048, 0.083]	0.023	0.970	0.990	--
	Metric	101.620	7	14.52	0.077	[0.064, 0.090]	0.046	0.958	0.976	−0.014
	Partial Metric*	51.298	6	8.55	0.057	[0.044, 0.072]	0.025	0.977	0.988	−0.002
English proficiency and preference	All	282.320	8	35.29	0.091	[0.082, 0.100]	0.022	0.982	0.991	--
	Asian	80.390	8	10.05	0.070	[0.057, 0.085]	0.024	0.988	0.993	--
	Latinx	212.420	8	26.55	0.105	[0.093, 0.117]	0.019	0.979	0.989	--
	Configural	292.810	16	18.3	0.091	[0.082, 0.101]	0.021	0.982	0.990	--
	Metric	343.69	20	17.18	0.088	[0.080, 0.097]	0.021	0.983	0.989	−0.001
	Scalar	476.580	24	19.86	0.095	[0.088, 0.103]	0.021	0.980	0.984	−0.005
	Strict	574.600	30	19.15	0.093	[0.087, 0.100]	0.023	0.981	0.981	−0.003
Acculturative Stress	All	1272.954	27	47.15	0.132	[0.126, 0.138]	0.084	0.527	0.645	--
	Asian	532.070	27	19.71	0.120	[0.111, 0.129]	0.087	0.534	0.650	--
	Latinx	565.287	27	20.94	0.122	[0.113, 0.131]	0.073	0.624	0.718	--
	Configural	1097.360	54	20.32	0.121	[0.115, 0.127]	0.081	0.585	0.689	--
	Metric	1432.590	62	23.11	0.129	[0.123, 0.135]	0.109	0.525	0.591	−0.098
	Partial Metric**	1130.834	59	19.17	0.117	[0.111, 0.123]	0.083	0.610	0.680	−0.009

^*Set EI4 free;

^**set AS7–9 free.

Multigroup Confirmatory Factor Analysis

The following analyses examined the model fit across the two groups using MG-CFA. Ethnic Identification. First, the analysis tested for equal form by placing equality constraints on the factorial structure across groups (configural invariance). Results showed adequate fit indices which supported the similar item cluster patterns which mapped well on the same number factor model. Specifically, RMSEA suggested moderate fit (.065) while SRMR suggested good fit (0.023), and both TLI and CFI were above .95. Next, metric noninvariance was found when examining the two groups. As the metric invariance test showed a significant drop in fit (ΔCFI = −.014), partial metric invariance was conducted by identifying the noninvariant item loadings based on the procedures outlined in Cheung and Rensvold (1999). Item 4 (“Importance for same racial/ethnic group to marry within group”), when allowed to vary, increased fit to meet metric invariance (ΔCFI = −.002). The partial metric invariance determines if each group’s items are equally related to their latent variable. In this case, item 4 was less related to Ethnic Identification for Latinx than the Asian sample. This aligned with Table 2 where item 4 showed a smaller loading onto the factor in Latinx sample (Latinx: .20; Asian: .43).

English Proficiency and Preference.

As seen in Table 3, each model was invariant as compared to the previous model with the largest change in CFI = .005. These results suggested that each subsample had the same factorial structure (configural), factor loadings (metric), item means (scalar), and error variances (strict) for all items; this implied that the scale performs similarly for both samples and that the subscale scores can be interpreted the same regardless of the race/ethnicity.

Acculturative Stress.

As seen in Table 2, results showed that loadings onto Acculturative Stress were small to moderate (Asian range: .13–.69; Latinx range: .25–.66). Specifically, items related to government and legal status (items 7 to 9) had smaller loadings among the Asian sample (range: .13 to .16) than the Latinx sample (range: .42 to .51). Following support for configural invariance across groups, the metric invariance was conducted by imposing equality constraints on all factor loadings across groups, as shown in Table 3. The test resulted in a significant CFI drop in model fit relative to the equal configural invariance (△CFI = .098), suggesting that at least one item loading was noninvariant across groups (Brown, 2014). Therefore, partial metric invariance was examined by identifying the noninvariant item loadings; a series of invariance tests were conducted by constraining each item loading one at a time. This process identified noninvariant items that significantly degraded the model. Once items were identified, the test for partial metric invariance then allowed one item loadings at a time to be freely estimated across groups until △CFI ≤ .01. After “freeing” items 7 to 9, (“Questioned about legal status,” “Think might be deported if go to social/government agency,” and “Avoid health service due to INS?”), fit indices supported a marginally good fit and the change of CFI is less than .01 (△CFI = .009). Overall, the results indicated that the general item–factor relationships were the same across the two groups after loosening a portion of the constraints.

Discussion

The purpose of this study is to test the psychometric properties of three Acculturation domains and understand how these measures vary across Asian and Latinx samples. MG-CFA was used to examine whether items vary or measure similarly between Latinx and Asian Americans. For Ethnic Identification, partial metric invariance was achieved when item 4 (“Importance for same racial/ethnic group to marry within group”) was set vary. Similarly, items 7–9 (“Questioned about legal status,” “Think might be deported if go to social/government agency,” and “Avoid health service due to INS?”) which were related to government or legal status were also degrading the model when set constrained. These findings demonstrated that measurement invariance could not simply be assumed across the two populations.

Understanding reasons for differential reporting by domain can help us better understand each population’s sensitivity to particular items. For Ethnic Identification, the difference in attitude toward marrying in-group may perhaps be due to a few reasons. First, interracial marriages for Asian Americans were deemed illegal until the banning of anti-miscegenation laws by the US Supreme Court in 1967. The sociopolitical context may have subsequently promoted the tradition and the importance of marrying within among Asian Americans. Secondly, a study found that 68% of Latinx Americans had outdated at least once (Tucker & Mitchell-Kernan, 1995). Latinx Americans are more accustomed to interracial dating which may indirectly make marrying within less critical. It is important to note that studies on ethnic identity are often conducted with adolescents and young adults, an important developmental stage for identity. Items on dating and marriage coincide with the importance of exploring intimacy within this developmental stage.

For Acculturative Stress, items related to government and legal status are more relevant to Latinx Americans maybe relate to the relatively large amount of unauthorized immigrants in this group (Passel & D’Vera, 2016). As pointed out earlier, Latinx Americans are more likely to be targets of unfair immigrant policy (e.g., ICE), making these stressors more salient. It also confirms their relatively disadvantaged socioeconomic position (i.e., legal status) which isolated them from the larger society and subsequent acculturated opportunities.

For English Language Proficiency and Preference, strict invariance was achieved. This implied that language items performed similarly for both Asian and Latinx subsamples which allows scores to be interpreted the same way. This is useful because language items are quick and convenient and often correlate with measurement scales that explain more variance in acculturation scales than other constructs (Marin, 1992). A demonstration of MI allows researchers to conduct cross-cultural comparisons without any psychometric concerns.

Conclusion

This study has several major strengths, including large sample sizes, sophisticated statistical analyses, and incorporating popular measurement domains across disciplines. Nevertheless, there are also some limitations. The primary limitation is the use of the limited number of items (e.g., four items only in Ethnic Identification) and relatively poor psychometric property in Acculturative Stress. Also, the analyses may be benefited from including additional prevalent domains (e.g., measures for cultural practices and values, individualism vs. collectivism, etc.). In addition, literature has shown considerable heterogeneity within ethnic subgroups (e.g., Chinese, Vietnamese, Filipino, Cuban, Mexicans, Puerto Rican, etc.) and simply assuming MI across all subgroups can be problematic. Further research may consider looking at differential item functioning across different racial/ethnic subgroups. Lastly, acculturation measures should also consider accounting for age. For example, identity development (e.g., Erikson’s psychosocial development) may cause individual’s ethnic identification to vary tremendously (Erikson & Erikson, 1998). The information provided in this study can also better inform clinicians in understanding different aspects of acculturation in practice. For example, instead of one size fits all, social workers and other clinicians may gain knowledge about certain aspects of acculturation that are fundamentally different between populations. Subsequently, it can inform their practice with racially/ethnically diverse client populations by focusing on relevant acculturation aspects specific to the clients’ backgrounds.

Data availability statement:

Data associated with this paper can be found in Inter-university Consortium for Political and Social Research data repository under https://doi.org/10.1002/mpr.181