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European Journal of Psychotraumatology logoLink to European Journal of Psychotraumatology
. 2024 Dec 9;15(1):2430923. doi: 10.1080/20008066.2024.2430923

Migrant students’ self-reported executive function skills in relation to mental health, postmigration stress, and positive appraisals of self and the social context

Auto-reporte en habilidades de función ejecutiva de estudiantes migrantes en relación con la salud mental, el estrés postmigratorio, las valoraciones positivas de sí mismos y del contexto social

Marianne Opaas a,CONTACT, Tore Wentzel-Larsen a, Alexander Nissen a, Per Kristian Hilden a, Raija-Leena Punamäki b, Caroline Spaas c, Signe Smith Jervelund d, Reeta Kankaanpää b,e, Morten Skovdal d, Kirsi Peltonen e, Lucia De Haene c, Sofie de Smet c,f, An Verelst g, Ilse Derluyn g, Arnfinn J Andersen a
PMCID: PMC11632921  PMID: 39648846

ABSTRACT

Background: Refugee and non-refugee migrant youths may carry a double burden of past adversities and post-migration stress while trying to continue schooling and adapt to their new social and cultural environment. Executive functioning skills are central to learning and navigating in the new context. Knowledge of how young migrants’ executive functioning is associated with stressful factors and positive or potentially protective factors, could contribute to understanding and possibly finding ways to support these young learners.

Objective: To investigate how potentially stressful and positive factors are associated with executive function skills.

Method: In a secondary, explorative analysis of questionnaire responses from 1312 migrant students in secondary schools in five European countries, the associations of planning- and initiative executive function skills (PIS-EF) with stressful factors (e.g. emotional and behavioural problems, daily stress, discrimination) and positive factors (e.g. resilience, school belonging, social support) were analysed by linear regression. Furthermore, differences between male/female and refugee/non-refugee migrants were examined.

Results: Positive factors accounted for almost one-fifth of the variance in the students’ self-reported PIS-EF and stress factors only one-tenth. Resilience showed the strongest association with students’ PIS-EF, followed by Prosocial behaviour and School belonging. Hyperactivity, and symptoms of anxiety and depression were negatively associated with PIS-EF. Posttraumatic stress symptoms were minimally associated with the investigated aspects of executive functions. Adjusted for other variables, no variables showed significant differences in the association with EF between males and females, and refugee and non-refugee migrant students.

Conclusions: Positive factors were more strongly associated with executive functioning than stressful factors and could represent pathways to strengthen executive functioning. To support migrant youths’ functioning, the school, healthcare, and social systems should take a resource-oriented perspective and lay the ground for migrant youth's feeling of belongingness and active use of their personal resources.

KEYWORDS: Migrant students, refugees, executive function, mental health symptoms, postmigration stress, resilience, school belonging, adolescents

HIGHLIGHTS

  • Mental health symptoms and postmigration stressors as well as positive or potentially protective factors, such as resilience and social support, were investigated for their association with executive functioning among refugee and non-refugee migrant youth in secondary schools in five European countries.

  • Resilience, prosocial behaviour, and school belonging were positively and more strongly associated with the studied aspects of executive functioning (PIS-EF), than hyperactivity and symptoms of anxiety and depression, which were negatively associated with PIS-EF.

  • Interventions aiming to create the best possible conditions for migrant youths’ resilience, opportunities for prosocial behaviour, and a school environment that fosters a sense of belonging, could strengthen these young learners’ executive- and overall functioning.

1. Introduction

Executive functions, such as goal setting, planning, initiative taking, attention, and working memory, are acknowledged as prerequisites for learning and academic achievement (Donati et al., 2019; Escolano-Pérez & Bestué, 2021; Laurent, 2020), as well as for many aspects of social and overall functioning (Barr, 2018; Zelazo et al., 2016; Zorza et al., 2016). Young migrants’ executive functioning (EF) may be affected by mental health problems and post-migration stressors, such as daily life problems and discrimination. Conversely, positive or potentially protective factors, such as resilience and social support, may mitigate the effects of such stress. Existing research has predominantly focused on mental health problems and stressful experiences in association with EF. However, few studies have investigated the associations of positive or potentially protective factors with EF in migrant youth populations (Scharpf et al., 2022). Due to the central role of EF for learning and social functioning, knowledge about factors associated with EF could inform actions directed at enhancing immigrant adolescents’ school-related functioning and prospects to succeed in the new country.

Research extensively documents the traumatic experiences and losses faced by refugee children and youth during mass conflicts in their country of origin and during flight (Fazel et al., 2012). Thus, the risk of posttraumatic stress symptoms (PTSS), posttraumatic stress disorder (PTSD) and other mental health problems are found to be heightened among refugees (Blackmore et al., 2020). Among children and youth with other migrant backgrounds, traumatic experiences are not as common, but PTSS and other mental health problems are frequent also among these youths (Kouider et al., 2014; Spaas et al., 2022). Refugee and non-refugee migrant youth share the stress of adapting to a new country that may be more or less welcoming and culturally and linguistically different. Both groups commonly report stressful post-migration experiences such as discrimination (Metzner et al., 2022; Spaas et al., 2022). We presume for all learners, including refugees and migrants, that wellbeing and a mind that is not occupied by worries are fundamental to their ability to thrive and learn. Learning the language of the reception country and acquiring education are crucial for migrant youths’ later adjustment in working life and society (Christensen & Stanat, 2007). Findings in a systematic review indicated that high academic ambition, supportive home environment, and supportive peer relationships were success factors for learning, while bullying, racial discrimination, and pre- and post-migration trauma were risk factors (Graham et al., 2016). Such positive factors along with different sources of stress have not, to our knowledge, been examined for young migrants’ EF. This is where the current study aims to contribute.

In this paper, the term ‘executive functions’ (EFs) refers to the brain's higher order executive capacities, whereas ‘executive functioning’ (EF) refers to how these capacities operate in the present. We will shortly introduce the brain's executive functions, relevant research, factors often studied in relation to EF, and other factors that we consider relevant for exploration in relation to executive functioning.

1.1. The executive functions

EFs entail higher-order cognitive abilities that are crucial for learning and academic success in school and work (Bauer et al., 2021; Berthelsen et al., 2017; Maja et al., 2022), and for facilitating social behaviour (Zorza et al., 2016). Various terms are used to describe different cognitive tasks and subdomains of EF, including working memory, inhibition, and cognitive flexibility (Op den Kelder et al., 2018); complex tasks, verbal fluency, inhibition, shifting, and working memory (Nyvold et al., 2021); and Planning and Initiative, Attention, and Self-Control and Self-Monitoring (sub-scales of the AEFI; see Methods; Van der Elst et al., 2012). These functions and their development are vital for conscious, goal-directed thought and action (Barr, 2018; Berthelsen et al., 2017). When operative, EFs enable the individual to regulate attention, resist distractions, tolerate frustration, inhibit impulsivity, flexibly shift between tasks and approaches, to draw on past experiences in the consideration of alternative acts and their consequences, and to plan for the future (Zelazo et al., 2016). When impaired, working memory may suffer, and focusing, following directions, and handling of emotions can be difficult (Federico & Orsolini, 2022). EFs start to develop in early childhood and undergo extended development during adolescence and early adulthood (Berthelsen et al., 2017; Laub et al., 2020).

Dependent on the timing, adverse childhood experiences (ACEs) and extreme life stress may negatively affect the development or functioning of cognitive processes falling under the label of EFs (Maja et al., 2022). Executive dysfunction has been found to moderate the relationship between ACEs and mental health (Trossman et al., 2021) and in particular between ACEs and posttraumatic stress disorder (PTSD), suggesting a centrality of executive dysfunction in developing PTSD after trauma exposure (Aupperle et al., 2012; Hodgeon et al., 2018). However, adversity in childhood may also lead to enhanced cognitive skills, rather than deficits. Neural plasticity may facilitate the development of stress-adapted capacities and skills that enable the individual to function within harsh and volatile environments (BJ Ellis et al., 2020). Furthermore, studies have shown that when discriminating between threat-related and deprivation-related childhood adverse experiences, only deprivation was linked to inadequate development of EFs (Lambert et al., 2016; Sheridan et al., 2017).

Much of the research on EF uses experimental design and specific tasks to examine executive functions (Keating et al., 2022; Scharpf et al., 2022). Such performance-based measures provide observable and relatively neutral information on specific skills related to EFs (Maja et al., 2022). Still, the context, method, and content of performance-based testing could affect the results (Mirabolfathi et al., 2022; Snyder et al., 2014). Conversely, self-reported behavioural measures of EF (Dixson & Scalcucci, 2021) can provide ecologically valid information reflecting daily-life functioning connected with EF (Maja et al., 2022), but depend on how the respondents see themselves and choose to respond.

1.2. Stressful factors associated with executive functioning

Among adults and non-refugee youth, previous research has linked EF difficulties to higher levels of trauma exposure, higher levels of PTSS, an established PTSD, other trauma-related mental health problems, and to higher age (Barzilay et al., 2018; Li et al., 2019; Nyvold et al., 2021; Op den Kelder et al., 2018; Polak et al., 2012). According to Van der Kolk (2014), ‘recovery from trauma involves the restoration of executive functioning’.

Research in refugee youth populations have found positive associations of EF with trauma exposure and PTSD (Scharpf et al., 2022) and a negative association of EF with current poverty rather than war-related potentially traumatic experiences (A Chen et al., 2019), which seem to support the findings that early adversity may lead to enhanced cognitive skills (BJ Ellis et al., 2020), while early deprivation may lead to their underdevelopment (Lambert et al., 2016; Sheridan et al., 2017). An additional explanation for the positive association of EF with trauma experiences and PTSS, suggested by Scharpf et al. (2022), was that youth with better EF might have higher reflective and introspective capacities enabling the reporting of more traumatic experiences and symptoms. A finding offering an important distinction was that adolescents with a traumatic background and with a high level of PTSS performed significantly worse on performance based EF tasks than controls who had not been exposed to previous trauma, but only when exposed to trauma-related distractors – not when exposed to neutral distractors (Mirabolfathi et al., 2022).

The present evidence indicates a complex relationship between EF and adversity, where early, severe stress may modify and deprivation or neglect obstruct the development of EFs, where later stress and trauma may impede or further modify EFs, where inadequately developed or impeded EFs may increase vulnerability to PTSD, where negative effects on EF of trauma and high levels of PTSS may primarily be found when individuals are distressed by trauma-reminders, and where perhaps research methods and context, and the population studied, will impact on whether PTSS in turn are found to aggravate or be positively or negatively related to EF.

Other distressing/stressful factors that have been related to EF in children and youth populations, are hyperactivity (Chwastek et al., 2022; Craig et al., 2016), anxiety, and depression (Alfonso and Lonigan, 2021; Friedman et al., 2018; Owens et al., 2012; Snyder et al., 2014), and experiences of discrimination (Keating et al., 2022). In general, post-migration stressors, such as uncertain asylum status, discrimination, lack of social support, language problems, and financial difficulties, are known to negatively affect the mental health and functioning of refugee children and youth (Bronstein & Montgomery, 2011; Juang et al., 2018; Spaas et al., 2022). However, knowledge about such post-migration stressors in relation to EF in migrant populations is lacking.

1.3. Positive factors associated with executive functioning

In recent years, protective factors have gained focus in research related to mental health, trauma, and psychological and academic functioning at school (d’Abreu et al., 2021; Korpershoek et al., 2020; Renshaw et al., 2014). Among adolescents from refugee and other migrant backgrounds, studies of the associations between positive or protective factors such as social support or resilience and academic success/learning are scarce (Wong et al., 2018), and even scarcer in relation to EF. Relevant for our study could be positive factors such as resilience, prosocial behaviour, social support, wellbeing, and students’ sense of school belonging, which have been studied in relation to EF in populations other than migrant adolescents (Bauer et al., 2021; Dixson & Scalcucci, 2021; Hirani et al., 2022; Scharpf et al., 2022; Taylor & Ruiz, 2019; Van der Graaff et al., 2018; Zorza et al., 2016), or studied in relation to aspects of functioning such as learning or academic success (Baker et al., 2019; Balaž et al., 2021; Graham et al., 2016; Khawaja & Schweitzer, 2017; Korpershoek et al., 2020; Lam et al., 2015; Pagel & Edele, 2022; Pekrun et al., 2017; Renshaw et al., 2014; Wong et al., 2018). Dixson and Scalcucci (2021) suggested psychosocial factors may represent a pathway to improve adolescent EF.

1.4. Differences relevant to executive functioning between genders and migrant backgrounds

Male and female young migrants and migrants with and without a refugee background are likely to have different histories of pre-migration hardships (Mundy et al., 2020), may face different strains in the new country (Hollander et al., 2011; Mohwinkel et al., 2018), and may experience different obstacles to learning and succeeding in the new country. Studies in the general literature on gender differences in EF yield inconsistent results depending on maturational level, cultural setting and the specific EF task (A Chen et al., 2019; Grissom and Reyes, 2019; Scharpf et al., 2022). We have not found studies on associations between EF and other variables comparing migrant boys and girls. Furthermore, there are few, if any, studies comparing refugee with non-refugee migrant youth regarding EF and associated variables.

1.5. Aims

Our aim was to explore the associations of stressful and positive factors with self-reported EF in a migrant youth population. Such knowledge may be essential for planning interventions aimed at supporting young migrants’ learning and potential to succeed in their new country. We wanted to examine emotional and behavioural problems, daily life stresses and perceived discrimination for their expected negative associations with EF, and factors like resilience, a sense of school belonging, prosocial behaviour, wellbeing, and perceived support from family and friends for their expected positive associations with EF. We also aimed to examine how these relationships varied for male and female migrant students, and for migrant students with and without a refugee background.

2. Method

The current explorative study used questionnaire data from a large-scale intervention study, the RefugeesWellSchool project (RWS; an EU-Horizon 2020 funded project, grant number 754849), including refugee- and non-refugee migrant youths in secondary schools in Europe. The aim of the main study was to examine the effect of psychosocial interventions on migrant students’ mental health and wellbeing. Ethical clearance was given in each country, and for the whole project. A comprehensive questionnaire on a range of topics was composed from whole or parts of commonly used questionnaires. It was translated to 22 different languages. Students were informed about the study, and that participating was voluntary. Data was collected in the classrooms or in smaller groups. Help was available from teachers, research staff, and interpreters where needed. For more details, see Spaas et al. (2022).

For our research aims, we used self-reported pre-intervention questionnaire data for all measures. These were collected in 2019–2020. The questionnaire included the ‘Planning and Initiative’ subscale (hereafter termed PIS-EF) of the Amsterdam Executive Function Inventory (AEFI; Van der Elst et al., 2012). The subscale included questions related to the EF area of cognitive flexibility, which was found to best predict educational attainment after age 11 (Federico & Orsolini, 2022). We examined the associations of PIS-EF with the questionnaire variables PTSS, emotional symptoms, conduct problems, hyperactivity, peer problems, daily life stress, and perceived ethnic discrimination (potentially stressful factors) and with wellbeing, resilience, school belonging, prosocial behaviour, and perceived support from family and friends (positive or potentially protective factors).

2.1. Participants

We used data from five of the six European countries taking part in the RWS project: Belgium, Denmark, Finland, Norway, and Sweden. The UK data was not included, as we could not resolve some scoring inconsistencies in one of their scales. From the data set, we included migrant students age 11–24 years, with a length of stay in the resettlement country from zero to eight years, and who had reported their gender as male or female. Based on our selection criteria, the sample consisted of 706 male and 606 female students with a refugee or non-refugee migrant background (N = 1312). For details, see Table 1.

Table 1.

Country of present residence, origin and reason for migrating.

  All
(N = 1312)		 Male migrant students
(N = 706, 53.8% of all)		 Female migrant students
(N = 606, 46.2% of all)
Variable M (SD) M (SD) M (SD)
Age (years) 15.5 (2.0) 15.5 (1.9) 15.5 (2.2)
Time in reception country (years) 1.93 (1.80) 1.78 (1.63) 2.11 (1.96)
Country of residence Per cent (n) Per cent (n) Per cent (n)
Residing in Belgium 41.2 (540) 42.4 (299) 39.8 (241)
Residing in Denmark 18.4 (241) 19.1 (135) 17.5 (106)
Residing in Norway 17.1 (224) 16.9 (119) 17.3 (105)
Residing in Sweden 13.0 (171) 11.3 (80) 15.0 (91)
Residing in Finland 10.4 (136) 10.3 (73) 10.4 (63)
  All (N = 1145) Males (N = 628) Females (N = 517)
Origin Per cent (n) Per cent (n) Per cent (n)
Middle East1 33.7 (386) 32.6 (205) 35.0 (181)
Asia2 20.6 (236) 25.2 (158) 14.9 (77)
Africa2 28.2 (323) 25.5 (160) 31.5 (163)
Europe within EU3 12.5 (143) 12.3 (77) 12.8 (66)
Europe outside EU 2.3 (26) 2.5 (16) 1.9 (10)
Other regions and CoO4 2.8 (32) 1.9 (12) 3.9 (20)
  All (N = 1137) Males (N = 612) Females (N = 525)
Reason for migrating5 Per cent (n) Per cent (n) Per cent (n)
Fleeing war6 37.3 (424) 39.7 (243) 34.5 (181)
Fleeing other danger/ persecution6 10.6 (120) 10.5 (64) 10.7 (56)
To be reunited with family 18.4 (209) 17.0 (104) 20.0 (105)
Parents’ Labour migration 22.3 (253) 21.6 (132) 23.0 (121)
Other responses 11.5 (131) 11.3 (69) 11.8 (62)
Refugee background, per cent 47.0 (593) 49.3 (334) 44.3 (259)
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Note. Countries according to participants’ own text responses were divided into regions. 1Middle East = The Asian and African countries around the Mediterranean coast + Iran, Iraq, Kurdistan, Palestine, and Azerbaijan. 2Except countries included in the Middle East. 3Including members of the European Economic Association (EEA). 4CoO = Countries of origin. 5Mutually exclusive categories. 6The students who ticked one of these two categories were merged, and constitute ‘Refugees’ in this study.

2.2. Measures

The Planning and Initiative Subscale of the Amsterdam Executive Function Inventory (PIS-EF; Van der Elst et al., 2012) is one of three subscales in the AEFI. The other two subscales are Attention, and Self-Control, and Self-Monitoring. The PIS-EF consists of five items that relate largely to goal-directed thought and action and to cognitive flexibility/shifting (I can make fast decisions; I am well organised; It is easy for me to come up with a different solution if I get stuck; I am full of new ideas; and I am curious, I want to know how things work). Responses are given on a 3-point Likert scale (1 = not true; 2 = partly true; and 3 = true). In our study, the mean score of PIS-EF was used, range 1–3.

The Children's Revised Impact of Event Scale (CRIES-8; Yule, 1992) is a self-report measure of PTSS for children from age 8 to 18. CRIES-8 comprises two subscales, Intrusion/Re-experiencing (four items) and Avoidance (four items). The eight items are scored on a 4-point Likert scale (0 = Not at all, 1 = Rarely, 3 = Sometimes, 5 = Often). The sum score, range 0–40, was used in this study. Clinical cut-off indicating possible PTSD is ≥ 17.

The Strengths and Difficulties Questionnaire (SDQ, R Goodman, 1997; 2001) is a measure of emotional and behavioural difficulties and strengths in children. Each of the 25 items is scored on a 3-point Likert scale (0 = Not true, 1 = Somewhat true, 2 = Certainly true). We used its five subscales, Emotional symptoms (tapping anxiety and depressive symptoms), Hyperactivity, Behavioural problems, Peer relationship problems, and Prosocial behaviour, and their individual sum scores, range 0–10.

The Daily Stressors Scale for Young Refugees (DSSYR; Vervliet et al., 2014) assesses post-migration daily stress during the last month by 15 items. Six items from the scale is used. Items are scored on a 4-point Likert scale (from 1 = Never to 4 = Always). We reversed values so that increasing values mean increasing daily stress. The sum score was used, range 6–24.

The Perceived Ethnic Discrimination Questionnaire-Community Version (PEDQ-CV; Brondolo et al., 2005) assesses experiences of discrimination. We used nine items from a 17 items brief version (the Brief PEDQ-CV). Items are scored on a 4-point Likert scale (from 1 = Never to 4 = Always). We used the sum score of the nine items, range 9–36.

The Child and Youth Resilience Measure (CYRM-12; Liebenberg et al., 2013; Ungar, 2016) comprises 12 items tapping resilience. Responses are given on a 5-point Likert scale (from 1 = Not at all to 5 = A lot). We used the total sum score, range 12–60.

The Multidimensional Scale of Perceived Social Support (MSPSS; Zimet et al., 1988) is a measure of psychosocial support. The scale comprises 12 items divided into three subscales. Two subscales were included, Support from family (four items) and Support from friends (four items), scored on a 4-point Likert scale from 1 (Not at all) to 4 (A lot). The mean for each subscale was used, range 1–4.

The Psychosocial Sense of School Membership (PSSM) scale (Goodenow, 1993) was used to tap students’ sense of school belonging. Nine items from the original scale were included, and were scored on a 5-point Likert scale (from 1 = Not at all true to 5 = Completely true). Scores on items with a negative meaning were reversed. Increasing values mean a stronger sense of school belonging. The mean score for the nine items was used in this study, range 1–5.

Wellbeing was measured by one question: ‘How would you rate your overall wellbeing?’ Responses were given on a 5-point Likert scale from 1 to 5 (1 = Very bad, 2 = Bad, 3 = Normal, 4 = Good, 5 = Very good).

The instruments, developed for children and adolescents, are further described in previous publications from the study (e.g. Spaas et al., 2022, 2023). In this study, male and female, and refugee and non-refugee migrant students are termed subgroups, although group-membership is mutually exclusive only within each pair. When variables are directly referred to, variable names are capitalised, but when the variable constructs are referred to in their more generic meaning, we use lowercase.

2.3. Statistical procedures

For descriptives, t-tests and chi-squared tests were run for continuous and ordinal variables and for proportions/percentages, respectively, between male and female, and between refugee and non-refugee migrant students. In the variables, missing items were left missing. For computing mean scores, 75% of the items constituting the variable had to be completed. For sum scores, the ensuing mean was multiplied by the number of items in the scale. We calculated effect sizes for the differences in means between male and female, refugee and non-refugee students by Cohen's d, and by Cliff's delta for the difference in estimates between two groups on an ordinal variable (Wellbeing). Cliff's delta ranges from −1 to 1 (Mangiafico, 2016). In our case, a positive value indicates that the proportion of cases to non-cases in the first group dominates that of the second, 0 indicates no substantial differences, and a negative value indicates that the proportion in the second group dominates that of the first group. Odds ratio was computed for 2 × 2 tables (Male/Female, Refugee/Non-Refugee migrant, above clinical cutoff for possible PTSD/ below clinical cutoff for possible PTSD). For Cohen's d the following benchmarks were used: small effect size (d = 0.2), medium (d = 0.5), and large effects size (d = 0.8) (Cohen, 1992). It is suggested that these d-values correspond with r and Spearman's rho = .1, .3, and .5 (Cohen, 1992), with OR = 1.68, 3.47, and 6.71 (based on 2 by 2 tables; H Chen et al., 2010), and with Cliff's delta values 0.15, 0.33, and 0.47 (Romano et al., 2006), for small, medium, and large differences, respectively.

In the regressions, PIS-EF was modelled as the dependent variable. All scale scores were transformed to a 0–100 scale, which makes it possible to compare the sizes of the coefficients directly. The coefficient then signifies the size of change in PIS-EF in percentage points (PP) per 1 PP increase in the independent variable. First, regressions were run individually for each independent variable. Then three linear regression models were fitted: Model 1 included all stress-related variables, Model 2 included all positive or potentially protective variables, and Model 3 included both stressful and positive variables. All explanatory variables were continuous except Wellbeing. In the regressions with Wellbeing, Very Bad was reference for the other Wellbeing response alternatives. Next, Model 3 was run separately for males and females, and for refugees and non-refugee migrants. Differences in variables’ association with PIS-EF within each pair were judged as of possible interest if there was none or just some overlap in the confidence intervals. For these differences, a 95% percentile confidence interval was computed by a bootstrap procedure with 10,000 replications. Statistical level of significance: p < .05. Descriptives were run in IBM SPSS Statistics, 28.0. Linear regressions and bootstrap procedures were run in R4.1.0, with the R package boot for the bootstrap procedure.

3. Results

Table 2 shows that relative to male students, female students reported significantly more Emotional symptoms, had stayed significantly longer in the resettlement country, scored significantly higher on Prosocial behaviour, and tended to have a higher PTSS score. The difference between male and female participants on Emotional symptoms was of small to medium effect size, the other effect sizes were small. Differences between male and female students on executive functioning (PIS-EF), Wellbeing, and Perceived ethnic discrimination were non-significant and very small. Compared with the non-refugee migrant students, refugee students were significantly older, had stayed longer in the resettlement country, scored significantly higher on PTSS, reached more frequently the clinical cut-off score for possible PTSD, scored higher on Daily stress, Prosocial behaviour, Peer problems, Emotional symptoms, and scored lower on Conduct problems. Differences between refugee and non-refugee migrant students were of medium effect size for Age and PTSS, while the effect sizes of the other differences were small. The differences between refugee and non-refugee migrant students on Perceived ethnic discrimination and Wellbeing were negligible. About two fifths of the participants scored at or above cutoff for a possible PTSD according to the CRIES-8 guidelines. On Wellbeing, about 5% of the participants reported their wellbeing as ‘Very bad’ or ‘Bad’, and 66.5% as ‘Good’ or ‘Very good’. Responses were about equally dispersed among the different subgroups. See Table 2 for details.

Table 2.

Descriptives for all participants, male and female, refugee and non-refugee migrant students, and analyses of the differences between them.

  All
N = 1312		 Male migrant students
N = 706
(53.8% of all)		 Female migrant students
N = 606
(46.2% of all)		 Gender difference Refugee students
N = 593
(47.0% of 12621)		 Non-refugee migrant students
N = 669
(53.0% of 12621)		 Difference refugee/non-refugee migrant students
Dichotome variable N Per cent (n)   Per cent (n) N Per cent (n) Chi-Square (df) p Odds ratio (95% CI; p) N Per cent (n) N Per cent (n) Chi-Square (df) p Odds ratio (95% CI; p)
PTSD2 (CRIES-8 ≥ cutoff) 1253 41.6 (521) 720 39.5 (263) 593 44.0 (258) 2.56 (1) .110 0.83 (0.66 - 1.04; .110) 559 50.6% (283) 652 33.7% (220) 35.330 (1) < .001 2.01 (1.60 - 2.54; < .001)
Variable N M (SD) N M (SD) / N M (SD) p Cohens d (95% CI) N M (SD) N M (SD) p Cohens d (95% CI)
Age (years) 1312 15.5 (2.0) 706 15.5 (1.9) 606 15.5 (2.2) .874 −.01 (−.12,.10) 593 15.9 (2.2) 669 15.0 (1.8) <.001 .44 (.33, .55)
Time in reception country (years) 1312 1.93 (1.80) 706 1.78 (1.63) 606 2.11 (1.96) .001 −.18 (−.29, −.07) 593 2.09 (1.62) 669 1.77 (1.91) .002 .18 (.07, .29)
PIS-EF3 (AEFI) 1242 2.35 (0.42) 673 2.36 (0.43) 569 2.34 (0.40) .342 .05 (−.06, .17) 556 2.37 (0.42) 641 2.33 (0.41) .087 .10 (−.01, .21)
Posttraumatic stress symptoms (CRIES-8) 1253 13.8 (10.8) 666 13.3 (10.7) 587 14.4 (10.9) .060 −.11 (−.22, .004) 559 16.3 (10.2) 652 11.9 (10.9) <.001 .42 (.31, .54)
Emotional symptoms (SDQ) 1269 3.07 (2.34) 681 2.72 (2.22) 588 3.47 (2.42) <.001 −.32 (−.44, −.21) 573 3.23 (2.36) 650 2.95 (2.34) .039 .12 (.01, .23)
Conduct problems (SDQ) 1272 1.72 (1.50) 682 1.74 (1.56) 590 1.69 (1.42) .565 .03 (−.08, .14) 577 1.60 (1.54) 650 1.79 (1.46) .022 −.13 (−.24, −.02)
Hyperactivity (SDQ) 1265 2.95 (1.94) 679 3.01 (1.91) 586 2.88 (1.97) .254 .06 (−.05, .18) 572 2.95 (1.98) 648 2.96 (1.91) .943 −.004 (−.12, .11)
Peer problems (SDQ) 1263 2.86 (1.67) 680 2.91 (1.71) 583 2.80 (1.62) .228 .07 (−.04, .18) 571 2.98 (1.63) 647 2.74 (1.69) .012 .14 (.03, .26)
Daily stress (DSSYR) 1242 9.13 (4.07) 656 9.25 (4.14) 586 8.99 (3.99) .261 .06 (−.05, .18) 558 9.72 (4.22) 638 8.66 (3.92) <.001 .26 (.15, .38)
Perceived ethnic discrimination (PEDQ) 1245 14.1 (6.0) 674 14.3 (6.4) 571 13.8 (5.4) .143 .08 (−.03, .20) 558 13.9 (5.8) 640 14.1 (6.0) .606 −.03 (−.14, .08)
Prosocial behaviour (SDQ) 1271 8.24 (1.84) 682 8.09 (1.97) 589 8.40 (1.66) .003 −.17 (−.28, −.06) 576 8.51 (1.68) 649 8.04 (189) <.001 .26 (−14, .38)
Resilience (CYRM) 1259 47.4 (7.6) 679 47.1 (7.7) 580 47.8 (7.4) .155 −.08 (−.19, −03) 568 48.2 (7.6) 645 46.8 (7.4) .002 .18 (.07, .29)
Support from family (MSPSS) 1259 3.32 (0.75) 676 3.29 (0.77) 583 3.35 (0.73) .195 −.07 (−.18, .04) 566 3.29 (0.80) 644 3.33 (0.71) .385 −.06 (−.16, .06)
Support from friends (MSPSS) 1265 2.91 (0.84) 682 2.88 (0.82) 583 2.94 (0.86) .197 −.07 (−.18, .04) 573 2.89 (0.83) 645 2.93 (0.85) .343 −.05 (−.17, .06)
School belonging (PSSM4) 1237 3.82 (0.66) 668 3.81 (0.66) 569 3.83 (0.65) .561 −.03 (−.15, .08) 550 3.84 (0.62) 641 3.78 (0.68) .112 .09 (−.02, .21)
  All Male students Female students Gender difference Refugee migrant students Non-refugee migrant students Difference refugees/other migrants
Response on Wellbeing N Per cent (n) N Per cent (n) N Per cent (n) Chi-Square (df) p Cliff's delta (95% CI) N Per cent (n) N Per cent (n) Chi-square (df) p Cliff's delta (95% CI)
Wellbeing Very bad 1266 1.1 (14) 677 1.0 (7) 589 1.2 (7) .07 (1) .793   574 0.9 (5) 643 1.2 (8) .399 (1) .527  
Wellbeing Bad 1266 4.0 (51) 677 4.4 (30) 589 3.6 (21) .61 (1) .434   574 4.2 (24) 643 3.9 (25) .067 (1) .795  
Wellbeing Normal 1266 28.4 (359) 677 26.6 (180) 589 30.4 (179) 2.24 (1) .134   574 30.0 (172) 643 27.4 (176) .999 (1) .318  
Wellbeing Good 1266 32.4 (410) 677 33.7 (228) 589 30.9 (182) 1.11 (1) .292   574 30.5 (175) 643 33.3 (214) 1.088 (1) .297  
Wellbeing Very Good 1266 34.1 (432) 677 34.3 (232) 589 34.0 (200) .01 (1) .907   574 34.5 (198) 643 34.2 (220) .011 (1) .918  
Wellbeing (total)             3.02 (4) .554 0.02 (-.05 to 0.08)         1.92 (4) .750 0.01 (−0.05 to 0.08)
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Note. 1Fifty participants did not respond to their reason for migration. 2PTSD = Possible Posttraumatic stress disorder, clinical cutoff ≥ 17. 3PIS-EF = The Planning and Initiative Executive Functions subscale. 4Only nine items of the PSSM was used. For a meaningful level of accuracy, scales with values < 1 have three decimals; < 10 have two decimals; and > 10 have one decimal. Chi-Square test p-values: Asymptotic Significance. Odds ratio is computed for males compared to females, and for refugees compared to other migrants.

Table 3 displays the results for the unadjusted and adjusted regressions for all participants. Unadjusted for other independent variables, all variables except PTSS were significantly related to EF. The one-item Wellbeing variable with five response alternatives was positively and significantly related to PIS-EF, and responding better than Very bad on Wellbeing was associated with 15.1–25.5 percentage points’ (PP) higher PIS-EF. Among the other variables, Resilience was most strongly associated with PIS-EF: A one PP increase in Resilience was associated with an increase of 0.530 PP on PIS-EF.

Table 3.

Unadjusted and adjusted regression coefficients with the executive functioning variable PIS-EF as dependent variable (Models 1, 2, and 3).

    Model 1 Model 2 Model 3
  Unadjusted1 Adjusted for stress-related variables Adjusted for positive factors Adjusted for all independent variables
Independent variable coeff. (95% CI) p coeff. (95% CI) p coeff. (95% CI) p coeff. (95% CI) p
Posttraumatic stress symptoms .001 (−.043, .045) .968 .079 (.032, .125) < .001   .043 (−.002, .089) .061
Emotional symptoms −.156 (−.204, −.107) < .001 −.100 (−.159, −.041) < .001   −.096 (−.154, −.038) .001
Conduct problems −.224 (−.302, −.146) < .001 −.073 (−.162, .016) .106   .067 (−.020, .155) .131
Hyperactivity −.255 (−.313, −.196) < .001 −.169 (−.236, −.102) < .001   −.098 (−.163, −.033) .003
Peer problems −.152 (−.221, −.083) < .001 −.042 (−.116, .032) .267   .049 (.−.024, .123) .395
Daily stress −.099 (−.151, −.047) < .001 −.052 (−.104, .001) .053   .017 (.−.034, .069) .512
Ethnic discrimination −.217 (−.287, −.147) < .001 −.109 (−.187, −.030) .007   −.027 (−.104, .050) .490
Prosocial behaviour .299 (.238, .361) < .001   .116 (.052, .180) < .001 .141 (.073, .210) < .001
Resilience .530 (.463, .598) < .001   .376 (.292, .460) < .001 .335 (.246, .424) < .001
Support from family .235 (.158, .311) < .001   .045 (−.033, .124) .260 .020 (−.061, .102) .622
Support from friends .206 (.138, .274) < .001   −.004 (−.075, .066) .905 .001 (−.074, .077) .969
School belonging .360 (.292, .429) < .001   .138 (.064, .212) < .001 .103 (.023, .182) .011
Response alternatives coeff. (95% CI) p coeff. (95% CI) p coeff. (95% CI) p coeff. (95% CI) p
Well-being Bad 15.1 (3.1, 27.1) .014   7.7 (−4.2, 19.6) .207 11.2 (−1.2, 23.6) .077
Well-being Normal 15.7 (4.9, 26.5) .004   5.7 (−5.2, 16.6) .305 9.7 (−1.7, 21.1) .096
Well-being Good 18.2 (7.4, 28.9) .001   5.4 (−5.5, 16.3) .332 9.4 (−2.1, 21.0) .109
Well-being Very good 25.5 (14.7, 36.3) < .001   9.7 (−1.3 20.7) .084 13.8 (2.2, 25.5) .020
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Note. All variables are transformed to 0–100 scales. All regression coefficients are unstandardised. 1Each independent variable was run separately. Model Summary: Model 1, adjusted for the stress related variables, ‘explains’ 9% of the variance in PIS-EF (N = 1157, R2 = .090, p < .001). Model 2, adjusted for the positive factors ‘explains’ 19.5% of the variance in PIS-EF (N = 1188, R2 = .195, p < .001). The fully adjusted model (Model 3) ‘explains’ 20.9% of the variance in PIS-EF (N = 1126, R2 = .209, p < .001). Wellbeing Very Bad is here reference for the other Wellbeing response alternatives. For a meaningful level of accuracy, scales with values < 1 have three decimals; < 10 have two decimals; and > 10 have one decimal.

In Model 1, adjusted for all stress-related variables, three variables, Hyperactivity, Ethnic discrimination, and Emotional symptoms were negatively and statistically significant, but to a small or minimal extent associated with PIS-EF. Posttraumatic stress symptoms, however, was positively, statistically significantly, but minimally related to PIS-EF.

In Model 2, adjusted for all positive or potentially protective variables, Resilience, School belonging and Prosocial behaviour were significantly and positively associated with PIS-EF, with medium to small effect-sizes.

In Model 3, responding Very Good on Wellbeing (rather than Very bad) was significantly associated with an increase of 13.8 PP on PIS-EF. Among the other variables, Resilience, Prosocial behaviour, and School belonging accounted for the largest associations with PIS-EF, all significantly and in a positive direction. Hyperactivity and Emotional symptoms were negatively associated with PIS-EF with small effect sizes. The stress-related variable PTSS was, however, positively, minimally and non-significantly associated with PIS-EF.

Table 4 shows the fully adjusted regression with all explanatory variables included for each of the subgroups. Resilience was positively and significantly associated with PIS-EF in all subgroups, and most strongly for males. Prosocial behaviour was also significantly and positively associated with PIS-EF for all subgroups, and most strongly for refugees. Wellbeing was positively and significantly associated with PIS-EF for refugee students, and non-significantly for the other groups. School belonging was positively and significantly associated with PIS-EF for male and for non-refugee migrant students, and non-significantly for female and refugee migrant students. Hyperactivity was negatively associated with PIS-EF in all the regressions, significantly for females and non-refugees, and non-significantly for males and refugees. Emotional symptoms were negatively and most strongly associated with PIS-EF for non-refugee migrant students, and to some extent for male and female migrant students, but non-significantly for refugees. The remaining variables were all non-significantly associated with PIS-EF.

Table 4.

Regressions with the executive functioning variable PIS-EF as dependent variable, adjusted for all independent variables for males and females, refugees and other migrants.

  Males students Female students Refugees Non-refugee migrants
Independent variable Coeff. (95% CI) p Coeff. (95% CI) p Coeff. (95% CI) p Coeff. (95% CI) p
Posttraumatic stress symptoms .041 (−.026, .109) .229 .046 (−.017, .109) .153 .029 (−.044, .103) .435 .056 (−.006, .118) .078
Emotional symptoms −.089 (−.176, −.002) .045 −.083 (−.167, .000) .050 −.047 (−.137, .043) .306 −.142 (−.223, −.062) < .001
Conduct problems .097 (−.021, .216) .107 .015 (−.121, .151) .828 .045 (−.088, .179) .505 .054 (−.069, .177) .390
Hyperactivity −.090 (−.181, .002) .054 −.113 (−.208, −.017) .020 −.094 (−.196, .007) .068 −.091 (−.180, −.003) .043
Peer problems .047 (−.057, .152) .374 .047 (−.061, .156) .391 .037 (−.076, .151) .518 .061 (−.042, .165) .241
Daily stress −.011 (−.085, .063) .768 .044 (−.031, .119) .248 .021 (−.058, .100) .605 .022 (−.052, .096) .565
Ethnic discrimination −.027 (−.128, .074) .599 −.034 (−.156, .088) .587 −.026 (−.148, .097) .681 −.036 (−.142, .071) .511
Prosocial behaviour .143 (.051, .234) .002 .135 (.027, .242) .014 .196 (.087, .305) < .001 .133 (.037, .230) .007
Resilience .358 (.235, .482) < .001 .311 (.180, .441) < .001 .338 (.198, .479) < .001 .302 (.180, .425) < .001
Support from family .016 (−.096, .128) .785 .016 (−.104, .137) .791 .070 (−.047, .186) .241 −.042 (−.162, .078) .489
Support from friends −.018 (−.128, .092) .744 .022 (−.083, .127) .680 .008 (−.107, .123) .893 .007 (−.097, .111) .897
School belonging .129 (.017, .241) .025 .085 (−.030, .200) .149 .094 (−.035, .222) .153 .125 (.018, .232) .022
Response alternatives coeff. (95% CI) p coeff. (95% CI) p coeff. (95% CI) p Coeff. (95% CI) p
Well-being Bad 15.9 (−2.7,, 34.5) .093 4.2 (−13.0, 21.3) .632 26.6 (5.5, 47.7) .014 −0.6 (−17.7, 16.4) .940
Well-being Normal 12.3 (−5.2, 29.8) .169 6.5 (−8.9, 22.0) .407 22.6 (2.7, 42.5) .026 0.6 (−14.8, 15.9) .941
Well-being Good 11.2 (−6.5, 28.9) .215 6.7 (−9.0, 22.4) .404 25.2 (5.1, 45.4) .014 −2.3 (−17.9, 13.3) .770
Well-being Very good 16.9 (−0.9, 34.7) .062 9.9 (−6.0, 25.8) .222 27.8 (7.4, 48.1) .008 2.9 (−12.8, 18.6) .719
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Note. All variables transformed to 0–100 scales so that their effect on PIS-EF can be compared. Unstandardised coefficients. For Male students, the model ‘explains’ 22.0% of the variance in PIS-EF (R2 = .220, p < .001). For Female students, the model ‘explains’ 20.6% of the variance in PIS-EF (R2 = .206, p < .001). For Refugee students, the model ‘explains’ 24.2% of the variance in PIS-EF (R2 = .242, p < .001). For Other migrant students, the model ‘explains’ 19.4% of the variance in PIS-EF (R2 = .194, p < .001). Wellbeing Very Bad is here reference for the other Wellbeing response alternatives. For a meaningful level of accuracy, scales with values < 1 have three decimals; with values < 10 have two decimals; and scales up to values > 10 have one decimal.

Bootstrapping was performed for the following variables between male and female participants: Hyperactivity, Prosocial behaviour, Resilience, and School belonging. Between refugee and non-refugee participants, bootstrapping was performed for the following variables: Emotional symptoms, Prosocial behaviour, Resilience, School belonging, Wellbeing bad, Wellbeing normal, Wellbeing Good, Wellbeing very good, and PTSS. None of these variables’ relationships with PIS-EF were significantly different between male and female, and between refugee and non-refugee migrant students.

To check for some associations with EF reported in the literature, we post hoc performed the following correlations: Between PTSD-level of symptoms and PIS-EF (Spearman's rho = .03, p = .267), between Age and PIS-EF (r = .03, p = .240), and between Time in reception country and PIS-EF (r = -.06, p = .044). The first two correlations were minimal and statistically non-significant, the last was statistically significant, negative, but minimal.

4. Discussion

Among the participating migrant students in this study, positive factors, and especially resilience, were more closely associated with PIS-EF than stress-related factors. All relationships with PIS-EF, except PTSS, were in the expected direction. There were no significant differences between male and female - and between refugee and non-refugee migrant students in the associations of the examined variables with PIS-EF. According to the normative data for the Planning and Initiative subscale of the AEFI for adolescents aged between 15 and 18 years (Van der Elst et al., 2012), our results on the PIS-EF correspond with around the 60th percentile for responders with an average level of education, and around the 65th percentile for youth with a low level of education. This means that the participants scored at least as good as 60–65% of other responders in this age group and educational level. This indicated that the migrant students scored comparably to the general youth population on PIS-EF. Van der Elst et al. (2012) found that age, gender, and educational level influenced scores on the AEFI. Age has been associated with poorer psychological adaptation/mental health in some of the cited studies (Pagel & Edele, 2022), with potential implications for EF. However, we found no significant correlation between age and PIS-EF. Despite potential differences in demography and other background factors, self-reported Planning and initiative EF skills were about the same in male and female, refugee and non-refugee migrant students.

For the whole group, adjusted for both stressful and positive or potentially protective factors, resilience, prosocial behaviour, school belonging, and wellbeing turned out as positively and significantly associated with PIS-EF. Studies have demonstrated the importance of resilience to the functioning of refugee and migrant youth (Gatt et al., 2020; Taylor & Ruiz, 2019). The participants’ high mean score on resilience, especially within the refugee group, could be linked with an inclination among these young people, based on their experience with conflict and the breaking of social ties, to mobilise their resources and rely on themselves. Promotion of refugee youth's resilience is noted to be of key importance to their positive adaptation and wellbeing (Jafari et al., 2022).

Resilience, prosocial behaviour, and the way individuals elicit or recognise social support may be an expression of well-functioning EFs (Bauer et al., 2021; Ellis et al., 2020; Zorza et al., 2016). In return, some such positive factors could also protect or enhance EF in the face of challenges and strains. In line with this, Dixson and Scalcucci (2021) suggested that psychosocial factors may represent pathways to improve adolescent EF. Our finding of a relationship between school belonging and PIS-EF among non-refugee migrants and male migrant students, resonates with Dixson and Scalcucci’s (2021) finding that school belonging predicted EF positively among high school students, and may resonate with the finding of a relationship between students’ sense of school-belonging and academic achievement (Korpershoek et al., 2020). Our finding that wellbeing was significantly associated with PIS-EF for refugee students, can, by extension, be seen in relation to Renshaw et al.'s (2014) proposition that wellbeing may be critical to success at school, and conversely, to Graham et al.'s (2016) conclusion that success at school is critical to the wellbeing of resettled children with a refugee background.

Social support from family and friends came out as weakly related to EF in our study. However, this should not be understood as indicating that family and friends are of little importance in (migrant) adolescents’ lives and to their learning. Social support at home and among peers have been found to be success factors for learning (Graham et al., 2016), and of importance to young people's resilience (Sleijpen et al., 2017). Family support is found to be important to many areas of the lives of young people (e.g. Baker et al., 2019), and thus the participants’ fairly high mean score on support from family could be important to their EF in more indirect ways. Furthermore, the participants’ somewhat lower mean score on support from friends may indicate a weakness of social ties with peers among migrant youth. This finding is worrying in a developmental period when EFs are found to be significantly affected by peer relationships and children's social life at school (Lecce et al., 2020). However, migrants’ social ties can be positively influenced by the conditions created at school, as argued by Jørgensen (2017).

According to the literature, the development (Aupperle et al., 2012) or perception (Zelazo et al., 2016) of stressors could be affected by the quality of individuals’ EFs. We anticipated that a daily life characterised by mental health problems and external stressors could in return also have a negative effect on individuals’ actual executive functioning. However, as noted, the only two variables that were significantly and negatively associated with PIS-EF for the whole group of participants, when adjusted for all variables, were hyperactivity and emotional symptoms. The negative association we found between hyperactivity and PIS-EF is not surprising, as hyperactivity implies difficulties with sustained attention, distractibility, and problems with behavioural self-control, organisation, and consideration of the consequences of one's acts (ICD-11), whereas EF, on the other hand, implies almost the opposite (Zelazo et al., 2016). Contrasting our findings, one study conducted in elementary schools in Germany including refugee children, newly arrived Roma children, and German-born immigrant children found that hyperactivity was not significantly associated with EF (Chwastek et al., 2022). Differences in age groups and the parts of EF being measured, and that teacher ratings of socio-emotional problems and performance tests of EF were used, may explain different results between their study and ours.

There are opposing findings regarding the relationship between anxiety and EF (Alfonso and Lonigan, 2021; Owens et al., 2012; Snyder et al., 2014), and between depression and EF (Friedman et al., 2018; Snyder et al., 2014). Emotional symptoms in the questionnaire that we used, consisted of questions regarding both anxiety and depression. Therefore, we cannot tell whether the respective items pulled the result in the same, or different directions, resulting in the modest, negative association of emotional symptoms with EF that we found. Participants’ depression could have exerted a more stable negative view of themselves, including questions related to PIS-EF. However, respondents’ presence or absence of situational anxiety (Alfonso and Lonigan, 2021) should not have influenced their results on PIS-EF since we used self-report rather than performance tests for assessment of EF. Furthermore, the context for responding to the questionnaire in our study was relatively non-stressful, was conducted in familiar classrooms, was voluntary, and did not ask about traumatic experiences.

Initially, we thought PTSS would be a potent source of disruption of the EF of the participants, as several studies in adult, children, and youth populations point to a negative association of trauma, of PTSS, or a complete PTSD, with EF (Barzilay et al., 2018; Nyvold et al., 2021; Woon et al., 2017). Our finding that PTSS, although high, was minimally related to PIS-EF, is in keeping with the results of studies by Chen et al. (2019) and Scharpf et al. (2022). Contingent on whether the context for the study and the methods used to assess EF are perceived as emotionally taxing, evoke trauma memories, or act as triggers of trauma-related reactions, or not, studies could find different associations between PTSS and EF/cognitive functioning (Mirabolfathi et al., 2022).

Post-migration living problems often represent disturbing elements in refugee's daily lives (Bronstein & Montgomery, 2011; Spaas et al., 2022; Tomren & Opaas, 2024; Verelst et al., 2022). Recent discrimination has been found to be negatively associated with EF among college students of mixed ethnic origin (Keating et al., 2022). In our unadjusted regression, living problems such as peer problems, daily stress, and perceived ethnic discrimination were all significantly and negatively related to the EF variable used. However, none of these variables were significantly related to EF when adjusting for all the other variables included in the study. The self-reported data of the participants, who were in their early phase of resettlement (see Wu et al., 2021), showed that positive factors were more strongly associated with their PIS-EF. We tentatively suggest that the developmental impetus in childhood and adolescence may spur migrant youth to focus on positive forces within and without, rather than the more problematic sides of their daily lives.

Strengths of this study were the large number of participants from five countries in Europe, the investigation of the associations of both stressful and positive variables with PIS-EF, and the examination of differences between genders and between migrant students with and without a refugee background. Having data only from one of three subscales of the AEFI limited the chance to see how results on a fuller spectre of EF would have been associated with the included variables. Another limitation is that our discussion of, and comparison with other studies on EF was rather crude, as different ways of testing, and different EFs could yield different relationships with the examined variables. The self-reported data could imply bias, but can also have provided valid information of how executive functions operated in participants’ daily lives. Another aspect of self-report is that the students’ responses to some of the items could be influenced by a tendency to evaluate oneself in the same way, positively or negatively. Finally, the study is cross-sectional and explorative, and cannot justify causal assumptions.

5. Conclusion and implications

The self-reported resilience of the migrant adolescents in this study, and to a somewhat lesser degree their prosocial functioning and sense of school belonging were positively related to their self-reported executive functioning (in terms of PIS-EF), and more strongly so than their self-reported mental health symptoms and post-migration difficulties. This applied to male and female as well as refugee and non-refugee migrant students. A reported feeling of wellbeing was especially related to refugee students’ executive functioning. The students’ executive functions probably had contributed to forming many of the factors investigated here as independent variables. However, the possibility that present day stressful or benign conditions could work back on the students’ actual executive functioning, could open up for ways to support or protect the students EF.

A concern for the potential negative impact of PTSS on migrant students’ learning has been voiced (Spaas et al., 2022). However, to the extent that PIS-EF is connected to migrant students’ learning, PTSS does not seem to be the problem – except, maybe, when cognitive functioning is acutely disturbed by traumatic intrusions (Mirabolfathi et al., 2022). Judging from the present study, there are other sources of distress and stress that may be more urgent obstacles to learning for migrant youth, such as emotional symptoms, hyperactivity, conduct problems, and ethnic discrimination. These should be actively addressed to prevent or alleviate their possible negative impact on EF (and their certain negative impact on various other aspects of life).

Adverse events and stressors before and after migration do not simply add up to increasing maladaptive or pathological outcomes. Positive and potentially protective factors may counteract the effects of various forms of stress upon EF. In extension of our findings we suggest that strengthening social ties to support migrant youths’ resilience, creating opportunities for prosocial behaviour, as well as laying the ground for a socially welcoming context that allows for a feeling of school belonging and wellbeing could protect or enhance migrant students’ EF. Albeit not forgetting the negative effects of mental health problems and the importance of adequate help, when needed, these study findings highlight the importance of being resource oriented, and work for migrant students’ experience of themselves as coping, prosocial, and resourceful members of school and the new society.

Steps to forward this explorative investigation of factors related to migrant youths’ EF would be to perform more rigorous studies. Most important is to identify factors related to the present that could be prevented, lessened, or strengthened in order to affect migrant students’ EF and ability to succeed in school and in the new country, irrespective of the characteristics or experiences they bring with them from the past.

Acknowledgements

The authors are grateful to the adolescents, schools and teachers who participated in this study. We also thank all who contributed through different phases of the study. The RefugeesWellSchool project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 754849.

Funding Statement

This work was supported by Horizon 2020 Framework Programme.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are not publicly available due to different licences in each country and concerns of adequate de-identification of the data for this vulnerable population. However, the data can be made available for researchers upon reasonable request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data that support the findings of this study are not publicly available due to different licences in each country and concerns of adequate de-identification of the data for this vulnerable population. However, the data can be made available for researchers upon reasonable request.

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