International Journal of Psychology, 2014 Vol. 49, No. 3, 175–182, DOI: 10.1002/ijop.12017
Structural model of acculturation attitudes and related psychosocial variables: Empirical evidence in native Spaniards ´ Pedro J. Perez Moreno1 , Antonio J. Rojas Tejada2 , Marisol Navas Luque2 , and Oscar M. Lozano Rojas1 1
Department of Clinical, Experimental and Social Psychology, University of Huelva, Huelva, Spain 2 Department of Psychology, University of Almer´ıa, Almeria, Spain
T
his work falls within the framework of the study of acculturation processes of natives and immigrants. Its goal is to test an explanatory multi-group model of natives’ acculturation attitudes as a function of diverse psychosocial variables: Prejudice and natives’ appraisal of their own culture (in a direct way) and inter-group contact and perceived inter-group similarity (in an indirect way). Participants were 499 Spaniards surveyed for their attitude towards Romanian immigrants and 493 towards Ecuadorian immigrants. The indicators used took into account three socio-cultural spheres: peripheral, intermediate and central areas. This multi-group model shows an adequate fit to the data. Keywords: Acculturation; Prejudice; Structural equations.
In the decade from 2000 to the present, Spain’s census has seen an increase in its proportion of immigrants from 2.3 to 12.2% (Instituto Nacional de Estad´ıstica, 2010). This unavoidable migratory phenomenon implies an adaptation process that involves changes both in the immigrant population and in the recipient society and its members. This adaptation can be seen as the result of an acculturation process. In their acculturation model, Berry et al. (Berry, Kim, Power, Young, & Bujaki, 1989) propose the existence of two dichotomic independent attitudinal dimensions: the attitude towards maintaining one’s own culture and the attitude towards contact with members of the out-group and its culture. There is evidence of numerous individual, group, inter-group and contextual variables that condition the acculturation process of natives and immigrants (Berry, 2001; Phinney, Horenczyck, Liebkind, & Vedder, 2001; Piontkowski, Rohmann, & Florack, 2002). Among the models of acculturation developed that consider these variables is the Relative Acculturation Extended Model (RAEM) (e.g., Navas, Garc´ıa, & Rojas, 2006; Navas,
Garc´ıa, S´anchez, Rojas, Pumares, & Fern´andez, 2005; Navas, Rojas, Garc´ıa, & Pumares, 2007), which takes into account the above-mentioned evidence, as well as incorporating those obtained by investigations conducted in the Spanish context. On the basis of Berry’s and Bourhis’ acculturation models, the RAEM proposes that the natives’ acculturation attitude has two dimensions—their attitude towards the immigrants maintaining their own culture of origin and their attitude towards the immigrants adopting the host culture. According to RAEM, the natives’ rating of their own culture (in-group culture) will directly influence their attitude towards the immigrants adopting the host culture. RAEM predicts that the acculturation attitude, in its two dimensions, is directly influenced by the natives’ prejudiced attitude. Not many investigations (e.g., Berry, Phinney, Sam, & Vedder, 2006) have attempted to relate these two variables (prejudiced attitude and acculturation options), probably because prejudice has traditionally been studied in the majority groups’ attitude towards the
Correspondence should be addressed to Pedro J. P´erez Moreno, Clinical, Experimental and Social Psychology, University of Huelva, Huelva, Spain. (E-mail: [email protected]). This work was performed within a Project funded by the State Secretariat for Universities, Research and Development of the National RD&I Plan (Reference SEJ2004-07369/PSIC) and an Excellence Research Project funded by the Andalusian Regional Ministry for Innovation, Science and Business (Reference P09-SEJ-4657) and FEDER Founds.
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minority groups, whereas the acculturation process to a new host society has traditionally been studied in the minority groups. However, in recent years, there has been an attempt to demonstrate empirically that the levels of prejudice towards immigrants in the host society must be related to the natives’ preferred acculturation options for immigrants (e.g., Zick, Wagner, van Dick, & Petzel, 2001). This hypothesis has been tested and confirmed using data collected from various areas of Spain and from immigrants of different ethnocultural origin (e.g., Navas et al., 2006). Prejudiced attitude is directly influenced by three factors: inter-group contact, perceived inter-group similarity and rating of the in-group culture. These three factors are related to each other. The relations proposed among these variables in the theoretical model are based on the empirical evidence obtained in prior investigations. Contact with members of the out-group, under certain conditions, improves inter-group relations. Contact can prove that negative stereotypes are erroneous; it can decrease the perception of out-group homogeneity and increase the perception of similarity with the out-group and, therefore, reduce the prejudiced attitude towards the out-group (Pettigrew, 1986). Investigations of perceived out-group similarity relate it negatively to prejudiced attitude (Brown, 1984; Hogg, 1992), and show that it is a good predictor of such attitudes (G´omez-Berrocal & Navas, 2000). The positive rating of the in-group—ingroup favouritism—(Turner, Brown, & Tajfel, 1979) is closely related to people’s need and motivation to achieve or maintain a positive group or social identity. The goal of this investigation is to confirm the fit between a theoretical model (Figure 1) that comprises the two dimensions that make up acculturation attitudes with the psychosocial variables related in the literature (prejudiced attitude, inter-group contact, perceived inter-group similarity, in-group rating) and the data obtained from a sample of native Spaniards, using multi-group structural equations to test the model empirically. The relations showed in the model have been tested previously (bivariate data analysis) but multi-group structural equations’ analysis evaluates all the concurrent relations jointly. The latent variables or factors are indicated by circles. The observed variables or items are indicated by squares. The Contact with the Out-Group (CON), the Perceive Inter-group Similarity (PER-SIM) and the In-Group Rating (IN-R) are exogenous factors (their antecedents are not included in the model). The correlations among the exogenous variables are represented by curved arrows. These exogenous factors explain the endogenous factors. The Prejudiced Attitude (PRE-ATT), the Attitude towards Maintaining the Immigrants’ Culture of Origin (ATTMICO) and the Attitude towards Adopting the Host Culture (ATT-AHC) are endogenous factors. The paths from the exogenous to the endogenous variables are represented by straight arrows. All the exogenous factors
are related to the PRE-ATT, which, in turn, is related to the ATT-MICO and the ATT-AHC, both latent factors. The IN-R is related to the ATT-AHC. Finally, each item has a sample error term, as well as each endogenous factor has an unexplained variance term. Taking into account that the acculturation options of groups are conditioned by their ethnocultural or national origin (Bourhis, Mo¨ıse, Perreault, & Sen´ecal, 1997; Piontkowski et al., 2002), the value of the correlations may depend on it. METHODS Participants Participants were 992 native Spaniards; 499 responded to questions referring to the out-group of Romanian immigrants—Group SR—and 493 responded to questions referring to the out-group of Ecuadorian immigrants—Group SE. All of them were residents of 12 municipalities of four Mediterranean autonomous communities with more than 2% of the total census being Romanian and Ecuadorian immigrants. Specifically, they were from the municipalities of the Autonomous Communities of Andalusia, Murcia, Valencia and Catalonia. Mean age of Group SR was 45.0 years (SD = 16.8), with 48.3% men and 50.7% women. In Group SE, the mean age was 45.1 years (SD = 16.7) with 49.3% men and 50.1% women. Sample selection was performed with multistage sampling. In the first stage, experts selected 12 municipalities with a high reception rate of immigrants from the Spanish Mediterranean area. The inclusion criterion of the municipalities was having more than 20,000 inhabitants, 5% of them immigrants and 2% belonging to the collective census of Romanians and Ecuadorians. In the second stage, the sample of natives was stratified by sex and age (with proportional affixation), performing random routes in the diverse target areas. The sample error assumed for the total sample was ±3.2% (p = q = .5, 95.5% confidence level), and for the SR and SE subsamples, with the same conditions and statistical parameters, the sample error rose to ±4.3% for each one. Variables and instruments Contact with the out-group Two items were employed: “What degree of contact do you have with (Romanian/Ecuadorian) persons?” and “How do you feel about the contact you have had or have with (Romanian/Ecuadorian) persons?”. The first one had six response options: “No contact” (1 point); “You see them around a lot because of neighbourhood, work, or school issues, but you don’t usually talk to them unless they talk to you” (2 points); “You see them around a lot © 2013 International Union of Psychological Science
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Figure 1. Representative structural model of the predictions of the RAEM for the native samples.
because of neighborhood, work, or school issues, and you frequently relate to them” (3 points); “You have friends in that group” (4 points); “You have relatives in that group” (5 points); and “Your intimate partner belongs to that group” (6 points). The second item about the nature of CON was responded to on a scale ranging from 1 (Very unpleasant) to 5 (Very pleasant).
own group in the RAEM spheres, averaged as before. The response options ranged between 1 (Very bad) and 5 (Very good). The reliability coefficients, estimated by means of Cronbach alpha coefficient, were .76 for SR and .70 for SE group. Prejudiced attitude
Perceive inter-group similarity This was measured with an ad hoc scale, made up of eight items concerning the participants’ perceptions of “how different or similar were the persons of the outgroup (Romanians or Ecuadorian) to those of the in-group (Spaniards)”. Each one of these items corresponded to a sphere contemplated in the RAEM: political, social wellbeing and work (which were averaged to obtain the value of the peripheral component); economic and social (which were averaged to estimate the intermediate component); and family, religious and values (whose mean is the value of the central component). The response options ranged between 1 (Very different) and 5 (Very similar). The reliability coefficients, estimated by means of Cronbach alpha coefficient, were .81 for SR and .80 for SE group. In-group rating This was measured with an ad hoc scale, made up of eight items that measure the participants’ rating of their © 2013 International Union of Psychological Science
The prejudice scale employed (Rojas, Lozano, Navas, & P´erez, 2011) has three dimensions: opinion about the out-group (cognitive component of prejudice), emotions (affective component) and preferred social distance from the out-group (co-native component or behavioral intention). The cognitive component is made up of eight items referring to the socio-cultural spheres of the outgroup contemplated in the RAEM, averaged to obtain the estimations of all three spheres. The eight items had Cronbach alpha values of .82 for SR and .75 for SE group. The affective component of prejudice, or emotions towards the out-group, was measured with seven items: three items of positive emotions (admiration, empathy and respect), and four items of negative emotions considered “subtle” by investigators of modern, subtle or aversive prejudice (mistrust, discomfort, insecurity and indifference). The value of the Cronbach alpha coefficients was .81 for SR and .76 for SE group. To measure the co-native/behavioural component, we used an item to refer to the type of relationship (close or
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distant) that the participants prefer to have with members of the out-group. Acculturation attitudes We used eight items for each one of both variables. Each one of these items corresponded to a sphere contemplated in the RAEM. The first scale measured the ATT-MICO. The second scale measured the ATT-AHC. All the items were responded to on a scale ranging from 1 (Not at all) to 5 (Very much). The value of Cronbach alpha of the first scale (Maintenance) was .87 in SR and .84 in SE group and of the second scale (Adoption) was .85 in SR and .90 in SE group. Procedure We used an extensive questionnaire in which we asked about diverse variables related to acculturation attitudes, including the above-mentioned variables. Trained personnel administered this questionnaire individually. The administration was carried out in the selected person’s home. Statistical analyses First, in each sample we tested the structure of singlegroup models with the antecedents of Prejudice (CON, PER-SIM and IN-R), the PRE-ATT, and the ATT-MICO and the ATT-AHC. We assessed the differences of the loading of each latent construct on each area: if there was any statistical difference, it will prove that those areas have different significance in the meaning of that factor. Second, we conducted a multi-group analysis with both native’s samples, restricting the loadings by the means of the previous results. In the multi-group analysis, we specified the influence of antecedents, as exogenous variables, over the PRE-ATT, as well as an influence of this over the ATT-MICO and the ATT-AHC. In the multi-group model, we first tested the invariance configuration: the constructs should be conceptualized equally (with the same structure) in the different groups. If an adequate fit was obtained, we then tested the metric invariance of the model, restricting the loading values of the items of each factor. Next, if the model of metric invariance was adequate, we compared the covariances and regression coefficients among the factors to determine whether the influence or association among the factors was similar in both samples. Both invariance models represent the habitual approach to providing evidence of construct validity (Byrne, 2006). If the analysis reveals any difference between the groups, it will prove that the ethnocultural origin of the immigrant out-group is a relevant predictor of the natives’ acculturation process.
We use as observable variables, the mean scores for the items of the areas (Peripheral, Intermediate and Central) in the case of the PER-SIM, both the Acculturation Attitudes, and the IN-R. CON includes the observable variables Degree of contact and Satisfaction with contact. Finally, PRE-ATT includes the means of the observable variables Co-native Prejudice, Affective Prejudice, and the three components of Cognitive Prejudice: Peripheral, Intermediate and Central. To test goodness of fit (how well the model reproduces the matrix of covariances), we employed the maximum likelihood estimation method, correcting the χ2 statistic by means of the Satorra–Bentler robust χ2 test (SBχ2 , Satorra & Bentler, 1994). We also used the SBχ2 /df quotient, considering that the fit is adequate if the value is ≤3.0 (Carmines & McIver, 1981). Likewise, other fit indexes were taken into account, such as the global goodness of fit index (GFI; J¨oreskog & S¨orbom, 1989), and comparative fit indexes, such as the comparative-fit-index (CFI; Bentler, 1990) and the incremental-fit-index (IFI; Bollen, 1989). Values ≥.90 in these indexes are interpreted as an adequate fit. We also interpreted the value of the standardized root meansquare (SRMR; J¨oreskog & S¨orbom, 1989), considering an adequate fit if its value is ≤.08 (Hu & Bentler, 1989) and the value of residual root mean square error of approximation (RMSEA; Byrne, 2006), considering values ≤.08 indicators of adequate fit (Browne & Cudeck, 1993). To verify the loss of fit due to the imposition of restrictions in the multi-group model, we assessed the change in CFI (CFI), considering values ≥.01 indicative of a relevant loss of fit (Cheung & Rensvold, 2002) as well as the statistical significance of the change of SBχ2 index, using for this purpose the SBDIFF program (Crawford & Henry, 2003). The specific restrictions in the diverse invariance models were evaluated with the χ2 test. If any restriction presented an inadequate fit, we followed an iterative process of releasing the parameters with p < .05 and largest χ2 , until obtaining an adequate fit. The EQS 6.0 program was used for the analysis (Bentler, 2005). RESULTS Contrast between different areas We tested (for SR and SE) if each area had a different loading in their respective latent construct. In each sample we tested three models: (a) Antecedents or Exogenous variables, testing the PER-SIM and IN-R, both correlated with CON; (b) PRE-ATT, with the measurement model of this construct and (c) Attitudes towards Immigrant’s Acculturation, assuming ATT-MICO correlated with the ATT-AHC. In each model and factor, we constrained the values of most extreme loadings to be similar to the median one. The programme used a chi-square test to © 2013 International Union of Psychological Science
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TABLE 1 Values of the fit indexes Single group SR
χ df p χ2 /df SBχ2 df p SBχ2 /df GFI CFI IFI ST.RMR RMSEA 2
Multi-group SE
Model 2
Model 3
EX
PRE
ATT
EXG
PRE
ATT
Model 1
First step
Last step
First step
Last step
46.793 20 .0006 2.340 46.203 20 .0008 2.310 .971 .955 .956 .055 .058
2.235 3 .5251 .745 2.051 3 .5620 .684 .998 1.000 1.003 .013 .000
18.963 7 .0083 2.709 17.302 7 .0155 2.472 .984 .982 .982 .056 .062
55.861 20 .0000 2.793 52.410 20 .0001 2.620 .967 .908 .910 .065 .065
4.593 3 .2041 1.531 4.760 3 .1902 1.587 .995 .993 .993 .025 .039
10.987 6 .0888 1.831 10.262 6 .1140 1.710 .991 .991 .991 .041 .043
495.943 250 .0000 1.984 456.878 250 .0000 1.828 .937 .947 .948 .058 .033
526.967 262 .0000 2.011 485.293 262 .0000 1.852 .933 .943 .944 .074 .033
506.932 259 .0000 1.957 465.508 259 .0000 1.797 .935 .947 .948 .060 .032
559.568 267 .0000 2.096 512.923 267 .0000 1.921 .929 .937 .938 .102 .034
515.042 264 .0000 1.951 472.129 264 1.788 .934 .947 .948 .065 .032
Ex, Exogenous variables; PRE, Prejudiced Attitude; ATT, Attitude.
prove if the constrains are plausible. If a restriction failed to be assumed, it was released and then the model was tested again in an iterative process that stopped when all restrictions accepted the null hypothesis. By means of this procedure, we found that some loadings are statistically different. In SR sample, Peripheral PER-SIM was different from Central PER-SIM, χ2 (1) = 34.027, p = .0000, and Intermediate IN-R was different from Central IN-R, χ2 (1) = 13.547, p = .0000; Peripheral Cognitive Prejudice was different from Central Cognitive Prejudice, χ2 (1) = 184.682, p = .0000; and there were significant differences between Peripheral and Intermediate ATT-MICO, χ2 (1) = 37.330, p = .0000 and between Peripheral and Intermediate ATT-AHC, χ2 (1) = 22.133, p = .0000. In SE sample, Peripheral PER-SIM was different from Central PER-SIM, χ2 (1) = 14.597, p = .0001, and Intermediate IN-R was different from Central IN-R, χ2 (1) = 5.114, p = .0237; Peripheral Cognitive Prejudice was different from Central Cognitive Prejudice, χ2 (1) = 19.887, p = .0000; and there were significant differences between Central and Intermediate ATT-MICO, χ2 (1) = 24.394, p = .0000 and between Peripheral and Intermediate ATT-AHC, χ2 (1) = 25.413, p = .0000. The remaining factor loadings of every latent construct were statistically equivalent to one another. These differences showed that the areas have a different load in each of the mentioned variables, as was stated in the RAEM. Table 1 shows GFIs of the final models for both samples. Goodness of fit of the multi-group structural model The variables and their relations are shown in Figure 1. The observable variables are the mean scores for the © 2013 International Union of Psychological Science
items of the Peripheral area, the Intermediate area, and the Central area in the case of the PER-SIM, both the Acculturation Attitudes and the IN-R. CON includes the observable variables CON and nature of CON. Finally, PRE-ATT includes the means of the observable variables Co-native Prejudice, Affective Prejudice, and the three components of Cognitive Prejudice: Peripheral, Intermediate and Central. Each observable variable has its corresponding sample error. Finally, each latent exogenous factor has an error (Di ) that represents the variables not included in the model, which could explain it. Owing to the high similarity of the items, we took into account the correlations among the measurement errors of each area in the latent factors where out-group was assessed (PER-SIM, PRE-ATT, and both Acculturation Attitudes), and where the contact was assessed (CON and the Co-native component of the PRE-ATT). These trials are not included in Figure 1, to facilitate its interpretation. Though the correlated errors are usually interpreted as a lack of fit, in case of having substantive sense they should be included in the model. This is a common situation, particularly with respect to social psychological research (Byrne, 2006, p. 112). The fit of Model 1 (configurational invariance model) can be considered adequate (see Table 1). Although the χ2 and SBχ2 tests were statistically significant, χ2 (250, N = 779) = 495.943, p = .0000 and SBχ2 (250, N = 779) = 456.878, p = .0000, both the χ2 /df quotient (1.984) and the SBχ2 /df (1.828) were lower than 3.0. The rest of the indicators provide values higher than .90 (CFI = .947, IFI = .948, and GFI = .937). We can assume that the fit of the structural model is adequate and similar in both samples. The theoretical structure of the model has a good fit to the data collected from the sample.
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Next, we tested the factor invariance model, first restricting the value of the item loadings on the factors (Model 2). The Model 2 shows adequate GFIs, except for chi-square test, χ2 (262, N = 779) = 526.967, p = .0000 and SBχ2 (262, N = 779) = 485.293, p = .0000. Comparing the goodness of fit of Model 1 with that of Model 2 with the SB Scaled Difference (SBχ2 Scaled Difference (12) = 28.361, p = .0049) we found statistically significant differences. This result indicates that the factor invariance model has a lower fit than the configurational invariance model. We tested the significance of the restrictions imposed on Model 2, finding there were some unrealistic assumptions, and we proceeded releasing them. First, we released the constraint of factor CON loading on item “CON” χ2 (1, N = 779) = 8.710, p = .0032; then, the factor PER-SIM loading on item “Intermediate” χ2 (1, N = 779) = 6.330, p = .0119; finally, the factor CON loading on item “nature of CON” χ2 (1, N = 779) = 6.346, p = .0118. Although χ2 test has p < .05 (χ2 (262, N = 779) = 526.967, p = .0000; and SBχ2 (250, N = 779) = 465.508, p = .0000) χ2 /df has an adequate value (χ2 /df = 1.957, and SBχ2 /df = 1.797) as well as the other goodness of fit index (GFI = .935, CFI = .947, IFI = .948, SRMR = .060). It is acceptable to consider that the measurement model has statistically similar structure and loadings except for that of CON and PER-SIM. Comparing the Model 1 and final Model 2 fit, we obtained an SB Scaled Difference (9) = 9.268, p = .4129. There was no statistical difference between the fit of both models. We then restricted the covariance and regression coefficients between factors (see Figure 1) to determine whether the relations among the latent constructs were similar in both groups (Model 3). The fit indexes are shown in Table 1. Both χ2 tests were statistically significant, χ2 (267, N = 779) = 559.568, p = .0000 and SBχ2 (267, N = 779) = 512.923, p = .0000, with χ2 /df = 2.096 and SBχ2 /df = 1.921. However, all the fit indexes obtained results higher than .090 and an RMSEA value of .034 (90% confidence interval between .031 and .040). The value of SRMR showed a lack of fit. The test on the difference between Model 1 and Model 3, Satorra–Bentler scaled χ2 statistics showed relevant differences (SB Scaled Difference (17) = 54.329, p = .000). The model’s fit was inadequate. We proceeded to release the inadequate constraints. First, we released the regression coefficient of PRE-ATT on PER-SIM, χ2 (1, N = 779) = 20.510, p = .0000, then, the regression coefficient of PRE-ATT on IN-R χ2 (1, N = 779) = 12.593, p = .0004 and finally the regression coefficient of the ATT-MICO on PRE-ATT χ2 (1, N = 779) = 4.619, p = .0316. At this step, all constrains were correctly imposed (p > .05). Table 1 shows the final Model 3 goodness of fit. Although both χ2 based indexes, sensitive to sample size, were statistically significant, χ2 (264, N = 779) = 515.042, p = .0000 and SBχ2 (264,
N = 779) = 472.129, p = .0000, both chi-square ratios were .90 (GFI = .934, CFI = .947, IFI = .948), SRMR were .05) all the regression coefficients of the final model were statistically significant (p < .05) with absolutes values ranging from .112 to .948. The model has an acceptable fit (SR and SE samples). Figure 2 shows the final model with the standardized regression coefficients for both samples. DISCUSSION This work has developed a theoretical model that relates acculturation attitudes and the psychosocial variables of PRE-ATT, CON, PER-SIM and IN-R in two samples of native Spaniards who assessed Romanian and Ecuadorian immigrants. The goal was to empirically contrast the relations specified in the theoretical model, carried out using the RAEM and in the theoretical and empirical evidence described in the psychosocial literature, with the data obtained from the two sample sets of natives. The process employed to contrast the model took into account the possible differences in the structure of the two samples (SR and SE) and three areas—peripheral, intermediate and central. The relations specified are based on previous psychosocial literature that establishes that CON, PER-SIM, and the natives’ IN-R are predictors of PRE-ATT towards immigrants. We conducted structural equation analysis to obtain empirical evidence about the model. First, we confirm each area has a different role in the formation of the latent variables involved in the model, restricting the load of each area of every variable to have the same value. The results show that not all the restrictions were acceptable: loading of Peripheral area over PRE-ATT is lower than the Intermediate and Central areas, both on SR and SE samples. This is true, as well, in ATT-MICO and ATT-AHC. The RAEM proposes that depending on the sphere in which the interaction with persons from other cultures occurs, people do not generally use the © 2013 International Union of Psychological Science
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Figure 2. Latent variables and standardized regression coefficients in the structural model of the predictions of the RAEM for the native samples.
same strategies or do not prefer the same acculturation options (Navas et al., 2005). We find that these results are consistent with that postulate. We specified a multi-group model, involving the results of both groups (SR and SE). The multi-group analysis shows that the structure of the model is statistically similar for both groups. However, there are different regression coefficients in some paths; specifically, the manner in which PER-SIM and IN-R are related to PRE-ATT, and how this one is related to ATT-MICO. In all cases, the relation was stronger in the group of natives who rated Romanian immigrants than in the group that assessed Ecuadorians. The ethnocultural or national origin of people is a relevant element that must be taken into account when assessing the acculturation process (Bourhis et al., 1997; Piontkowski et al., 2002). The model reflects that the natives’ level of prejudice towards immigrants is related to the natives’ preferred acculturation options for immigrants (e.g. Navas et al., 2006; Zick et al., 2001). CON is related to PER-SIM and IN-R, all being related to PRE-ATT (e.g. Brown, 1984; G´omez-Berrocal & Navas, 2000; Hogg, 1992; Pettigrew, 1986). It would be a helpful exercise to prove the model with other variables that predict the natives’ attitude towards immigrants’ acculturation. It would increase the proportion of explained variance of both attitudes. Testing a comparable model with samples of immigrants (by means of a similar procedure) should give empirical support for the RAEM. Another limitation of the study is the concomitance of the measurement of all elements. This implies a lack of the longitudinal sense of the conclusions that is needed to establish the steps of a process. There is a need for longitudinal studies that © 2013 International Union of Psychological Science
take into account these steps, especially in the immigrant population. The results obtained in the present work are an important contribution to the field of prejudice and the acculturation process. PRE-ATT is an antecedent of natives’ acculturation attitude towards the two groups of immigrants (Romanians and Ecuadorians), as had been hypothesized and verified using the RAEM in correlational studies, with a multivariate data analysis that allows to test the relations structure. The results can guide the policies of social intervention: reduction of the levels of prejudice in the native population would favour non-assimilationist acculturation options. And this would probably lead to an improvement of inter-group relations. The results also show that the reduction of PRE-ATT is related to the CON, PER-SIM and IN-R in RAEM spheres. There are obviously other psychosocial variables, such as perceived cultural enrichment, the perception of out-group threat, the status and power relations between groups, etc. (e.g., Bourhis et al., 1997), and even variables of another nature (political, economic, etc.), which may underlie the native population’s prejudiced attitudes towards certain groups of immigrants, and which were not included in this investigation. Moreover, it should not be forgotten that prejudice is mainly characterized by its specificity, that is, by the importance of contextual factors, such as the ethnocultural origin of the immigrant out-group, the state of the intergroup relations at specific places and times, and others. However, despite the limitations of this study (in the number of antecedent variables considered), the variables included do act as antecedents of prejudiced attitude, and the PRE-ATT determines the natives’ acculturation
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options towards immigrants of Romanian and Ecuadorian origin. Manuscript received June 2012 Revised manuscript accepted May 2013 First published online November 2013
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Hu, L., & Bentler, P. (1989). Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. Instituto Nacional de Estad´ıstica (2010). Principales series de poblaci´on desde 1998. Poblaci´on extranjera desde 1998 [Main population series from 1998. Foreign population since 1998—Data file]. Retrieved from http:// www.ine.es/jaxi/tabla.do?path=/t20/e245/p08/l0/&file= 01006.px&type=pcaxis&L=0 J¨oreskog, K. G., & S¨orbom, D. (1989). LISREL 7 User’s reference guide. Chicago, IL: Scientific Software. Navas, M., Garc´ıa, M. C., & Rojas, A. J. (2006). Acculturation strategies and attitudes of African immigrants in the south of Spain: between reality and hope. Cross-Cultural Research, 40, 331–351. Navas, M. S., Garc´ıa, M. S., S´anchez, J., Rojas, A. J., Pumares, P., & Fern´andez, J. S. (2005). Relative acculturation extended model: new contributions with regard to the study of acculturation. International Journal of Intercultural Relations, 29, 21–37. Navas, M., Rojas, A. J., Garc´ıa, M. C., & Pumares, P. (2007). Acculturation strategies and attitudes according to the Relative Acculturation Extended Model (RAEM): The perspectives of natives versus immigrants. International Journal of Intercultural Relations, 31, 67–86. Pettigrew, T. F. (1986). The intergroup contact hypothesis reconsidered. In M. Hewstone & R. Brown (Eds.), Contact and conflict in intergroup encounters (pp. 69–195). New York, NY: Blackwell. Phinney, J. S., Horenczyck, G., Liebkind, K., & Vedder, P. (2001). Ethnic identity, immigration, and well-being: an interactional perspective. Journal of Social Issues, 57(3), 493–510. Piontkowski, U., Rohmann, A., & Florack, A. (2002). Concordance of acculturation attitudes and perceived threat. Group Processes & Intergroup Relations, 5(3), 221–232. Rojas, A. J., Lozano, O. M., Navas, M., & P´erez, P. J. (2011). Prejudiced attitude measurement using the Rasch rating scale model. Psychological Reports, 109(2), 553–572. Satorra, A., & Bentler, P. M. (1994). Corrections to test statistics and standard errors in covariance structure analysis. In A. V. Eye & C. C. Clogg (Eds.), Latent variables analysis: Applications for developmental research (pp. 399–419). Thousand Oaks, CA: Sage. Satorra, A., & Bentler, P. M. (2001). A scaled difference chi-square test statistic for moment structure analysis. Psychometrika, 66, 507–514. Turner, J. C., Brown, R. J., & Tajfel, H. (1979). Social comparison and group interest in ingroup favouritism. European Journal of Social Psychology, 9, 187–204. Zick, A., Wagner, U., van Dick, R., & Petzel, T. (2001). Acculturation and prejudice in Germany: majority and minority perspectives. Journal of Social Issues, 57(3), 541–557.
© 2013 International Union of Psychological Science
Structural model of acculturation attitudes and related psychosocial variables: Empirical evidence in native Spaniards ´ Pedro J. Perez Moreno1 , Antonio J. Rojas Tejada2 , Marisol Navas Luque2 , and Oscar M. Lozano Rojas1 1
Department of Clinical, Experimental and Social Psychology, University of Huelva, Huelva, Spain 2 Department of Psychology, University of Almer´ıa, Almeria, Spain
T
his work falls within the framework of the study of acculturation processes of natives and immigrants. Its goal is to test an explanatory multi-group model of natives’ acculturation attitudes as a function of diverse psychosocial variables: Prejudice and natives’ appraisal of their own culture (in a direct way) and inter-group contact and perceived inter-group similarity (in an indirect way). Participants were 499 Spaniards surveyed for their attitude towards Romanian immigrants and 493 towards Ecuadorian immigrants. The indicators used took into account three socio-cultural spheres: peripheral, intermediate and central areas. This multi-group model shows an adequate fit to the data. Keywords: Acculturation; Prejudice; Structural equations.
In the decade from 2000 to the present, Spain’s census has seen an increase in its proportion of immigrants from 2.3 to 12.2% (Instituto Nacional de Estad´ıstica, 2010). This unavoidable migratory phenomenon implies an adaptation process that involves changes both in the immigrant population and in the recipient society and its members. This adaptation can be seen as the result of an acculturation process. In their acculturation model, Berry et al. (Berry, Kim, Power, Young, & Bujaki, 1989) propose the existence of two dichotomic independent attitudinal dimensions: the attitude towards maintaining one’s own culture and the attitude towards contact with members of the out-group and its culture. There is evidence of numerous individual, group, inter-group and contextual variables that condition the acculturation process of natives and immigrants (Berry, 2001; Phinney, Horenczyck, Liebkind, & Vedder, 2001; Piontkowski, Rohmann, & Florack, 2002). Among the models of acculturation developed that consider these variables is the Relative Acculturation Extended Model (RAEM) (e.g., Navas, Garc´ıa, & Rojas, 2006; Navas,
Garc´ıa, S´anchez, Rojas, Pumares, & Fern´andez, 2005; Navas, Rojas, Garc´ıa, & Pumares, 2007), which takes into account the above-mentioned evidence, as well as incorporating those obtained by investigations conducted in the Spanish context. On the basis of Berry’s and Bourhis’ acculturation models, the RAEM proposes that the natives’ acculturation attitude has two dimensions—their attitude towards the immigrants maintaining their own culture of origin and their attitude towards the immigrants adopting the host culture. According to RAEM, the natives’ rating of their own culture (in-group culture) will directly influence their attitude towards the immigrants adopting the host culture. RAEM predicts that the acculturation attitude, in its two dimensions, is directly influenced by the natives’ prejudiced attitude. Not many investigations (e.g., Berry, Phinney, Sam, & Vedder, 2006) have attempted to relate these two variables (prejudiced attitude and acculturation options), probably because prejudice has traditionally been studied in the majority groups’ attitude towards the
Correspondence should be addressed to Pedro J. P´erez Moreno, Clinical, Experimental and Social Psychology, University of Huelva, Huelva, Spain. (E-mail: [email protected]). This work was performed within a Project funded by the State Secretariat for Universities, Research and Development of the National RD&I Plan (Reference SEJ2004-07369/PSIC) and an Excellence Research Project funded by the Andalusian Regional Ministry for Innovation, Science and Business (Reference P09-SEJ-4657) and FEDER Founds.
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minority groups, whereas the acculturation process to a new host society has traditionally been studied in the minority groups. However, in recent years, there has been an attempt to demonstrate empirically that the levels of prejudice towards immigrants in the host society must be related to the natives’ preferred acculturation options for immigrants (e.g., Zick, Wagner, van Dick, & Petzel, 2001). This hypothesis has been tested and confirmed using data collected from various areas of Spain and from immigrants of different ethnocultural origin (e.g., Navas et al., 2006). Prejudiced attitude is directly influenced by three factors: inter-group contact, perceived inter-group similarity and rating of the in-group culture. These three factors are related to each other. The relations proposed among these variables in the theoretical model are based on the empirical evidence obtained in prior investigations. Contact with members of the out-group, under certain conditions, improves inter-group relations. Contact can prove that negative stereotypes are erroneous; it can decrease the perception of out-group homogeneity and increase the perception of similarity with the out-group and, therefore, reduce the prejudiced attitude towards the out-group (Pettigrew, 1986). Investigations of perceived out-group similarity relate it negatively to prejudiced attitude (Brown, 1984; Hogg, 1992), and show that it is a good predictor of such attitudes (G´omez-Berrocal & Navas, 2000). The positive rating of the in-group—ingroup favouritism—(Turner, Brown, & Tajfel, 1979) is closely related to people’s need and motivation to achieve or maintain a positive group or social identity. The goal of this investigation is to confirm the fit between a theoretical model (Figure 1) that comprises the two dimensions that make up acculturation attitudes with the psychosocial variables related in the literature (prejudiced attitude, inter-group contact, perceived inter-group similarity, in-group rating) and the data obtained from a sample of native Spaniards, using multi-group structural equations to test the model empirically. The relations showed in the model have been tested previously (bivariate data analysis) but multi-group structural equations’ analysis evaluates all the concurrent relations jointly. The latent variables or factors are indicated by circles. The observed variables or items are indicated by squares. The Contact with the Out-Group (CON), the Perceive Inter-group Similarity (PER-SIM) and the In-Group Rating (IN-R) are exogenous factors (their antecedents are not included in the model). The correlations among the exogenous variables are represented by curved arrows. These exogenous factors explain the endogenous factors. The Prejudiced Attitude (PRE-ATT), the Attitude towards Maintaining the Immigrants’ Culture of Origin (ATTMICO) and the Attitude towards Adopting the Host Culture (ATT-AHC) are endogenous factors. The paths from the exogenous to the endogenous variables are represented by straight arrows. All the exogenous factors
are related to the PRE-ATT, which, in turn, is related to the ATT-MICO and the ATT-AHC, both latent factors. The IN-R is related to the ATT-AHC. Finally, each item has a sample error term, as well as each endogenous factor has an unexplained variance term. Taking into account that the acculturation options of groups are conditioned by their ethnocultural or national origin (Bourhis, Mo¨ıse, Perreault, & Sen´ecal, 1997; Piontkowski et al., 2002), the value of the correlations may depend on it. METHODS Participants Participants were 992 native Spaniards; 499 responded to questions referring to the out-group of Romanian immigrants—Group SR—and 493 responded to questions referring to the out-group of Ecuadorian immigrants—Group SE. All of them were residents of 12 municipalities of four Mediterranean autonomous communities with more than 2% of the total census being Romanian and Ecuadorian immigrants. Specifically, they were from the municipalities of the Autonomous Communities of Andalusia, Murcia, Valencia and Catalonia. Mean age of Group SR was 45.0 years (SD = 16.8), with 48.3% men and 50.7% women. In Group SE, the mean age was 45.1 years (SD = 16.7) with 49.3% men and 50.1% women. Sample selection was performed with multistage sampling. In the first stage, experts selected 12 municipalities with a high reception rate of immigrants from the Spanish Mediterranean area. The inclusion criterion of the municipalities was having more than 20,000 inhabitants, 5% of them immigrants and 2% belonging to the collective census of Romanians and Ecuadorians. In the second stage, the sample of natives was stratified by sex and age (with proportional affixation), performing random routes in the diverse target areas. The sample error assumed for the total sample was ±3.2% (p = q = .5, 95.5% confidence level), and for the SR and SE subsamples, with the same conditions and statistical parameters, the sample error rose to ±4.3% for each one. Variables and instruments Contact with the out-group Two items were employed: “What degree of contact do you have with (Romanian/Ecuadorian) persons?” and “How do you feel about the contact you have had or have with (Romanian/Ecuadorian) persons?”. The first one had six response options: “No contact” (1 point); “You see them around a lot because of neighbourhood, work, or school issues, but you don’t usually talk to them unless they talk to you” (2 points); “You see them around a lot © 2013 International Union of Psychological Science
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Figure 1. Representative structural model of the predictions of the RAEM for the native samples.
because of neighborhood, work, or school issues, and you frequently relate to them” (3 points); “You have friends in that group” (4 points); “You have relatives in that group” (5 points); and “Your intimate partner belongs to that group” (6 points). The second item about the nature of CON was responded to on a scale ranging from 1 (Very unpleasant) to 5 (Very pleasant).
own group in the RAEM spheres, averaged as before. The response options ranged between 1 (Very bad) and 5 (Very good). The reliability coefficients, estimated by means of Cronbach alpha coefficient, were .76 for SR and .70 for SE group. Prejudiced attitude
Perceive inter-group similarity This was measured with an ad hoc scale, made up of eight items concerning the participants’ perceptions of “how different or similar were the persons of the outgroup (Romanians or Ecuadorian) to those of the in-group (Spaniards)”. Each one of these items corresponded to a sphere contemplated in the RAEM: political, social wellbeing and work (which were averaged to obtain the value of the peripheral component); economic and social (which were averaged to estimate the intermediate component); and family, religious and values (whose mean is the value of the central component). The response options ranged between 1 (Very different) and 5 (Very similar). The reliability coefficients, estimated by means of Cronbach alpha coefficient, were .81 for SR and .80 for SE group. In-group rating This was measured with an ad hoc scale, made up of eight items that measure the participants’ rating of their © 2013 International Union of Psychological Science
The prejudice scale employed (Rojas, Lozano, Navas, & P´erez, 2011) has three dimensions: opinion about the out-group (cognitive component of prejudice), emotions (affective component) and preferred social distance from the out-group (co-native component or behavioral intention). The cognitive component is made up of eight items referring to the socio-cultural spheres of the outgroup contemplated in the RAEM, averaged to obtain the estimations of all three spheres. The eight items had Cronbach alpha values of .82 for SR and .75 for SE group. The affective component of prejudice, or emotions towards the out-group, was measured with seven items: three items of positive emotions (admiration, empathy and respect), and four items of negative emotions considered “subtle” by investigators of modern, subtle or aversive prejudice (mistrust, discomfort, insecurity and indifference). The value of the Cronbach alpha coefficients was .81 for SR and .76 for SE group. To measure the co-native/behavioural component, we used an item to refer to the type of relationship (close or
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distant) that the participants prefer to have with members of the out-group. Acculturation attitudes We used eight items for each one of both variables. Each one of these items corresponded to a sphere contemplated in the RAEM. The first scale measured the ATT-MICO. The second scale measured the ATT-AHC. All the items were responded to on a scale ranging from 1 (Not at all) to 5 (Very much). The value of Cronbach alpha of the first scale (Maintenance) was .87 in SR and .84 in SE group and of the second scale (Adoption) was .85 in SR and .90 in SE group. Procedure We used an extensive questionnaire in which we asked about diverse variables related to acculturation attitudes, including the above-mentioned variables. Trained personnel administered this questionnaire individually. The administration was carried out in the selected person’s home. Statistical analyses First, in each sample we tested the structure of singlegroup models with the antecedents of Prejudice (CON, PER-SIM and IN-R), the PRE-ATT, and the ATT-MICO and the ATT-AHC. We assessed the differences of the loading of each latent construct on each area: if there was any statistical difference, it will prove that those areas have different significance in the meaning of that factor. Second, we conducted a multi-group analysis with both native’s samples, restricting the loadings by the means of the previous results. In the multi-group analysis, we specified the influence of antecedents, as exogenous variables, over the PRE-ATT, as well as an influence of this over the ATT-MICO and the ATT-AHC. In the multi-group model, we first tested the invariance configuration: the constructs should be conceptualized equally (with the same structure) in the different groups. If an adequate fit was obtained, we then tested the metric invariance of the model, restricting the loading values of the items of each factor. Next, if the model of metric invariance was adequate, we compared the covariances and regression coefficients among the factors to determine whether the influence or association among the factors was similar in both samples. Both invariance models represent the habitual approach to providing evidence of construct validity (Byrne, 2006). If the analysis reveals any difference between the groups, it will prove that the ethnocultural origin of the immigrant out-group is a relevant predictor of the natives’ acculturation process.
We use as observable variables, the mean scores for the items of the areas (Peripheral, Intermediate and Central) in the case of the PER-SIM, both the Acculturation Attitudes, and the IN-R. CON includes the observable variables Degree of contact and Satisfaction with contact. Finally, PRE-ATT includes the means of the observable variables Co-native Prejudice, Affective Prejudice, and the three components of Cognitive Prejudice: Peripheral, Intermediate and Central. To test goodness of fit (how well the model reproduces the matrix of covariances), we employed the maximum likelihood estimation method, correcting the χ2 statistic by means of the Satorra–Bentler robust χ2 test (SBχ2 , Satorra & Bentler, 1994). We also used the SBχ2 /df quotient, considering that the fit is adequate if the value is ≤3.0 (Carmines & McIver, 1981). Likewise, other fit indexes were taken into account, such as the global goodness of fit index (GFI; J¨oreskog & S¨orbom, 1989), and comparative fit indexes, such as the comparative-fit-index (CFI; Bentler, 1990) and the incremental-fit-index (IFI; Bollen, 1989). Values ≥.90 in these indexes are interpreted as an adequate fit. We also interpreted the value of the standardized root meansquare (SRMR; J¨oreskog & S¨orbom, 1989), considering an adequate fit if its value is ≤.08 (Hu & Bentler, 1989) and the value of residual root mean square error of approximation (RMSEA; Byrne, 2006), considering values ≤.08 indicators of adequate fit (Browne & Cudeck, 1993). To verify the loss of fit due to the imposition of restrictions in the multi-group model, we assessed the change in CFI (CFI), considering values ≥.01 indicative of a relevant loss of fit (Cheung & Rensvold, 2002) as well as the statistical significance of the change of SBχ2 index, using for this purpose the SBDIFF program (Crawford & Henry, 2003). The specific restrictions in the diverse invariance models were evaluated with the χ2 test. If any restriction presented an inadequate fit, we followed an iterative process of releasing the parameters with p < .05 and largest χ2 , until obtaining an adequate fit. The EQS 6.0 program was used for the analysis (Bentler, 2005). RESULTS Contrast between different areas We tested (for SR and SE) if each area had a different loading in their respective latent construct. In each sample we tested three models: (a) Antecedents or Exogenous variables, testing the PER-SIM and IN-R, both correlated with CON; (b) PRE-ATT, with the measurement model of this construct and (c) Attitudes towards Immigrant’s Acculturation, assuming ATT-MICO correlated with the ATT-AHC. In each model and factor, we constrained the values of most extreme loadings to be similar to the median one. The programme used a chi-square test to © 2013 International Union of Psychological Science
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TABLE 1 Values of the fit indexes Single group SR
χ df p χ2 /df SBχ2 df p SBχ2 /df GFI CFI IFI ST.RMR RMSEA 2
Multi-group SE
Model 2
Model 3
EX
PRE
ATT
EXG
PRE
ATT
Model 1
First step
Last step
First step
Last step
46.793 20 .0006 2.340 46.203 20 .0008 2.310 .971 .955 .956 .055 .058
2.235 3 .5251 .745 2.051 3 .5620 .684 .998 1.000 1.003 .013 .000
18.963 7 .0083 2.709 17.302 7 .0155 2.472 .984 .982 .982 .056 .062
55.861 20 .0000 2.793 52.410 20 .0001 2.620 .967 .908 .910 .065 .065
4.593 3 .2041 1.531 4.760 3 .1902 1.587 .995 .993 .993 .025 .039
10.987 6 .0888 1.831 10.262 6 .1140 1.710 .991 .991 .991 .041 .043
495.943 250 .0000 1.984 456.878 250 .0000 1.828 .937 .947 .948 .058 .033
526.967 262 .0000 2.011 485.293 262 .0000 1.852 .933 .943 .944 .074 .033
506.932 259 .0000 1.957 465.508 259 .0000 1.797 .935 .947 .948 .060 .032
559.568 267 .0000 2.096 512.923 267 .0000 1.921 .929 .937 .938 .102 .034
515.042 264 .0000 1.951 472.129 264 1.788 .934 .947 .948 .065 .032
Ex, Exogenous variables; PRE, Prejudiced Attitude; ATT, Attitude.
prove if the constrains are plausible. If a restriction failed to be assumed, it was released and then the model was tested again in an iterative process that stopped when all restrictions accepted the null hypothesis. By means of this procedure, we found that some loadings are statistically different. In SR sample, Peripheral PER-SIM was different from Central PER-SIM, χ2 (1) = 34.027, p = .0000, and Intermediate IN-R was different from Central IN-R, χ2 (1) = 13.547, p = .0000; Peripheral Cognitive Prejudice was different from Central Cognitive Prejudice, χ2 (1) = 184.682, p = .0000; and there were significant differences between Peripheral and Intermediate ATT-MICO, χ2 (1) = 37.330, p = .0000 and between Peripheral and Intermediate ATT-AHC, χ2 (1) = 22.133, p = .0000. In SE sample, Peripheral PER-SIM was different from Central PER-SIM, χ2 (1) = 14.597, p = .0001, and Intermediate IN-R was different from Central IN-R, χ2 (1) = 5.114, p = .0237; Peripheral Cognitive Prejudice was different from Central Cognitive Prejudice, χ2 (1) = 19.887, p = .0000; and there were significant differences between Central and Intermediate ATT-MICO, χ2 (1) = 24.394, p = .0000 and between Peripheral and Intermediate ATT-AHC, χ2 (1) = 25.413, p = .0000. The remaining factor loadings of every latent construct were statistically equivalent to one another. These differences showed that the areas have a different load in each of the mentioned variables, as was stated in the RAEM. Table 1 shows GFIs of the final models for both samples. Goodness of fit of the multi-group structural model The variables and their relations are shown in Figure 1. The observable variables are the mean scores for the © 2013 International Union of Psychological Science
items of the Peripheral area, the Intermediate area, and the Central area in the case of the PER-SIM, both the Acculturation Attitudes and the IN-R. CON includes the observable variables CON and nature of CON. Finally, PRE-ATT includes the means of the observable variables Co-native Prejudice, Affective Prejudice, and the three components of Cognitive Prejudice: Peripheral, Intermediate and Central. Each observable variable has its corresponding sample error. Finally, each latent exogenous factor has an error (Di ) that represents the variables not included in the model, which could explain it. Owing to the high similarity of the items, we took into account the correlations among the measurement errors of each area in the latent factors where out-group was assessed (PER-SIM, PRE-ATT, and both Acculturation Attitudes), and where the contact was assessed (CON and the Co-native component of the PRE-ATT). These trials are not included in Figure 1, to facilitate its interpretation. Though the correlated errors are usually interpreted as a lack of fit, in case of having substantive sense they should be included in the model. This is a common situation, particularly with respect to social psychological research (Byrne, 2006, p. 112). The fit of Model 1 (configurational invariance model) can be considered adequate (see Table 1). Although the χ2 and SBχ2 tests were statistically significant, χ2 (250, N = 779) = 495.943, p = .0000 and SBχ2 (250, N = 779) = 456.878, p = .0000, both the χ2 /df quotient (1.984) and the SBχ2 /df (1.828) were lower than 3.0. The rest of the indicators provide values higher than .90 (CFI = .947, IFI = .948, and GFI = .937). We can assume that the fit of the structural model is adequate and similar in both samples. The theoretical structure of the model has a good fit to the data collected from the sample.
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Next, we tested the factor invariance model, first restricting the value of the item loadings on the factors (Model 2). The Model 2 shows adequate GFIs, except for chi-square test, χ2 (262, N = 779) = 526.967, p = .0000 and SBχ2 (262, N = 779) = 485.293, p = .0000. Comparing the goodness of fit of Model 1 with that of Model 2 with the SB Scaled Difference (SBχ2 Scaled Difference (12) = 28.361, p = .0049) we found statistically significant differences. This result indicates that the factor invariance model has a lower fit than the configurational invariance model. We tested the significance of the restrictions imposed on Model 2, finding there were some unrealistic assumptions, and we proceeded releasing them. First, we released the constraint of factor CON loading on item “CON” χ2 (1, N = 779) = 8.710, p = .0032; then, the factor PER-SIM loading on item “Intermediate” χ2 (1, N = 779) = 6.330, p = .0119; finally, the factor CON loading on item “nature of CON” χ2 (1, N = 779) = 6.346, p = .0118. Although χ2 test has p < .05 (χ2 (262, N = 779) = 526.967, p = .0000; and SBχ2 (250, N = 779) = 465.508, p = .0000) χ2 /df has an adequate value (χ2 /df = 1.957, and SBχ2 /df = 1.797) as well as the other goodness of fit index (GFI = .935, CFI = .947, IFI = .948, SRMR = .060). It is acceptable to consider that the measurement model has statistically similar structure and loadings except for that of CON and PER-SIM. Comparing the Model 1 and final Model 2 fit, we obtained an SB Scaled Difference (9) = 9.268, p = .4129. There was no statistical difference between the fit of both models. We then restricted the covariance and regression coefficients between factors (see Figure 1) to determine whether the relations among the latent constructs were similar in both groups (Model 3). The fit indexes are shown in Table 1. Both χ2 tests were statistically significant, χ2 (267, N = 779) = 559.568, p = .0000 and SBχ2 (267, N = 779) = 512.923, p = .0000, with χ2 /df = 2.096 and SBχ2 /df = 1.921. However, all the fit indexes obtained results higher than .090 and an RMSEA value of .034 (90% confidence interval between .031 and .040). The value of SRMR showed a lack of fit. The test on the difference between Model 1 and Model 3, Satorra–Bentler scaled χ2 statistics showed relevant differences (SB Scaled Difference (17) = 54.329, p = .000). The model’s fit was inadequate. We proceeded to release the inadequate constraints. First, we released the regression coefficient of PRE-ATT on PER-SIM, χ2 (1, N = 779) = 20.510, p = .0000, then, the regression coefficient of PRE-ATT on IN-R χ2 (1, N = 779) = 12.593, p = .0004 and finally the regression coefficient of the ATT-MICO on PRE-ATT χ2 (1, N = 779) = 4.619, p = .0316. At this step, all constrains were correctly imposed (p > .05). Table 1 shows the final Model 3 goodness of fit. Although both χ2 based indexes, sensitive to sample size, were statistically significant, χ2 (264, N = 779) = 515.042, p = .0000 and SBχ2 (264,
N = 779) = 472.129, p = .0000, both chi-square ratios were .90 (GFI = .934, CFI = .947, IFI = .948), SRMR were .05) all the regression coefficients of the final model were statistically significant (p < .05) with absolutes values ranging from .112 to .948. The model has an acceptable fit (SR and SE samples). Figure 2 shows the final model with the standardized regression coefficients for both samples. DISCUSSION This work has developed a theoretical model that relates acculturation attitudes and the psychosocial variables of PRE-ATT, CON, PER-SIM and IN-R in two samples of native Spaniards who assessed Romanian and Ecuadorian immigrants. The goal was to empirically contrast the relations specified in the theoretical model, carried out using the RAEM and in the theoretical and empirical evidence described in the psychosocial literature, with the data obtained from the two sample sets of natives. The process employed to contrast the model took into account the possible differences in the structure of the two samples (SR and SE) and three areas—peripheral, intermediate and central. The relations specified are based on previous psychosocial literature that establishes that CON, PER-SIM, and the natives’ IN-R are predictors of PRE-ATT towards immigrants. We conducted structural equation analysis to obtain empirical evidence about the model. First, we confirm each area has a different role in the formation of the latent variables involved in the model, restricting the load of each area of every variable to have the same value. The results show that not all the restrictions were acceptable: loading of Peripheral area over PRE-ATT is lower than the Intermediate and Central areas, both on SR and SE samples. This is true, as well, in ATT-MICO and ATT-AHC. The RAEM proposes that depending on the sphere in which the interaction with persons from other cultures occurs, people do not generally use the © 2013 International Union of Psychological Science
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Figure 2. Latent variables and standardized regression coefficients in the structural model of the predictions of the RAEM for the native samples.
same strategies or do not prefer the same acculturation options (Navas et al., 2005). We find that these results are consistent with that postulate. We specified a multi-group model, involving the results of both groups (SR and SE). The multi-group analysis shows that the structure of the model is statistically similar for both groups. However, there are different regression coefficients in some paths; specifically, the manner in which PER-SIM and IN-R are related to PRE-ATT, and how this one is related to ATT-MICO. In all cases, the relation was stronger in the group of natives who rated Romanian immigrants than in the group that assessed Ecuadorians. The ethnocultural or national origin of people is a relevant element that must be taken into account when assessing the acculturation process (Bourhis et al., 1997; Piontkowski et al., 2002). The model reflects that the natives’ level of prejudice towards immigrants is related to the natives’ preferred acculturation options for immigrants (e.g. Navas et al., 2006; Zick et al., 2001). CON is related to PER-SIM and IN-R, all being related to PRE-ATT (e.g. Brown, 1984; G´omez-Berrocal & Navas, 2000; Hogg, 1992; Pettigrew, 1986). It would be a helpful exercise to prove the model with other variables that predict the natives’ attitude towards immigrants’ acculturation. It would increase the proportion of explained variance of both attitudes. Testing a comparable model with samples of immigrants (by means of a similar procedure) should give empirical support for the RAEM. Another limitation of the study is the concomitance of the measurement of all elements. This implies a lack of the longitudinal sense of the conclusions that is needed to establish the steps of a process. There is a need for longitudinal studies that © 2013 International Union of Psychological Science
take into account these steps, especially in the immigrant population. The results obtained in the present work are an important contribution to the field of prejudice and the acculturation process. PRE-ATT is an antecedent of natives’ acculturation attitude towards the two groups of immigrants (Romanians and Ecuadorians), as had been hypothesized and verified using the RAEM in correlational studies, with a multivariate data analysis that allows to test the relations structure. The results can guide the policies of social intervention: reduction of the levels of prejudice in the native population would favour non-assimilationist acculturation options. And this would probably lead to an improvement of inter-group relations. The results also show that the reduction of PRE-ATT is related to the CON, PER-SIM and IN-R in RAEM spheres. There are obviously other psychosocial variables, such as perceived cultural enrichment, the perception of out-group threat, the status and power relations between groups, etc. (e.g., Bourhis et al., 1997), and even variables of another nature (political, economic, etc.), which may underlie the native population’s prejudiced attitudes towards certain groups of immigrants, and which were not included in this investigation. Moreover, it should not be forgotten that prejudice is mainly characterized by its specificity, that is, by the importance of contextual factors, such as the ethnocultural origin of the immigrant out-group, the state of the intergroup relations at specific places and times, and others. However, despite the limitations of this study (in the number of antecedent variables considered), the variables included do act as antecedents of prejudiced attitude, and the PRE-ATT determines the natives’ acculturation
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options towards immigrants of Romanian and Ecuadorian origin. Manuscript received June 2012 Revised manuscript accepted May 2013 First published online November 2013
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