In this paper, we study the adjustment outcomes of emotional <\/em>acculturation, an aspect of implicit acculturation, over time. We are broadly interested in the benefits and potential costs of emotional fit among youth of immigrant minority background attending ethnically diverse schools. As in previous research, we conceptualizeemotional fit as the fit between minorities\u2019 emotional patterns and the normative emotional patterns in the majority culture (e.g., De Leersnyder et al., 2011; Jasini, De Leersnyder, Ceulemans, et al., 2023).<\/p>\n\n\n\n Emotional acculturation can be understood against the background of cultural differences in the prevalent emotional patterns (e.g., Kitayama et al., 2006; Mesquita et al., 2016). There is an initial misfit between the prevalent emotion patterns in the culture of origin (or heritage) and those in the new or dominant culture. We have found that the degree to which individuals from immigrant-descent engage with the dominant culture (e.g., time in the new culture, number of dominant culture friends) is in fact associated\u00a0 with their emotional acculturation; i.e. the fit of their patterns of emotions with the normative patterns of the dominant culture (De Leersnyder et al., 2011; Jasini et al., 2019; Jasini, De Leersnyder, Ceulemans, et al., 2023; Jasini, De Leersnyder, Gagliolo, et al., 2023).<\/p>\n\n\n\n There is good reason to assume that emotional acculturation benefits the psychological and social adjustment outcomes of immigrant minorities. Emotion acculturation \u2013i.e., having emotions that match the norm of the majority culture\u2014may provide minorities with tools to understand and fulfil the cultural demands in their everyday life. Emotional fit with culture may enable minorities to view social situations through the lenses of the majority culture members but may also give them a sense of belonging or of being part of the culture, which in turn may lead to adaptive behaviors in contexts emphasizing the majority culture values.<\/p>\n\n\n\n There are additional reasons to assume emotional acculturation may have positive outcomes. First, emotions play an important role in forging and maintaining good relationships with others (Boiger & Mesquita, 2012; Fischer & Manstead, 2016; Parkinson, 1996; Parkinson et al., 2005). Second, emotional similarity is beneficial, even outside of migration contexts. Emotional similarity, whether between close friends, the partners of romantic relationships, or the members of work teams, has been linked to relationship satisfaction and (group) identification (e.g., Anderson et al., 2003; Delvaux et al., 2015; Rosenblatt & Greenberg, 1988; Schachter, 1959). Furthermore, having emotions that fit those of a group also predicts self-categorization as a group member (Livingstone et al., 2011), which in the case of immigrant minorities, may be consequential for their sense of belonging in the majority culture group (e.g., Phinney et al., 2001). Consistent with previous research, studies on individuals from immigrant-descent have found that their fit to the normative emotions in the majority culture is associated with relational and health benefits (Consedine et al., 2014; Jasini et al., 2018, 2019; Jasini, De Leersnyder, Gagliolo, et al., 2023).<\/p>\n\n\n\n Evidence for the benefits of minorities\u2019 emotional fit with the majority culture norm is still limited in scope and largely based in cross-sectional research. One exception is longitudinal research with middle school students from immigrant-descent (Jasini, De Leersnyder, Gagliolo, et al., 2023). The study yielded bidirectional longitudinal associations between immigrant-descent minority students\u2019 emotional fit to the majority norm and their contact with majority peers the next year. Emotional acculturation (measured as fit with the majority norm) predicted contact with majority peers one year later, and was also predicted by contact with majority a year earlier. The current study both replicates and expands on these results, and does so in a school context.<\/p>\n\n\n\n Acculturation processes are domain-specific<\/a>: In the realm of explicit acculturation, both the types of acculturation orientations, and their respective links to adjustment outcomes have been found to be dependent on the specific context (e.g., Arends-T\u00f3th & van de Vijver, 2004; Karata\u015f, 2025). We expect implicit acculturation that results from adjustments to the task requirements of the sociocultural context, to be equally domain-specific. For this reason, and given pragmatic considerations, we chose to conduct our research in one particular domain: the school context.<\/p>\n\n\n\n Understanding the consequences that emotional acculturation may have for minority youth in school contexts is important considering that the school may be the primary and most significant majority culture context for minority youth. School is the context that provides continuous opportunity for contact with majority culture members and exposure to the majority culture norms (Schachner et al., 2018; Vedder & Motti-Stefanidi, 2016). Here we focus specifically on the link between minorities\u2019 emotional fit and social outcomes in the context of secondary schools. Acculturation research has referred to these outcomes as \u2018sociocultural adjustment\u2019 \u2013 i.e., the extent to which one has the cultural competence to navigate effectively and function well in the social networks and social situations in the majority culture (Berry, Phiney, et al., 2006; Searle & Ward, 1990; Ward & Kennedy, 1999).<\/p>\n\n\n\n In the context of the school, emotional fit may help minorities to meet the cultural tasks in that particular context and function well in peer relationships, the learning domain, as well as in the students\u2019 relationship with the school in general (i.e., complying with the values, norms and expectations of the school). Alongside the previously documented role of emotional fit in peer relationships (Jasini, De Leersnyder, Ceulemans, et al., 2023) we expect emotional fit to positively predict the extent to which minorities like being in school and are motivated to learn, feel active and engaged rather than passive and disengaged in the learning process, and show behaviors that are in line with the prescribed school norms (cf. Stephens et al., 2012). School motivation, school behavioral engagement and disengagement, and norm-related behaviors at school are considered some of the most important indicators of socio-cultural adjustment of minority youth in schools (Bond et al., 2007; Chase et al., 2014; Dotterer & Lowe, 2011; Finn & Rock, 1997). While the role of explicit acculturation processes on these indicators has been studied (Baysu et al., 2014; Benner et al., 2018; Civitillo et al., 2024), this study is the first to examine the role of implicit acculturation processes such as emotional acculturation on sociocultural adjustment.<\/p>\n\n\n\n Finally, we explore whether sociocultural adjustment outcomes of emotional acculturation differ depending on perceived school climate. Perceived discrimination<\/a> may harm minority students\u2019 willingness to interact with majority culture members as well as to engage in educational tasks (Civitillo et al., 2023, 2024; Cooper & S\u00e1nchez, 2016; Hood et al., 2017; Titzmann & Jugert, 2015; Verkuyten et al., 2019). Relatedly, previous research has shown that whereas a strong orientation towards the majority can be positively associated with school adjustment (e.g., high motivation, good school engagement, and low school maladaptive behaviors; Berry, Phinney, et al., 2006; Hillekens et al., 2023; Schachner et al., 2016, 2018), in contexts where students report high levels of perceived discrimination, having a strong orientation towards both the majority culture and the heritage culture, can become \u00a0a liability, and is associated with lower academic adjustment and achievement (Baysu et al., 2011). One reason may be that perceptions of discrimination become more hurtful as minority youth adopt the majority culture norms and belong, as they may start comparing themselves to their majority peers, noticing their disadvantage to them (Verkuyten, 2024<\/a>). This may lead to disengagement.<\/p>\n\n\n\n In the present study, we focus on the longitudinal sociocultural adjustment consequences of emotional acculturation for immigrant-origin minority youth in a school context. We are interested in both benefits and costs of emotional acculturation in immigrant minority youth and how these relate to varying levels of perceived discrimination at school. Our first hypothesis<\/em> is that emotional fit with the majority culture is positively associated with sociocultural adjustment over time. As part of testing this hypothesis, we seek to replicate findings from previous research that the emotional acculturation of minority students of immigrant-descent predicts their contact with majority peers over time. As another part, we test the role of minority students\u2019 emotional acculturation in longitudinally predicting their school motivation\/engagement, another aspect of their sociocultural adjustment that has not been studied in conjunction with emotional acculturation. Our second hypothesis<\/em> is that the longitudinal association between minority students\u2019 emotional fit and their sociocultural adjustment outcomes is negatively affected to the extent they perceive discrimination in school. Emotional acculturation may be less adaptive or even disruptive when perceived discrimination is high.<\/p>\n\n\n\n Participants were 1588 minority students who attended waves 1 and 2 of the Leuven-CILS study.[i]<\/a> Minority students were classified as such when they, or at least one of their parents or grandparents, were born in a non-neighboring country to Belgium. We specifically focused on non-neighboring minorities based on findings from previous research showing that whereas minorities from neighboring countries to Belgium (i.e., France, Germany, Luxembourg, the Netherlands, the UK) do not differ in their emotional fit to the majority culture compared to the majority group (Jasini et al., 2019), minorities from non-neighboring countries had on average a lower emotional fit than the majority culture members. \u00a0\u00a0<\/p>\n\n\n\n To account for potential contact with majority members within the school context, we excluded participants from schools where 60% or more of the student body consisted of minority students (N<\/em> = 626 minority students excluded). Additionally, to ensure consistency in the school context over the course of the study, we excluded participants who changed schools between the two data collection waves (N<\/em> = 13 minority students excluded).<\/p>\n\n\n\n The final sample included in the analyses is 949 minority students from 53 secondary schools. On average, participants were 14.93 years old in wave 1 of data collection (range 12.57 \u2013 19.41 years old; SD<\/em> = 1.27). Fifty-five % of the participants identified themselves as female (N<\/em> = 519), 43% identified themselves as male (N<\/em> = 412) and 2% of the participants did not report their gender (N<\/em> = 18). Of the final sample, 28% were foreign-born (i.e., 1st<\/sup> generation minorities, N <\/em>= 264). Another 34% were second generation minorities, with both parents born outside of Belgium (N <\/em>= 326). A total of 25% were classified as 2.5 generation, with one parent born abroad and one born in Belgium (N <\/em>= 234). Additionally, 7% were third generation, with parents born in Belgium and at least one foreign-born grandparent (N <\/em>= 64). For 6% of the minority participants, generational status could not be determined due to missing data (N <\/em>= 61). In terms of country of origin, most participants came from Poland (37%, N <\/em>= 353), Turkey (24%, N <\/em>= 224), and Morocco (21%, N <\/em>= 197). The remaining participants originated from a range of other countries (e.g., Italy, Congo; 15%, N <\/em>= 144). For 3% of participants (N <\/em>= 31), the country of origin could not be determined due to missing data. About half of the participants reported that their mothers and fathers had a lower than higher vocational education or university degree (52% of mothers completed high school [N <\/em>= 493]; 51% of fathers completed high school [N = <\/em>488]).<\/p>\n\n\n\n For this study, we utilized data from the first two waves of the Leuven-CILS study (Leuven Children of Immigrants Longitudinal Study; Phalet et al., 2018). The Leuven-CILS study, which took place from 2012 throughout 2015, had a three-wave longitudinal design (i.e., with one year between two consecutive data collection waves) and aimed to uncover the processes behind the achievement gap between majority and immigrant minority students in Flemish secondary schools. Both majority and minority students were recruited through a stratified random sampling method, departing from a list of secondary schools provided by the Flemish Ministry of Education (Phalet et al., 2018). Before data collection, the ethical considerations and guidelines were approved by the ethical committee for the social sciences at KU Leuven. Informed active consent was obtained from participants as well as from their parents, teachers, and school administrators. Participants completed questionnaires in Dutch, their language of instruction, during class time and under the supervision of a teacher and a research assistant.<\/p>\n\n\n\n Participants\u2019 emotional fit with the majority emotion norms was assessed in each wave using the Emotional Patterns Questionnaire (EPQ; De Leersnyder et al., 2011). Participants were asked to recall two emotional experiences in the school context that aligned with two out of four different prompts. The prompts varied in two main dimensions of emotional experience (i.e., Kitayama et al., 2000); valence (positive or negative) and social engagement of the situation (i.e., socially engaging or a socially disengaging). Half of the participants received two socially engaging prompts (i.e., \u201cThink about an event that you experienced at school not so long ago, as a result of which you felt good\/bad about your relationships with other people\u201d). The other half were asked to recall two socially disengaging emotional situations (i.e., \u201cThink about an event that you experienced at school not so long ago, as a result of which you felt good\/bad about yourself\u201d).<\/p>\n\n\n\n For each of the two recalled emotional experiences, participants were asked to rate the degree in which they experienced a list of 15 emotions on a Likert scale ranging from 1 (very much<\/em>) to 5 (not at all<\/em>): I felt good, happy, sad, proud, guilty, connected, frustrated, elated, ashamed, angry, surprised, indebted, reliant, disappointed, and respectful. This specific list was constructed to capture positive vs. negative emotions, as well as socially engaging (emotions that mark relatedness; e.g., \u201cI felt ashamed\u201d) and socially disengaging emotion words (emotions that mark individuality; e.g., \u201cI felt proud\u201d).<\/p>\n\n\n\n The \u201cI felt good\u201d and \u201cI felt sad\u201d emotion items were omitted as they served as general checks (i.e., whether participants described an emotional prompt that aligned with the prompt in terms of valence). We conducted a Simultaneous Component Analysis (SCA; De Roover et al., 2012) to assess the measurement equivalence of the remaining 13 emotion items across the majority and minority group. The results showed that \u201cI felt surprised\u201d was not structurally equivalent across both groups and was therefore omitted from further analyses (see Jasini et al., 2019; Jasini, De Leersnyder, Gagliolo, et al., 2023 for an overview of the analysis).<\/p>\n\n\n\n We computed participants\u2019 emotional fit scores at each wave by means of profile correlations. In a first step, for each type of situation, we computed the average 12-emotion item profile of all the majority participants in the sample by calculating the average intensity on each of the 12 emotion items across the majority sample. Next, we correlated each participant\u2019s emotional profile with the average majority profile of the corresponding situation. Thus, up to two emotional fit scores were computed for every participant, one emotional fit score for positive situations, and one for negative situations. We calculated emotional fit scores only for participants who rated at least nine out of 12 emotion items (i.e., for participants with valid data on 75% of the variables needed for the correlation analysis) to ensure that we get reliable correlation scores. We further transformed these two correlation scores into Fisher z-values and computed their average. At the end of this procedure, each participant had one final emotional fit score that was included in the analyses.<\/p>\n\n\n\n We captured participants\u2019 perceived discrimination at school at wave 1 via four items, introduced by the prompt \u201cIn my school\u2026\u201d: (1) \u201cdifferent cultures and religions are treated with respect\u201d, <\/em>(2) \u201cthey take strong action against racism and discrimination\u201d, <\/em>(3) \u201cteachers treat all students equally regardless of their religion or descent\u201d,<\/em> and(4) \u201cteachers say that you shouldn\u2019t discriminate against students with another culture or origin\u201d<\/em> (\u03b1 = .66; adapted from Teachers\u2019 Multicultural Attitude Scale, Thijs et al., 2012; and used in previous studies, Baysu et al., 2024). All items were rated on a scale from 1 (strongly agree<\/em>) to 5 (strongly disagree<\/em>). These items were averaged to denote the participants\u2019 individual perceptions of discrimination at school.<\/p>\n\n\n\n Contact with majority members was measured with two items: (1) \u201cHow many of your friends are of Belgian origin\u201d (rated on a Likert scale ranging from 1 [almost all or all<\/em>] to 5 [almost none or none at all<\/em>]) and (2) \u201cHow often do you spend your school breaks with students of Belgian origin?\u201d (rated on a Likert scale ranging from 1 [every day<\/em>] to 5 [never<\/em>]). The ratings were reverse-scored and combined into a composite index (Spearman-Brown coefficients were .71 at wave 1 and .66 at wave 2) with higher scores reflecting higher majority contact.<\/p>\n\n\n\n School engagement was assessed separately for motivation in school <\/em>([1] \u201cI like to learn new things in class\u201d,\u00a0 [2] \u201cI feel good in class\u201d, and [3] \u201cI like to be in class\u201d; wave 1 \u03b1 = .71, wave 2 \u03b1 = .73), behavioral engagement<\/em> ([1] \u201cI work as hard as I can in class\u201d, [2] \u201cI listen carefully during the class\u201d, and [3] \u201cI pay attention in class\u201d; wave 1 \u03b1 = .80, wave 2 \u03b1 = .83), behavioral disengagement<\/em> ([1] \u201cIn class my thoughts easily wander away\u201d, [2] \u201cI often think of other things during class\u201d, and [3] \u201cI do not really do my best at school\u201d; wave 1 \u03b1 = .63, wave 2 \u03b1 = .61) (the items of these three scales were adapted from the Engagement versus Disaffection with Learning scale; Skinner et al., 2008). The items were rated on a Likert scale ranging from 1 (strongly disagree<\/em>) to 5 (strongly agree<\/em>). For each of the three constructs, the ratings were averaged so that each participant had one score for motivation in school, one score for behavioral engagement, and one score for behavioral disengagement. We furthermore assessed non-compliant behaviorat school <\/em>by means of three items (How often do you [1] \u201cget a punishment in school?\u201d, [2] \u201cskip a lesson without permission?\u201d, and [3] \u201ccome late to school?\u201d; wave 1 \u03b1 = .55, wave 2 \u03b1 = .54) which were adapted from (Wang et al., 2011). The items were rated on a Likert scale ranging from 1 (never<\/em>) to 5 (every day<\/em>). The ratings were averaged to denote participants\u2019 non-compliant behavior at school.<\/p>\n\n\n\n We controlled for participants\u2019 age reported at wave 1 and gender (dummy-coded with \u201cboy\u201d as a reference group).[ii]<\/a><\/p>\n\n\n\n We tested two hypotheses for each outcome using multilevel regressions where students were nested in schools. In each regression model, we used outcome variables that were measured at the second wave, and predictors and control variables that were measured at wave 1.<\/p>\n\n\n\n To test H1, we included emotional fit at wave 1 as a predictor of the outcome variables (i.e., majority contact and school engagement), while we controlled for age, gender, and the outcome variable measured at wave 1. To test H2, we carried out multilevel moderation analyses, in which we included an interaction term between perceived discrimination at wave 1 and emotional fit at wave 1 as predictor of outcomes at wave 2, controlling for age, gender, and outcome variable measured at wave 1. Perceived discrimination was modeled at the individual level. For all analyses, we centered the continuous predictors around the grand mean. In these analyses, we aimed to test only the time-lagged effect of emotional fit and perceived discrimination on adjustment outcomes and therefore, we did not control for the autoregressive effects between emotional fit at wave 1 and 2, and between perceived discrimination at wave 1 and 2. We established that the hypotheses were met when (i) the model with predictors or the interaction fit the data better than the preceding model and (ii) when the associations (i.e., as indicated by regression coefficients) were found to be significant and in the hypothesized direction.<\/p>\n\n\n\n To account for potential school-level influences, we also conducted additional analyses in which perceived discrimination was modeled at the second level rather than the individual level. First, we examined whether school-level perceptions of discrimination moderated the association between emotional fit and the outcomes. Next, we examined the original individual-level interaction model and included the school-level interaction as an additional control. The pattern of findings remained consistent and the conclusion reported below were unaffected by the inclusion of school-level perceptions. The results of these analyses are reported in the supplementary materials at https:\/\/github.com\/AnouckCochez\/Paradoxical-Effect-of-Emotional-Acculturation<\/a>.<\/p>\n\n\n\nEmotional Acculturation and its Associated Adjustment Outcomes<\/strong><\/h3>\n\n\n\n
Potential Benefits and Costs of Emotional Fit in Multicultural Secondary Schools \u00a0<\/strong><\/h3>\n\n\n\n
The Present Study<\/strong><\/h3>\n\n\n\n
Method<\/strong><\/h2>\n\n\n\n
Participants<\/strong><\/h3>\n\n\n\n
Procedure<\/strong><\/h3>\n\n\n\n
Materials<\/strong><\/h3>\n\n\n\n
Emotional Fit With Majority Culture<\/strong><\/h4>\n\n\n\n
Perceived Discrimination at School<\/strong><\/h4>\n\n\n\n
Majority Contact<\/strong><\/h4>\n\n\n\n
School Engagement<\/strong><\/h4>\n\n\n\n
Control Variables<\/strong><\/h4>\n\n\n\n
Analytical Strategy<\/strong><\/h3>\n\n\n\n
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