Available via license: CC BY 4.0
Content may be subject to copyright.
Citation: Schelfhout, S.;
Vandecasteele, R.; De Maesschalck, S.;
D’hondt, F.; Willems, S.; Derous, E.
Intercultural Competence Predicts
Intercultural Effectiveness: Test of an
Integrative Framework. Int. J.
Environ. Res. Public Health 2022,19,
4490. https://doi.org/10.3390/
ijerph19084490
Academic Editors: David L. Rowland
and Paul B. Tchounwou
Received: 19 January 2022
Accepted: 1 April 2022
Published: 8 April 2022
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
published maps and institutional affil-
iations.
Copyright: © 2022 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
International Journal of
Environmental Research
and Public Health
Article
Intercultural Competence Predicts Intercultural Effectiveness:
Test of an Integrative Framework
Stijn Schelfhout 1,2,3,*, Robin Vandecasteele 4, Stéphanie De Maesschalck 4, Fanny D’hondt 5, Sara Willems 4,6
and Eva Derous 1,3
1Research Group Vocational and Personnel Psychology, Department of Work, Organisation and Society,
Faculty of Psychology and Educational Sciences, Ghent University, H. Dunantlaan 2, 9000 Ghent, Belgium;
eva.derous@ugent.be
2
Department of Experimental Psychology, Faculty of Psychology and Educational Sciences, Ghent University,
Henri Dunantlaan 2, 9000 Ghent, Belgium
3Interdepartmental Research Group Vocational and Personnel Psychology, Faculty of Psychology and
Educational Sciences, Ghent University, Henri Dunantlaan 2, 9000 Ghent, Belgium
4Research Group Equity in Health Care, Quality & Safety, Department of Public Health and Primary Care,
Faculty of Medicine and Health Sciences, Ghent University, University Hospital Campus Entrance 42, C.
Heymanslaan 10, 9000 Ghent, Belgium; robin.vandecasteele@ugent.be (R.V.);
stephanie.demaesschalck@ugent.be (S.D.M.); sara.willems@ugent.be (S.W.)
5
Department of Sociology, Faculty of Political and Social Sciences, Ghent University, Sint-Pietersnieuwstraat 41,
9000 Ghent, Belgium; fanny.dhondt@ugent.be
6Centre for the Social Study of Migration and Refugees, Ghent University, H. Dunantlaan 2,
9000 Ghent, Belgium
*Correspondence: stijn.schelfhout@ugent.be
Abstract:
Why does someone thrive in intercultural situations; while others seem to struggle? In 2014,
Leung and colleagues summarized the literature on intercultural competence and intercultural effec-
tiveness into a theoretical framework. This integrative framework hypothesizes that the interrelations
between intercultural traits, intercultural attitudes and worldviews, and intercultural capabilities
predict the effectiveness with which individuals respond to intercultural situations. An empirically
verified framework can contribute to understanding intercultural competence and effectiveness in
health care workers, thus contributing to more equity in health care. The present study sets out to test
this integrative framework in a specific health care context. Future health care practitioners (N= 842)
in Flanders (Belgium) were questioned on all multidimensional components of the framework. Struc-
tural equation modeling showed that our data were adequate to even a good fit with the theoretical
framework, while providing at least partial evidence for all hypothesized relations. Results further
showed that intercultural capabilities remain the major gateway toward more effective intercultural
behavior. Especially the motivation and cognition dimensions of cultural intelligence seem to be
key factors, making these dimensions an excellent target for training, practical interventions, and
identifying best practices, ultimately supporting greater intercultural effectiveness and more equity
in health care.
Keywords:
intercultural traits; intercultural attitudes and worldviews; intercultural capabilities; inter-
cultural competence; intercultural effectiveness; multicultural personality; ethnocentrism;
ethnorelativism; cultural intelligence; cultural self-efficacy
1. Introduction
In our ever globalizing world of today, interculturalism is becoming the norm. People
select and communicate cultural information (for instance regarding ethnicity, race, religion
and nationality) according to the situation and their personal interests [
1
]. Moreover, in
health care, such communication can define interactions between practitioners and patients
with diverse cultural background [
2
–
5
]. This intercultural and interacting health care
Int. J. Environ. Res. Public Health 2022,19, 4490. https://doi.org/10.3390/ijerph19084490 https://www.mdpi.com/journal/ijerph
Int. J. Environ. Res. Public Health 2022,19, 4490 2 of 21
setting can instigate specific challenges, especially as these interactions can threaten equity
in health care [
6
–
8
]. Literature features quite some variance in how equity in health care
is described [
9
]. Lane and colleagues reviewed this equity literature and suggested a
practically operationalized definition of equity in health care depending on the specific
application [
10
]. Following Lane and colleagues [
10
], the present study thus defines equity
in health care as follows: Reducing disparities toward access to and use of health care
services for groups of people with different nationality or ethnic backgrounds. As a prime
example of such a challenge to equity in health care, ethnic prejudice is described as the
unjustified or incorrect attitude toward individuals based solely on their membership of
certain groups like race or nationality [
11
,
12
]. As a consequence, ethnic prejudice can
cause inequity in health care as people from different races or nationalities are receiving
suboptimal treatment, resulting in less favorable therapy outcomes and poorer health
altogether [13–15].
Recently, literature aimed at studying problems such as ethnic prejudice in a broader
framework of intercultural interaction [
16
,
17
]. Indeed, why do some people thrive in
intercultural situations, while others seem to struggle? To answer this question, Leung
and colleagues proposed an integrative framework that theorizes how the intercultural
competence of individuals leads to effective behavior in intercultural situations [
18
]. The
model is developed based on an extensive review of theoretical and empirical developments
in the intercultural competence literature. As such, the model describes how personality,
world views (including attitudes), and knowledge of different cultures interact toward
effectiveness in intercultural situations. The framework benefits from a broad scope that
can be applied to a multitude of settings including health care. The authors have explicitly
stated that researchers should explore how the components of intercultural competence
interrelate regarding their effect on intercultural effectiveness, instead of viewing the
different components as independent predictors.
For sure, the merit of this framework cannot be underestimated in summarizing the
extant literature on intercultural competence and its (theorized) effects on intercultural
effectiveness. However, despite the authors’ call for empirical validation, to this date and to
our knowledge, the theoretical framework has not been empirically verified in full. Toward
a specific setting like health care, such a verification can provide us with an invaluable
basis to further study and even remedy urgent problems like ethnic prejudice that threaten
equity in health care.
The present study in Flanders (i.e., the largest region in Belgium) therefore aims to
provide empirical verification of the framework on intercultural competence by investigat-
ing how the components of intercultural effectiveness interrelate in exerting their effects on
intercultural effectiveness. In doing so, the present study also focuses on identifying which
specific framework components are responsible for intercultural effective behavior in a
health care setting. Following the advice of Brottman and colleagues, these components
can become the future target of training, intervention, and evaluation, in order to establish
a compendium of best health care practice and education [
19
]. For instance, the present
study is conducted within the EdisTools project. The project wants to improve intercultural
effectiveness of practitioners toward clients in key domains of society like health care by
developing a set of digital tools for training and education.
1.1. The Framework of Intercultural Competence and Intercultural Effectiveness
Dias and colleagues describe intercultural competence as a multifaceted and com-
plex concept, that combines the knowledge and skills needed to perform effectively and
appropriately when interacting with others who are culturally different [
20
]. Literature
already features a plethora of articles on the nature of this knowledge and these skills as
intercultural competence is becoming key in important areas of human interaction such as
education and healthcare. Leung and colleagues have summarized this literature into an
integrative framework that theorizes how three components of intercultural competence
interact to achieve intercultural effectiveness [
18
]. First, intercultural traits indicate how
Int. J. Environ. Res. Public Health 2022,19, 4490 3 of 21
well an individual’s personality is able to handle intercultural situations [
21
,
22
]. Second,
intercultural worldviews indicate how individuals perceive (information from) other cul-
tures [
23
–
25
]. Finally, intercultural capabilities represent an amalgam of what a person can
undertake in order to be effective in an intercultural situation such as a job interview where
participants have different cultural backgrounds [26,27].
1.1.1. Intercultural Traits
The Big Five (extraversion, agreeableness, openness, conscientiousness, and emo-
tional stability) of human personality are known to be good predictors of how successful
individuals are in actually evaluating (intercultural) situations and also appropriately re-
sponding to these situations [
28
]. For instance, Shaffer and colleagues reported that expats
showed a positive relation of r= 0.24 between emotional stability and work adjustment
and a negative relation of r=
−
0.27 between emotional stability and cognitions about
early withdrawal from the job [
29
]. Toward multicultural settings, van der Zee and van
Oudenhoven have proposed a contextualized model of five multicultural personality traits
that have incremental validity above and beyond the original Big Five [
22
,
30
,
31
]. Cultural
empathy thus refers to empathy toward the feelings, thoughts, and behavior of individuals
with a diverse culture. Emotional stability refers to the ability to stay calm despite novel
and stressful intercultural conditions. Flexibility reflects an aptitude in interpreting novel
intercultural situations as a positive challenge, while also adapting to these situations.
Open mindedness represents an unprejudiced disposition toward differences in culture.
Finally, social initiative refers to actively approaching intercultural social situations while
also taking the initiative in these situations. A high score on these multicultural personality
dimensions was found to be predictive regarding the successful adjustment of employees,
students, migrants, and expats in their intercultural work or study activities, even when
controlling for the original Big Five [
32
–
34
]. Recently, a Short Form of the Multicultural
Personality Questionnaire (i.e., SF-MPQ with 40 items) [
35
] has also been validated for use
in health care-related contexts [36].
The predictive value of traits as constructs is partly explained by their stability, as
personality traits are known to be quite stable over the lifespan, especially past child-
hood [
37
,
38
]. For instance, literature indicates that personality traits are associated with
ethnocentric world views like ethnic prejudice and right-wing authoritarianism [
39
,
40
].
Personality traits are also associated with intercultural capabilities like cultural intelli-
gence [
41
,
42
]. The framework of Leung and colleagues [
18
] thus hypothesizes the following
relations regarding intercultural traits, intercultural worldviews, and intercultural capabili-
ties (see further).
H1.
Higher scores on intercultural traits predict a more ethnorelative world view (As a standalone
investigation, the present study’s cross-sectional data do not allow for a strict causal interpretation
of the results. However, (a) as the hypotheses are investigated through regression SEM analyses
and (b) as the hypotheses tested are the result of prior extensive theoretical and empirical research in
extant literature, the present study’s hypotheses are posited as predictions.).
H2. Higher scores on intercultural traits predict higher scores on intercultural capabilities.
1.1.2. Intercultural Worldviews
Intercultural worldviews address how individuals perceive information from other
cultures [
23
–
25
]. As an example, the Developmental Model of Intercultural Sensitivity
places ethnocentrism and ethnorelativism at both ends of a continuum that represents
increasing intercultural competence [
43
,
44
]. An individual with an ethnocentric disposition
almost exclusively observes the world through the looking glass of its own culture [
45
].
An individual with an ethnorelative disposition emphasizes the complexities and contra-
dictions of many different countries and cultures instead [
46
]. Research by Hammer has
shown that a score on this continuum can predict reduced intercultural anxiety, satisfaction
with studying abroad, the number of intercultural friends, and inclusion policies on staff
Int. J. Environ. Res. Public Health 2022,19, 4490 4 of 21
recruiting [
47
,
48
]. In health care specifically, Kaya and colleagues showed that Turkish
nursing students showed a negative correlation between intercultural sensitivity and eth-
nocentrism of about r=
−
0.40 [
49
]. Based on the already extensive literature on the topic,
Leung and colleagues hypothesized that an ethnorelative world view has a positive effect
on intercultural capabilities [18,50,51].
H3. A more ethnorelative world view predicts higher scores on intercultural capabilities.
1.1.3. Intercultural Capabilities
Intercultural capabilities focus on what a person can do to be effective in an intercul-
tural interaction like showing knowledge of other cultures [
52
]. One often-used conceptual-
ization of intercultural capabilities is (inter)cultural intelligence [53]. Cultural intelligence
can be described as a set of adaptable properties that allows an individual to effectively
manage intercultural situations [
54
]. Literature already reached consensus that cultural
intelligence at least features a (meta) cognitive dimension (i.e., knowledge about different
cultures), a motivational dimension (i.e., motivation to interact with people from different
cultures), and a behavioral dimension (i.e., knowledge about how to act in intercultural
interactions) [
52
,
55
–
58
]. Research on these dimensions with adolescents showed a posi-
tive relation with contact and cooperation and multiculturalism in both immigrant and
non-immigrant students [
59
]. In health care specifically, Harrison and colleagues found
that intercultural competence of health care professionals and effective practitioner-patient
engagement are strongly related regarding ethnic minority populations [60].
These observed effects are possible due to the adaptable nature of intercultural capabilities.
In other words, capabilities like cultural knowledge are teachable and thus trainable, making
these capabilities a prime target for training and education interventions in order to improve
an individual’s intercultural competence and eventually also the individual’s effectiveness
in intercultural situations [
61
]. In the framework of Leung and colleagues [
18
], intercultural
capabilities are thus hypothesized to have a positive effect on intercultural effectiveness.
H4. Higher scores on intercultural capabilities predict higher scores on intercultural effectiveness.
1.2. Intercultural Effectiveness
The goal of intercultural competence in an individual is for that individual to exhibit
effective behavior in intercultural situations. The downside of studying actual behavior lies
in the fact that you can observe the behavior, but you cannot directly tell why individuals
exhibit said behavior. As an alternative, literature harbors classic models that explain
human behavior through different psychological (multidimensional) constructs that can
be measured instead of actual behavior. For instance, the Social Cognitive Theory posits
that human behavior can be explained through the determinants of self-efficacy belief (i.e.,
can I make it happen?), outcome expectation (i.e., what will be the outcome if it happens?),
and goal representation (i.e., what will I gain if it happens?) [
62
]. Self-efficacy belief is
regarded the most essential component as an individual with low self-belief will have a
very low chance to initiate the behavior to begin with [
63
]. As such, previous studies have
already indicated a strong connection between general self-efficacy and behavior [
64
,
65
].
For instance, meta-analytic evidence on the theory of planned behavior shows that as
perceived behavioral control, self-efficacy can have major average correlations with actual
behavior of about r= 0.46 [
66
]. More specifically, literature has also already established a
relationship between cultural intelligence and self-efficacy [
67
,
68
]. For example, Quine and
colleagues reported that Canadian nursing students self-rated their cultural self-efficacy as
moderate when dealing with diabetes patients from aboriginal ancestry [
69
]. Moreover,
Quine and colleagues also showed that higher cultural self-efficacy was related to greater
intercultural communication and lower intercultural anxiety, with an explained variance of
about 33 to 35% [69].
Cultural self-efficacy can be operationalized as a multidimensional construct. As an
example, Briones and colleagues suggest a five-dimensional construct as operationalized
Int. J. Environ. Res. Public Health 2022,19, 4490 5 of 21
in the cultural self-efficacy scale for adolescents or CSES-A [
70
]. The process dimension
indicates how well individuals estimate their own ability to process information about
other cultures. The mix dimension indicates how well individuals estimate they would mix
within other cultures. The cope dimension indicates how well individuals estimate their
ability to cope with homesickness and separation from loved ones. The understanding
dimension indicates how well individuals estimate their ability to understand other ways
of life. Finally, the language dimension indicates how well individuals estimate they are
able to learn and understand other languages. Both the multidimensional construct as well
as the instrument are already quite common in health care literature [71–73].
1.3. Present Study
The present study aims to empirically verify the integrative framework of Leung and
colleagues in a health care setting [
18
]. To this extent, H1 to H4 are tested in a structural
equation model (SEM), using a multidimensional approach. For the present study, a
multidimensional approach is important as such an approach can pinpoint how exactly
the intercultural competence triangle (through multidimensional cultural intelligence)
relates to intercultural effectiveness (through multidimensional cultural self-efficacy). Such
interrelations are key to establishing future training, intervention, and evaluation targets,
in order to establish a compendium of best health care practice and education [19].
The framework by Leung and colleagues does not elaborate on two relations: (a) does
multicultural personality have a direct effect on intercultural effectiveness and (b) does an
individual’s world view have a direct effect on intercultural effectiveness [18]?
First, literature already reports some evidence of direct effects of various dimensions
of multicultural personality on intercultural effectiveness. Indeed, Ward and Fischer
found that flexibility, social initiative, and emotional stability had a direct effect on the
general adjustment of international students in New-Zealand [
42
]. Moreover, the general
personality trait openness to experience was found to have a direct effect on adaptive
performance [
74
] and job performance [
75
], albeit partially mediated through the motivation
dimension of cultural intelligence. As a specific example from health care, Herrera and
Owens found that higher post-traumatic stress disorder (PTSD) in US service members
was predicted by higher levels of open mindedness and lower levels of flexibility and
emotional stability [
21
]. As such, we have examined the possibility of extending the
proposed framework of Leung and colleagues with a direct relation between (multicultural)
personality traits and intercultural effectivity [18].
H5.
Higher scores on intercultural traits directly predict higher scores on intercultural effectiveness.
Second, literature also reports direct effects of world views on intercultural effec-
tiveness. For sure, an ethnocentric world view in health care professionals is known to
lead to negative outcomes like misdiagnosis, mistreatment, and undertreatment in cul-
turally diverse individuals [
76
]. For instance, an experimental design in a health context
revealed that the willingness to interact with an intercultural health professional correlated
negatively with ethnocentrism, r=−0.19 [77].
H6. A more ethnorelative world view directly predicts higher scores on intercultural effectiveness.
Figure 1summarizes the presented hypotheses toward the empirical verification of
the integrative framework of intercultural competence and effectiveness.
Int. J. Environ. Res. Public Health 2022,19, 4490 6 of 21
Int. J. Environ. Res. Public Health 2022, 19, x FOR PEER REVIEW 6 of 22
Figure 1 summarizes the presented hypotheses toward the empirical verification of
the integrative framework of intercultural competence and effectiveness.
Figure 1. Hypotheses summary: test of an integrative framework. Note: The grey squares represent
intercultural competence. The operationalizations of intercultural competence and effectiveness are
presented in italic. H1, H2, H3, and H4 represent the empirical test of the integrative framework as
proposed by Leung et al., 2014. H5 and H6 represent additional hypotheses in dashed arrows. All
hypothesized relationships are expected to have positive effects.
2. Materials and Method
2.1. Data and Procedure
The data were gathered in the context of the EdisTools project, a large Strategic Basic
Research project in Belgium (Flanders), subsidized by Scientific Organizations Flanders.
This EdisTools project aims to map out interculturalism and prejudice in four different
professional settings, which are also embedded in legislation as constitutional rights: ed-
ucation, health care, housing, and work. The project focuses on the intercultural effective-
ness of the ethnic majority (i.e., Belgian) service provider (i.e., teachers, doctors, estate
agents and employers) toward the ethnic minority client (i.e., learners, patients, potential
tenants, and job applicants respectively). This project was approved by the Ethical Medi-
cal Committee of Ghent University Hospital, with approval number BC-07577. Practically,
the project wants to improve intercultural effectiveness in key domains of society like
health care by developing a set of digital tools for training and education. As the present
study also focuses on identifying key pathways of intercultural competence for purposes
of future education and training in a medical context, a student sample of undergraduate
medical students was deemed appropriate. In April 2020 and April 2021, all students in
the 1st year of Medical School, in the pre-Master program in Management and Organiza-
tion of Healthcare, and in pre-Master Program in Health Promotion at the Faculty of Med-
icine and Health Sciences of a large Belgian University with a top 100 rating in the Aca-
demic Ranking of World Universities (ARWU; see also [78]) were therefore invited to par-
ticipate in the present study and fill out an online survey. All students gave informed
Figure 1.
Hypotheses summary: test of an integrative framework. Note: The grey squares represent
intercultural competence. The operationalizations of intercultural competence and effectiveness are
presented in italic. H1, H2, H3, and H4 represent the empirical test of the integrative framework as
proposed by Leung et al., 2014. H5 and H6 represent additional hypotheses in dashed arrows. All
hypothesized relationships are expected to have positive effects.
2. Materials and Method
2.1. Data and Procedure
The data were gathered in the context of the EdisTools project, a large Strategic Basic
Research project in Belgium (Flanders), subsidized by Scientific Organizations Flanders. This
EdisTools project aims to map out interculturalism and prejudice in four different professional
settings, which are also embedded in legislation as constitutional rights: education, health care,
housing, and work. The project focuses on the intercultural effectiveness of the ethnic majority
(i.e., Belgian) service provider (i.e., teachers, doctors, estate agents and employers) toward the
ethnic minority client (i.e., learners, patients, potential tenants, and job applicants respectively).
This project was approved by the Ethical Medical Committee of Ghent University Hospital,
with approval number BC-07577. Practically, the project wants to improve intercultural
effectiveness in key domains of society like health care by developing a set of digital tools for
training and education. As the present study also focuses on identifying key pathways of
intercultural competence for purposes of future education and training in a medical context, a
student sample of undergraduate medical students was deemed appropriate. In April 2020
and April 2021, all students in the 1st year of Medical School, in the pre-Master program in
Management and Organization of Healthcare, and in pre-Master Program in Health Promotion
at the Faculty of Medicine and Health Sciences of a large Belgian University with a top 100
rating in the Academic Ranking of World Universities (ARWU; see also [
78
]) were therefore
invited to participate in the present study and fill out an online survey. All students gave
informed consent prior to filling out the survey. Response rate was 76% (N= 842), with
74% female students with an average age of M= 22.03 (SD = 3.28), Mdn = 21 (i.e., 69% of
the student population aged between 20 and 22). The vast majority of the students (96%)
had Belgian nationality. These numbers are in line with population statistics as 78% of the
Flemish health care practitioners are women [
79
], while 92% of the total Belgian population
has the Belgian nationality [
80
]. Slightly less than 11% of the students reported a parent or
grandparent with a non-Belgian nationality. Furthermore, 41% of the students reported (close)
friends, close colleagues, or family with a migration background.
2.2. Measures
2.2.1. Intercultural Traits
Intercultural traits were conceptualized as multicultural personality dimensions and
operationalized using the SF-MPQ [
35
]. The SF-MPQ has five subscales with eight items
Int. J. Environ. Res. Public Health 2022,19, 4490 7 of 21
each and a recurring instruction: “to what extent do the following statements apply to
you?” Participants have to respond to this question on a 5-point Likert scale from 1 (totally
not applicable) to 5 (completely applicable). For cultural empathy (MPQ-CE, M= 4.18,
SD = 0.43,
α
= 0.80), the subscale included items like “Is a good listener”. For flexibility
(MPQ-FX, M= 2.45, SD = 0.71,
α
= 0.87), the subscale included items like “Works according
to plan” (reverse coded). For social initiative (MPQ-SI, M= 3.32, SD = 0.64,
α
= 0.85), the
subscale included items like “Takes initiative”. For emotional stability (MPQ-ES, M= 3.08,
SD = 0.71,
α
= 0.85), the subscale included items like “Is insecure” (reverse coded). Finally,
for open mindedness (MPQ-OP, M= 3.45, SD = 0.53,
α
= 0.78), the subscale included items
like “Has broad range of interests”. Important to note, although the five dimensions of the
MPQ are correlated [33], the MPQ does not support an overarching general dimension.
2.2.2. Intercultural Attitudes and Worldviews
Intercultural attitudes and worldviews were conceptualized through the ethnocentric-
ethnorelative continuum (EC-ER) and operationalized using six items adapted from the
European Social Survey [
81
] on a ten-point Likert scale (M= 6.67, SD = 1.37,
α
= 0.81). As an
example, participants had to respond to items like “Would you say it is generally bad or good
for the economy that people come to live here from other countries?” A higher or lower score
on the EC-ER scale respectively represents a more ethnorelative or ethnocentric world view.
2.2.3. Intercultural Capabilities
Intercultural capabilities were conceptualized as cultural intelligence (CQ) and opera-
tionalized using the Adapted Self-Report CQ Scale [
56
]. The Adapted Self-Report CQ Scale
has four subscales with six items each. For each item, participants had to indicate to which
degree they agreed to the presented statement on a 5-point Likert scale (1—strongly disagree
to 5—strongly agree). For motivation (CQ-MOT, M= 3.88, SD = 0.53,
α
= 0.79), the sub-
scale included items like “It’s fun for me to interact with people from other cultures”. For
cognition (CQ-COG, M= 2.86, SD = 0.67,
α
= 0.87), the subscale included items like “I can
describe how parents treat their children in various cultures”. For metacognition (CQ-META,
M= 3.53
,
SD = 0.56, α
= 0.75), the subscale included items like “When I meet people from
another culture, I try to find out how to act appropriately in that culture”. And finally, for
behavior (CQ-BEH, M= 3.57, SD = 0.48,
α
= 0.68), the subscale included items like “If there is
a misunderstanding between people from different cultures, I try to clear it up”.
2.2.4. Intercultural Effectiveness
Intercultural effectiveness was conceptualized as cultural self-efficacy (CSE) and opera-
tionalized using the CSES-A [
70
]. The Brottman and colleagues review on cultural competence
in health care mentioned that CSES-A was the most frequent (i.e., about 6%) assessment tool
found in the selected papers [
19
,
70
]. This scale has five subscales with a varying amount
of items. For each item, participants had to answer to a recurring question on a five-point
Likert scale (1—cannot do at all to 5—certainly can do): “In the situations posed below, mark
to what extent you feel capable of carrying them out using the options given”. For process
(CSE-process, five items, M= 3.61, SD = 0.53,
α
= 0.74), the subscale included items like
“Speaking to people from a different culture, I can realize what I know about that culture”. For
mix (CSE-mix, eight items, M= 3.82, SD = 0.56,
α
= 0.87), the subscale included items like “If I
lived in a different culture, I would be able to make new friends”. For cope (CSE-cope, four
items, M= 2.90, SD = 0.86,
α
= 0.88), the subscale included items like “If I lived in a different
culture, I would be able to overcome loneliness”. For understanding (CSE-US, five items,
M= 3.66, SD = 0.62,
α
= 0.78), the subscale included items like “Approaching a different
culture, I can understand other religious beliefs”. And finally, for language (CSE-LAN, three
items, M= 3.17, SD = 0.85,
α
= 0.86), the subscale included items like “Approaching a different
culture, I can learn a language different from mine”.
Int. J. Environ. Res. Public Health 2022,19, 4490 8 of 21
2.3. Analyses
Analyses were conducted using a SEM set up by means of the lavaan package in
R [
82
,
83
]. For an overview on SEM-analyses, we also refer to Rosseel [
82
,
84
]. For an
overview regarding modifying and reporting SEM, we refer to Ullman and Bentler [
85
] and
Schreiber and colleagues [
86
]. For analyzing model fit, we made use of common guidelines
in literature by Hu and Bentler [
87
], Kenny and colleagues [
88
], and Rosseel [
82
]. As SEM
literature shows quite some controversy regarding cherry picking fit indices, the present
study features a small, but commonly reported battery of fit indices. The chi-square test
is the primary test for SEM. A model has a good fit if the chi-square test does not reach
significance at the
α
= 0.05 level. However, literature has reached consensus that this test is
too strict. As such, we report a set of three other fit indices, that are generally considered as
complementary [
89
]. The first index used is the Root Mean Square Error of Approximation
(RMSEA). The RMSEA renders an absolute fit value (i.e., no comparison to other models),
of which the 90% confidence interval (CI) should have a lower value no higher than 0.05
and a higher value lower than 0.08. The second index used is the Standardized Root Mean
Square Residual (SRMR). The SRMR also renders an absolute fit value, which should be
lower than 0.08. Finally, the third index used is the Comparative Fit Index. The CFI is an
incremental (relative) index that compares models to the (worst possible) null model. In a
model with an adequate fit, the CFI should be higher than 0.95. However, if the RMSEA
of the baseline model is too good (i.e., RMSEA < 0.158), the CFI estimate will be too low,
rendering the CFA useless as a measure of fit [
88
]. Literature does recommend caution in
interpreting these rules of thumb too rigorously. Researchers should primarily aim for fit
indices that show similar results, while also scanning for other indications of bad fit like
non-significant parameters at different levels of significance (The p-values are reported
with three decimals to allow for model respecification at different significance levels.). For
a concise overview on additional SEM fit literature, we also refer to Kenny [90].
A SEM analyses consists of two major parts. The structural part presents path analyses
on how variables interact with each other. The latent part allows to assess how individual
items load on latent constructs, as is the case in confirmatory factor analyses (CFA). For
the present study, we are primarily interested in the structural part, as specific regression
analyses will allow us to test H1 through H6 and the instruments are already validated
in various studies (see Section 1Introduction). However, as the validity of data is always
dependent on both population and instrument, we have used CFA to evaluate the construct
validity of the data, generated by the full battery of instruments. As the full models are
quite extensive, we have provided two variance–covariance matrices as a data supplement,
allowing full replication of our results.
3. Results
3.1. Preliminary Analysis: First Order Correlations and CFA
Table 1shows the first order Pearson correlation coefficient for all variables. Important
to note, both the total scales as well as the subscales (if present) are included. To assess
the construct validity of our data, we performed a CFA on the following (sub-)scales and
their theorized individual internal structure: MPQ (CE, FX, SI, ES, and OM), EC-ER, four
subscales of CQ (MOT, COG, META and BEH) and five subscales of CSE (process, mix, cope,
US, and LAN). The model converged after 128 iterations, with
χ2(N= 842, 4333) = 12301.53
,
p< 0.001. The set of fit indices showed a somewhat mixed result. Both the RMSEA = 0.047,
90% CI [0.046, 0.048], p= 1.000 as well as the SRMR = 0.068 indicated an adequate to even a
good fit, while the CFI = 0.77 indicated a poor fit. However, closer inspection of the base
null model (which the CFA model is compared against to calculate the CFI) revealed that
the null model rendered a RMSEA = 0.097, which violates the condition that the null model
has to have an RMSEA > 0.158. As such, the CFI is no longer considered informative. As
the CFA model fits the data adequately, we therefore conclude that our obtained data allow
us to draw valid conclusions regarding the present study’s hypotheses.
Int. J. Environ. Res. Public Health 2022,19, 4490 9 of 21
Table 1. Correlation matrix.
M SD EC-ER MPQ-
CE MPQ-FX MPQ-
SI
MPQ-
ES
MPQ-
OP
CSE-
process
CSE-
mix
CSE-
cope
CSE-
US
CSE-
LAN CSE CQ-
MOT
CQ-
COG
CQ-
META
CQ-
BEH CQ
EC-ER 39.99 8.2 1 0.181 ** 0.153 ** 0.066 0.066 0.398 ** 0.308 ** 0.296 ** 0.021 0.362 ** 0.075 * 0.319 ** 0.470 ** 0.121 ** 0.256 ** 0.194 ** 0.371 **
MPQ-CE 33.42 3.44 1 −0.070 * 0.261 ** −0.062 0.387 ** 0.338 ** 0.265 ** 0 0.303 ** 0.127 ** 0.302 ** 0.415 ** 0.144 ** 0.229 ** 0.238 ** 0.366 **
MPQ-FX 19.62 5.66 1 0.099 ** 0.257 ** 0.148 ** 0.064 0.141 ** 0.003 0.108 ** 0.043 0.113 ** 0.101 ** 0.05 −0.025 −0.047 0.033
MPQ-SI 26.58 5.13 1 0.273 ** 0.275 ** 0.224 ** 0.288 ** 0.037 0.130 ** 0.134 ** 0.249 ** 0.145 ** 0.112 ** 0.081* 0.022 0.136 **
MPQ-ES 24.66 5.71 1 0.218 ** 0.108 ** 0.173 ** 0.141 ** 0.062 0.101 ** 0.180 ** 0.073 * 0.116 ** −0.052
−0.146
** 0.01
MPQ-OP 27.63 4.22 1 0.503 ** 0.434 ** 0.145 ** 0.365 ** 0.298 ** 0.512 ** 0.518 ** 0.303 ** 0.291 ** 0.167 ** 0.471 **
CSE-
process 18.06 2.67 1 0.521 ** 0.152 ** 0.498 ** 0.358 ** 0.721 ** 0.538 ** 0.386 ** 0.238 ** 0.187 ** 0.502 **
CSE-mix 3.52 4.45 1 0.306 ** 0.446 ** 0.349 ** 0.829 ** 0.559 ** 0.230 ** 0.191 ** 0.158 ** 0.414 **
CSE-
cope 11.61 3.42 1 0.111 ** 0.147 ** 0.534 ** 0.132 ** 0.147 ** −0.033 −0.045 0.083 *
CSE-US 18.31 3.09 1 0.296 ** 0.682 ** 0.524 ** 0.390 ** 0.233 ** 0.204 ** 0.502 **
CSE-
LAN 9.51 2.56 1 0.587 ** 0.240 ** 0.315 ** 0.156 ** 0.076 * 0.302 **
CSE 88.02 11.05 1 0.598 ** 0.413 ** 0.226 ** 0.169 ** 0.524 **
CQ-MOT 23.31 3.17 1 0.279 ** 0.311 ** 0.270 ** 0.668 **
CQ-COG 17.17 3.99 1 0.186 ** 0.155 ** 0.651 **
CQ-
META 21.16 3.34 1 0.557 ** 0.731 **
CQ-BEH 21.4 2.9 1 0.682 **
CQ 83.05 9.13 1
Note: MPQ = multicultural personality questionnaire, CE = cultural empathy, FX = flexibility, SI = social initiative, ES = emotional stability, OP = open mindedness,
EC-ER = ethnocentric–ethnorelative continuum, CQ = cultural intelligence, MOT = motivation, COG = cognition, META = meta-cognition, BEH = behavior, CSE = cultural self-efficacy,
US = understanding, LAN = language. * p< 0.05, ** p< 0.01.
Int. J. Environ. Res. Public Health 2022,19, 4490 10 of 21
3.2. Model 1: Saturated Model
We started our analyses with a model featuring the total scale scores, without subdimen-
sions. Model 1 thus features the scores on the five MPQ scales (i.e., CE, FX, SI, ES and OM), as
well as the total scores on EC-ER, CQ, and CSE. As such, Model 1 aims to test all hypotheses (H1
to H6) at a structural path level, without subscales. Model 1 converged after 40 iterations, using
maximum likelihood as means of estimation. Model 1 is a fully saturated model, meaning that
all variances, covariances, and means of the observed variables are perfectly reproduced. The chi-
square test on the saturated model renders
χ2
(N= 842, 0) = 0. Our set of selected fit indices also
renders perfect fitting values, which are inherent to saturated models: RMSEA = 0,
SRMR = 0
and CFI = 1. Table 2shows all regressions within Model 1. Model 1 also rendered an explained
variance of R
2
= 0.17 for EC-ER, R
2
= 0.30 for CQ and R
2
= 0.39 for CSE. Although the model is sat-
urated and thus inherently has the best possible fitindices, the model still harbors non-significant
pathways. These pathways have to be removed in Model 2 in order to evaluate the present
study’s hypotheses.
Table 2. Regressions from model 1.
H Regression E SE z p ML
EC-ER ~
H1 MPQ-CE 0.18 0.11 1.55 0.121 0.06
H1 MPQ-FX 0.22 0.06 3.43 0.001 0.11
H1 MPQ-SI −0.12 0.07 −1.67 0.096 −0.06
H1 MPQ-ES −0.05 0.07 −0.77 0.441 −0.03
H1 MPQ-OP 0.99 0.09 10.66 0.000 0.38
CQ ~
H2 MPQ-CE 0.17 0.03 6.03 0.000 0.20
H2 MPQ-FX −0.01 0.02 −0.62 0.537 −0.02
H2 MPQ-SI 0.00 0.02 −0.06 0.952 0.00
H2 MPQ-ES −0.03 0.02 −1.81 0.070 −0.06
H2 MPQ-OP 0.24 0.03 9.33 0.000 0.33
CQ ~
H3 EC-ER 0.06 0.01 6.69 0.000 0.21
CSE-TOT ~
H4 CQ 0.40 0.04 10.79 0.000 0.35
H5 MPQ-CE 0.05 0.03 1.56 0.120 0.05
H5 MPQ-FX 0.02 0.02 0.92 0.358 0.03
H5 MPQ-SI 0.06 0.02 2.95 0.003 0.09
H5 MPQ-ES 0.06 0.02 2.99 0.003 0.09
H5 MPQ-OP 0.22 0.03 7.48 0.000 0.26
H6 EC-ER 0.02 0.01 2.07 0.038 0.06
Note: H = hypothesis, H1 = higher scores on intercultural traits predict a more ethnorelative world view,
H2 = higher scores on intercultural traits predict higher scores on intercultural capabilities, H3 = a more eth-
norelative world view predicts higher scores on intercultural capabilities, H4 = higher scores on intercultural
capabilities predict higher scores on intercultural effectiveness, H5 = higher scores on intercultural traits directly
predict higher scores on intercultural effectiveness, H6 = a more ethnorelative world view directly predicts higher
scores on intercultural effectiveness. MPQ = multicultural personality questionnaire, CE = cultural empathy,
FX = flexibility, SI = social initiative, ES = emotional stability, OP = open mindedness, EC-ER = ethnocentric–
ethnorelative continuum, CQ = cultural intelligence, MOT = motivation, COG = cognition, META = meta-cognition,
BEH = behavior, CSE = cultural self-efficacy, TOT = Total score of all five subscales, E= estimate, SE = stan-
dard error of the estimate, z= normalized estimate, p= result of the statistical test on the z–score to reject the
null-hypothesis of z= 0, ML = model loading. The dependent variables of the regressions are indicated in italic.
3.3. Model 2: Structural Model
Figure 2shows the structural Model 2. Model 2 converged after 32 iterations. The
chi-square test for Model 2 is non-significant,
χ2
(N= 842, 8) = 13.85, p= 0.086, which
indicates that Model 2 has an adequate fit, even when testing against the most conservative
test possible. For reasons of comparability, we also report the RMSEA = 0.029, 90% CI
[0.000, 0.055], p= 0.901, the SRMR = 0.020, and the CFI = 0.993. Table 3shows all regressions
within Model 2. Model 2 also rendered an explained variance of R
2
= 0.17 for EC-ER,
Int. J. Environ. Res. Public Health 2022,19, 4490 11 of 21
R
2
= 0.30 for CQ and R
2
= 0.39 for CSE. However, Model 2 did not include the subscales for
CQ and CSE. These subscales are crucial to assess how intercultural competence has an
effect on intercultural effectiveness.
Int. J. Environ. Res. Public Health 2022, 19, x FOR PEER REVIEW 12 of 22
Figure 2. Graphical representation of Model 2. Note: MPQ = multicultural personality questionnaire,
CE = cultural empathy, FX = flexibility, SI = social initiative, ES = emotional stability, OP = open
mindedness, EC_ER = ethnocentric–ethnorelative continuum, CQ = cultural intelligence, CSE = cul-
tural self-efficacy, US = understanding, LAN = language. All reported relationships have positive
and significant effects of at least p < 0.05.
Table 3. Regressions from Model 2.
H Regression E SE z p ML
EC-ER ~
H1 MPQ-FX 0.19 0.06 3.01 0.003 0.10
H1 MPQ-OP 1.00 0.08 12.07 0.000 0.38
CQ ~
H2 MPQ-CE 0.19 0.03 6.69 0.000 0.21
H2 MPQ-OP 0.22 0.02 9.08 0.000 0.31
CQ ~
H3 EC-ER 0.06 0.01 6.70 0.000 0.21
CSE ~
H4 CQ 0.42 0.04 11.35 0.000 0.36
H5 MPQ-SI 0.07 0.02 3.38 0.001 0.10
H5 MPQ-ES 0.05 0.02 3.02 0.003 0.09
H5 MPQ-OP 0.23 0.03 8.26 0.000 0.27
H6 EC-ER 0.02 0.01 2.19 0.029 0.07
Note: H = hypothesis, H1 = high scores on intercultural traits predict an ethnorelative world view,
H2 = higher scores on intercultural traits predict higher scores on intercultural capabilities, H3 = a
Figure 2.
Graphical representation of Model 2. Note: MPQ = multicultural personality ques-
tionnaire, CE = cultural empathy, FX = flexibility, SI = social initiative, ES = emotional stability,
OP = open mindedness
, EC_ER = ethnocentric–ethnorelative continuum, CQ = cultural intelligence,
CSE = cultural self-efficacy
, US = understanding, LAN = language. All reported relationships have
positive and significant effects of at least p< 0.05.
Table 3. Regressions from Model 2.
H Regression E SE z p ML
EC-ER ~
H1 MPQ-FX 0.19 0.06 3.01 0.003 0.10
H1 MPQ-OP 1.00 0.08 12.07 0.000 0.38
CQ ~
H2 MPQ-CE 0.19 0.03 6.69 0.000 0.21
H2 MPQ-OP 0.22 0.02 9.08 0.000 0.31
CQ ~
H3 EC-ER 0.06 0.01 6.70 0.000 0.21
CSE ~
H4 CQ 0.42 0.04 11.35 0.000 0.36
H5 MPQ-SI 0.07 0.02 3.38 0.001 0.10
H5 MPQ-ES 0.05 0.02 3.02 0.003 0.09
H5 MPQ-OP 0.23 0.03 8.26 0.000 0.27
H6 EC-ER 0.02 0.01 2.19 0.029 0.07
Note: H = hypothesis, H1 = high scores on intercultural traits predict an ethnorelative world view, H2 = higher
scores on intercultural traits predict higher scores on intercultural capabilities, H3 = a more ethnorelative world
view predicts high scores on intercultural capabilities, H4 = higher scores on intercultural capabilities predict
higher scores on intercultural effectiveness, H5 = higher scores on intercultural traits directly predict higher scores
on intercultural effectiveness, H6 = a more ethnorelative world view directly predicts higher scores on intercultural
effectiveness. MPQ = multicultural personality questionnaire, CE = cultural empathy, FX = flexibility, SI = social
initiative, ES = emotional stability, OP = open mindedness, EC-ER = ethnocentric–ethnorelative continuum,
CQ = cultural intelligence, MOT = motivation, COG = cognition, META = meta-cognition, BEH = behavior,
CSE = cultural self-efficacy, E= estimate, SE = standard error of the estimate, z= normalized estimate, p= result
of the statistical test on the z–score to reject the null–hypothesis of z= 0, ML = model loading. The dependent
variables of the regressions are indicated in italic.
Int. J. Environ. Res. Public Health 2022,19, 4490 12 of 21
3.4. Model 3: Structural Model with Subscales
For Model 3a, we started from the full set of subscale scores: EC-ER, MPQ (i.e., CE,
FX, SI, ES, and OM), CQ (i.e., CQ-MOT, CQ-COG, CQ-META, and CQ-BEH), and CSE (i.e.,
CSE-process, CSE-mix, CSE-cope, CSE-US, and CSE-LAN). However, the model did not show
adequate fit measures. First, the chi-square test was significant
χ2
(N= 842, 6) = 306.036,
p< 0.001
. Second, the set of fit indices indicated an insufficient fit of the model with the
RMSEA = 0.244, 90% CI [0.221, 0.267], p< 0.001, the SRMR = 0.049, and the CFI = 0.892.
As such, Model 3b removed all non-significant pathways at the
α
= 0.05 significance level
and again at the
α
= 0.01 significance level to improve the model fit in subsequent iterations.
The significance of the pathways is evaluated using the z-score, which is a function of both
the unstandardized effect as well as the standard error of the effect. This respecified Model 3b
showed a significant chi-square test,
χ2
(N= 842, 47) = 141.857, p< 0.001. However, our set
of fit indices showed an adequate to good fit of Model 3b, with the RMSEA = 0.049, 90% CI
[0.040, 0.058], p= 0.557, the SRMR = 0.042, and the CFI = 0.966. Table 4shows all regressions
within Model 3b. Table 5shows the explained variances for all endogenous (sub) scales.
Table 4. Regressions from Model 3b.
H Regression E SE z p ML
EC-ER ~
H1 MPQ-OP 1.00 0.08 12.07 0.000 0.38
H1 MPQ-FX 0.19 0.06 3.01 0.003 0.10
CQ-MOT ~
H2 MPQ-CE 0.30 0.04 8.40 0.000 0.24
H2 MPQ-OP 0.30 0.03 9.67 0.000 0.30
H3 EC-ER 0.12 0.01 1.51 0.000 0.31
CQ-COG ~
H2 MPQ-OP 0.38 0.04 9.24 0.000 0.30
CQ-META ~
H2 MPQ-CE 0.17 0.04 3.85 0.000 0.13
H2 MPQ-OP 0.17 0.03 5.02 0.000 0.16
H3 EC-ER 0.07 0.01 4.85 0.000 0.17
CQ-BEH ~
H2 MPQ-CE 0.23 0.04 6.23 0.000 0.21
H3 EC-ER 0.05 0.01 4.57 0.000 0.15
SE-process ~
H4 CQ-MOT 0.31 0.03 9.77 0.000 0.31
H4 CQ-COG 0.16 0.02 7.49 0.000 0.21
H5 MPQ-CE 0.11 0.04 3.17 0.002 0.09
H5 MPQ-OP 0.25 0.03 7.53 0.000 0.25
SE-mix ~
H4 CQ-MOT 0.47 0.03 14.51 0.000 0.45
H5 MPQ-OP 0.15 0.03 4.63 0.000 0.14
H5 MPQ-SI 0.14 0.02 6.39 0.000 0.17
SE-cope ~
H4 CQ-MOT 0.16 0.06 2.95 0.003 0.10
H4 CQ-COG 0.13 0.04 3.15 0.002 0.10
H5 MPQ-ES 0.11 0.04 2.74 0.006 0.09
SE-US ~
H4 CQ-MOT 0.38 0.04 9.85 0.000 0.33
H4 CQ-COG 0.24 0.03 9.26 0.000 0.26
H5 MPQ-CE 0.15 0.04 3.54 0.000 0.11
Int. J. Environ. Res. Public Health 2022,19, 4490 13 of 21
Table 4. Cont.
H Regression E SE z p ML
H6 EC-ER 0.07 0.01 5.14 0.000 0.16
SE-LA ~
H4 CQ-COG 0.30 0.04 7.15 0.000 0.23
H5 MPQ-OP 0.36 0.05 6.68 0.000 0.22
Note: H = hypothesis, H1 = high scores on intercultural traits predict an ethnorelative world view, H2 = higher
scores on intercultural traits predict higher scores on intercultural capabilities, H3 = a more ethnorelative world
view predicts high scores on intercultural capabilities, H4 = higher scores on intercultural capabilities predict
higher scores on intercultural effectiveness, H5 = higher scores on intercultural traits directly predict higher scores
on intercultural effectiveness, H6 = a more ethnorelative world view directly predicts higher scores on intercultural
effectiveness. MPQ = multicultural personality questionnaire, CE = cultural empathy, FX = flexibility, SI = social
initiative, ES = emotional stability, OP = open mindedness, EC-ER = ethnocentric–ethnorelative continuum,
CQ = cultural intelligence, MOT = motivation, COG = cognition, META = meta-cognition, BEH = behavior,
CSE = cultural self-efficacy, US = understanding, LAN = language, E= estimate, SE = standard error of the
estimate, z= normalized estimate, p= result of the statistical test on the z–score to reject the null–hypothesis of
z= 0, ML = model loading. The dependent variables of the regressions are indicated in italic.
Table 5. Explained variance in endogenous variables of Model 3b.
CQ-MOT CQ-COG CQ-
META
CQ-
BEH EC-ER SE-
Process SE-Mix SE-Cope SE-US SE-LAN
R20.397 0.092 0.116 0.076 0.167 0.384 0.361 0.035 0.339 0.135
Note: EC-ER = ethnocentric–ethnorelative continuum, CQ = cultural intelligence, MOT = motivation, COG = cognition,
META = meta-cognition, BEH = behavior, CSE = cultural self-efficacy, US = understanding, LAN = language.
To finalize our analyses, we inspected the modification indices of Model 3b. Modifica-
tion indices present information on possible model improvements by presenting alternative
pathway relations that can possibly improve the model. Conservatively, we only considered
modification indices above 10.83, as this threshold corresponds with an effect size of which
the p-value is lower than 0.001. Analyses rendered eight possible extensions to the model,
with a maximum modification index of 20.51. We did not observe any pathways that were
linked to our hypotheses, which strengthens the validity of Model 3b. We did observe four
possible additions in which CQ subscales are regressed on other CQ subscales, and four
possible additions in which CQ subscales were regressed on CSE subscales. Especially the
latter suggestions are interesting, suggesting that self-efficacy can also have an (recursive)
effect on intercultural competencies. However, for the present study, we do not have
sufficient theoretical grounds to add these possible additions to the final model.
As we now have adequate fit measures on a model with specific subscales and no non-
significant regressions in Model 3b, we can assess our hypotheses based on the regressions
of the model.
3.5. Hypotheses Evaluation
For H1 (i.e., higher scores on intercultural traits predict an ethnorelative world view)
Table 4shows that the regression of EC-ER on both MPQ-OP as well as MPQ-FX is significant.
We therefore conclude, we have at least partial empirical evidence that supports H1.
For H2 (i.e., higher scores on intercultural traits predict higher scores on intercultural
capabilities), Table 4shows that (a) the regression of CQ-MOT on MPQ-CE and MPQ-OP is
significant; (b) the regression of CQ-COG on MPQ-OP is significant; (c) the regression of
CQ-META on MPQ-CE and MPQ-OP is significant; and (d) the regression of CQ-BEH on
MPQ-CE is significant. In sum, two out of five MPQ dimensions are positively related to
all four dimensions of CQ. We therefore conclude that we have at least partial empirical
evidence that supports H2.
For H3 (i.e., a more ethnorelative world view predicts higher scores on intercultural
capabilities), Table 4shows that the respective regressions of CQ-MOT, CQ-MET, and
CQ-BEH on EC-ER are significant. In sum, EC-ER was positively related to three out of four
Int. J. Environ. Res. Public Health 2022,19, 4490 14 of 21
dimensions of CQ. We therefore conclude that we have at least partial empirical evidence
that supports H3.
For H4 (i.e., higher scores on intercultural capabilities predict higher scores on inter-
cultural effectiveness), Table 4shows that (a) the regression of CSE-process on CQ-MOT
and CQ-COG is significant; (b) the regression of CSE-mix on CQ-MOT is significant; (c)
the regression of CSE-cope on CQ-MOT and CQ-COG is significant; (d) the regression of
CSE-US on CQ-MOT and CQ-COG is significant; and (e) the regression of CSE-LAN on
CQ-COG is significant. In sum, two out of four dimensions of CQ are positively related to
all five dimensions of CSE. We therefore conclude that we have at least partial empirical
evidence that supports H4.
For H5 (i.e., higher scores on intercultural traits predict higher scores on intercultural
effectiveness), Table 4shows that (a) the regression of SE-process on MPQ-CE and MPQ-OP
is significant; (b) the regression of SE-mix on MPQ-OP and MPQ-SI is significant; (c) the
regression of CSE-cope on MPQ-ES is significant; (d) the regression of CSE-US on MPQ-CE
is significant; and (e) the regression of CSE-LAN on MPQ-OP is significant. In sum, four
out of five dimensions of the MPQ are positively related to all five dimensions of CSE. We
therefore conclude that we have at least partial empirical evidence that supports H5.
Finally, for H6 (i.e., a more ethnorelative world view predicts higher scores on inter-
cultural effectiveness), Table 4shows that the regression of CSE-US on EC-ER is significant.
As EC-ER is only related to one out of five sub-dimensions of CSE, we conclude that we
have some partial empirical evidence that supports H6.
For replication of our analyses, two variance-covariance matrices were added as
Supplementary Materials.
4. Discussion
Today, effective intercultural interaction is an essential part of ensuring equity in
health care [
2
–
6
,
9
,
10
,
16
,
17
]. Negative outcomes like prejudice are responsible for subopti-
mal treatment of people from different race or nationality, resulting in less favorable therapy
outcomes [
13
–
15
]. Leung and colleagues have summarized the literature on the effective-
ness of intercultural interaction (i.e., inside and outside of health care) into a theoretical
framework [
18
]. This integrative framework hypothesizes that intercultural competence
determines how effective individuals handle intercultural situations. This competence is
determined through the interrelations between three key framework components: inter-
cultural traits, intercultural interactions and worldviews, and intercultural capabilities.
Although the theoretical importance of this framework cannot be underestimated, the
authors themselves have called for empirical verification. Addressing this call, the present
study empirically tested the integrative framework on intercultural effectiveness, rather
than just studying parts of it. As such, we conceptualized all framework components using
validated multidimensional constructs, operationalized with appropriate instruments. Ulti-
mately, a validated framework can identify which framework components are responsible
for intercultural effective behavior. Moreover, these components can become the target of
training, intervention, and identification of best practices to ensure all ethnic groups of
patients with different nationalities are treated fairly toward more equity in health. As an
example, the EdisTools project will use these findings to develop a set of digital tools for
training and education in health care.
A fairly large sample of (future) health care practitioners from the faculty of Medicine
and Health Sciences of a large Western-European university filled out the online survey
including the operationalized constructs. Using structural equation modeling on the data
obtained, we tested the general fit and the hypothesized relations from the framework. In
doing so, we also tried to explore how exactly the different components of the framework
are interrelated and if we could possibly extend the model.
For the first time in literature, to the best of our knowledge, the present study em-
pirically verified the full theorized framework proposed by Leung and colleagues (2014),
as the model fitted our data quite well. First, the present study replicated the (latent)
Int. J. Environ. Res. Public Health 2022,19, 4490 15 of 21
structure of four independently developed instruments, thus validating our data toward
the current research. Second, the battery of fit indices indicated an adequate fit, for models
with and without subscales (see also Figure 2). Third, the hypothesized relations between
the components of the framework were at least partially confirmed (see also Figure 1).
Finally, the present study provided at least partial evidence for possible future additions to
the framework.
In line with literature, multicultural personality traits were positively related to both
the ethnocentric–ethnorelative worldview continuum [
39
,
40
], as well as multidimensional
cultural intelligence [
41
,
42
]. Closer inspection of the framework components revealed
that individuals with an open mind have a more ethnorelative disposition, while also
showing better cultural capabilities through a higher score on motivation, cognition, and
metacognition. Our findings also indicated that culturally empathic individuals showed
a higher cultural intelligence through higher scores on motivation, metacognition, and
behavior. As such, these two multicultural personality traits, open mindedness, and cultural
empathy, seem to cover the full spectrum of cultural intelligence dimensions. These results
were also largely in line with literature as the motivational dimension was pointed out as
the key dimension that was positively related to the personality traits [41,42].
Moreover, also in line with the literature, individuals with a more ethnorelative dis-
position showed better intercultural capabilities [
50
,
51
]. Indeed, analogous to the cultural
empathy trait, an individual’s ethnorelative disposition was related positively to the motiva-
tion, metacognition, and behavior dimension of the individual’s cultural intelligence.
Higher levels of cultural intelligence also predicted higher levels of cultural self-
efficacy. These findings were also largely in line with literature [
52
,
58
,
64
,
68
]. An individual
with higher scores on the motivation and cognition dimension of cultural intelligence
showed higher levels of cultural self-efficacy through higher scores on the process, mix,
cope, and understanding dimensions and on the process, cope, understanding, and lan-
guage dimensions respectively.
Finally, the present study also explored possible extensions of the framework. First,
four multicultural personality traits had a direct effect on intercultural effectiveness.
(a) Open minded, (b) emotionally stable, (c) culturally empathic individuals or individ-
uals that take (d) social initiative also showed higher levels of self-efficacy across all
(sub)dimensions that was not mediated fully by the other components of the framework.
Although the open mindedness trait thus represented an influential node in the framework
with seven outgoing pathways, it was not the only dimension of multicultural personality
that had a direct effect on cultural self-efficacy. Although we did not find a direct effect of
flexibility which is at odds with literature [
42
], our results are largely in line with literature
as the present study shows direct effects regarding four out of five multicultural personality
traits on intercultural effectiveness [
21
,
74
,
75
]. Despite literature already features reports of
direct effects regarding all five traits, these reports are inconclusive in pinpointing a trait
of which the positive effect on intercultural effectiveness is consistent over situations. For
the time being, we therefore advise to refrain from extending the existing framework with
direct pathways from intercultural traits to intercultural effectiveness until more research
on the matter is presented.
Second, the present study also reported some partial evidence that an ethnorelative
world view is directly related to intercultural effectiveness through a larger understanding.
This finding seems plausible that a broader view on the world evokes greater understanding
of other cultures. The finding is also further supported by reports in literature of an
ethnocentric view that evokes less understanding [
76
,
77
]. However, we again evaluate the
existing evidence from literature and from the present study as insufficient to warrant an
extension of the existing framework until more research is presented. Still, we do advocate
testing the presence of direct pathways between (a) intercultural traits and effectiveness
and (b) intercultural world views and effectiveness in future studies, as specific samples
can always cause additional effects, above and beyond the current integrative framework.
Int. J. Environ. Res. Public Health 2022,19, 4490 16 of 21
Third and finally, analyses also revealed possible recursive pathways of self-efficacy
to intercultural capabilities. Although these pathways can prove a worthwhile addition to
the framework in the future, more theoretical and practical research needs to be conducted
before such framework adaptations are warranted. At the moment, we consider the
evidence too limited and too divergent (i.e., four possible pathways between cultural
intelligence subdimensions and four possible pathways from self-efficacy subdimensions
to cultural intelligence subdimensions) to suggest a specific recurrent pathway setup.
Summarizing our findings regarding the framework pathways, the main pathway
in the framework from traits to effectiveness leads from open mindedness and cultural
empathy (over an ethnorelative disposition) to cultural intelligence and ultimately to
cultural self-efficacy, affecting all five self-efficacy subdimensions. In this indirect pathway,
the motivation dimension of cultural intelligence is the first key node, as the node receives
three pathways and is also sending out four pathways toward cultural self-efficacy. The
second key node is the cognitive dimension of cultural intelligence, which receives only
one pathway, but is also sending out four pathways toward cultural self-efficacy. This
evidence confirms that knowledge and motivation form the prime gateway toward effective
intercultural behavior [41,42,58,74,75].
4.1. Implications for Practice
The empirical validation of the framework can have important consequences for inter-
ventions that want to increase the effectivity of individuals in intercultural health situations
by targeting specific components of intercultural competence. To obtain a basic under-
standing of an individual’s potential for intercultural effective behavior, a measurement of
multicultural personality can serve as a baseline at the start of an intervention or education
in health care. The specific results of the present study seem to suggest that researchers
and practitioners should focus on the traits of open mindedness and cultural empathy.
However, as traits are less suited for actual interventions that want to change behavior due
to their higher stability [
37
,
38
], we instead advise to focus on the key node of motivation
and cognition to a lesser extent for actual intervention. Indeed, both the present study and
literature already indicate that the relation between cultural intelligence (motivation and
cognition) and effective intercultural behavior is fairly strong as already stated. Moreover,
cultural intelligence is quite malleable, making for an excellent candidate to target directly
in future training, interventions, and identifying best practices, ultimately improving the
intercultural effectiveness of individuals [19,58].
As a practical example of a future intervention, health care education can start by
making students aware that motivated and educated practitioners will treat patients with
a different cultural background more fairly and more effectively. This awareness can
be complemented with a training that focuses on familiarizing students with important
cultural phenomena and learning them how to incorporate these phenomena in treatment
procedures. For instance, patients that adhere to the ways of Islam are not allowed to eat
from sunrise to sunset during Ramadan. As a consequence, such a matter of faith can
influence the diet of the patient during recovery. Health practitioners have to ensure that
such nutritional issues are (at the very least) the subject of dialogue between practitioners
and patients. In such a way, openminded responses to patient questions, supported
by practitioner motivation and knowledge, can go a long way in making therapy and
therapy outcomes during recovery more effective across patients with different cultural
backgrounds, thus ensuring more equity in health care.
4.2. Limitations and Future Research
First, the theoretical framework clearly fits our data quite well [
18
]. Despite the good
fit between the current empirical data and the proposed theoretical framework, we do
acknowledge that we cannot rule out the possibility of additional components. For instance,
patient/practitioner diversity is not limited to cultural aspects like ethnicity, but can also
include gender or generation variables like the Six G’s Approach [
91
]. However, such
Int. J. Environ. Res. Public Health 2022,19, 4490 17 of 21
an investigation into additional components is beyond the scope of the present study
as the present study primarily focused on exploring the component relations within the
framework. Second, the framework should be replicated using different conceptualizations,
measures, and population samples of future health care practitioners. Although we have
used specific conceptualizations of the core constructs, the present study does replicate
the internal structure of four independent conceptualizations and instruments, while also
providing empirical verification for the hypothesized framework relations. As such, we are
confident that our empirical verification can serve as a baseline for future research. Third,
our study makes use of a proxy of real world behavior. By using multidimensional cultural
self-efficacy, we were able to also pinpoint how the different components of intercultural
competence were related to intercultural self-efficacy. Future research should however
include real-time behavior work adjustment, early withdrawal from intercultural jobs,
the number of intercultural friends, inclusion policies on staff recruiting, an interest in
politics and (a lack of) contact, and cooperation in both immigrant and non-immigrant
students [
25
,
47
,
48
]. Fourth, the sample consisted of a sample of mostly future practitioners.
Although such a sample validates our results toward education and previews the nature of
health care practitioners in the near future, toward actual practice we do advocate some
caution, as the students are not yet (fully) active. Finally, the framework should also be
tested comparing different settings both inside and outside of health care. Although our
hypotheses on the main components were confirmed, a health care setting could have
different important (sub-) dimensions compared to housing or work settings. Barring the
evidence on the motivational dimension from both literature and the present study, we
therefore acknowledge that some (sub) dimensional pathways could shift depending on
the setting of future studies. Of course, subsequent practical interventions should also take
into account such shifted pathways. We therefore advise to always verify the framework as
a baseline for practical interventions. To conclude, given the results of the present study
regarding the construct validity and hypothesized relations of the components, we are
cautiously optimistic that the empirically verified integrative framework is a robust starting
point for future studies on intercultural competence and effectiveness.
5. Conclusions
In conclusion, the present study empirically verifies an integrative framework of
intercultural competence and effectiveness. Intercultural capabilities remain the major
gateway toward more effective intercultural behavior, with motivation and cognition acting
as the key nodes in the framework. These dimensions are thus an excellent target for
training, practical interventions, and identifying best practices, ultimately supporting
greater intercultural effectiveness and more equity in health care.
Supplementary Materials:
The following supporting information can be downloaded at: https:
//www.mdpi.com/article/10.3390/ijerph19084490/s1, File S1: variance-covariance matrix full.txt
for replication of the CFA analyses, File S2: variance-covariance matrix sub.txt for the replication of
the structural SEM analyses.
Author Contributions:
Conceptualization, S.S. and E.D.; data curation, S.S.; formal analysis, S.S.;
funding acquisition, S.W. and E.D.; investigation, S.S., R.V., S.D.M., F.D., S.W. and E.D.; methodology,
S.S.; project administration, S.S., F.D., S.W. and E.D.; resources, S.S., S.D.M., S.W. and E.D.; software,
S.S.; supervision, S.S., F.D., S.W. and E.D.; validation, S.S.; visualization, S.S.; writing—original draft,
S.S.; writing—review and editing, S.S., R.V., S.D.M., F.D., S.W. and E.D. All authors have read and
agreed to the published version of the manuscript.
Funding:
This research was funded by Research Foundation-Flanders grant number [Strategic Basic
Research–S004119N]. The sponsors had no role in the design, execution, interpretation, or writing of
the study.
Institutional Review Board Statement:
The study was conducted according to the guidelines of the
Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of
UZGent, in collaboration with Ghent University (BC-07577, 22 April 2020).
Int. J. Environ. Res. Public Health 2022,19, 4490 18 of 21
Informed Consent Statement:
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement:
The data that support the findings of this study are available on
request from the corresponding author S.S. The data are not publicly available due to them containing
information that could compromise research participant privacy/consent. However, the variance–
covariance matrices of the data is provided online in .txt format, allowing for full verification and
replication of the complete study.
Acknowledgments:
The authors would like to explicitly thank Laura Van Raemdonck for her assis-
tance in setting up the present study.
Conflicts of Interest: The authors declare no conflict of interest.
References
1.
Abdallah-Pretceille, M. Interculturalism as a Paradigm for Thinking about Diversity. Intercult. Educ.
2006
,17, 475–483. [CrossRef]
2.
Capell, J.; Dean, E.; Veenstra, G. The Relationship between Cultural Competence and Ethnocentrism of Health Care Professionals.
J. Transcult. Nurs. 2008,19, 121–125. [CrossRef] [PubMed]
3.
Egede-Nissen, V.; Sellevold, G.S.; Jakobsen, R.; Sørlie, V. Minority Healthcare Providers Experience Challenges, Trust, and
Interdependency in a Multicultural Team. Nurs. Ethics 2019,26, 1326–1336. [CrossRef] [PubMed]
4. Epner, D.E.; Baile, W.F. Patient-Centered Care: The Key to Cultural Competence. Ann. Oncol. 2012,23, iii33–iii42. [CrossRef]
5.
Schouten, B.C.; Meeuwesen, L. Cultural Differences in Medical Communication: A Review of the Literature. Patient Educ. Couns.
2006,64, 21–34. [CrossRef]
6. Culyer, A.J.; Wagstaff, A. Equity and Equality in Health and Health Care. J. Health Econ. 1993,12, 431–457. [CrossRef]
7.
Höglund, A.T.; Carlsson, M.; Holmström, I.K.; Lännerström, L.; Kaminsky, E. From Denial to Awareness: A Conceptual Model for
Obtaining Equity in Healthcare. Int. J. Equity Health 2018,17, 9. [CrossRef]
8. Starfield, B. Improving Equity in Health: A Research Agenda. Int. J. Health Serv. 2001,31, 545–566. [CrossRef]
9.
Andia, T.S.; Lamprea, E. Is the Judicialization of Health Care Bad for Equity? A Scoping Review. Int. J. Equity Health
2019
,18, 61.
[CrossRef]
10.
Lane, H.; Sarkies, M.; Martin, J.; Haines, T. Equity in Healthcare Resource Allocation Decision Making: A Systematic Review. Soc.
Sci. Med. 2017,175, 11–27. [CrossRef]
11.
Paluck, E.L.; Green, D.P. Prejudice Reduction: What Works? A Review and Assessment of Research and Practice. Annu. Rev.
Psychol. 2009,60, 339–367. [CrossRef] [PubMed]
12.
Price, E.G.; Beach, M.C.; Gary, T.L.; Robinson, K.A.; Gozu, A.; Palacio, A.; Smarth, C.; Jenckes, M.; Feuerstein, C.; Bass, E.B.; et al.
A Systematic Review of the Methodological Rigor of Studies Evaluating Cultural Competence Training of Health Professionals.
Acad. Med. 2005,80, 578–586. [CrossRef] [PubMed]
13.
Cabral, A.L.L.V.; Giatti, L.; Martínez-Hernáez, Á.; Cherchiglia, M.L. Inequality in Breast Cancer Care in a Brazilian Capital City:
A Comparative Analysis of Narratives. Int. J. Equity Health 2019,18, 88. [CrossRef] [PubMed]
14.
Dovidio, J.F.; Fiske, S.T. Under the Radar: How Unexamined Biases in Decision-Making Processes in Clinical Interactions Can
Contribute to Health Care Disparities. Am. J. Public Health 2012,102, 945–952. [CrossRef]
15.
Johnson-Askew, W.L.; Gordon, L.; Sockalingam, S. Practice Paper of the American Dietetic Association: Addressing Racial and
Ethnic Health Disparities. J. Am. Diet. Assoc. 2011,111, 446–456. [CrossRef]
16.
Çingöl, N.; Karaka¸s, M.; Çelebi, E.; Zengin, S. Determining the Effect of an Intercultural Nursing Course on Empathic Skill and
Intercultural Sensitivity Levels: An Intervention Study. Nurse Educ. Today 2021,99, 104782. [CrossRef]
17.
Raval, V.V.; Ovia, T.; Freeman, M.; Raj, S.P.; Daga, S.S. Discourses about Race in the United States: A Thematic Analysis of Short
Essays. Int. J. Intercult. Relat. 2021,83, 98–113. [CrossRef]
18. Leung, K.; Ang, S.; Tan, M.L. Intercultural Competence. Annu. Rev. Organ. Psychol. Organ. Behav. 2014,1, 489–519. [CrossRef]
19.
Brottman, M.R.; Char, D.M.; Hattori, R.A.; Heeb, R.; Taff, S.D. Toward Cultural Competency in Health Care. Acad. Med.
2020
,95,
803–813. [CrossRef]
20.
Dias, D.; Zhu, C.J.; Samaratunge, R. Examining the Role of Cultural Exposure in Improving Intercultural Competence: Implications
for HRM Practices in Multicultural Organizations. Int. J. Hum. Resour. Manag. 2020,31, 1359–1378. [CrossRef]
21. Herrera, C.J.; Owens, G.P. Multicultural Personality and Posttraumatic Stress in U.S. Service Members. J. Clin. Psychol. 2015,71,
323–333. [CrossRef] [PubMed]
22.
Van der Zee, K.I.; van Oudenhoven, J.P. The Multicultural Personality Questionnaire: A Multidimensional Instrument of
Multicultural Effectiveness. Eur. J. Personal. 2000,14, 291–309. [CrossRef]
23.
Den Dekker, W. Global Mindset and Cross-Cultural Behavior: Improving Leadership Effectiveness; MacMillan Publishers Ltd.: London,
UK, 2016.
24.
Gielen, J.; van den Branden, S.; Broeckaert, B. The Operationalisation of Religion and World View in Surveys of Nurses’ Attitudes
toward Euthanasia and Assisted Suicide. Med. Health Care Philos. 2009,12, 423–431. [CrossRef] [PubMed]
25.
Piekut, A. Survey Nonresponse in Attitudes towards Immigration in Europe. J. Ethn. Migr. Stud.
2021
,47, 1136–1161. [CrossRef]
Int. J. Environ. Res. Public Health 2022,19, 4490 19 of 21
26.
Manroop, L.; Boekhorst, J.A.; Harrison, J.A. The Influence of Cross-Cultural Differences on Job Interview Selection Decisions. Int.
J. Hum. Resour. Manag. 2013,24, 3512–3533. [CrossRef]
27.
Wang, C.; Shakespeare-Finch, J.; Dunne, M.P.; Hou, X.-Y.; Khawaja, N.G. How Much Can Our Universities Do in the Development
of Cultural Intelligence? A Cross-Sectional Study among Health Care Students. Nurse Educ. Today 2021,103, 104956. [CrossRef]
28.
Connor-Smith, J.K.; Flachsbart, C. Relations between Personality and Coping: A Meta-Analysis. J. Personal. Soc. Psychol.
2007
,93,
1080–1107. [CrossRef]
29.
Shaffer, M.A.; Harrison, D.A.; Gregersen, H.; Black, J.S.; Ferzandi, L.A. You Can Take It with You: Individual Differences and
Expatriate Effectiveness. J. Appl. Psychol. 2006,91, 109–125. [CrossRef]
30.
Van der Zee, K.I.; van Oudenhoven, J.P. The Multicultural Personality Questionnaire: Reliability and Validity of Self- and Other
Ratings of Multicultural Effectiveness. J. Res. Personal. 2001,35, 278–288. [CrossRef]
31.
Van der Zee, K.; van Oudenhoven, J.P. Culture Shock or Challenge? The Role of Personality as a Determinant of Intercultural
Competence. J. Cross-Cult. Psychol. 2013,44, 928–940. [CrossRef]
32.
Bakker, W.; van der Zee, K.; van Oudenhoven, J.P. Personality and Dutch Emigrants’ Reactions to Acculturation Strategies. J.
Appl. Soc. Psychol. 2006,36, 2864–2891. [CrossRef]
33.
Van Oudenhoven, J.P.; van der Zee, K.I. Predicting Multicultural Effectiveness of International Students: The Multicultural
Personality Questionnaire. Int. J. Intercult. Relat. 2002,26, 679–694. [CrossRef]
34.
Van Oudenhoven, J.P.; Mol, S.; van der Zee, K.I. Study of the Adjustment of Western Expatriates in Taiwan ROC with the
Multicultural Personality Questionnaire. Asian J. Soc. Psychol. 2003,6, 159–170. [CrossRef]
35.
Van der Zee, K.; van Oudenhoven, J.P.; Ponterotto, J.G.; Fietzer, A.W. Multicultural Personality Questionnaire: Development of a
Short Form. J. Personal. Assess. 2013,95, 118–124. [CrossRef]
36.
Summerfield, L.P.; Prado-Gascó, V.; Giménez-Espert, M.D.C.; Mesa-Gresa, P. The Multicultural Personality Questionnaire (SF-40):
Adaptation and Validation of the Spanish Version. Int. J. Environ. Res. Public Health 2021,18, 2426. [CrossRef]
37.
Hampson, S.E.; Goldberg, L.R. A First Large Cohort Study of Personality Trait Stability over the 40 Years between Elementary
School and Midlife. J. Personal. Soc. Psychol. 2006,91, 763–779. [CrossRef]
38.
Vaidya, J.G.; Gray, E.K.; Haig, J.R.; Mroczek, D.K.; Watson, D. Differential Stability and Individual Growth Trajectories of Big Five
and Affective Traits during Young Adulthood. J. Personal. 2008,76, 276–304. [CrossRef]
39.
Horverak, J.G.; Sandal, G.M.; Bye, H.H.; Pallesen, S. Managers’ Selection Preferences: The Role of Prejudice and Multicultural
Personality Traits in the Assessment of Native and Immigrant Job Candidates. Eur. Rev. Appl. Psychol.
2013
,63, 267–275.
[CrossRef]
40.
Nesdale, D.; de Vries Robbé, M.; van Oudenhoven, J.P. Intercultural Effectiveness, Authoritarianism, and Ethnic Prejudice. J. Appl.
Soc. Psychol. 2012,42, 1173–1191. [CrossRef]
41.
Ang, S.; van Dyne, L.; Koh, C. Personality Correlates of the Four-Factor Model of Cultural Intelligence. Group Organ. Manag.
2006,31, 100–123. [CrossRef]
42.
Ward, C.; Fischer, R. Personality, Cultural Intelligence, and Cross-Cultural Adaptation. In Handbook on Cultural Intelligence: Theory,
Measurement and Applications; Sharpe: New York, NY, USA, 2008; pp. 159–176.
43.
Michael Paige, R.; Jacobs-Cassuto, M.; Yershova, Y.A.; DeJaeghere, J. Assessing Intercultural Sensitivity: An Empirical Analysis of
the Hammer and Bennett Intercultural Development Inventory. Int. J. Intercult. Relat. 2003,27, 467–486. [CrossRef]
44.
Bennett, M.J. Developmental Model of Intercultural Sensitivity. In The International Encyclopedia of Intercultural Communication;
Wiley: Hoboken, NJ, USA, 2017.
45.
Bizumic, B.; Duckitt, J. What Is and Is Not Ethnocentrism? A Conceptual Analysis and Political Implications. Political Psychol.
2012,33, 887–909. [CrossRef]
46.
Kirillova, K.; Lehto, X.; Cai, L. Volunteer Tourism and Intercultural Sensitivity: The Role of Interaction with Host Communities. J.
Travel Tour. Mark. 2015,32, 382–400. [CrossRef]
47.
Hammer, M.R. The Developmental Paradigm for Intercultural Competence Research. Int. J. Intercult. Relat.
2015
,48, 12–13.
[CrossRef]
48.
Hammer, M.R. Additional Cross-Cultural Validity Testing of the Intercultural Development Inventory. Int. J. Intercult. Relat.
2011
,
35, 474–487. [CrossRef]
49.
Kaya, Y.; Arslan, S.; Erba¸s, A.; Ya¸sar, B.N.; Küçükkelepçe, G.E. The Effect of Ethnocentrism and Moral Sensitivity on Intercultural
Sensitivity in Nursing Students, Descriptive Cross-Sectional Research Study. Nurse Educ. Today 2021,100, 104867. [CrossRef]
50.
Ng, K.-Y.; van Dyne, L.; Ang, S. From Experience to Experiential Learning: Cultural Intelligence as a Learning Capability for
Global Leader Development. Acad. Manag. Learn. Educ. 2009,8, 511–526. [CrossRef]
51.
Young, C.A.; Haffejee, B.; Corsun, D.L. The Relationship between Ethnocentrism and Cultural Intelligence. Int. J. Intercult. Relat.
2017,58, 31–41. [CrossRef]
52. Early, P.; Ang, S. Cultural Intelligence: Individual Interactions across Cultures; Stanford University Press: Redwood, CA, USA, 2003.
53.
Herrmann, E.; Call, J.; Hernàndez-Lloreda, M.V.; Hare, B.; Tomasello, M. Humans Have Evolved Specialized Skills of Social
Cognition: The Cultural Intelligence Hypothesis. Science 2007,317, 1360–1366. [CrossRef]
54. Peterson, B. Cultural Intelligence: A Guide to Working with People from Other Cultures; Intercultural Press: London, UK, 2004.
55.
Andresen, M.; Bergdolt, F. A Systematic Literature Review on the Definitions of Global Mindset and Cultural Intelligence—
Merging Two Different Research Streams. Int. J. Hum. Resour. Manag. 2017,28, 170–195. [CrossRef]
Int. J. Environ. Res. Public Health 2022,19, 4490 20 of 21
56.
Schwarzenthal, M.; Juang, L.P.; Schachner, M.K.; van de Vijver, F.J.R. A Multimodal Measure of Cultural Intelligence for
Adolescents Growing up in Culturally Diverse Societies. Int. J. Intercult. Relat. 2019,72, 109–121. [CrossRef]
57.
Van Dyne, L.; Ang, S.; Ng, K.Y.; Rockstuhl, T.; Tan, M.L.; Koh, C. Sub-Dimensions of the Four Factor Model of Cultural Intelligence:
Expanding the Conceptualization and Measurement of Cultural Intelligence. Soc. Personal. Psychol. Compass
2012
,6, 295–313.
[CrossRef]
58.
Chen, X.; Gabrenya, W.K. In Search of Cross-Cultural Competence: A Comprehensive Review of Five Measurement Instruments.
Int. J. Intercult. Relat. 2021,82, 37–55. [CrossRef]
59.
Schwarzenthal, M.; Schachner, M.K.; Juang, L.P.; van de Vijver, F.J.R. Reaping the Benefits of Cultural Diversity: Classroom
Cultural Diversity Climate and Students’ Intercultural Competence. Eur. J. Soc. Psychol. 2020,50, 323–446. [CrossRef]
60.
Harrison, R.; Walton, M.; Chauhan, A.; Manias, E.; Chitkara, U.; Latanik, M.; Leone, D. What Is the Role of Cultural Competence
in Ethnic Minority Consumer Engagement? An Analysis in Community Healthcare. Int. J. Equity Health
2019
,18, 191. [CrossRef]
[PubMed]
61.
Fang, F.; Schei, V.; Selart, M. Hype or Hope? A New Look at the Research on Cultural Intelligence. Int. J. Intercult. Relat.
2018
,66,
148–171. [CrossRef]
62. Bandura, A. Social Cognitive Theory: An Agentic Perspective. Annu. Rev. Psychol. 2001,52, 1–26. [CrossRef] [PubMed]
63. Bandura, A. Social Cognitive Theory of Self-Regulation. Organ. Behav. Hum. Decis. Processes 1991,50, 248–287. [CrossRef]
64.
Talsma, K.; Schüz, B.; Schwarzer, R.; Norris, K. I Believe, Therefore I Achieve (and Vice Versa): A Meta-Analytic Cross-Lagged
Panel Analysis of Self-Efficacy and Academic Performance. Learn. Individ. Differ. 2018,61, 136–150. [CrossRef]
65.
Zimmermann, J.; Greischel, H.; Jonkmann, K. The Development of Multicultural Effectiveness in International Student Mobility.
High. Educ. 2020,82, 171–192. [CrossRef]
66.
Armitage, C.J.; Conner, M. Efficacy of the Theory of Planned Behaviour: A Meta-Analytic Review. Br. J. Soc. Psychol.
2001
,40,
471–499. [CrossRef] [PubMed]
67.
Earley, P.C.; Peterson, R.S. The Elusive Cultural Chameleon: Cultural Intelligence as a New Approach to Intercultural Training for
the Global Manager. Acad. Manag. Learn. Educ. 2004,3, 100–115. [CrossRef]
68.
MacNab, B.R.; Worthley, R. Individual Characteristics as Predictors of Cultural Intelligence Development: The Relevance of
Self-Efficacy. Int. J. Intercult. Relat. 2012,36, 62–71. [CrossRef]
69.
Quine, A.; Hadjistavropoulos, H.D.; Alberts, N.M. Cultural Self-Efficacy of Canadian Nursing Students Caring for Aboriginal
Patients with Diabetes. J. Transcult. Nurs. 2012,23, 306–312. [CrossRef] [PubMed]
70.
Briones, E.; Tabernero, C.; Tramontano, C.; Caprara, G.V.; Arenas, A. Development of a Cultural Self-Efficacy Scale for Adolescents
(CSES-A). Int. J. Intercult. Relat. 2009,33, 301–312. [CrossRef]
71.
Berhanu, R.D.; Tesema, A.A.; Deme, M.B.; Kanfe, S.G. Perceived Transcultural Self-Efficacy and Its Associated Factors among
Nurses in Ethiopia: A Cross-Sectional Study. PLoS ONE 2021,16, e0254643. [CrossRef]
72.
Capone, V.; Petrillo, G. Patient’s Communication Perceived Self-Efficacy Scale (PCSS): Construction and Validation of a New
Measure in a Socio-Cognitive Perspective. Patient Educ. Couns. 2014,95, 340–347. [CrossRef]
73.
Tam, C.C.; Li, X.; Benotsch, E.G.; Lin, D. A Resilience-Based Intervention Programme to Enhance Psychological Well-Being and
Protective Factors for Rural-to-Urban Migrant Children in China. Appl. Psychol. Health Well-Being 2020,12, 53–76. [CrossRef]
74.
Oolders, T.; Chernyshenko, O.S.; Stark, S. Cultural Intelligence as a Mediator of Relationships between Openness to Experience
and Adaptive Performance. In Handbook on Cultural Intelligence: Theory, Measurement and Applications; Psychology Faculty
Publications: London, UK; New York, NY, USA, 2008; pp. 145–158.
75.
Ramalu, S.S.; Shamsudin, F. Mohd.; Subramania, C. The Mediating Effect of Cultural Intelligence on the Relationship between
Openness Personality and Job Performance among Expatriates on International Assignments. Int. Bus. Manag. 2012,6, 601–610.
[CrossRef]
76.
Greipp, M.E. Culture, Age and Gender: Effects on Quality of Predicted Self and Colleague Reactions. Int. J. Nurs. Stud.
1996
,33,
83–97. [CrossRef]
77.
Logan, S.; Steel, Z.; Hunt, C. Intercultural Willingness to Communicate within Health Services: Investigating Anxiety, Uncertainty,
Ethnocentrism and Help Seeking Behaviour. Int. J. Intercult. Relat. 2016,54, 77–86. [CrossRef]
78. Academic Ranking of World Universities. Available online: https://www.shanghairanking.com/ (accessed on 30 December 2021).
79.
The Labor Market from a Gender Point of View. Available online: https://statbel.fgov.be/nl/visuals/arbeid-en-gender (accessed
on 30 December 2021).
80.
Living Together in Diversity. Available online: http://www.samenleven-in-diversiteit.vlaanderen.be/ (accessed on 30 December 2021).
81.
European Social Survey 2002/2003: Technical Report. Available online: http://www.europeansocialsurvey.org (accessed on
16 June 2020).
82. Rosseel, Y. Lavaan: An RPackage for Structural Equation Modeling. J. Stat. Softw. 2012,48, 1–36. [CrossRef]
83.
R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria,
2020; Available online: http://www.r-project.org/ (accessed on 30 December 2021).
84. The Lavaan Project. Available online: https://lavaan.ugent.be/ (accessed on 30 December 2021).
85.
Ullman, J.B.; Bentler, P.M. Structural Equation Modeling. In Handbook of Psychology, 2nd ed.; John Wiley & Sons, Inc.: Hoboken,
NJ, USA, 2012.
Int. J. Environ. Res. Public Health 2022,19, 4490 21 of 21
86.
Schreiber, J.B.; Nora, A.; Stage, F.K.; Barlow, E.A.; King, J. Reporting Structural Equation Modeling and Confirmatory Factor
Analysis Results: A Review. J. Educ. Res. 2006,99, 323–338. [CrossRef]
87.
Hu, L.; Bentler, P.M. Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria versus New
Alternatives. Struct. Equ. Modeling Multidiscip. J. 1999,6, 1–55. [CrossRef]
88.
Kenny, D.A.; Kaniskan, B.; Mccoach, D.B. The Performance of RMSEA in Models with Small Degrees of Freedom. Sociol. Methods
Res. 2015,44, 486–507. [CrossRef]
89. Kline, R.B. Principles and Practice of Structural Equation Modeling; The Guilford Press: New York, NY, USA, 2016.
90. Measuring Model Fit. Available online: http://www.davidakenny.net/cm/fit.htm (accessed on 30 December 2021).
91.
Gumber, A.; Gumber, L. Improving Prevention, Monitoring and Management of Diabetes among Ethnic Minorities: Contextualiz-
ing the Six G’s Approach. BMC Res. Notes 2017,10, 774. [CrossRef] [PubMed]