The Nature of Islamophobia: A Test of a Tripartite View in Five Countries

Abstract

This article provides an examination of the structure of Islamophobia across cultures. Our novel measure—the Tripartite Islamophobia Scale (TIS)—embeds three theoretically and statistically grounded subcomponents of Islamophobia: anti-Muslim prejudice, anti-Islamic sentiment, and conspiracy beliefs. Across six samples (i.e., India, Poland, Germany, France, and the United States), preregistered analyses corroborated that these three subcomponents are statistically distinct. Measurement invariance analyses indicated full scalar invariance, suggesting that the tripartite understanding of Islamophobia is generalizable across cultural contexts. Furthermore, the subcomponents were partially dissociated in terms of the intergroup emotions they are predicted by as well as the intergroup outcomes they predict (e.g., dehumanization, ethnic persecution). For example, intergroup anger and disgust underpin Islamophobic attitudes, over and above the impact of fear. Finally, our results show that social dominance orientation (SDO) and ingroup identification moderate intergroup emotions and Islamophobia. We address both theoretical implications for the nature of Islamophobia and practical interventions to reduce it.

Full text

Empirical Research Paper
The Nature of Islamophobia: A Test
of a Tripartite View in Five Countries
Fatih Uenal
1,2
, Robin Bergh
1
, Jim Sidanius
1
, Andreas Zick
3
,
Sasha Kimel
4
, and Jonas R. Kunst
5
Abstract
This article provides an examination of the structure of Islamophobia across cultures. Our novel measure—the Tripartite
Islamophobia Scale (TIS)—embeds three theoretically and statistically grounded subcomponents of Islamophobia: anti-Muslim
prejudice, anti-Islamic sentiment, and conspiracy beliefs. Across six samples (i.e., India, Poland, Germany, France, and the
United States), preregistered analyses corroborated that these three subcomponents are statistically distinct. Measurement
invariance analyses indicated full scalar invariance, suggesting that the tripartite understanding of Islamophobia is generalizable
across cultural contexts. Furthermore, the subcomponents were partially dissociated in terms of the intergroup emotions they
are predicted by as well as the intergroup outcomes they predict (e.g., dehumanization, ethnic persecution). For example,
intergroup anger and disgust underpin Islamophobic attitudes, over and above the impact of fear. Finally, our results show that
social dominance orientation (SDO) and ingroup identification moderate intergroup emotions and Islamophobia. We address
both theoretical implications for the nature of Islamophobia and practical interventions to reduce it.
Keywords
fear, anger, disgust, islamophobia, measurement-invariance
Received October 9, 2019; revision accepted April 8, 2020
A growing number of people in the West view Islam and
Muslims negatively (e.g., Gallup, 2013). According to a
recent survey, 55%of Europe’s population agreed that
migration from predominantly Muslim countries should be
stopped (Goodwin et al., 2017). Similarly, Muslims are the
least favorably viewed, and most dehumanized, religious
group in the United States (Kteily et al., 2015; Pew Research
Center [PEW], 2017a), with outcomes ranging from institu-
tional discrimination (e.g., “Muslim Ban”) to hate crimes
(e.g., Elahi & Khan, 2017). In many parts of the world,
Muslims also face arbitrary detention, forced sterilization,
torture, and ethno-religious “cleansing” (Human Rights
Watch [HRW], 2018; United Nations [UN], 2018).
Yet, despite the prevalence of Islamophobia—commonly
used to refer to negative attitudes, emotions, and behaviors
toward the Islamic religion and Muslims—no agreed-upon
operationalization of the term exists (e.g., Bleich, 2011; Hel-
bling, 2012; Klug, 2012; Uenal, 2016a). This absence is
reflected in researchers’ use of disparate items and scales
(e.g., Imhoff & Recker, 2012; Lee et al., 2013). Moreover,
to the best of our knowledge, these measurement approaches
have not been validated cross-culturally. Crucially, due to
this dearth of cross-cultural validation, the extent to which
Islamophobia’s dimensionality is generalizable across
contexts remains unknown (Bleich, 2011; Ku
¨ntzl, 2008;
Uenal, 2016a; but see Kunst et al., 2013 for perceived Isla-
mophobia). Furthermore, Islamophobia’s underlying emo-
tional origins, psychological mechanisms, and its
consequences remain understudied (e.g., Choma et al.,
2012, 2016; Uenal, 2016a, 2016b, 2017c).
In this paper, we propose, and cross-culturally validate, a
tripartite view of Islamophobia, which differentiates between
psychologically distinct components. Importantly, we also
address a current debate over whether Islamophobia is pri-
marily fear-based or, instead, whether it is better explained
as socio-functional threat-based psychological reactions of
anger and/or disgust to a social group, in addition to fear
(e.g., Ketelaar, 2015; Neuberg & Schaller, 2016; Park
1
Harvard University, Cambridge, MA, USA
2
University of Cambridge, UK
3
Bielefeld University, Germany
4
California State University San Marcos, USA
5
University of Oslo, Norway
Corresponding Author:
Fatih Uenal, Department of Psychology, University of Cambridge,
Old Cavendish Building, Free School Lane, Cambridge CB2 3RQ, UK.
Email: fu212@cam.ac.uk
Personality and Social
Psychology Bulletin
1-18
ª2020 by the Society for Personality
and Social Psychology, Inc
Article reuse guidelines:
sagepub.com/journals-permissions
DOI: 10.1177/0146167220922643
journals.sagepub.com/home/pspb

et al., 2007; Plutchik, 1980). Finally, we test two individual
difference variables (social dominance orientation [SDO]
and ingroup identification), which might explain why some
individuals react with fear while others display anger and/or
disgust in response to Islam and Muslims (e.g., Choma et al.,
2016; Matthews & Levin, 2012). Thus, this paper aims to
advance research on the nature of Islamophobia by addres-
sing persistent theoretical and methodological issues
including Islamophobia’s conceptualization, measurement,
cross-cultural validity, emotional origins, and societal
consequences.
What Constitutes Islamophobia?
Most commonly, Islamophobia is defined as negative, fear-
based attitudes and behaviors toward Islam and its adher-
ents—Muslims (e.g., Bangstad, 2016; Bleich, 2011;
Conway, 1997; Halliday, 1999; Klug, 2012). Accordingly,
prominent measures of Islamophobia conflate items pertain-
ing to both Islam (religious concept) and Muslims (social
group; e.g., Helbling, 2012; Imhoff & Recker, 2012; Lee
et al., 2013). Yet, we argue that this comes with several
interrelated caveats.
Conflating Individuals and Concepts: Theoretical
and Methodological Concerns
In the social psychological literature, stereotyping, prejudice,
and discrimination primarily refer to biases toward individ-
uals based on their membership in a group and not toward the
cultures, religions, institutions, or ideologies that individuals
are a part of (e.g., Allport, 1954; Brown, 2010). In other
words, traditional bias measures assess attitudes toward
members of social groups (e.g., Jews, Atheists), not the
abstract concept the group is adhering to (e.g., Judaism,
Atheism). Importantly, research suggests that individuals are
evaluated more positively than their larger impersonal repre-
sentations (sometimes referred to as a person-positivity bias;
e.g., Sears, 1983). For example, political party leaders (indi-
viduals) are more positively evaluated than the political insti-
tution they are part of (i.e., Nilsson & Ekehammar, 1987).
Indeed, previous research indicates that Muslims are more
positively evaluated than their less personal representations
(e.g., Islam; Leibold & Ku
¨hnel, 2006). However, whereas
modern measures of negativity toward Jews and Judaism
differentiate between evaluation of its members (anti-Semit-
ism) and its religion (anti-Judaism); Bilewicz et al., 2013;
Bilewicz & Krzeminski, 2010), measures of Islamophobia
do not.
Although it may seem reasonable to assume that individ-
uals holding negative sentiments toward the Islamic religion
are likely to also be biased against Muslims (Klug, 2012;
Miles & Brown, 2003), this relationship remains understu-
died (Uenal, 2016a). Furthermore, the conflation between
Muslims and Islam has also triggered a heated debate about
the comparability of Islamophobia with other types of pre-
judices like anti-Semitism (e.g., Bangstad, 2016; Bleich,
2011; Ku
¨ntzl, 2008). To address this, here, we explicitly
examine both attitudes about Muslims (individuals) and
Islam (religious concept). We expect them to be statically
distinguishable.
A Secret Islamization of the West: Integrating
Islamophobic Conspiracy Beliefs
Another key component of Islamophobia—Islamophobic
conspiracy beliefs—also remains understudied and has not
yet been integrated into current conceptualizations and mea-
surements (O’Donnell, 2018; Swami et al., 2018; Uenal,
2016c). The belief in an Islamic conspiracy or a secret and
ongoing “Islamization of the Western world” (e.g., Hafez,
2013) shows resemblance to anti-Semitic narratives (e.g.,
Zia-Ebrahimi, 2018) and is propelled by the idea of a demo-
graphic threat (e.g., Schiffer & Wagner, 2011). Some believ-
ers claim that there is a well-orchestrated campaign (e.g.,
“EURABIA”) to impose Islamic practices on the West. Such
beliefs can have highly consequential outcomes. Indeed, they
inspired the Norwegian terrorist, Anders Behring Breivik, to
kill 77 people (Fekete, 2012; Uenal, 2016b).
Belief in conspiracies has been shown to be distinct from
stereotypes or prejudices (Abalakina-Paap et al., 1999; Mos-
covici, 1987). They are also uniquely associated with nega-
tive psychological and behavioral outcomes (Bilewicz &
Krzeminski, 2010), including political violence (Bartlett &
Miller, 2010), and they show strong associations with anxi-
ety, uncertainty, and a perceived lack of control (e.g., van
Prooijen & Douglas, 2018; Whitson & Galinsky, 2008).
Notably, in the context of anti-Semitism, Bilewicz and col-
leagues (2013) showed that conspiracy beliefs predicted dis-
criminatory behavioral intentions, above and beyond
prejudice alone. Based on this, we expect conspiracy beliefs
to be statistically distinct from anti-Muslim prejudice and
anti-Islam sentiment, to uniquely predict discriminatory atti-
tudes and behaviors, and to be primarily associated with
intergroup fear.
Emotional Underpinnings of Islamophobia: Who Is
Afraid of Islam?
Another understudied issue regards Islamophobia’s emo-
tional underpinning. Closely resembling concepts like
Homophobia and Xenophobia, Islamophobia has been con-
ceptualized from a standard social psychological research
perspective, which puts fear and uncertainty about outgroups
at the heart of the prejudiced mindset (e.g., Adorno et al.,
1950; Duckitt, 2001; Jost et al., 2003; Wilson, 1973). This
fear-primacy axiom is derived from research on the author-
itarian character and the conservative mind more generally,
which posits that political conservatism is embraced as an
ideology because of its fear, anxiety, and uncertainty
2Personality and Social Psychology Bulletin XX(X)

reducing qualities (Jost et al., 2003; Sibley & Duckitt, 2008).
Indeed, the most frequently cited psychological definitions
of Islamophobia hypothesize that fear is its main affective
component (e.g., Conway, 1997; Lee et al., 2013). Yet,
despite these claims, the role of fear in Islamophobia has not
been systematically explored.
A socio-functional threat-based perspective on prejudice
argues that different social groups can elicit different social
threat perceptions, which in turn motivate specific attitudi-
nal, emotional, and behavioral reactions to effectively miti-
gate perceived threats (e.g., Neuberg & Schaller, 2016; Park
et al., 2007). For instance, Choma and colleagues (2012,
2016) have shown that intergroup disgust sensitivity is a
robust predictor of Islamophobia. Given this, a socio-
functional perspective may be better suited to understanding
Islamophobia than focusing on fear alone. However, no pre-
vious studies have systematically analyzed multiple negative
emotions (i.e., fear, disgust, and anger) concurrently and,
thus, the emotional bases of Islamophobia and its subdimen-
sions remain unclear.
Fear, Anger, and Disgust: The Potential Moderating
Role of SDO and Ingroup Identification
A further understudied question is whether individual differ-
ences modulate the emotional reactions underlying Islamo-
phobia (e.g., Choma et al., 2016; Matthews & Levin, 2012).
Previous research has shown that group-based emotions can
toggle between fear, anger, and/or disgust depending on a
variety of other factors, including individual differences (for
an overview see, Mackie & Smith, 2015) such as ingroup
identification (e.g., Mackie et al., 2000) and SDO (Pratto
et al., 1994). In many Western countries, Muslims and Islam
are highly salient categories, frequently associated with neg-
ative connotations such as ideological/value conflicts, terror-
ism, as well as with realistic threats (e.g., to countries’
welfare systems; Bleich, 2011; Uenal, 2016a). Thus, individ-
uals highly identified with their ingroup and/or high in SDO
may be more likely to perceive Muslims and Islam as threa-
tening, albeit accompanied with differing emotional
reactions.
A significant body of research shows that negative out-
group affect is robustly predicted by SDO across various
intergroup contexts (e.g., Sidanius et al., 2017). Individuals
high in SDO are concerned with the maintenance of social
hierarchies in general and are especially averse to low-status
groups (e.g., Levin & Sidanius, 1999; Sibley & Duckitt,
2008). Importantly, some studies indicate that individuals
high in SDO react with more anger and disgust, rather than
fear, toward subordinate outgroups (e.g., Kossowska et al.,
2008; Matthews & Levin, 2012) that are perceived to threa-
ten the existing hierarchical order (Thomsen et al., 2008).
More specifically, for individuals high in SDO, when Mus-
lims and Islam are perceived as threatening, anger and dis-
gust should be amplified to reinforce boundaries and
preserve the hierarchical arrangement of society since these
emotions are associated with behavioral tendencies which
help facilitate actions to mitigate potential threats through
aggressive means. Thus, anger and disgust are more reflec-
tive of a high SDO mindset toward threatening outgroups
(e.g., Matthews & Levin, 2012; Sibley & Duckitt, 2008)
while, for individuals low in SDO, given their more egalitar-
ian worldview, the effects of existing anger and disgust
should be buffered.
Another such variable that might explain individual dif-
ferences in emotional reactions toward ethno-religious mino-
rities is ingroup identification. Individuals who are highly
identified with their ingroup tend to be more concerned
about the well-being and distinctiveness of their own group
and, in turn, more sensitive to ethnic/religious minority
groups as potential threats (e.g., Riek et al., 2006) and more
likely to react with negative intergroup affect (e.g., Mackie
et al., 2000). The relationship between ingroup identification
and specific emotional reactions seems less clear-cut than
with SDO and has been shown to vary in conjunction with
further variables such as perceived collective support
(Dumont et al., 2003; Mackie et al., 2000). Thus, the specific
affective response might vary independently of the strength
of identification. Importantly, however, ingroup identifica-
tion has been primarily linked to increased ingroup prefer-
ence and love rather than outgroup derogation and
aggression per se (Brewer, 1999; Levin & Sidanius, 1999).
Thus, Muslims and Islam might trigger protective strategies
to increase feelings of ingroup distinctiveness and facilitate
ingroup solidarity. Against this background, it seems reason-
able to assume that high ingroup identification might primar-
ily moderate feelings of fear and disgust toward Islam and
Muslims, such that higher fear and disgust might interact
with higher ingroup identification as a means to signal
ingroup distinctiveness and solidarity via outgroup deroga-
tion while, for individuals with low ingroup identification we
expect that group-based fear and disgust might be less salient
due to low group-based concern.
Overview of Studies
We had three main goals, which we tested across two studies,
the first of which included five separate samples. First, to the
best of our knowledge, there are no cross-national tests of the
structure of Islamophobia. Thus, our first goal was to fill this
research gap by cross-culturally validating our novel Islamo-
phobia measure across five different contexts (i.e., United
States, India, Germany, France, Poland). These five contexts
were selected because they differ in characteristics such as
culture, level of economic prosperity, relative size of Muslim
population, history of conflict, and levels of immigration—
all factors that may contribute to different understandings
(i.e., measurement structures) of Islamophobia. Here, partic-
ularly analytic attention was given to testing the cross-
cultural equivalence (or measurement invariance [MI]) of
Uenal et al. 3

the scale or “whether or not, under different conditions of
observing and studying phenomena, measurement operations
yield measures of the same attribute” (Horn & McArdle,
1992, p. 117). Next, despite assumptions about fear in par-
ticular underlying Islamophobia, to our knowledge, this has
also not been directly investigated. Thus, our second goal
was to test the relationship of our measure with the inter-
group emotions of fear, anger, and disgust. Given the cross-
cultural nature of the present research, we were able to test
whether the same emotions underpin Islamophobia across
cultures.
In Study 2, we aimed to further investigate the relation-
ship between intergroup emotions and Islamophobia by ana-
lyzing the role of two individual difference variables as
potential moderators of this relationship in the United States.
We also aimed to further gauge the scale’s psychometric
qualities by testing its incremental validity. Here, we pre-
dicted that the Tripartite Islamophobia Scale (TIS) would
predict negative intergroup outcomes such as dehumaniza-
tion and ethnic persecution above and beyond well-
established predictors. Furthermore, based on insights gained
from research on anti-Semitism (e.g., Bilewicz & Krze-
minski, 2010), we expected that the subcomponents of
anti-Muslim prejudice and conspiracy belief would predict
our criterion variables over and above anti-Islam sentiment.
For each study, the required sample sizes were calculated
via power analyses (G*Power, Faul et al., 2009) for each
statistical analysis individually to meet an 80%chance to
observe a small to medium effect (f
2
¼.04 to f
2
¼.05).
Detailed power analyses calculations for each statistical
analysis are included in SOM (S1). All measures, conditions,
quality checks, and data exclusions are reported in the
respective method sections and in the SOM (see Supplemen-
tal Tables S1–S4).
Study 1
Methods
Participants. The present study was preregistered (see http://
aspredicted.org/blind.php?x¼6sk9gm). We aimed to collect
300 participants in each country (for power analyses, see S1
in SOM). In the United States (n¼295) and India (n¼293),
thedatawerecollectedviaAmazonMTurk.InGermany
(n¼293), Poland (n¼297), and France (n¼288), the data
were collected via the online participant recruitment service
PROLIFIC. All samples were drawn between March and
April 2019. The sample was 44.9%female and the average
age was 36.4 (SD ¼12.24). Detailed descriptive statistics for
each country are provided in the SOM (Supplemental Tables
S1–S5).
Instruments
TIS. Based on a preliminary study (Uenal, 2016c) and a
review of existing academic and non-academic literature, 25
items were adapted and/or developed to measure the three
proposed subcomponents of Islamophobia. This item selec-
tion was subsequently presented and discussed in various
research labs in the United States, Germany, Austria, Poland,
and France and with leading academic researchers in Isla-
mophobia studies. This led to making further adjustments
and selecting 15 items in total. The final items were trans-
lated into English, Polish, and French from German and
back-translated by native speakers and/or professional trans-
lators (see Tables S14–S15 SOM for all translations). As
discussed in the “Introduction,” the TIS was designed to
capture three distinct aspects of beliefs and attitudes about
Muslims and Islam (see Table S3 SOM). Cronbach’s alphas
were satisfactory for each country and are listed in the SOM
(see Table S4). Anti-Muslim prejudice (average a¼.91),
anti-Islam sentiment (average a¼.91) Islamophobic con-
spiracy beliefs (average a¼.95), and TIS aggregated scale
(average a¼.93), were each measured with five items (see
Figure 1). These items were measured on a five-point scale
ranging from 1 (definitively false)to5(definitively true). In
addition to the scale, participants completed the following
measures assessed on 5-point scales ranging from 1 (strongly
disagree)to5(strongly agree), unless otherwise noted.
Intergroup emotions. The intergroup emotions of fear,
anger, and disgust were assessed with four items each framed
toward Muslims and four corresponding items framed
toward Islam (e.g., “I feel fearful when I think about Mus-
lims [Islam],” “I feel repelled when I think about Muslims
[Islam],” “I feel angry when I think about Muslims [Islam]”;
Mackie et al., 2000). Due to length considerations, for the
main analysis, we computed three variables, representing
Fear of Muslims and Islam (average a¼.97), Anger toward
Islam and Muslims (average a¼.97), and Disgust toward
Islam and Muslims (average a¼.97). Additional analyses
analyzing each emotion relating either to Islam or Muslims
individually, showed no overall differences and are provided
in the SOM (for correlation analysis see Table S5; for regres-
sion analyses see Tables S6–S7).
Analysis of data. We first ran confirmatory factor analyses
(CFA) in each country to test the proposed tripartite factor
structure of Islamophobia. To this end, we tested if a three-
factor model would fit the data better than a one-factor
model, or theoretically justifiable two-factor models, in each
analyzed country individually as well as in the overall sam-
ple. Next, we conducted multigroup MI analysis to test
whether the proposed TIS showed cross-cultural equiva-
lence. We then proceeded with the analysis of the emotional
underpinnings of Islamophobia. We tested whether fear,
anger, or disgust would be most predictive of our scale, by
running multiple regression analyses and relative weights
analysis (Tonidandel & LeBreton, 2015).
4Personality and Social Psychology Bulletin XX(X)

Results
Descriptive statistics. Table 1 shows the mean scores, standard
deviations, and intercorrelations among the intergroup emo-
tion variables and the Islamophobia subscales for the overall
aggregate sample.
Factorial structure and measurement equivalence
Confirmatory factor analysis. All CFAs were calculated
using lavaan version 0.5–23 in R (Rosseel, 2012). A test
of normality of the latent variables indicated a non-normal
distribution. We, therefore, employed the Satorra–Bentler
rescaling method for CFA estimation, as suggested by Ros-
seel (2012).
For the overall aggregate sample, the results revealed that
the proposed three-factor solution yielded good fit to the
data, w
2
/df ¼5.16; CFI ¼.98; TLI ¼.98; SRMR ¼.029;
RMSEA ¼.045 with 90%CI ¼[.041, .050]; and AIC ¼
54,336.215, and indeed better than a one-factor, w
2
/df ¼
18.85; CFI ¼.93; TLI ¼.91; SRMR ¼.48; RMSEA ¼.096
Figure 1. The three-factor measurement model of the Tripartite Islamophobia Scale.
Note. The numbers are standardized factor loadings as estimated in a configural model with no constraints. The model w
2
of 719.837 indicates
a lack of an absolute fit (p< .001), which is not uncommon for larger sample sizes (N¼1,466). However, all the other fit measures indicate
that the model has a good model fit: w
2
/df ¼5.16; CFI ¼.98; TLI ¼.98; SRMR ¼.029; and RMSEA ¼.045 with 90% CI ¼[.041, .050]. CFI ¼
comparative fit index; TLI ¼Tucker–Lewis index; SRMR ¼Standardized Root Mean Squared Error; RMSEA ¼root mean square error of
approximation; CI ¼confidence interval.
Uenal et al. 5

with 90%CI ¼[.092, .100]; and AIC ¼55,509.398, and all
possible two-factor solutions (see SOM Table S9). Next, the
three-factor model also yielded better results for each country
individually (see Tables S8–S9 in the SOM). Figure 1 depicts
the results of a CFA with the confirmed three-factor structure
for the overall aggregate sample.
MI analysis. Next, we tested whether our Islamophobia mea-
sure was cross-culturally equivalent by examining MI across
the five samples. The primary objective was to ensure that the
measurement models conducted under different conditions
(geography, population, culture) yielded equivalent represen-
tations of the same construct (Jo¨reskog, 1971). The process of
establishing MI includes six stages of analysis in total, of
which only the first three steps are reported here due to space
limitations (Steenkamp & Baumgartner, 1998). For further
details on additional analysis (i.e., bi-factor model, second-
order model), see caption of Table 2. By assessing whether
factor loadings, intercepts, and residual variances are equiva-
lent in a multigroup factor model (i.e., testing whether we
measure the same underlying construct across the different
contexts), we aimed to assure that comparisons that are made
on our Islamophobia measure are valid across groups. If the
first three levels of invariance—configural (same factor struc-
ture), metric (same factor loadings), and scalar (same intercept
loadings)—across groups are met, comparison of the construct
and item means across countries are justified. For comparison
of effects, however, only the first two levels of invariance are
required. Following Steenkamp and Baumgartner (1998), we
adopted a “bottom-up” test strategy.
Chi-squared difference tests are generally recommended
to test for MI by comparing nested models. However, the
chi-squared difference test is influenced by sample size,
almost always being significant in large samples (Chen,
2007). Therefore, we adopted a change in CFI between
nested models of 0.010inadditiontoachangeinthe
RMSEA of 0.015 or a change in SRMR of 0.030 (for
loading invariance) and 0.010 (for intercept invariance) as
an appropriate criterion indicating a significant decrement in
fit between models following Chen (2007). However, Chen
(2007) suggested primarily using the change in CFI among
the three indices for nested model comparisons as the other
two are also affected by sample size.
Table 2 shows the results of a multigroup confirmatory
factor analysis (MGCFA). The relative differences in CFI and
RMSEA between the three models were below the required
threshold of CFI
difference
0.010 and RMSEA
difference
0.015
(i.e., suggesting that they have equivalent fit to the data),
indicating configural invariance, full metric invariance, and
full scalar invariance. As a result, group comparison can be
made on valid grounds.
Emotional underpinnings of Islamophobia. Having established
cross-cultural equivalence at the metric level, the data further
enabled us to test whether our Islamophobia measure is pri-
marily associated with intergroup fear—as proposed by the
most commonly referenced definitions (e.g., Conway, 1997;
Lee et al., 2013)—or also by the intergroup emotions anger
and/or disgust, as implicated by a socio-functional
Table 2. Multiple-Group Confirmatory Factor Analysis: Fit Measures and Differences of the Invariance Analysis.
Model w
2
(df)Dw
2
CFI DCFI RMSEA DRMSEA SRMR DSRMR
Configural invariance 909.198(410) — .980 — 0.051 — 0.036 —
Full metric invariance 989.972(458) 80.77*** .977 0.003 0.051 0.000 0.054 0.018
Full scalar invariance 1171.276(506) 144.20*** .970 0.010 0.056 0.005 0.058 0.022
Note. In addition, we also tested an alternative approach to the first-order factor measurement invariance analysis by also testing a second-order measurement
invariance analysis and a bifactor model of our scale as comparisons. The results indicate that the fit of the first-order and second-order solutions fit the data
equally good and better than the bifactor models. Results can be obtained by contacting the author. Robust SEM Model-fit (Satorra–Bentler correction; Mplus
Variant). df ¼degrees of freedom; CFI ¼comparative fit index; delta CFI ¼difference in CFI from the previous model in the sequence; RMSEA ¼root mean
square error of approximation, SRMR ¼standardized root mean square residual.
*p< .05. **p< .01. ***p< .001.
Table 1. Means, Standard Deviations, and Intercorrelations Between All Variables Across Samples.
Variable M(SD)123456
1. Tripartite Islamophobia Scale 2.71 1.06 –
2. Anti-Muslim prejudice 2.60 1.12 .94***
3. Anti-Islam sentiment 3.12 1.13 .90*** .77***
4. Conspiracy beliefs 2.42 1.19 .93*** .83*** .72***
5. Fear Islam & Muslims 2.20 1.19 .76*** .72*** .66*** .72***
6. Anger Islam & Muslims 2.04 1.13 .81*** .79*** .70*** .74*** .79***
7. Disgust Islam & Muslims 1.86 1.10 .76*** .74*** .64*** .71*** .74*** .91***
*p< .05. **p< .01. ***p< .001.
6Personality and Social Psychology Bulletin XX(X)

perspective (e.g., Neuberg & Schaller, 2016). To this end, we
proceeded by testing whether fear, anger, and disgust are
uniquely and significantly predictive of Islamophobia and
to compare the relative strength of each intergroup emotion
on our criterion variables.
Given the high intercorrelation between the intergroup
emotions, we chose not to rely solely on standard multiple
regression analysis due to known issues in over- and/or under-
estimating the relative effect sizes within settings of multi-
collinearity (e.g., Tonidandel & LeBreton, 2015). As an
alternative we chose relative weights analysis (Johnson,
2000), which remedies multicollinearity issues by creating
new sets of predictors, which are orthogonal to the original
predictors and provide more accurate estimates of the relative
strength of each predictor. Specifically, we tested and com-
pared the relative weight of each intergroup emotion on the
TIS as a whole as well as on each of its subcomponents
following the approach outlined by Tonidandel and LeBreton
(2015). Comparing these weights within the sample yields
estimates about which emotion is relatively more important
compared to others in explaining our criterion variables. We
also included results from the traditional multiple regression
analyses to display the direction of the relationships between
intergroup emotions and our criterion variables.
Table 3 displays the results from the hierarchical regres-
sion and relative weights analyses. Due to length consid-
erations, the results for the hierarchical regression
analyses are presented in SOM (Tables S10–S11). Impor-
tance weights are interpreted as the proportion of each
variance’s contribution to the criterion value (Tonidandel
& LeBreton, 2015); therefore, higher relative weights are
associated with a higher portion of a model’s R
2
.The
rescaled importance weights are the percentage of the
importance weights’ contribution to a model’s R
2
value.
Hence, a higher percentage is interpreted as a higher pro-
portion of the total R
2
value. We included the beta values
for comparison purposes and to assess discrepancies
between them and importance weights.
In line with our expectations, all three emotions showed
unique and significant contributions in explaining our criter-
ion variables (see Table 3 and Tables S10–S11 in the SOM).
More specifically, intergroup anger was predictive of Isla-
mophobia, above and beyond fear, in the overall sample as
well as in the individual country analyses in terms of
explained variance. Intergroup disgust was predictive of Isla-
mophobia in the overall sample and for Germany and France
in the country-level analyses. For the United States, Poland,
and India, disgust was not predictive of Islamophobia over
and above fear and anger. Regarding the subcomponents,
again, anger was predictive of each subcomponent of our
scale across all five countries. Disgust was predictive of
some subcomponents in Germany, India, France but not in
the United States or Poland (see Table 3).
Taken at face value, the relative weight analyses indicate
that anger showed slightly larger and more consistent
relative importance weights and explained larger proportions
of variance for the TIS as a whole (IW ¼0.25, p< .05; RIW
¼36%), for anti-Islam sentiment (IW ¼0.20, p< .05;
RIW ¼37%), and anti-Muslim prejudice (IW ¼0.24
p< .05; RIW ¼37%), compared to fear and disgust. On the
other hand, fear showed larger relative importance weight
and explained larger proportions of variance in regard to
conspiracy beliefs (IW ¼0.21, p< .05; RIW ¼36%).
Next, we tested whether the relative importance weights
between the three emotions were significantly different from
each other (see Table 4).
Fear and anger did not show significant differences in their
relative weights in explaining TIS, 95%CI ¼[.014, .041],
anti-Islam sentiment, 95%CI ¼[.007, .045], or conspiracy
beliefs, 95%CI ¼[.046, .013]. However, for anti-Muslim
prejudices, the 95%CI ¼[.006, .063] did not include zero,
and thus the results indicate that anger (IW ¼0.24, p<
.05, RIW ¼37%) had a relatively larger weight size
compared to fear (IW ¼0.21, p<.05,RIW¼31%). In
the country-level analyses, anger and disgust did now
show significant differences in the United States, Poland,
or France. However, both anger and disgust were stronger
predictors, compared to fear, for the TIS, anti-Islam senti-
ment, and anti-Muslim prejudice, in Germany. Moreover,
both anger and disgust were also significantly stronger
predictors of anti-Muslim prejudice in India. Table 5
shows the comparison of relative importance weights with
disgust as reference predictor.
In the overall aggregated sample, both fear and anger
showed significantly larger associations compared to dis-
gust, except for anti-Muslim prejudice (see Table 5). Regard-
ing the individual country-analyses, anger was a
significantly stronger predictor, compared to disgust for the
United States and Poland, while fear and disgust did not
differ for these countries. Disgust was also a stronger pre-
dictor compared to fear in Germany (except for conspiracy
beliefs). Disgust was also relatively stronger compared to
fear in predicting anti-Muslim prejudice in India.
Study 1 Discussion
Study 1 lends support for our hypothesis that Islamophobia is
best explained as a three-factor model, consisting of anti-
Muslim prejudice, anti-Islam sentiment, and Islamophobic
conspiracy beliefs. The TIS also showed scalar invariance
in the overall sample. Hence, the TIS seems appropriate for
cross-cultural analysis, including the comparison of mean
values. As for the second aim of exploring emotional asso-
ciations with the TIS, the results were partially in line with
our expectations that anger and disgust would be predictive
of Islamophobia, above and beyond fear. In the aggregated
sample analyses, fear, anger, and disgust were all uniquely
associated with Islamophobia as a whole as well as its sub-
components. However, anger and fear did not differ in their
relative weight in explaining Islamophobia as a whole.
Uenal et al. 7

Regarding the analyses of the individual subcomponents,
anger was significantly more predictive than fear of the
anti-Muslim prejudice dimensions. Moreover, disgust was
less predictive than fear of all, except the anti-Muslim pre-
judice dimension. In terms of country-level analyses, we
found a more heterogenous picture which we discuss in more
detail in the general discussion.
Study 2
The aim of Study 2 was twofold. First, we investigated the
moderating role of two potential individual differences
(i.e., ingroup identification and social dominance orienta-
tion) on the relationship between intergroup emotions and
Islamophobia (e.g., Kossowska et al., 2008; Matthews &
Levin, 2012). Second, we investigated a number of
Table 3. Multiple Regression and Relative Importance of Intergroup Emotions on Islamophobia and Its Subcomponents in the Aggregated
Sample (N¼1,466).
Country Predictors
Tripartite Islamophobia
Scale Anti-Islam Sentiment Anti-Muslim Prejudice Conspiracy Beliefs
ß IW RIW (%) ß IW RIW (%) ß IW RIW (%) ß IW RIW (%)
5 Countries
(N¼1,466)
Fear Islam & Muslims 0.32*** .23* 34.04 0.25*** .18* 34.05 0.26*** .21* 31.93 0.35*** .21* 36.03
Anger Islam & Muslims 0.46*** .25* 36.10 0.50*** .20* 37.81 0.49*** .24* 37.34 0.30*** .20* 33.41
Disgust Islam &
Muslims
0.10** .20* 29.86 -0.01 .14* 28.13 0.10** .20* 30.73 0.18*** .18* 30.56
R
2
.69 .52 .65 .60
IW .69 .52 .65 .60
RIW 100 100 100 100
USA (n¼295) Fear Islam & Muslims 0.30*** .24* 33.39 0.29*** .19* 33.93 0.21*** .20* 30.84 0.35*** .22* 35.37
Anger Islam & Muslims 0.60*** .26* 36.90 0.63*** .22* 37.87 0.56*** .25* 37.53 0.48*** .22* 35.32
Disgust Islam &
Muslims
–0.03 .21* 29.71 –0.15 .16* 28.19 0.07 .21* 31.63 0.01 .18* 29.31
R
2
.71 .58 .66 .62
IW .71 .58 .66 .62
RIW 100 100 100 100
Germany
(n¼293)
Fear Islam & Muslims 0.20*** .17* 25.52 0.15*** .13* 23.87 0.14** .15* 22.79 0.25*** .13* 32.11
Anger Islam & Muslims 0.37*** .25* 37.48 0.37*** .21* 38.67 0.41*** .25* 39.25 0.19*** .14* 33.26
Disgust Islam &
Muslims
0.34*** .25* 36.99 0.30*** .21* 37.46 0.32*** .24* 37.95 0.27** .14* 34.62
R
2
.67 .56 .65 .42
IW .67 .56 .65 .42
RIW 100 100 100 100
Poland (n¼297) Fear Islam & Muslims 0.32*** .20* 35.67 0.25*** .12* 36.13 0.30*** .19* 35.26 0.30*** .16* 35.34
Anger Islam & Muslims 0.45*** .22* 38.10 0.40*** .13* 39.48 0.52*** .21* 40.46 0.29** .16* 34.84
Disgust Islam &
Muslims
0.06 .15* 26.22 –0.01 .08* 24.39 –0.03 .13* 24.27 0.18* .14* 29.82
R
2
.57 .34 .53 .46
IW .57 .34 .53 .46
RIW 100 100 100 100
France (n¼289) Fear Islam & Muslims 0.31*** .24* 32.43 0.28*** .18* 34.95 0.24*** .21* 29.40 0.31*** .21* 33.04
Anger Islam & Muslims 0.34*** .26* 34.51 0.43*** .19* 36.48 0.28*** .25* 34.45 0.21* .21* 32.84
Disgust Islam &
Muslims
0.28*** .24* 33.06 0.04 .15* 28.56 0.38*** .26* 36.15 0.33*** .22* 34.12
R
2
.74 .51 .72 .64
IW .74 .51 .72 .64
RIW 100 100 100 100
India
(n¼292)
Fear Islam & Muslims 0.20*** .21* 30.52 0.21* .17* 31.37 0.08 .18 27.72 0.26*** .21* 32.36
Anger Islam & Muslims 0.61*** .25* 36.93 0.64*** .20* 37.45 0.55*** .24 37.62 0.53*** .23* 35.75
Disgust Islam &
Muslims
0.04 .22* 32.55 –0.10 .17* 31.18 0.18 .22 34.66 0.04 .20* 31.89
R
2
.69 .54 .64 .64
IW .69 .54 .64 .64
RIW 100 100 100 100
Note. Importance weights are relative weights which sum to the R
2
of the full model. Rescaled importance weights are calculated by dividing the importance
weight by the R
2
of the model. IW ¼Importance Weight; RIW ¼Rescaled Importance Weight.
*p< .05. **p< .01. ***p< .001.
8Personality and Social Psychology Bulletin XX(X)

attitudinal and behavioral outcomes expected to differen-
tially relate to each subcomponent of the TIS. To this end,
we tested whether our Islamophobia scale would predict
negative intergroup outcome variables as criterion variables
while controlling for further related variables. Moreover,
based on previous research on anti-Semitism (e.g., Bilewicz
& Krzeminski, 2010), we hypothesized that prejudices and
conspiracy beliefs would be stronger predictors of intergroup
attitudes and behaviors focused on the overt domination and
subjugation of Muslims (i.e., ethnic persecution) than anti-
Islamic sentiment.
Methods
Participants. Amazon MTurk was used to collect a U.S. sam-
ple (N¼213) between March and April of 2019. The sample
consisted of 46.9%women and the average age was 31.70
(SD ¼1.17). Moreover, 14.6%had completed high school or
less, 22.5%had completed some college, 37.6%had com-
pleted a bachelor’s degree, and 8.5%had partially completed
or completed a graduate or professional degree. Detailed
descriptive statistics for the sample are provided in the SOM
(see Table S2).
Table 4. Comparing Relative Importance Weights of Intergroup Emotions in Predicting Islamophobia and Its Subcomponents Across All
Samples.
Country
Reference Predictor Emotion
(Intergroup Fear)
Tripartite
Islamophobia Scale
Anti-Islam
Sentiment
Anti-Muslim
Prejudice
Conspiracy
Beliefs
LLCI ULCI LLCI ULCI LLCI ULCI LLCI ULCI
5 Countries (N¼1,466) Anger Islam & Muslims 0.014 0.041 0.007 0.045 0.006 0.063 0.046 0.013
Disgust Islam & Muslims 0.055 0.002 0.055 0.007 0.036 0.020 0.063 0.003
USA (n¼295) Anger Islam & Muslims 0.039 0.079 0.039 0.081 0.006 0.096 0.059 0.058
Disgust Islam & Muslims 0.083 0.011 0.083 0.012 0.043 0.053 0.093 0.017
Germany (n¼293) Anger Islam & Muslims 0.022 0.140 0.032 0.133 0.048 0.171 0.064 0.072
Disgust Islam & Muslims 0.014 0.146 0.015 0.137 0.034 0.171 0.067 0.083
Poland (n¼297) Anger Islam & Muslims 0.064 0.092 0.058 0.085 0.053 0.103 0.080 0.075
Disgust Islam & Muslims 0.124 0.019 0.104 0.023 0.130 0.013 0.103 0.049
France (n¼289) Anger Islam & Muslims 0.032 0.088 0.046 0.068 0.024 0.103 0.062 0.065
Disgust Islam & Muslims 0.053 0.082 0.087 0.023 0.011 0.126 0.063 0.081
India (n¼292) Anger Islam & Muslims 0.008 0.097 0.024 0.084 0.016 0.116 0.034 0.071
Disgust Islam & Muslims 0.032 0.061 0.049 0.045 0.001 0.093 0.051 0.042
Note. The reference intergroup emotion fear is compared to anger and disgust. If zero is not included in the confidence intervals, weights are significantly
different from one another. Significant differences are displayed in bold. LLCI ¼Lower level confidence interval; ULCI ¼Upper level confidence interval.
Table 5. Comparing Relative Importance Weights of Intergroup Emotions in Predicting Islamophobia and Its Subcomponents Across All
Samples.
Country
Reference Predictor Emotion
(Intergroup Disgust)
Tripartite
Islamophobia Scale
Anti-Islam
Sentiment
Anti-Muslim
Prejudice
Conspiracy
Beliefs
LLCI ULCI LLCI ULCI LLCI ULCI LLCI ULCI
5 Countries (N¼1,466) Fear Islam & Muslims 0.001 0.055 0.006 0.055 0.020 0.036 0.003 0.062
Anger Islam & Muslims 0.027 0.059 0.035 0.066 0.026 0.059 0.000 0.034
USA (n¼295) Fear Islam & Muslims 0.023 0.077 0.011 0.085 0.055 0.041 0.014 0.093
Anger Islam & Muslims 0.018 0.009 0.023 0.098 0.010 0.078 0.005 0.076
Germany (n¼293) Fear Islam & Muslims 0.145 0.014 0.135 0.016 0.171 0.033 0.085 0.064
Anger Islam & Muslims 0.047 0.055 0.040 0.054 0.041 0.058 0.053 0.048
Poland (n¼297) Fear Islam & Muslims 0.021 0.124 0.019 0.107 0.014 0.130 0.047 0.102
Anger Islam & Muslims 0.029 0.108 0.014 0.091 0.048 0.128 0.021 0.065
France (n¼289) Fear Islam & Muslims 0.081 0.054 0.023 0.087 0.124 0.010 0.080 0.063
Anger Islam & Muslims 0.021 0.040 0.011 0.074 0.054 0.023 0.048 0.031
India (n¼292) Fear Islam & Muslims 0.061 0.033 0.047 0.049 0.093 0.001 0.041 0.053
Anger Islam & Muslims 0.002 0.073 0.008 0.070 0.011 0.062 0.002 0.059
Note. The reference intergroup emotion disgust is compared to anger and fear. If zero is not included in the confidence intervals, weights are significantly
different from one another. Significant differences are displayed in bold. LLCI ¼Lower level confidence interval; ULCI ¼Upper level confidence interval.
Uenal et al. 9

Instruments
TIS. The TIS developed in Study 1 was administered (anti-
Islam sentiment, a¼.91; anti-Muslim prejudice, a¼.92;
anti-Muslim conspiracy beliefs, a¼.97; TIS aggregated
scale, a¼.96) together with the same intergroup emotions
scales (fear of Islam and Muslims, a¼.97; anger toward
Islam and Muslims, a¼.97; disgust toward Islam and Mus-
lims, a¼.97). For the TIS, confirmatory factor analysis
replicated measurement structure from Study 1 (see Table
S13 in SOM).
Individual difference measures. We administered two addi-
tional measures, both scored on a five-point scale ranging
from 1 (strongly disagree)to5(strongly agree).
SDO. SDO was assessed through use of the 16-item (e.g.,
“Some groups of people are simply inferior to other groups”;
a¼.96) SDO-7 scale (Ho et al., 2015).
Ingroup identification. Ingroup identification was measured
using five items (e.g.; “I feel strongly connected to other
Americans”; a¼.96) adapted from the collective self-
esteem scale (Luhtanen & Crocker, 1992).
Predictive validation measures. To assess the incremental
validity of our scale, we administered three additional mea-
sures. All predictive measures were scored on a five-point
scale ranging from 1 (strongly disagree)to5(strongly agree)
unless stated otherwise.
Ethnic persecution. Ethnic persecution was measured by an
adapted version (Thomsen et al., 2008) of Altemeyer’s
(1996) posse scale. Six items assess one’s willingness to
participate in the politically sanctioned persecution of Mus-
lims (e.g., “I would participate in attacks on Muslim head-
quarters if supervised by the proper authorities”; a¼.93).
Anti-Muslim policy support. Support for anti-Muslim poli-
cies was assessed by nine items from Kteily et al. (2016; e.g.,
“We need to stop accepting Muslim refugees into this coun-
try, period”; a¼.97).
Dehumanization. Dehumanization of outgroup members
(i.e., Muslims) was assessed with the Ascent of Man scale
(Kteily et al., 2015) in which participants rated the average
“evolvedness” of Muslims from 0 to 100 (full humanity). We
used a reverse score for analysis, with higher values indicat-
ing more dehumanization.
Analysis of data. First, we tested whether SDO and/or ingroup
identification moderate the relationship between the inter-
group emotions and Islamophobia. Next, to test for the pre-
dictive validity of the TIS, we used hierarchical regression
analysis by stepwise regressing three criterion variables (e.g.,
ethnic persecutions) on the three subcomponents of TIS and
our individual differences measures.
Results
Table 6 shows the mean scores, standard deviations, and
intercorrelations among the criterion variables and the Isla-
mophobia subscales. All the measures showed significant
intercorrelations in the expected direction. Additional results
are provided in the SOM (Table S12), investigating each
intergroup emotion separately for Islam and Muslims.
Moderation analysis. To test whether ingroup identification
and/or SDO would moderate the relationship between the
three intergroup emotions and Islamophobia we ran a hier-
archical regression analysis. In the first step, we entered both
individual difference variables ingroup identification and
SDO along with the intergroup emotions. In the second step,
we additionally entered the interaction terms between the
moderators (centered) and the intergroup emotions (cen-
tered). Table 7 shows a summary of the hierarchical regres-
sion analysis for Islamophobia.
In the first step of the analysis, F(5, 207) ¼81.1, p< .001,
R
2
¼.66, only ingroup identification and intergroup anger
showed significant effects on Islamophobia. Entering the
interaction terms in the second step of the analysis,
F(11, 201) ¼39.11, p< .001, R
2
¼.68, increased the
explained variance slightly by 2%. In the second step, inter-
group disgust also showed a significant positive effect.
1
Regarding the moderation analyses, in line with our expec-
tations, ingroup identification and fear showed a significant
Table 6. Means, Standard Deviations, Scales, and Intercorrelations Between Variables (N¼213, United States: Sample 6).
Variable M(SD)12345678
1. Social dominance orientation 2.01 0.97 —
2. Ingroup identification 3.73 1.07 .26***
3. Fear of Islam & Muslims 2.17 1.29 .44*** .32***
4. Anger Islam & Muslims 2.12 1.23 .50*** .27*** .83***
5. Disgust Islam & Muslims 2.06 1.26 .51*** .25*** .80*** .95***
6. Anti-Islam Sentiment 2.50 0.96 .36*** .34*** .64*** .77*** .73***
7. Anti-Muslim Prejudice 2.08 0.97 .52*** .37*** .73*** .79*** .78*** .79***
8. Conspiracy Beliefs 2.38 1.36 .47*** .34*** .71*** .80*** .78*** .81*** .87***
9. Tripartite Islamophobia Scale 2.35 1.04 .48*** .37*** .75*** .83*** .80*** .92*** .94*** .94***
*p< .05. **p< .01. ***p< .001.
10 Personality and Social Psychology Bulletin XX(X)

interaction, such that higher fear was associated with
increased Islamophobia among those with higher ingroup
identification (see Figure 2).
Moreover, in line with our hypothesis, anger and SDO
showed a significant interaction such that higher anger was
associated with increased Islamophobia for individuals high
in SDO. Unexpectedly, SDO also showed a significant inter-
action with fear, such that higher fear was associated with
significantly higher Islamophobia for low SDO individuals.
No interaction between disgust and SDO or ingroup identi-
fication was indicated.
Predictive validity. Finally, we regressed three negative inter-
group outcome variables (dehumanization, support for anti-
Muslim policies, and ethnic persecutions) on demographic
indicators, ingroup identification, SDO, and our TIS sub-
scales in hierarchical multiple regression analyses. This
enabled us to test the incremental validity of our scale by
controlling for predictors expected to be related to the criter-
ion variables. In the first step, we entered demographic vari-
ables (age, gender, education, and political orientation),
ingroup identification and SDO. In the second step, we
entered all subcomponents of our Islamophobia scale (anti-
Muslim prejudice, anti-Islam sentiment, and conspiracy
beliefs) into the model (see Table 8).
Consistent with our expectation, anti-Muslim prejudice
and the conspiracy belief subcomponents were significant
and unique predictors, controlling for all the remaining
measures, and explained an additional 17%to 37%of the
total variance, over and above the well-established mea-
sures in the model (see Table 8).
2
In line with our expecta-
tion, anti-Muslim prejudice and conspiracy beliefs
outperformed anti-Islam sentiment in predictive power.
Conspiracy beliefs were, moreover, significantly associated
with dehumanization.
Study 2 Discussion
Study 2 tested two individual difference variables explaining
distinct emotional reactions to Islam and Muslims. Further-
more, we analyzed the incremental validity of the TIS. As
hypothesized, especially for individuals high in SDO, anger
was associated with higher Islamophobia. This is in line with
previous research indicating a close relationship between
SDO and intergroup anger (e.g., Matthews & Levin, 2012).
Table 7. Regression Analyses Predicting Islamophobia.
Model
Tripartite Islamophobia Scale
BSE(HC4) T p
Step 1
Ingroup identification 0.15 .05 2.72 .007
Social dominance
orientation
0.08 .07 1.22 .225
Intergroup fear 0.11 .08 1.44 .152
Intergroup anger 0.51 .15 3.32 .001
Intergroup disgust 0.21 .14 1.45 .148
Step 2
ID 0.14 .06 2.41 .017
SDO 0.12 .07 1.76 .079
Intergroup fear 0.08 .08 0.97 .334
Intergroup anger 0.41 .16 2.55 .011
Intergroup disgust 0.34 .15 2.18 .030
ID Fear 0.26 .09 2.88 .004
ID Anger 0.16 .14 1.15 .250
ID Disgust 0.08 .13 0.58 .565
SDO Fear 0.19 .07 2.61 .009
SDO Anger 0.39 .19 2.00 .046
SDO Disgust 0.24 .17 1.39 .166
Note. Continuous variables (ingroup identification, social dominance orien-
tation, and intergroup emotions) are centered. Significant effects are dis-
played in bold. ID ¼Ingroup identification; SDO ¼social dominance
orientation.
Figure 2. Simple slopes for interactions between intergroup emotions and ingroup identification and SDO.
Note. Ribbons present 95% confidence intervals. SDO ¼social dominance orientation.
Uenal et al. 11

Moreover, as expected, social identification moderated the
effects of fear on Islamophobia. Unexpectedly, the results
indicated that SDO also interacted with fear, such that higher
fear and low SDO interacted in predicting increased Islamo-
phobia. However, no interaction with disgust was shown.
This suggests that other potential moderating factors might
be at play that need further exploration to explain the disgust-
Islamophobia nexus. We will discuss these finding in more
detail in the general discussion.
Regarding the incremental validity of our scale, we
hypothesized and found support that, compared to anti-
Islamic sentiment, both anti-Muslim prejudice and conspi-
racy beliefs had larger effects on behavioral inclinations that
promote the active and forceful oppression of Muslims and
Islamic organizations (e.g., support for anti-Muslim poli-
cies). This prediction was partly based on research on anti-
Semitism, which showed that above and beyond anti-Semitic
prejudices, anti-Semitic conspiracy beliefs were most signif-
icantly predictive of negative intergroup outcome measures
(Bilewicz et al., 2013).
General Discussion
Since the introduction of the term about 30 years ago, several
conceptualizations and models of Islamophobia have been
proposed (Bleich, 2011; Klug, 2012). Yet, many theoretical
and methodological issues have persisted including a lack of
knowledge about Islamophobia’s (a) components, (b) cross-
cultural validity, (c) emotional underpinnings, (d) relation to
individual differences, and (e) societal consequences. In this
paper, we aimed to address each of these issues. Across
several cultures, we reliably distinguished between three dif-
ferent types of attitudes and beliefs about Islam and Mus-
lims, using the TIS. Second, across cultural contexts, we
systematically showed that both anger and—to a lesser
degree—disgust predict Islamophobia in addition to fear.
Third, we demonstrate that individual differences in the
emotional reactions of anger and fear can be explained as a
function of SDO and ingroup identification. Finally, we ana-
lyze the scale’s predictive validity and demonstrate its rele-
vance in explaining important societal outcomes (e.g.,
blatant dehumanization, anti-Muslim policy support).
A New and Cross-Culturally Valid
Islamophobia Measure
One of the more persistent issues regarding research on
Islamophobia was the lack of a cross-culturally validated
instrument to measure the phenomena across time, groups,
and geographical regions. Therefore, we designed and tested
our Islamophobia measure in five different cultural contexts.
The results show that our TIS instrument indicates full scalar
invariance. This suggests that the scale assesses the same
underlying constructs in each setting and, hence, may be
used to make valid comparisons, including among different
mean levels, of Islamophobia across cultures.
Moreover, we contribute to current discussions of the
comparability of Islamophobia with anti-Semitism and other
prejudices, a topic which has triggered heated debates in the
academic and public discourse, including questioning
whether or not these phenomena are comparable to each
other (e.g., Ku
¨ntzl, 2008; Uenal, 2016b). Our results indicate
Table 8. Regression Analysis With the Three Subcomponents of the Tripartite Islamophobia Scale and Criterion Variables (N¼213,
Sample 6).
Islamophobia criteria
Dehumanization Anti-Muslim policy Ethnic persecution
ßSE(HC4) pßSE(HC4) pßSE(HC4) p
Step 1
Age .19 0.06 .752 .18 0.03 .581 .05 0.04 .198
Gender .13 0.14 .348 .15 0.08 .045 .18 0.09 .048
Education .00 0.05 .972 .04 0.03 .187 .04 0.03 .231
Political orientation .05 0.06 .412 .00 0.03 .957 .03 0.04 .519
Ingroup identification .07 0.07 .338 .04 0.04 .300 .00 0.04 .962
SDO .18 0.09 .049 .18 0.03 <.001 .05 0.04 <.001
Step 2
Anti-Islam Sentiment .03 0.13 .795 .13 0.07 .075 .17 0.08 .037
Anti-Muslim Prejudice .12 0.16 .452 .73 0.09 <.001 .52 0.10 <.001
Conspiracy Beliefs .39 0.12 <.001 .37 0.06 <.001 .26 0.07 <.001
Adjusted R
2
.36 .83 .67
Change in adjusted R
2
.17 .37 .23
Standard error of estimate .97 .53 .62
Significant Fchange p< .001 p<.001 p< .001
Note. Values reflect bcoefficients for the full model. Age: 1 (lower) - 5 (higher); Gender: 1 (Male) – 2 (Female); Education: 1 (low) - 12 (high); Political
Orientation: 1 (left) - 5 (right). All constructs were entered stepwise in a two-step hierarchical regression model. Significant effects are displayed in bold.
SDO ¼Social dominance orientation.
12 Personality and Social Psychology Bulletin XX(X)

that—comparable to modern anti-Semitism—Islamophobia
manifest itself in different ways: negative sentiments against
the Islamic religion, prejudice against Muslim individuals,
and conspiracy beliefs about Muslims as collective agents
with malicious and deceptive intentions. Our measure, thus,
offers a conceptually sound way to compare Islamophobia
with other forms of prejudices and conspiracy beliefs.
Conspiracy Beliefs as Component of Islamophobia
Our research advances theoretical discussions on Islamopho-
bia by adding to a neglected, yet crucial, aspect of the con-
cept: conspiracy beliefs. The results of this paper indicate
that Islamophobic conspiracy beliefs were a statistically
unique factor in five different cultural settings. We also
found that the subcomponents disassociated in terms of the
downstream intergroup outcomes they best predicted (i.e.,
ethnic persecution, dehumanization, anti-Muslim policy sup-
port). Similar to findings on anti-Semitism (Bilewicz et al.,
2013; Bilewicz & Krzeminski, 2010), on which we partly
based our hypothesis, we found that beyond anti-Islam senti-
ment alone, anti-Muslim prejudice and especially adherence
to conspiracy beliefs were most predictive of these out-
comes. Both of these subcomponents explained our three
criterion variables over and above anti-Islamic sentiment.
Crucially, our scale also showed good incremental validity
and predicted the criterion variables, even when controlling
for demographic variables, ingroup identification, and social
dominance orientation. Moreover, we found that the conspi-
racy beliefs sub-component showed robust association with
fear across the samples and, compared to disgust, slightly
stronger associations with fear in the overall sample analy-
ses. This finding aligns with previous experimental research
showing that belief in conspiracy theories is associated with
anxiety, uncertainty, and a perceived lack of control (e.g.,
van Prooijen & Douglas, 2018; Whitson & Galinsky, 2008).
Emotional Underpinnings of Islamophobia
Across Cultures
Taking a socio-functional and threat-based approach to pre-
judice (e.g., Neuberg & Schaller, 2016), we hypothesized
that anger and disgust would be predictive of Islamophobia,
above and beyond fear. Indeed, we found that, controlling for
intergroup fear, anger and disgust were unique and signifi-
cant predictors of Islamophobia in the aggregated sample,
explaining Islamophobia taken as a whole as well as its
subcomponents, albeit to varying degrees. Nevertheless,
applying a more stringent test to compare the relative
strength of each emotion showed that anger and fear did not
significantly differ in their relative predictive strength for the
aggregated Islamophobia scale. However, anger was a sig-
nificantly stronger predictor for the anti-Muslim prejudice
component compared to both fear and disgust. Also, both
anger and fear were significantly stronger predictors,
compared to disgust, of the aggregated scale as well as two
of its subcomponents. Thus, in addition to fear, considering
both anger and disgust as integral parts of Islamophobia
seems warranted.
In the country level analyses, the results were more het-
erogeneous. To start with, fear did not differ in relative
strength from anger and disgust for the United States,
Poland, and France. However, for Germany, we found that
both anger and disgust showed significantly stronger asso-
ciations with Islamophobia compared to fear. Anger, on the
other hand, was significantly stronger compared to disgust
for the United States, Poland and, partially, also for both
France (anti-Islam sentiment) and India (TIS and anti-
Islam sentiment).
Overall, this paper advances research on the emotional
underpinning of Islamophobia by providing cross-cultural
evidence for the relevance of the anger- and disgust-bases
of Islamophobia. While our results indicate that fear does
play a significant role in explaining Islamophobia, as sug-
gested by the most prominent definitions and conceptualiza-
tions of current Islamophobia, our results ascribe anger an
equally large role for explaining Islamophobia. Disgust,
though significantly smaller in effect size, also played a
significant role in predicting Islamophobia in the aggregated
sample, and thus warrants more attention. Our findings on
the country-level of analysis paint a more heterogeneous
picture and point to context-dependent emotional underpin-
nings of Islamophobia. While it exceeds the aim and scope of
this paper to explain the country-level variations that were
not based on representative samples, they nevertheless raise
intriguing questions as to how to explain such cross-cultural
differences. For instance, in Germany, France, and also par-
tially in India where anger and disgust were significant pre-
dictors of Islamophobia and most of its individual
subcomponents, there are much larger Muslim populations
(6.1%in Germany, 8.8%in France, and 15%in India; PEW,
2017b) compared to the United States and Poland (less than
1%of the overall population; PEW, 2017b). Given this,
greater anger and disgust reactions in these samples might
be a function of perceptions of increased socio-economic
competition as well as perceptions of decreased collective
support for the non-Muslim ingroup relative to population
strength. Another interesting pattern which emerged is that
anti-Muslim prejudice was more strongly associated with
anger compared to fear, and in some countries, also stronger
compared to disgust. Future research should further investi-
gate these patterns and contextual differences.
Fear and Anger: Moderation by SDO and Ingroup
Identification
This article also advances previous research by examining
how differential emotional underpinnings of Islamophobia
seem to partially serve as a function of psychological
mechanisms (i.e., SDO and ingroup identification). Partially
Uenal et al. 13

in line with our hypotheses, we found that individuals who
scored higher on SDO showed more Islamophobia in con-
junction with anger, but not disgust or fear. This is in accor-
dance with previous research analyzing the associations of
SDO and emotions in predicting negative intergroup out-
comes, which points to anger as the primary affective com-
ponent of an SDO mindset (e.g., Matthews & Levin, 2012).
SDO has been consistently shown to be a robust predictor of
negative outgroup attitudes and behavior signaling aggres-
sion toward low-status groups (Sidanius et al., 2017). An
interesting, yet unexpected, finding of our study is the sig-
nificant interaction between fear and SDO negatively pre-
dicting Islamophobia. More specifically, our results show
that the effect of fear on Islamophobia seems to be buffered
for high SDO individuals, while for low SDO individuals,
fear leads to more Islamophobia. Low SDO has been previ-
ously associated with less negative intergroup bias. Individ-
uals low in SDO are construed as more egalitarian and less
dominant and as such, less prejudiced. However, our results
indicate, if intergroup fear is present, low SDO can be asso-
ciated with higher prejudice.
In contrast to SDO, we hypothesized that fear and disgust,
but not anger, would interact with higher ingroup identifica-
tion in predicting Islamophobia. Indeed, for individuals
highly identified with their ingroup, we found that fear
amplifies Islamophobic attitudes and beliefs. We interpret
this finding in light of research which shows that ingroup
identification is more indicative of ingroup love rather than
outgroup derogation per se (Brewer, 1999; Levin & Sidanius,
1999). Individuals highly attached to their ingroup might
adopt derogatory outgroup attitudes as a means of signaling
their ingroup preference and thereby reasserting their distinc-
tiveness and facilitating ingroup solidarity. Nevertheless, pre-
vious research has also shown that the association between
ingroup identification and negative outgroup affect varies in
tandem with other factors, such as perceived collective support
(e.g., Mackie & Smith, 2015). Future studies might consider
assessing both ingroup identification and perceived collective
support as potential moderators to further explore the fear-
Islamophobia nexus. Finally, we could not find an interaction
with either of our moderators and disgust. Previous research
has shown that right-wing authoritarianism (Altemeyer, 1996),
an individual difference construct closely related, yet distinct
from SDO, might be a better suited moderator between disgust
and prejudice (e.g., Sibley & Duckitt, 2008).
Overall, our findings add to previous efforts of assessing
ideological attitudes and social identification together with
intergroup emotions in predicting specific intergroup out-
comes (e.g., Kossowska et al., 2008; Matthews & Levin,
2012). In addition to corroborating previous results, our find-
ings contribute to research by showing that low SDO can also
be associated with higher prejudice, given the presence of
intergroup fear. This is novel in light of previous research
which has consistently found low SDO to be associated with
less prejudice across different intergroup contexts (Sidanius
et al., 2017). Our results indicate that an egalitarian and non-
dominant worldview, as indicated by low levels of SDO,
might not be sufficient to buffer the effects of fear on pre-
judice, at least not in the case of Islamophobia. Future studies
could further explore this relationship.
Limits on Generality
While we believe that the cross-cultural approach taken in
this study is a strength, the results should also be interpreted
in light of some limitations. For instance, some socio-
demographics varied between the countries (see Table S2
SOM). Moreover, although MTurk samples (and, presum-
ably, PROLIFIC samples as well), are more representative
than traditional social psychological samples (Paolacci &
Chandler, 2014), these samples are not fully representative.
In addition, concepts like Islamophobia are not static entities
and develop over time. Thus, future research might reevalu-
ate item selections depending on time, geography, and socio-
political contexts, and potentially add further items to the
scale. Indeed, the cross-cultural approach taken in the pres-
ent research does not claim that the culturally most relevant
or even most valid aspects of Islamophobia were assessed in
each study. Although the item selection was based on exten-
sive preliminary research and literature and was discussed
with researchers from most of the countries in which data
were collected, future research may profitably validate the
content of the scales by, for instance, using qualitative meth-
ods as well. Besides others, this may allow a validation of the
scale’s content against people’s evaluations, attitudes, and
feelings regarding Muslims and their religion from a
bottom-up perspective. Furthermore, future studies could
consider behavioral validation methods, in addition to self-
report validation approaches, to further gauge the psycho-
metric properties of our scale.
Moreover, the three subcomponents of the TIS were
strongly correlated. On the one hand, this may indicate the
intertwined nature of Islamophobic attitudes and sentiments.
On the other hand, future refinements of this scale may test
whether rephrasing some of the items possibly reduces lin-
guistic overlap between them, which may have led to higher
inter-item correlations. Nevertheless, despite these findings,
it is important to note that our proposed three-factor solution
was confirmed across five culturally different countries sup-
porting the tripartite nature of Islamophobia. Furthermore,
criterion validation analyses further corroborated our tripar-
tite view by showing theoretically justifiable, and statisti-
cally significant disassociation, of the three subcomponents
in regard to their respective emotional antecedents as well as
the intergroup outcomes they predict.
Practical Implications and Future Directions
An interesting area for future research highlighted by the
present work concerns Islamophobic conspiracy beliefs. Our
14 Personality and Social Psychology Bulletin XX(X)

results indicate that the phenomenon is common across the
analyzed cultural contexts and statistically distinct from the
other two subcomponents. Yet, it remains an under-
investigated phenomenon. Further research on the emotional
bases of Islamophobia (and other prejudices) in different
regional contexts could advance knowledge on the proximal,
ultimate, and societal factors that may explain cross-country
variations. Future studies could also investigate further indi-
vidual and group differences as potential moderators of the
relationship between intergroup emotions and Islamophobia.
Specifically, analyzing the role of perceived collective sup-
port and threat perceptions in fear-modulation might prove
fruitful.
We hope that by providing a more rigorous operationali-
zation, as well as enhanced tools of assessment of Islamo-
phobia and its substantive subcomponents, the present
research can help facilitate further research concerned with
the causes and consequences of Islamophobia.
Acknowledgments
We want to thank the reviewers and editor for their helpful
comments.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect
to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, author-
ship, and/or publication of this article: This research was supported,
in part, by a post-doctoral stipend from the Humboldt University
Berlin within the Excellence Initiative of the states and the federal
government (German Research Foundation).
Ethical Approval
This study was approved by Harvard University-Area Committee
on the Use of Human Subject (IRB 16-1810).
ORCID iDs
Fatih Uenal https://orcid.org/0000-0002-8155-3066
Robin Bergh https://orcid.org/0000-0002-5041-7723
Jonas R. Kunst https://orcid.org/0000-0002-5319-1256
Data Availability
Please contact the PI for data accessibility.
Preregistration
AsPredicted #20961 (http://aspredicted.org/blind.php?x¼6sk9gm)
Notes
1. Only main effects and two-way interactions were predicted.
However, we also conducted analyses with all possible and
meaningful interactions. These interactions were not significant,
and did not improve the predictive ability of the models. These
higher order interactions are not discussed in this paper.
2. In two out of the three regression analyses, the anti-Islam senti-
ment subcomponent shows a negative regression coefficient.
However, running the analyses without the other two subcom-
ponents indicates that anti-Islam sentiment has a significant and
positive effect on the outcome variables. Given the high inter-
correlation between the subcomponents, these results are due to
multicollinearity and thus the negative coefficient can be inter-
preted as suppression effect rather than a true negative effect.
Supplemental Material
Supplemental material for this article is available online.
References
Abalakina-Paap, M., Stephan, W. G., Craig, T., & Gregory, W. L.
(1999). Beliefs in conspiracies. Political Psychology,20(3),
637-647. http://doi.org/10.1111/0162-895X.00160
Adorno, T. W., Frenkel-Brunswik, E., Levinson, D. J., & Sanford,
R. N. (1950). The authoritarian personality. Harper & Row.
Allport, G. W. (1954). The nature of prejudice. Addison-Wesley.
Altemeyer, B. (1996). The authoritarian specter. Harvard Univer-
sity Press.
Bangstad, S. (2016). Islamophobia: What’s in a Name? Journal of
Muslims in Europe,5(2), 145-169. http://doi.org/10.1163/
22117954-12341324
Bartlett, J., & Miller, C. (2010). The power of unreason: conspiracy
theories, extremism and counter-terrorism. Demos. http://wester
nvoice.net/PowerofUnreason.pdf
Bilewicz, M., & Krzeminski, I. (2010). Anti-Semitism in Poland
and Ukraine: The belief in Jewish control as a mechanism of
scapegoating. International Journal of Conflict and Violence,
4(2), 234-243.
Bilewicz, M., Winiewski, M., Kofta, M., & W´ojcik, A. (2013).
Harmful ideas, The structure and consequences of Anti-
Semitic beliefs in Poland. Political Psychology,34(6),
821-839. http://doi.org/10.1111/pops.12024
Bleich, E. (2011). What is Islamophobia and how much is there?
Theorizing and measuring an emerging comparative concept.
American Behavioral Scientist,55(12), 1581-1600. http://doi.
org/10.1177/0002764211409387
Brewer, M. B. (1999). The psychology of prejudice: Ingroup love or
outgroup hate? Journal of Social Issues, 55(3), 429-444. https://
doi.org/10.1111/0022-4537.00126
Brown, R. (2010). Prejudice: its social psychology (2nd ed.).
Wiley-Blackwell.
Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of
measurement invariance. Structural Equation Modeling: A Mul-
tidisciplinary Journal,14(3), 464-504. http://doi.org/10.1080/
10705510701301834
Choma, B. L., Haji, R., Hodson, G., & Hoffarth, M. (2016). Avoid-
ing cultural contamination: Intergroup disgust sensitivity and
religious identification as predictors of interfaith threat, faith-
based policies, and islamophobia. Personality and Individual
Differences,95, 50-55. http://doi.org/10.1016/j.paid.2016.02.
013
Uenal et al. 15

Choma, B. L., Hodson, G., & Costello, K. (2012). Intergroup dis-
gust sensitivity as a predictor of islamophobia: The modulating
effect of fear. Journal of Experimental Social Psychology,
48(2), 499-506. http://doi.org/10.1016/j.jesp.2011.10.014
Conway, G. (1997). Islamophobia—A challenge for us all. Report
of the Runnymede Trust Commission on British Muslims and
Islamophobia. https://www.runnymedetrust.org/uploads/publi
cations/pdfs/islamophobia.pdf
Duckitt, J. (2001). A dual-process cognitive-motivational theory
of ideology and prejudice. Advances in Experimental Social
Psychology,33, 41-113. https://doi.org/10.1016/s0065-
2601(01)80004-6
Dumont, M., Yzerbyt, V., Wigboldus, D., & Gordijn, E. H. (2003).
Social categorization and fear reactions to the September 11th
terrorist attacks. Personality and Social Psychology Bulletin,
29(12), 1509-1520. https://doi.org/10.1177/0146167203256923
Elahi, F., & Khan, O. (2017). Islamophobia. Still a challenge for us
all. A 20th-anniversary report. https://www.runnymedetrust.
org/projects-and-publications/equality-and-integration/islamo
phobia.html
Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statis-
tical power analyses using G*Power 3.1: Tests for correlation
and regression analyses. Behavior Research Methods,41(4),
1149-1160. https://doi.org/10.3758/BRM.41.4.1149
Fekete, L. (2012). The Muslim conspiracy theory and the Oslo
massacre. Race & Class,53(3), 30-47. http://doi.org/10.1177/
0306396811425984
Gallup. (2013). Islamophobia: understanding anti-Muslim senti-
ment in the West. http://www.gallup.com/poll/157082/islamo
phobia-understanding-anti-muslim-sentiment-west.aspx
Goodwin, M. J., Raines, T., & Cutts, D. (2017). What do Europeans
think about Muslim immigration? https://www.chathamhouse.
org/expert/comment/what-do-europeans-think-about-muslim-
immigration
Hafez, F. (2013). Islamophobe Weltverschwo¨ rungstheorien [Isla-
mophobic conspiracy theories]. Journal Fu
¨r Psychologie,
21(1), 1-22.
Halliday, F. (1999). “Islamophobia” reconsidered. Ethnic and
Racial Studies,22(5), 892-902. http://doi.org/10.1080/
014198799329305
Helbling, M. (2012). Islamophobia in the west: Measuring and
explaining individual attitudes (M. Helbling, Ed.). Routledge.
Ho, A. K., Sidanius, J., Kteily, N., Sheehy-Skeffington, J., Pratto, F.,
Henkel, K. E., ... Stewart, A. L. (2015). The nature of social
dominance orientation: Theorizing and measuring preferences for
intergroup inequality using the new SDO
7
scale. JournalofPer-
sonality and Social Psychology,109(6), 1003-1028. http://doi.
org/10.1037/pspi0000033
Horn, J. L., & McArdle, J. J. (1992). A practical and theoretical
guide to measurement invariance in aging research. Experimen-
tal Aging Research,18(3), 117-144. https://doi.org/10.1080/03
610739208253916
Human Rights Watch. (2018). “Eradicating ideological viruses.”
China’s campaign of repression against Xinjiang’s Muslims.
https://www.hrw.org/report/2018/09/09/eradicating-ideologi
cal-viruses/chinas-campaign-repression-against-xinjiangs
Imhoff, R., & Recker, J. (2012). Differentiating Islamophobia:
Introducing a new scale to measure Islamoprejudice and secular
Islam critique. Political Psychology,33(6), 811-824. http://doi.
org/10.1111/j.1467-9221.2012.00911.x
Johnson, J. W. (2000). A heuristic method for estimating the rela-
tive weight of predictor variables in multiple regression. Multi-
variate Behavioral Research, 35(1), 1-19. https://doi.org/10.
1207/S15327906MBR3501_1
Jo¨ reskog, K. G. (1971). Simultaneous factor analysis in several
populations. Psychometrika,36(4), 409-426. http://doi.org/10.
1007/BF02291366
Jost, J. T., Glaser, J., Kruglanski, A. W., & Sulloway, F. J. (2003).
Political conservatism as motivated social cognition. Psycholo-
gical Bulletin,129(3), 339-375. http://doi.org/10.1037/0033-
2909.129.3.339
Ketelaar, T. (2015). Evolutionary psychology and emotion: A brief
history. In V. Zeigler-Hill, L. L. M. Welling, & T. K. Shack-
elford (Eds.), Evolutionary perspectives on social psychology
(pp. 51-67). Springer. http://doi.org/10.1007/978-3-319-12697-
5_5
Klug, B. (2012). Islamophobia: A concept comes of age. Ethnicities,
12(5), 665-681. http://doi.org/10.1177/1468796812450363
Kossowska, M., Bukowskia, M., & Van Hielb, A. (2008). The
impact of submissive versus dominant authoritarianism and neg-
ative emotions on prejudice. Personality and Individual Differ-
ences,45, 744-749.
Kteily, N., Bruneau, E., Waytz, A., & Cotterill, S. (2015). The
ascent of man: Theoretical and empirical evidence for blatant
dehumanization. Journal of Personality and Social Psychology,
109(5), 901-931. http://doi.org/10.1037/pspp0000048
Kteily, N., Hodson, G., & Bruneau, E. (2016). They see us as less
than human: Metadehumanization predicts intergroup conflict
via reciprocal dehumanization. Journal of Personality and
Social Psychology,110(3), 343-370. http://doi.org/10.1037/
pspa0000044
Kunst, J. R., Sam, D. L., & Ulleberg, P. (2013). Perceived islamo-
phobia: Scale development and validation. International
Journal of Intercultural Relations,37(2), 225-237. https://doi.
org/10.1016/j.ijintrel.2012.11.001
Ku
¨ntzl, M. (2008). “Islamophobia” or “Truthophobia”? Berlin’s
anti-Semitism center is going astray. https://www.wsj.com/arti
cles/SB122869182286886467
Lee, S. A., Reid, C. A., Short, S. D., Gibbons, J. A., Yeh, R., &
Campbell, M. L. (2013). Fear of Muslims: Psychometric evalua-
tion of the Islamophobia Scale. Psychology of Religion and
Spirituality,5(3), 157-171. http://doi.org/10.1037/a0032117
Leibold, J., & Ku
¨hnel, S. (2006). Islamophobie: Differenzierung tut
not [Islamophobia: Differentiation is necessary]. In W. Heit-
meyer (Ed.), Deutsche Zusta
¨nde. Folge 4 (pp. 135-155).
Suhrkamp.
Levin, S., & Sidanius, J. (1999). Social dominance and social iden-
tity in the United States and Israel: Ingroup favoritism or
16 Personality and Social Psychology Bulletin XX(X)

outgroup derogation? Political Psychology,20(1), 99-126.
https://doi.org/10.1111/0162-895X.00138
Luhtanen, R., & Crocker, J. (1992). A collective Self-Esteem Scale:
Self-evaluation of one’s social identity. Personality and Social
Psychology Bulletin,18(3), 302-318. http://doi.org/10.1177/
0146167292183006
Mackie, D. M., Devos, T., & Smith, E. R. (2000). Intergroup emo-
tions: Explaining offensive action tendencies in an intergroup
context. Journal of Personality and Social Psychology,79(4),
602-616. http://doi.org/10.1037//0022-3514.79.4.602
Mackie, D. M., & Smith, E. R. (2015). Intergroup emotions. In M.
Mikulincer, P. R. Shaver, J. F. Dovidio, & J. A. Simpson (Eds.),
APA handbook of personality and social psychology. Vol. 2:
Group processes (pp. 263-293). American Psychological Asso-
ciation. https://doi.org/10.1037/14342-010
Matthews, M., & Levin, S. (2012). Testing a dual process model of
prejudice: Assessment of group threat perceptions and emotions.
Motivation and Emotion,36(4), 564-574. https://doi.org/10.
1007/s11031-012-9280-y
Miles, R., & Brown, M. (2003). Racism (2nd ed.). Routledge.
Moscovici, S. (1987). The conspiracy mentality. In C. F. Graumann
& S. Moscovici (Eds.), Changing conceptions of conspiracy (pp.
151-169). Springer. http://doi.org/10.1007/978-1-4612-4618-3
Neuberg, S. L., & Schaller, M. (2016). An evolutionary threat-
management approach to prejudices. Current Opinion in
Psychology,7, 1-5. http://doi.org/10.1016/j.copsyc.2015.06.004
Nilsson, I., & Ekehammar, B. (1987). Person-positivity bias in
political perception? European Journal of Social Psychology,
17(2), 247-252. https://doi.org/10.1002/ejsp.2420170210
O’Donnell, S. J. (2018). Islamophobic conspiracism and neoliberal
subjectivity: The inassimilable society. Patterns of Prejudice,
52(1), 1-23. http://doi.org/10.1080/0031322X.2017.1414473
Paolacci, G., & Chandler, J. (2014). Inside the Turk: Understanding
Mechanical Turk as a participant pool. Current Directions in
Psychological Science,23(3), 184-188. https://doi.org/10.
1177/0963721414531598
Park, J. H., Schaller, M., & Crandall, C. S. (2007). Pathogen-
avoidance mechanisms and the stigmatization of obese people.
Evolution and Human Behavior,28(6), 410-414. http://doi.org/
10.1016/j.evolhumbehav.2007.05.008
Pew Research Center. (2017a). Americans express increasingly
warm feelings toward religious groups. http://assets.pewre
search.org/wp-content/uploads/sites/11/2017/02/15093007/Feel
ing-thermometer-report-FOR-WEB.pdf
Pew Researc h Center. (2017b). Europe’s growing Muslim population.
https://www.pewforum.org/2017/11/29/europes-growing-mus
lim-population/
Plutchik, R. (1980). Emotion: A psychoevolutionary synthesis.
Harper & Row.
Pratto, F., Sidanius, J., Stallworth, L. M., & Malle, B. F. (1994).
Social dominance orientation: A personality variable predicting
social and political attitudes. Journal of Personality and Social
Psychology,67(4), 741-763. https://doi.org/10.1037//0022-3
514.67.4.741
Riek, B. M., Mania, E. W., & Gaertner, S. L. (2006). Intergroup
threat and outgroup attitudes: A meta-analytic review. Person-
ality and Social Psychology Review,10(4), 336-353. https://doi.
org/10.1207/s15327957pspr1004_4
Rosseel, Y. (2012). lavaan: An R package for structural equation
modeling. Journal of Statistical Software,48(2), 1-36. http://doi.
org/10.18637/jss.v048.i02
Schiffer, S., & Wagner, C. (2011). Anti-Semitism and Islamopho-
bia—New enemies, old patterns. Race & Class,52(3), 77-84.
http://doi.org/10.1177/0306396810389927
Sears, D. O. (1983). The person-positivity bias. Journal of Person-
ality and Social Psychology,44(2), 233-250. https://doi.org/10.
1037/0022-3514.44.2.233
Sibley, C. G., & Duckitt, J. (2008). Personality and prejudice: A
meta-analysis and theoretical review. Personality and Social
Psychology Review,12(3), 248-279. https://doi.org/10.1177/
1088868308319226
Sidanius, J., Cotterill, S., Sheehy-Skeffington, J., Kteily, N., &
Carvacho, H. (2017). Social dominance theory: Explorations
in the psychology of oppression. In C. G. Sibley & F. K. Barlow
(Eds.), The Cambridge handbook of the psychology of prejudice
(pp. 149-187). Cambridge University Press. http://doi.org/10.
1017/9781316161579.008
Steenkamp, J. E. M., & Baumgartner, H. (1998). Assessing mea-
surement invariance in cross-national consumer research.
Journal of Consumer Research,25(1), 78-107. http://doi.org/
10.1086/209528
Swami, V., Barron, D., Weis, L., & Furnham, A. (2018). To Brexit
or not to Brexit: The roles of Islamophobia, conspiracist beliefs,
and integrated threat in voting intentions for the United King-
dom European Union membership referendum. British Journal
of Psychology,109(1), 156-179. http://doi.org/10.1111/bjop.
12252
Thomsen, L., Green, E. G. T., & Sidanius, J. (2008). We will hunt
them down: How social dominance orientation and right-wing
authoritarianism fuel ethnic persecution of immigrants in fun-
damentally different ways. Journal of Experimental Social
Psychology,44(6), 1455-1464. http://doi.org/10.1016/j.jesp.
2008.06.011
Tonidandel, S., & LeBreton, J. M. (2015, June 1). RWA web: A
free, comprehensive, web-based, and user-friendly tool for rela-
tive weight analyses. Journal of Business and Psychology,30,
207-216. https://doi.org/10.1007/s10869-014-9351-z
Uenal, F. (2016a). Disentangling Islamophobia: The differential
effects of symbolic, realistic, and terroristic threat perceptions
as mediators between social dominance orientation and Islamo-
phobia. Journal of Social and Political Psychology,466-90.
https://doi.org/10.5964/jspp.v4i1.463
Uenal, F. (2016b). Islamophobia & Anti-Semitism. Comparing the
social psychological underpinnings of Anti-Semitic and Anti-
Muslim beliefs in contemporary Germany. Islamophobia
Studies Journal,3(2), 35-55.
Uenal, F. (2016c). The “secret Islamization” of Europe: Explor-
ing integrated threat theory for predicting Islamophobic
conspiracy stereotypes. International Journal of Conflict and
Uenal et al. 17

Violence,10(1), 93-108. https://doi.org/10.41119/UNIBI/ijcv.
499
United Nations. (2018, March 6). “No other conclusion,” ethnic
cleansing of Rohingyas in Myanmar continues—Senior UN rights
official. UN News. https://news.un.org/en/story/2018/03/1004232
van Prooijen, J.-W., & Douglas, K. M. (2018). Belief in conspiracy
theories: Basic principles of an emerging research domain. Eur-
opean Journal of Social Psychology,48(7), 897-908. https://doi.
org/10.1002/ejsp.2530
Whitson, J. A., & Galinsky, A. D. (2008). Lacking control increases
illusory pattern perception. Science,322(5898), 115-117. http://
doi.org/10.1126/science.1159845
Wilson, G. D. (1973). The psychology of conservatism. Academic
Press.
Zia-Ebrahimi, R. (2018). When the elders of Zion relocated to
Eurabia: Conspiratorial racialization in antisemitism and Isla-
mophobia. Patterns of Prejudice,52(4), 314-337. https://doi.
org/10.1080/0031322X.2018.1493876
18 Personality and Social Psychology Bulletin XX(X)