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The Sociofunctional Model of Prejudice: Questioning the Role of Emotions in the Threat-Behavior Link

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  • Université de Paris (Paris-descartes)

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The sociofunctional model of prejudice (Cottrell & Neuberg, 2005) states that behaviors toward an outgroup are determined by emotions felt toward this outgroup, and that these emotions are determined by threats this group represents for one’s own group. Although widely cited in literature, this intuitively appealing model is not as supported as it is sometimes assumed. As a matter of fact, seminal data supporting the model have not been replicated, and the mediating role of emotions in the threat-behavior link remains in need of empirical evidence. Two studies were aimed at filling this gap by measuring specific threats, emotions and their associated behavioral intentions. Our results provide mixed support for the sociofunctional. We found evidence of the threat-emotion, the threat-behavior and the emotion-behavior links described in this model, but only partial support for the mediational role of emotion in the threat-behavior link.
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Prejudice has traditionally been defined as a general nega-
tive attitude toward outgroups (Allport, 1954). However,
in previous decades, this view has been criticized for its
inability to capture the diversity of (negative) feelings
observed toward different groups (e.g., Cottrell & Neuberg,
2005; Mackie & Smith, 2003; Smith, 1993). Among these
theoretical proposals, the sociofunctional model of preju-
dice (Cottrell & Neuberg, 2005) provides a fine-grained
analysis of prejudice, with the aim of explaining a large
diversity of feelings and behaviors toward social groups.
Based on an evolutionary approach, this model suggests
that prejudice should be better described as a set of
specific emotions elicited by perceived threats posed by
other groups. Ingroup feelings toward outgroups would
be functional reactions to qualitatively different threats
associated with the outgroup. Rather than a global nega-
tive feeling emerging from a unique global threat, feelings
toward outgroups would be more nuanced and deter-
mined by the specific threat the outgroup represent for
ingroup in the situation. Considering prejudice as a global
negative feeling would thus mask the variety of emotions
felt toward outgroups (e.g., anger, fear, disgust, pity, guilt),
and thus obscure the prejudice-behavior link.
The sociofunctional model identifies a set of five fun-
damental intergroup threats and connects each of them
to a primary functional emotional reaction and its pro-
totypic behavioral motivation. However, although widely
cited in literature, this intuitively appealing model is not
as supported as it is sometimes assumed. Seminal data
supporting the model have not been replicated, and the
mediating role of emotions in the threat-behavior link
remains in need of empirical evidence. The present studies
were aimed at providing a test of the three paths hypothe-
sized by the sociofonctional model, from perceived threats
to behavioral intentions via specific emotions.
The ve threat-emotion-behavior proles
proposed by the sociofunctional model
Regarding the first threat-emotion-behavior profile,
namely the ‘obstacle-anger-aggression’ profile, research
has shown that anger emerges when people are prevented
from attaining their goal (e.g., Berkowitz, 2012) and moti-
vates various aggressive behaviors in order to remove the
obstacle preventing goal achievement (Berkowitz, 2012;
Carver & Harmon-Jones, 2009; Cottrell & Neuberg, 2005).
In this way, Cottrell and Neuberg argues that anger arises
when outgroup is perceived as a threat to ingroup’s goal
achievement, motivating aggressive reactions. The model
identifies six specific threats falling within this framework.
This is the case when the outgroup (1) threatens ingroup’s
economic resources, (2) threatens ingroup property, (3)
threatens personal freedoms and rights, (4) when the
outgroup does not want to reciprocate relationship with
the ingroup, (5) when the outgroup is seen as a threat for
social coordination and finally, (6) when the ingroup does
not trust the outgroup.
The second path is referred to as the ‘contamination-
disgust-rejection’ profile. Disgust arises when people
encounter physical or moral contaminants, resulting in
rejection behavior to protect the self (e.g., Rozin, Haidt, &
McCauley, 1999). The sociofunctional model then argues
that outgroups elicit disgust (1) when they are perceived
Aubé, B., and Ric, F. (2019). The Sociofunctional Model of Prejudice:
Questioning the Role of Emotions in the Threat-Behavior Link.
International Review of Social Psychology
, 32(1): 1, 1–15, DOI:
https://doi.org/10.5334/irsp.169
RESEARCH ARTICLE
The Sociofunctional Model of Prejudice: Questioning
the Role of Emotions in the Threat-Behavior Link
Benoite Aubé and François Ric
The sociofunctional model of prejudice (Cottrell & Neuberg, 2005) states that behaviors toward an
outgroup are determined by emotions felt toward this outgroup, and that those emotions are determined
by threats this group represents for one’s own group. Although widely cited in literature, this intuitively
appealing model is not as supported as sometimes assumed. In fact, seminal data supporting the model
have not been replicated, and the mediating role of emotions in the threat-behavior link remains in need of
empirical evidence. Two studies were aimed at lling this gap by measuring specic threats, emotions and
their associated behavioral intentions. Our results provide mixed support for the sociofunctional model.
We found evidence of the threat-emotion, the threat-behavior and the emotion-behavior links described
in this model, but only partial support for the mediational role of emotion in the threat-behavior link.
Keywords: prejudice; emotions; threats; intergroup relations; replication
Université de Bordeaux, FR
Corresponding author: Benoite Aubé (aube.benoite@hotmail.fr)
Aubé and Ric: A Test of the Sociofunctional Model2
as a source of disease (physical contaminant) or (2) when
they support ideas opposed to those of the ingroup (moral
contaminant; Cottrell & Neuberg, 2005). Both specific
threats would lead to avoidance behaviors or to rejection
of threatening outgroups in order to preclude contamina-
tion (Cottrell & Neuberg, 2005; Neuberg & Cottrell, 2002;
Rozin et al., 1999).
The third profile is the ‘safety-fear-escape’ profile.
Research has shown that fear emerges when people are
physically endangered and this emotional reaction moti-
vates escape behaviors (e.g., Ledoux, 1996). The socio-
functional model suggests that outgroups perceived as
threatening for ingroup’s physical safety elicit fear in
ingroup members that ultimately results in motivation to
escape (Ledoux, 1996; Neuberg & Cottrell, 2002).
According to the ‘reciprocity by inability-pity-prosocial
behavior’ profile, pity arises from an outgroup perceived
as unable to reciprocate intergroup relationships (Cottrell
& Neuberg, 2005). At the behavioral level, pity would lead
to prosocial behaviors (Camps, Stouten, Tuteleers, & van
Son, 2014) in order to improve the ability of the outgroup
members to reciprocate in the future.
Finally, the fifth profile is ‘morality-guilt-repair.’ Cottrell
and Neuberg (2005) argue that guilt is elicited by groups
that represent a threat to the ingroup’s morality, especially
as a result of negative ingroup actions toward this group
(e.g., Branscombe, Doosje, & McGarty, 2002). Because of
outgroup suffering, ingroup members may be motivated
to behave in a way that restores their image of moral
group, such as helping outgroup members (e.g., Ketelaar
& Au, 2003).1
In the first test of their model, Cottrell and Neuberg
(2005) asked Americans students to assess threats and
affective reactions evoked by several social groups. They
observed that, regardless of the group, the set of spe-
cific perceived threats predicted the hypothesized set of
emotions. By demonstrating the threat-emotion profiles,
Cottrell and Neuberg (2005) provided preliminary evi-
dence in support of their model. However, even though
they hypothesized an effect of the threat-emotion profiles
on behavioral intentions toward outgroups, they did not
provide an empirical support to this hypothesis.
In an attempt to fill this gap, several studies have shown
that threat-emotion profiles evoked by groups predicted
policy attitudes (Cottrell, Richards, & Nichols, 2010) or
behavioral intentions toward groups (Johnston & Glasford,
2014; Kamans, Otten, & Gordijn, 2011; Kuppens & Yzerbyt,
2012). For example, when physically threatened by an out-
group, powerless people report being scared and willing to
escape the situation. In contrast, when valuable resources
are threatened, they report anger and intention to con-
front the outgroup (Kamans et al., 2011). Consistent with
the sociofunctional model, this research showed that per-
ceiving a threat to physical safety triggers fear and motive
escape reactions while perceiving a threat to resources
arouses anger feelings and motivate aggression. Moreover,
Johnston and Glasford (2014) showed that different threat-
emotion profiles were related to either passive or active
harm (Cuddy, Fiske, & Glick, 2007). In this study, American
participants evaluated three groups (i.e., activist feminist,
gay men and Mexican Americans) on threats (i.e., obsta-
cle, contamination, physical safety), emotions (i.e., anger,
disgust, fear) and harm (passive and active harm) these
groups represented to American people. Results showed
that the obstacle-anger profile was related to active harm
(i.e., attack, harass) whereas contamination-disgust and
physical safety-fear profiles were related to passive harm
(i.e., exclude, demean). In addition, by showing that each
emotion mediated the expected link between threat and
harm, these findings provide empirical data supporting
the sociofunctional model. However, this research pre-
sents several limitations. First, participants were asked to
respond from the perspective of ‘Americans.’ Such ques-
tions might measure shared knowledge concerning social
group’s profiles rather than individuals’ adhesion to this
knowledge. As a result, it may not be truly indicative of
individual behaviors toward these groups. Then, the
order of threats, emotions and behaviors measures were
presented in a fixed order. It is possible that this presen-
tation format constrained participants’ responses and par-
tially account of the observed relationships between the
constructs.
To our knowledge, no empirical research has thus
far tested the relevance of all threat-emotion-behavior
profiles hypothesized by Cottrell and Neuberg (2005).
Our aim was to provide such a test. To this end, we used
a correlational design similar to the one used by Cottrell
and Neuberg (2005) in which participants were asked to
report the perceived threats posed by groups as well as
their felt emotions toward these groups and their behav-
ioral intentions towards them. These social groups were
selected in order to offer a wide variety of emotional and
behavioral reactions in our population. Although such a
design does not make it possible to test the causal links
hypothesized by the sociofunctional model, it allows cap-
turing a wide range of threats, emotions and behavioral
intentions, and thus their potential links at the individual
level and beyond normative reactions to social groups.
Some of the measures were general and others were
more specific. General measures captured the percep-
tions of social groups on the positive-negative continuum
(i.e., general threat, global prejudice, approach-avoidance
intentions) while specific measures were related to more
fined-grained threats, emotions, and behavioral inten-
tions, as it is described in the sociofunctional model.
We first expected to replicate Cottrell and Neuberg’s
results (2005), namely that each of the five specific threats
should predict the suspected emotion (H1a). However,
our main aim was to test their links with behavioral inten-
tions. We thus hypothesized that each behavioral inten-
tion should predominantly be predicted by one of the
five threats (H1b) and one of the five emotions (H1c) as
described in the sociofunctional model. More importantly,
we tested the five threat-emotion-behavioral intention
profiles by evaluating the mediating role of emotions in
the threat-behavioral intention links (H2). Specifically, we
hypothesized that anger should mediate the link between
obstacle threat and the tendency to aggress outgroup
members (i.e., to remove the obstacle posed by the group;
Carver & Harmon-Jones, 2009). Disgust should mediate
Aubé and Ric: A Test of the Sociofunctional Model 3
the link between contamination threat and the tendency
to reject objects or ideas of outgroup members (i.e., to
minimize contamination; Rozin et al., 1999). Fear should
mediate the link between the threat to physical safety and
the tendency to escape the outgroup (Neuberg & Cottrell,
2002; Ledoux, 1996). Pity should mediate the link between
the threat to reciprocal relationships with the ingroup by
inability and the tendency to act in a prosocial way toward
the outgroup (e.g., by helping them; Camps et al., 2014;
Penner, Dovidio, Piliavin, & Schroeder, 2005). Guilt should
mediate the link between the ingroup’s morality threat
and the tendency to restore balanced relationships with
outgroup members (e.g., by helping them; Ketelaar & Au,
2003). Finally, we tested a secondary hypothesis, namely
if, as predicted by the sociofunctional model, specific emo-
tions are better predictors of behavioral intentions than
global prejudice, then each of the five threat-behavioral
intention links should be better mediated by the predict-
able emotion than by global prejudice (H3).
Unlike Cottrell and Neuberg (2005), it is worth noting
that, in our studies, participants assessed only one social
group. This point is of particular importance as each group
was thus evaluated independently, reducing the influence
of comparison processes and of experimental demand. In
addition, the groups of measures (threats, emotions, and
behavioral intentions) were presented in a random order
for each participant to reduce the likelihood of systematic
measure contamination.
Study 1
Method
Participants
According to Green (1991), the minimum sample size
would require N 50 + 8* number of predictors (here, 5),
that means at least 90 participants for our study. However,
because we had twelve groups to evaluate and wanted
to obtain relatively stable evaluation for each group, we
planned to obtain at least 25 participants per group (for
a total of at least 300 participants). A total of 397 partici-
pants completed the questionnaire. Fifteen were removed
from the sample because they were not native French
speakers. Thirteen other reported not being students and
nine strongly identified to the outgroup they assessed
(i.e., score > 6 on a 9-point scale, see below). Finally, 360
participants were maintained in the sample (325 women;
Mage = 20.25, SDage = 2.90). Twenty-seven to 34 participants
evaluated each group. The proportion of women, χ2 (11)
= 10.20, p = .51, and age, F(11, 348) = 0.38, p = .96, did
not differ between group conditions. Most of participants
were psychology students (95%), the remaining partici-
pants being students in social sciences. They completed
the questionnaire after clicking on a link submitted on the
Facebook pages of psychology students of three French
universities.
Procedure
Participants clicked on the link and then signed a con-
sent form before filling the questionnaire administered
in French. Each participant assessed only one group ran-
domly selected among 10 outgroups (i.e., Africans, Arabs,
Asian French, Unemployed, Homeless people, Right-wing
extremists, Gypsies, Physically disabled people, Obese
people, HIV-positive people) and two ingroups (i.e.,
native-born French people and Students). Pretests showed
that these two ingroups were not perceived as threatening
by French students, and that they globally evoked positive
feelings.
The groups were selected on the basis of the threats
and emotions they convey. We wanted to use a wide range
of social groups in order to obtain various profiles of
threats, emotions, and behavioral intentions. We selected
the groups on the basis of work from public institutions,
associations fighting against prejudice and newspaper
articles. Asian French are stereotypically perceived as pos-
sessing numerous of shops with cheap wear in France,
thus this group should be perceived as threatening for
job or economic resources of French people (because of
perceived unfair competition). Unemployed people are
considered as responsible for their situation, particularly
because they are stereotyped as lazy (Milland & Flament,
2010). Thus, the Unemployed might be perceived as
threatening for reciprocity by choice, as well as for social
coordination and trust relations with the French nation.
Right-wing extremists promote protectionist ideas and
are perceived as racist among students. As a result, they
should be perceived as threatening to rights and liber-
ties, as well as to social coordination and values of French
students. Furthermore, because they are stereotypically
associated with extremist Muslims, Arabs were expected
to be perceived as threatening for physical safety and to
evoke fear (Dotsch & Wigboldus, 2008). Homeless peo-
ple are stereotypically associated with mental illness,
drugs, and alcohol consumption, laziness, and dirt. Thus,
they should be perceived as threatening physical safety
of French students (i.e., ‘they are crazy, thus they can be
violent’). Moreover, they should threaten relations of
reciprocity with French nation because they choose not
to reciprocate (i.e., ‘they are lazy’) or for reasons outside
of their control (i.e., ‘they are crazy’). Finally, they should
be perceived as threatening ingroup health (i.e., ‘they are
dirty’; Harris & Fiske, 2006). Obese people are stereotyped
as dirty and lazy because they are perceived as responsible
for their extra weight. Thus, they should be perceived as
posing a contamination threat via physical contamination
(Rozin et al., 1999) or transmission of poor moral values
(Vartanian, 2010). HIV-positive people suffer a transmit-
table disease. Thus, as they could be contaminant, they
should be perceived as posing a threat to physical health
(Earnshaw, Smith, Chaudoir, Lee, & Copenhaver, 2012)
and hence to physical safety. Gypsies are stereotypically
perceived as thieves and beggars (Guimelli & Deschamps,
2000; Echebarria Echabe & Fernandez Guede, 2006). Thus,
they should be perceived as posing a threat to ingroup
property, physical safety, and ingroup values. Physically
disabled people are perceived as incompetent but coura-
geous (Rohmer & Louvet, 2011). Thus they should evoke
pity because they should be perceived as willing but being
unable to reciprocate equally. Moreover, they have been
shown to evoke disgust because of their physical anomaly
(Park, Faulkner, & Schaller, 2003). Finally, French Africans
Aubé and Ric: A Test of the Sociofunctional Model4
should be perceived as threatening for the perception of
ingroup’s morality. Some African countries were French
colonies, thus current difficulties of Africans people are
often perceived by French people as the results of a long
exploitation of Africans wealth from French government.
It is worth mentioning that we were not interested in
whether each social group evokes the suspected threat,
emotion and behavioral intention. Our aim was instead
to test whether each of the five threat-emotion profiles
evoked by groups predicted behavioral intentions toward
them. Thus our hypotheses focused specifically and
uniquely on the links between several variables character-
izing the selected groups, independently of the specific
group under consideration. In other words, what we were
expecting was to collect reactions to groups evoking a
wide range of threats and emotions, no matter the specific
links between each target group and the threat-emotion-
behavioral intention profiles.
As in Cottrell and Neuberg’s study (2005), the question-
naire included general and specific measures of both per-
ceived threats and emotions to which we added measures
of general and specific behavioral intentions. Items reflect-
ing threats and emotions were adapted from Cottrell and
Neuberg’s work. Each group of measures (threats, emo-
tions, and behavioral intentions) always began with the
general measure that was immediately followed by spe-
cific measures presented in a random order. The same
applies for the order of the group of measures (threats,
emotions, and behavioral intentions) that was randomly
determined for each participant.
Measures of threats
Participants first indicated the extent to which each group
was dangerous and represented a threat for France and
French people (general threat; all responses were given on
9-point scales; 1 = strongly disagree; 9 = totally agree), and
then the extent to which it was perceived as representing
specific threats (all responses were given on 9-point scales;
1 = strongly disagree; 9 = totally agree). For the six obsta-
cle threats, participants indicated the extent to which the
group represented a threat to France and to French peo-
ple concerning jobs and economic resources, properties,
rights and freedoms, reciprocity relations by choice, social
coordination, and trust relations. For the two contamina-
tion threats, participants indicated the extent to which the
group was threatening physical health and values of French
people. For the physical safety threat, participants indicated
the extent to which the group was threatening for physi-
cal safety of French people. For the reciprocity by inability
threat, participants indicated the extent to which the group
threatened the reciprocity of their relationships with French
people due to group’s inability. Finally, for the morality
threat, participants indicated the extent to which the group
was threatening to the morality of French people. Each of
these 11 specific threats was measured with two items.
Measures of aective reactions
Participants indicated the extent to which they were
experiencing each type of emotional feelings when they
were thinking about the social group (9-point scales; 1
= not at all; 9 = extremely). General affect was assessed
by asking participants to indicate the degree to which
they were experiencing positive as well as negative feel-
ings toward the target group through two independent
items. Then participants reported the extent to which
they were feeling specific emotions when thinking about
the target group. Following Cottrell and Neuberg’s proce-
dure (2005), we measured emotions directly relevant for
the sociofunctional model while the other emotions (i.e.,
envy, happiness, respect, contempt, sadness, pride, secu-
rity, and sympathy) were included as filler items to create
a broader context.2
Measures of behavioral intentions
Participants indicated the extent to which they tended to
exhibit each behavioral reactions toward the target group
on 9-point scales (1 = not at all; 9 = extremely). First, partici-
pants indicated the extent to which they tend to approach
and to avoid members of the target group with two inde-
pendent items. Then, we measured more specific behav-
ioral intentions. Participants had to indicate the extent to
which they tend to behave aggressively toward the target
group, to escape the target group, to rejection objects or
ideas from the target group, and to help the target group.
The four broad categories of behavioral intentions were
based on the five threat-emotion profiles proposed by
the sociofunctional model. Because the reciprocity by
inability-pity-prosocial behavior and morality-guilt-repair
profiles involved the same kind of behavior (i.e., help), we
created a common item to measure behavioral intentions
of these two profiles.
Finally, in order to ensure that participants identified
with the ingroups and not with the outgroups, partici-
pants were asked to indicate the extent to which they
were identifying with the outgroup that they were assess-
ing as well as with each of the two ingroups (1 = not at all;
9 = totally).
Results
Data simplication and check
Composite scores and difference scores. In order to make
data processing easier, we created a composite score for
each category of threats, emotions, and behavioral inten-
tions. We first averaged the scores of the 12 items measur-
ing obstacle threats,3 α = .96, to create one composite score.
The same was done with the four items measuring con-
tamination threats,4 α = .76. For the two-item scales, reli-
ability of the measure was estimated by Spearman-Brown
correlations, as recommended by Eisinga, Grotenhuis and
Pelzer (2013). Correlations were significant for the two
items measuring safety threat, rs = .57, p < .001, the two
measuring reciprocity by inability, rs = .26, p < .001, and
the two measuring morality threat, rs = .46, p < .001, cate-
gories. For emotions, we created a score for anger, rs = .33,
p < .0001, and for fear, rs = .59, p < .0001. Disgust, pity, and
guilt, were measured with only one item per emotion. This
was also the case for the four behavioral reactions.
Then, we computed a measure of global prejudice by
subtracting the score of item measuring the general posi-
tive feeling toward the target group from the score of the
item measuring the general negative feeling. The higher
the score, the stronger the global negative prejudice.
Aubé and Ric: A Test of the Sociofunctional Model 5
Finally, we created a global measure of approach-avoid-
ance tendencies by subtracting approach score from the
avoidance one for each target group. The higher the score,
the more the group activate avoidance.
Check of group’s heterogeneity of evaluations. To
ensure that outgroups evoked different patterns of spe-
cific threats, emotions, and behavioral intentions, we
performed three independent ANOVAs by including the
groups and each category of specific measures (perceived
threats, emotions, or behavioral intentions), the last
one being treated as a within-subjects factor. For each
ANOVA, results showed a significant main effect of group,
Fs < 14.17, ps < .001, η2
ps > .26, and of specific measure,
Fs > 60.62, p < .001, η2
ps > .15. Importantly, each interac-
tion reached significance, Fs > 11.86, ps < .001, η2
ps > .27,
indicating that groups evoked different patterns of spe-
cific threats, emotions, and behavioral intentions.
Multiple regression analyses
H1a: from threats to emotions. We regressed each emo-
tion score on the five threat categories simultaneously. As
depicted in Table 1, results showed that each threat cat-
egory predicted the expected emotion, all bs > .13, ts(354)
= 1.95, ps < .05. The results indicate that the links hypoth-
esized by the sociofunctional model are all significant. It
is however worth noting, that as in Cottrell and Neuberg
seminal work (2005, p. 781, Table 5), each threat predict
also other ‘secondary’ emotions. For instance, obstacle
threat category also predicted disgust, fear, and guilt,
bs > |.26|, ts(354) > 2.93, ps < .004. In terms of secondary
emotions, this may be explained by the fact that obstacle
threat is qualified as an obstacle to ingroup’s goal achieve-
ment, a feature that is inherent to many threat categories.
H1b: from threats to behavioral intentions. We per-
formed several multiple regressions with each behavioral
intention as outcome and the five threat categories as pre-
dictors (see Table 2). Results showed that three of the five
threat categories predicted the expected behavioral inten-
tions (obstacle, contamination, morality), bs > .13, ts(354)
= 1.95, ps < .05, the two remaining categories (safety, reci-
procity by inability) were not significant, bs < .11, ps > .09.
Moreover, once again, obstacle threat predominantly
predicted each behavioral reaction, bs > |.26|, ts(354) >
|2.95|, ps < .003.
H1c: from emotions to behavioral intentions. We con-
ducted five multiple regressions by regressing each behav-
ioral intention on the five emotions simultaneously (see
Table 3). Anger, disgust, and fear significantly predicted
respectively aggression, rejection, and escape, bs > .18,
ts(354) > 2.59, ps < .01. However, pity and guilt did not
predict help intentions, bs < .10, ps > .09. Moreover, unlike
previous results, disgust predominantly predicted each
behavioral intention, bs > .28, ts(354) > 4.39, ps < .001.
Mediation analyses
H2: testing the ve threat-emotion-behavioral intention
proles. We first tested a simple mediation model with
5000 bootstrap samples (Preacher & Hayes, 2008) includ-
Table 1: Standardized Regression Coefficients of Each Emotion on Threat Categories in Study 1.
Independent
Variable
Dependent Variable
Anger Disgust Fear Pity Guilt
Obstacle .42*** .33*** .35*** .10 –.26**
Contamination .28*** .31*** .09 .21* .03
Safety –.09 –.02 .13*–.01 .07
Rec. Inability .15*** .15*** .13** .16** .19***
Morality .11** –.05 –.02 .15** .25***
Note. Rec. Inability = Reciprocity by inability threat category. Regression coefficients in boldface type reflect the predictions.
*** p < .001; ** p < .01; * p < .05.
Table 2: Standardized Regression Coefficients of Each Behavioral Reaction on Threat Categories in Study 1.
Independent
Variable
Dependent Variable
Aggress. Rejection Escape Help
Obstacle .52*** .46*** .40*** –.26**
Contamination .16*.29*** .15*–.25**
Safety –.15* –.07 .11 .13
Rec. Inability .08 .15*** .08 –.02
Morality –.02 –.07 –.01 .12*
Note. Rec. Inability = Reciprocity by inability threat category. Aggress. = Aggression. Regression coefficients in boldface type reflect
the predictions. *** p < .001; ** p < .01; * p < .05.
Aubé and Ric: A Test of the Sociofunctional Model6
ing the general threat as predictor, the global prejudice
as mediator and approach-avoidance index as outcome.
Results showed that general threat significantly pre-
dicted global prejudice, b = 1.23, t(357) = 18.06, p < .001,
η2
p = .48, and approach-avoidance index, b = 0.91, t(357)
= 11.79, p < .001, η2
p = .28. Moreover, the mediating effect
of general prejudice emerged, b = 0.81, 95% CIs [0.68,
0.95], indicating that the greater the general threat, the
more participants expressed negative feelings and the
more they tended to avoid the target group. This finding
reflects the basic view of general prejudice. However, our
aim was to go one step further by exploring the role of
specific emotions in the threat-behavior link. To this end,
we tested a multiple mediation model with 5000 boot-
strap samples (Preacher & Hayes, 2008) for each hypoth-
esized threat-emotion-behavior profiles described in the
sociofonctional model.
The threat predictor, the behavioral intention outcome,
and the five emotions mediators were included in the
model (see Figure 1). The benefit of this method is that
it allows testing the mediational weight of each emo-
tion in the threat-behavior link. Indeed, we expected that
each specific threat would guide the behavioral inten-
tion toward group through a specific emotion. However,
because perception of a specific threat can imply the
presence of another threat (e.g., threat to health implies
a threat to physical safety), it is possible, as we have
observed in the previous analyses, that a single threat
elicits a main emotion as well as other secondary emo-
tions (Cottrell & Neuberg, 2005; Neuberg & Cottrell,
2002). Thus, one may suspect that secondary emotions
have played a major mediating role in the expected
threat-behavior link. Multiple mediation model bypasses
this problem by controlling all mediators included in the
model.
We first analyzed the obstacle-anger-aggression pro-
file. Obstacle threat was found to predict anger, b = 0.63,
t(353) = 14.82, p < .001, η2
p = .38, and aggression, b =
0.50, t(353) = 12.90, p < .001, η2
p = .32. However, anger
did not mediate the threat-aggression link, b = 0.03, 95%
CIs [–0.04, 0.12], while, surprisingly, disgust did, b = 0.09,
95% CIs [0.01, 0.18]. No other mediating effect emerged,
bs < 0.05, 95% CIs [–0.02, 0.13].
Then, we analyzed the contamination-disgust-rejection
profile. Contamination threat was found to significantly
predict disgust, b = 1.07, t(353) = 13.83, p < .001, η2
p = .35,
and rejection, b = 1.25, t(353) = 15.60, p < .001, η2
p = .41.
Moreover, the expected indirect effect of disgust emerged,
b = 0.42, 95% CI [0.25, 0.62]. The greater the threat to
contamination, the more disgust was experienced, and
the more participants tended to reject the outgroup. Note
that fear also mediated the contamination-rejection link,
b = 0.10, 95% CI [0.00, 0.62]. The remaining mediating
effects did not emerge, bs < |0.06|, 95% CIs [–0.09, 0.21].
For the safety-fear-escape profile, safety threat signifi-
cantly predicted fear, b = 0.70, t(353) = 10.64, p < .001, η2
p
= .24, and escape, b = 0.86, t(353) = 11.41, p < .001, η2
p =
.27. As expected, the mediating effect of fear emerged, b =
0.21, 95% CI [0.11, 0.34]. The greater the threat to physical
safety, the more fear was felt, and the more participants
tended to escape the outgroup. However, we also observed
an unexpected indirect effect of disgust, b = 0.32, 95% CI
[0.21, 0.46]. No other effect was significant, bs < |0.02|,
95% CIs [–0.11, 0.07].
For the reciprocity by inability-pity-help profile, reci-
procity by inability threat was found to significantly pre-
dict pity, b = 0.23, t(353) = 4.23, p < .001, η2
p = .05, but
did not predict help, b = –0.08, p = .13. We thus stopped
mediation analysis.
For the last morality-guilt-help profile, threat to moral-
ity was found to significantly predict guilt, b = 0.25, t(353)
= 5.75, p < .001, η2
p = .08, and to marginally predict help,
b = 0.10, t(353) = 1.85, p = .06, η2
p = .01. However, guilt
did not mediate the morality-help link, b = 0.02, 95% CI
[–0.01, 0.06], whereas fear did, b = –0.02, 95% CI [–0.05,
0.00]. The stronger the morality threat, the more people
were afraid and the less they were willing to help the out-
group. No other mediating effect emerged, bs < |0.02|,
95% CIs [–0.04, 0.06].
H3: testing the global prejudice vs. emotion as pre-
dominant mediator. We performed five multiple media-
tions (one for each profile) by including the specific threat
as predictor, the specific behavioral intention as outcome,
and the global prejudice and the predictable emotion
as mediators (the other emotions were not included to
avoid multicollinearity problems). Results showed that
anger was a better predictor of aggression intention than
global prejudice, banger = 0.13*/bprej = 0.09* (coefficients
with * sign have CI positive limits). However, for the four
other profiles, the global prejudice better mediated the
Table 3: Standardized Regression Coefficients of Each Behavioral Reaction on Emotions in Study 1.
Independent
Variable
Dependent Variable
Aggress. Rejection Escape Help
Anger .18*.16*.00 .06
Disgust .28*** .48*** .46*** –.37***
Fear .20** .17** .33*** –.14*
Pity –.09 –.12*–.03 .01
Guilt –.05 .00 –.04 .10
Note. Aggress. = Aggression. Regression coefficients in boldface type reflect the predictions. *** p < .001; ** p < .01; * p < .05.
Aubé and Ric: A Test of the Sociofunctional Model 7
threat-behavioral intention links compared to the emo-
tion, bdisg. = 0.27*/bprej = 0.32*; bfear = 0.22*/bprej = 0.27*;
bpit = 0.01/bprej = –0.36*; bguilt = 0.01/bprej = 0.02.
Discussion
The present study partially replicated Cottrell and Neu-
berg’s findings (2005), by showing that each threat sys-
tematically predicted the expected emotion. However,
results are somewhat obscured by the predominance of
obstacle threat in predictions of emotions and behavio-
ral intentions. It is worth noting that this result was also
observed in the work by Cottrell and Neuberg (2005).
Moreover, regression analyses showed that threats and
emotions only partially predicted expected behavioral
intentions. It is possible that the absence of relationships
comes from the quality of the items. Some formulations of
Figure 1: Multiple mediators models in Study 1 with threat categories as predictors, specific emotions as mediators,
and behavioral intentions as outcomes. Threat-emotion-behavior path in bold are derived from the sociofunctional
model. Regression coefficients are unstandardized. ***p < .001, **p < .01, *p < .05.
Aubé and Ric: A Test of the Sociofunctional Model8
items were quite direct and probably hurt the sensitivity
of participants. Consequently, they could have chosen the
lowest points of the scales (e.g., safety items, M = 1.81, SD
= 1.41) that would have not happened if the items were
phrased in a more socially acceptable manner.
Regarding mediational analyses, the data provide
relatively weak support to the sociofunctional model.
The results showed that (1) only two out of the five pro-
files emerged (i.e., contamination-disgust-rejection and
safety-fear-escape) and (2) except for the obstacle-anger-
aggression profile, global prejudice better mediated the
threat-behavioral intention links than emotion. One
might argue that these mixed findings could be due to
methodological limitations. We measured behavioral
intentions with four items (aggression, rejection, escape,
help) that have been created from the five specific emo-
tions included in the model. However, by condensing the
behavioral intentions into four broad categories, we poten-
tially missed some of the behavioral intentions. Second,
IP addresses were not registered. Therefore, we could not
rule out the possibility that participants answered the
questionnaire several times. Third, some emotions were
measured with two items (i.e., fear and anger) but others
were measured with only one item (i.e., disgust, pity, and
guilt), which could cast doubt on the reliability of these
measures. To address all of these issues, we conducted a
second study.
Study 2
This study followed the methodology of Study 1. The study
measured the same perceived threats, specific emotions
and behavioral intentions toward the same groups as the
previous study. Some items were modified for a better
understanding but the content remained very similar to
Study 1. Moreover, we measured more specific behavio-
ral intentions. These items were inspired by unpublished
items sent to us by the authors of the model. Finally, emo-
tions were all measured with two items. We expected to
find all the threat-emotion-behavior profiles described in
the sociofunctional model.
Method
Participants
To estimate the sample, we applied the same method as
in Study 1. A total of 384 questionnaires were completed.
When a same IP address appeared twice, we only the first
response was included in the sample thus, excluding there-
fore 41 participants. Moreover, 14 participants reported
not to being students and 12 strongly identified to the
outgroup they assessed (i.e., score > 6 on a 9-point scale).
Finally, 317 participants were maintained in the sample
(289 women; Mage = 21.28, SDage = 4.54). The proportion of
women, χ2 (11) = 14.33, p = .21, and age, F(11, 305) = 0.72,
p = .71, did not differ between group conditions. Most of
participants were psychology students (91%), the remain-
ing participants were students from social sciences.
Procedure
To start the questionnaire, participants clicked on a link
posted on the Facebook pages of French psychology stu-
dent groups and signed a consent form. Twelve groups
were evaluated (i.e., Africans, Arabs, Asian French, Unem-
ployed, Homeless people, Right-wing extremists, Gypsies,
Physically disabled people, Obese people, HIV-positive
people, native-born French people, and Students). The
questionnaire is presented in Appendix.
Measure of threats
After the general threat, the eleven specific threats were
each measured with two items (presented in a random
order). Specific threats were those described by the socio-
functional model (see Study 1). All threats were measured
on a 9-point scale (1 = strongly disagree; 9 = totally agree).
Measures of aective reactions
Participants first indicated their general affect (two posi-
tive and two negative feelings items) toward the target
group. Then, they indicated the extent to which they were
feeling specific emotions about the target group (9-point
scale; 1 = not at all; 9 = extremely). Items were presented
in a random order. Emotions were the same as in Study 1
(anger, disgust, fear, pity, guilt for target emotions; envy,
happiness, respect, hurt, sadness, pride, security, and sym-
pathy for filler items), all measured with two items.
Measures of behavioral intentions
Participants first indicated the extent to which they exhib-
ited general positive and negative behavioral intentions
toward the target group with two items for each inten-
tion. Then, we measured behavioral intentions associated
with the 11 specific threats with two items for each (pre-
sented in a random order). Participants answered with
9-point scales (1 = strongly disagree; 9 = totally agree).
Finally, as in study 1, we measured participants iden-
tification to ingroups and to the outgroup they assessed
(1 = not at all; 9 = totally).
Results
Data simplication and check
Composite scores and difference scores. As in Study 1,
we created a composite score for each category of threats,
emotions, and behavioral intentions. For obstacle threats,
we averaged the scores of the 12 specific threats to cre-
ate one unique score (α = .95).5 The same procedure was
used for the 12 items of behavioral intentions linked to
obstacle threat (α = .84). For contamination threat, the
two items reflecting the threat to health, rs = .44, p < .001,
and the 2 items reflecting the threat to values, rs = .71,
p < .001, were averaged. The same was done for behav-
ioral intentions linked to contamination threat (behavio-
ral intentions linked to health threat, rs = .67, p < .001;
behavioral intentions linked to values threat, rs = .32,
p < .001).6 Moreover, correlations between items measur-
ing the threat of reciprocity by inability and their asso-
ciated behavioral intentions were significant but really
weak (rss = |.14|, ps = .01). Thus we decided to exclude
these data from all analyses. Finally, the two scores of
each remaining threat (i.e., rs-safety = .55 and rs-morality = .40,
ps < .0001), each associated behavioral intention (i.e.,
respectively, rs = .52 and rs = .27, ps < .0001) and each
emotion (i.e., rs-fear = .73 and rs-guilt = .57, p < .0001) were
independently averaged.
Aubé and Ric: A Test of the Sociofunctional Model 9
Then we computed scores of general measures. The
scores of items measuring general threat, negative feel-
ings, positive feelings, negative behavioral intentions
(rss > .69, ps < .0001) and positive behavioral intentions
(rs = .36, ps < .0001) were independently averaged to cre-
ate several composite scores, ps < .001. Finally, we sub-
tracted the positive feelings score (approach intentions)
toward the target group from the score of the item meas-
uring negative feelings (avoidance intentions). The higher
the score, the stronger the global negative prejudice (the
avoidance intention).
Check of group’s heterogeneity of evaluations. To
ensure that outgroups evoked different patterns of spe-
cific threats, emotions, and behavioral intentions, we
performed three independent ANOVAs by including the
groups and each type of specific measures (perceived
threats, emotions or behavioral intentions), the last one
being treated as a within-subjects factor. For each ANOVA,
results showed a main effect of groups, Fs > 9.50, p < .001,
η2
ps > .35, and a main effect of specific measure, Fs >
94.99, ps < .001, η2
ps > .24. Importantly, each interaction
was significant, Fs < 10.50, ps < .001, η2
ps > .27, attesting
to the diversity of threats, emotions, and behavioral inten-
tions evoked by the groups.
Multiple regression analyses
H1a: from threats to emotions. We conducted five mul-
tiple regressions by regressing each emotion score on the
five threats simultaneously. As depicted in Table 4, results
showed that each threat predicted the expected emotion,
bs > .18, ts(311) = 3.52, ps < .001, except for values threat
that was not significant, b = .11, p = .16. Again, some
threats also predict other ‘secondary’ emotions such as the
obstacle threat which predicted disgust and fear.
H1b: From threats to behavioral intentions. Multiple
regressions of each behavioral reaction of the five threats
showed that each threat predicted the expected behavioral
intention, bs > .27, ts(311) = 5.42, ps < .001 (see Table 5).
H1c: From emotions to behavioral intentions. We
regressed each behavioral intention on the four emotions
predictors simultaneously. Results showed that each emo-
tion predicted four of the five expected behavioral inten-
tions, bs > .27, ts(311) = 5.22, ps < .001 (see Table 6). The
only exception was the disgust-reaction to values threat
link that was not significant, b = .08, p = .23. Unexpectedly,
anger strongly predicted behavioral intention linked to
values threat, b = .11, t(311) = 7.60, p < .001. This could
mean that value rejection would be a form of more pas-
sive (more socially acceptable) form of aggression.
Mediation analyses
H2: Testing the threat-emotion-behavioral intention
proles. As in Study 1, we first performed a simple media-
tion model with 5000 bootstrap samples (Preacher &
Hayes, 2008) including the general threat as predictor,
the global prejudice as mediator and approach-avoidance
index as outcome. Results showed that the general threat
significantly predicted global prejudice, b = 1.39, p < .001,
Table 4: Standardized Regression Coefficients of Each Emotion on Threat Categories in Study 2.
Independent
Variable
Dependent Variable
Anger Disgust Fear Guilt
Obstacle .49*** .24*.18*.02
Health .12** .18** .16** –.07
Values .25*** .11 .12 –.13
Safety .02 .17*.35*** .07
Morality –.04 .02 –.02 .30***
Note. Regression coefficients in boldface type reflect the predictions. *** p < .001; ** p < .01; * p < .05.
Table 5: Standardized Regression Coefficients of Each Behavioral Intention on Threat Categories in Study 2.
Independent
Variable
Dependent Variable
Aggress. Phys.
rejection
Values
rejection
Escape Repair
Obstacle .63*** –.19 .28** .25*–.29**
Health .11** .43*** –.01 .03 .02
Values .10 –.02 .43*** –.13 –.14
Safety .05 .19*–.00 .39*** .01
Morality –.07*.06 –.03 .13** .27***
Note. Aggress. = Aggression. Phys. rejection = Physical rejection. Regression coefficients in boldface type reflect the predictions.
*** p < .001; ** p < .01; * p < .05.
Aubé and Ric: A Test of the Sociofunctional Model10
η2
p = .48, and approach-avoidance index, b = 1.20, p <
.001, η2
p = .36. Moreover, the indirect effect of general
prejudice emerged, b = 1.08, 95% CI [0.92, 1.26], indi-
cating that the greater the general threat, the more par-
ticipants expressed negative feelings and the more they
tended to avoid the target group. Then we performed mul-
tiple mediation analysis with the threat as predictor, the
behavioral intentions as outcomes, and the four emotions
as mediators (see Figure 2).
We started with the obstacle-anger-aggression profile.
The obstacle threat was found to predict anger, b = 0.94,
t(311) = 20.55, p < .001, η2
p = .57, and the related behavio-
ral intention, b = 0.57, t(311) = 23.40, p < .001, η2
p = .64.
However, the mediating effects of anger, b < –0.00, 95%
CI [–0.07, 0.07] or of other emotions, bs < 0.04, 95% CIs
[–0.03, 0.10], did not emerged.
Then, the subsequent analysis showed that the health
threat predicted disgust, b = 0.73, t(311) = 7.55, p < .001, η2
p
= .15 and the related behavioral intention, b = 0.27, t(311)
= 8.35, p < .001, η2
p = .18. Importantly, the expected medi-
ating effect of disgust emerged, b = 0.20, 95% CI [0.08,
0.38]. The greater number of people who see a threat to
ingroup health, the more disgust the participants experi-
enced, and the more participants tended to reject physical
contact with the outgroup. Unexpectedly, the mediating
effect of anger, b = –0.25, 95% CI [–0.40, –0.14], and fear,
b = 0.15, 95% CI [0.05, 0.29], also emerged. Thus, it seems
that when participants felt threatened by contamina-
tion, they felt angry and the less they tended to aggress
the outgroup. This is a mean of avoiding any contact with
outgroup. The same could be argued for fear: The more
participants felt threatened by contamination, the more
they felt afraid and the more they tended to avoid the out-
group. No other mediating effect emerged, b = –.01, 95%
CI [–0.03, 0.00].
For the values-disgust-rejection profile, the threat pre-
dicted disgust, b = 0.51, t(311) = 9.58, p < .001, η2
p = .23,
and the expected behavioral intention, b = 0.58, t(311) =
15.55, p < .001, η2
p = .44. However, the mediating effect
of disgust did not emerge, b = 0.03, 95% CI [–0.02, 0.09].
Interestingly, anger was the only significant mediating
effect, b = 0.13, 95% CI [0.03, 0.23], indicating that the
more participants perceived a threat to ingroup values,
the more they were angry and desired to attack the out-
group. The remaining mediating effects were not signifi-
cant, bs < |0.03|, 95% CIs [–0.09, 0.04].
For the physical safety-fear-escape profile, the threat sig-
nificantly predicted fear, b = 0.74, t(311) = 14.32, p < .001,
η2
p = .40, and escape intentions, b = 0.45, t(311) = 10.55, p
< .001, η2
p = .26. Moreover, the expected mediating effect
of fear emerged b = 0.22, 95% CI [0.13, 0.32]. The more
participants felt threatened for ingroup safety, the more
they experienced fear and the more they are motivated
to escape the outgroup. Unexpectedly, anger also played
a mediating role, b = –0.12, 95% CI [–0.21, –0.03]. This
effect indicates that the more participants perceived a
threat to safety, the more they felt angry and the less they
tended to escape the outgroup. This could denote a par-
ticipant’s willingness to challenge the outgroup. No other
effect emerged, bs < |0.01|, 95% CIs [–0.05, 0.09].
Finally, the morality threat significantly predicted guilt,
b = 0.21, t(311) = 5.47, p < .001, η2
p = .09, and repair inten-
tions, b = 0.22, t(311) = 4.78, p < .001, η2
p = .07. Moreover,
as expected, the mediating effect of guilt emerged, b =
0.05, 95% CI [0.03, 0.09], indicating that the more people
saw a threat to their moral image, the more they felt guilty
and the more they engaged in repair behaviors. No other
effects were significant, bs < 0.01, 95% CIs [–0.03, 0.03].
H3: testing the global prejudice vs. emotion as pre-
dominant mediator. As in Study 1, we tested five multi-
ple mediation models (one for each profile) by including
the specific threat as predictor, the specific behavioral
intention as outcome and both global prejudice and the
predicted emotion as mediator. Results showed that for
the health-disgust-rejection, the security-fear-escape and
the morality-guilt-repair profiles, the predictable emo-
tion better mediated the threat-behavioral intention
link than global prejudice, bdisgust = 0.20*/bprej = –0.07*;
bfear = 0.21*/bprej = –0.03; bguilt = 0.05*/bprej = 0.02 (coef-
ficients with * sign have CI positive limits). By contrast,
for both obstacle-anger-aggression and values-disgust-
rejection profiles, global prejudice was a better mediator
than the predictable emotion, banger = –0.03/bprej = 0.12*;
bvalue-disg. = –0.01/bprej = 0.16*.
Discussion
The results of Study 2 enlighten and complete those
observed in Study 1. We again observed that threat cat-
egories globally predicted the related emotion (except for
values threat, see below) as well as the related behavioral
intention. Moreover, each emotion predicted behavioral
intentions. Those findings provide support for the pro-
Table 6: Standardized Regression Coefficients of Each Behavioral Intention on Emotions in Study 2.
Independent
Variable
Dependent Variable
Aggress. Phys.
rejection
Values
rejection
Escape Repair
Anger .42*** –.37*** .51** –.13 –.28***
Disgust .12*.41*** .08 .06 –.07
Fear .20*.34*** .03 .56*** .01
Guilt –.09*.04 –.08 .10*.27***
Note. Aggress. = Aggression. Phys. rejection = Physical rejection. Regression coefficients in boldface type reflect the predictions.
*** p < .001; ** p < .01; * p < .05.
Aubé and Ric: A Test of the Sociofunctional Model 11
files described in the sociofunctional model. Though not
the focus of this paper, we observe also that secondary
emotions emerged, as predicted by the sociofunctional
model. For example, obstacle threats predicted not only
anger, but also fear and disgust (Cottrell & Neuberg, 2005).
However, the results of the mediation analyses test-
ing more directly the hypothesized profiles are mixed.
Three of the five mediations succeeded but two failed.
Specifically, disgust mediated the health-rejection link,
fear mediated the physical safety-escape link and guilt
mediated the moral-repair link. Importantly, global preju-
dice did not overtake the mediating role of the emotions.
In contrast, as in Study 1, anger did not mediate the obsta-
cle-aggression link. This result is of prime importance for
the sociofunctional model, and will be further discussed
in the General Discussion section.
Figure 2: Multiple mediators models in Study 2 with threat categories as predictors, specific emotions as mediators,
and behavioral intentions as outcomes. Threat-emotion-behavior path in bold are derived from the sociofunctional
model. Regression coefficients are unstandardized. ***p < .001, **p < .01, *p < .05.
Aubé and Ric: A Test of the Sociofunctional Model12
In addition, disgust did not mediate the values-rejec-
tion link. This could mean that disgust measures were
too broad and did not differentiate physical disgust from
moral disgust. Physical disgust occurs to protect the self
from potential diseases contamination (Haidt, Rozin,
McCauley, & Imada, 1997; Neuberg, Kenrick, & Schaller,
2011) whereas moral disgust refers to moral violation
(Haidt et al., 1997). Consequently, physical disgust should
occur when people perceive a threat to ingroup health
whereas moral disgust should arise when people perceive
a threat to moral values. However, it is worth noting that
if the literature supports the hypothesis that physical dis-
gust triggers rejection, this is not the case for the impact of
moral disgust. Some argue that moral disgust is an exten-
sion of physical disgust (Rozin, Haidt, & McCauley, 1999)
while others relate moral disgust to anger and thus to
aggression behaviors (Jones, 2007; Lee & Ellsworth, 2013).
Our results would support the second option since they
suggest that a threat of values-rejection is linked to anger.
As a result, our measures of anger may have captured the
moral disgust feelings of participants that could not have
been expressed in disgust measures. This explanation
remains speculative and in need of further investigations.
Finally, we acknowledge that low correlations for some
two items measures (e.g., the two items measuring the
threat to moral values or those measuring behavioral
intentions linked to morality threat) may be perceived as
limitations of our findings. However, for correlations infe-
rior to .40, we performed additional statistical analyses
with the most prototypic item of the measured construct.
Globally, results are similar to those presented in the core
text and does not change conclusions.
General Discussion
The aim of the present studies was to provide a complete
test of the sociofunctional model. In support of the model,
the findings first showed that (a) perceived threats predict
the hypothesized emotions, (b) perceived threats predict
hypothesized behavioral intentions and (c) emotions pre-
dict hypothesized behavioral intentions, as described in
this model. These results replicate those of Cottrell and
Neuberg (2005) and go one step further by providing evi-
dence for the presently untested links between threats,
emotions and behavioral intentions. Moreover, while the
general threat-prejudice-behavioral intention profile pre-
dicted by the traditional views of prejudice emerged, our
results showed that more specific measures better predict
specific behavioral intentions (and ultimately, should bet-
ter predict discriminatory behaviors).
The results on the mediations hypothesized by the
socio functional model received only mixed support.
In Study 1, only two mediations emerged and emotion
better mediated the link between threat and behavioral
intention for only one mediation. The results of Study
2 provided clearer evidence, but for only three profiles:
health-disgust-rejection, safety-fear-escape, and the moral-
guilt-repair. Interestingly, in this second study, emotions
predicted behavioral intentions to a greater extent than
global prejudice did. These findings support the emo-
tional prejudice view that claims that emotions measures
capture a diversity of (negative) feelings toward outgroups
that global prejudice measures obscure. The differences
of results between the two studies moreover suggest that
small variation in either the population and/or the mate-
rial used to measure threats, emotions, and behavioral
intentions can have a dramatic impact on the findings.
Small differences with the original results can also be due
to the non-comparative context of our research which
contrasts with the one designed by Cottrell and Neuberg
in which participants were evaluating all the groups and
thus probably engage in comparison processes, some-
thing that is less likely here (i.e., participants evaluated
only one group).
One particularly surprising result is related to the obsta-
cle-anger-aggression profile. As expected, the threat-emo-
tion, the threat-behavior, and the emotion-behavior links
were significant. However, the emotional mediation failed
in both studies and global prejudice better mediated the
obstacle-aggression link in Study 2. Why did it fail? A first
possibility could be related to the use of self-reported
measures. The self-reported methodology is useful to test
the model as a whole with minimal materials. These meas-
ures are supposed to reflect the reactions that participants
would have in real life when encountering outgroup mem-
bers. However, aggressive behaviors are socially undesira-
ble and thus their expression can be highly constrained by
social desirability. Although our experimental conditions
have been optimized to reduce social desirability bias (e.g.,
study conducted on internet, anonymity), one cannot be
sure that participants were honest or able to truly report
what their reactions would be in situation. This analysis
raises the question of the relevance of self-reported meth-
odology for the obstacle profile, and more generally the
hypotheses derived from this model. More engaging situ-
ations including measures of actual behaviors should pro-
vide a better context to test these hypotheses. We should
note however that, although possible, such an explanation
is rather unlikely. If participants were controlling their
responses, we should not get any link between threats and
emotions, between threats and behavioral intentions, and
between emotions and behavioral intentions. Moreover,
this explanation should also be true for emotions like dis-
gust or fear. However, these profiles all emerged making
such explanation unlikely.
Another explanation refers to the validity of the model.
Although the obstacle profile seems correct at the theo-
retical level, it might not exist in real life. Two studies are
not enough to conclude definitively on this issue, and an
absence of results is not compelling evidence. However,
these results raise concerns about this profile and by
extension, about the contribution of the model as a
whole. This is especially true because we have attempted
to improve the methodology of previous studies by ran-
domizing all measures groups, as well as all items within
each group, and by having participants evaluate a unique
group (instead of all in the original study), thus precluding
comparison effects. Since the publication of this model,
little research has been conducted including the behavio-
ral component of the model (Johnston & Glasford, 2014;
Kamans et al., 2011; Kuppens & Yzerbyt, 2012). Thus, rep-
lications of the present studies are needed to conclude
about the obstacle-anger-aggression profile.
Aubé and Ric: A Test of the Sociofunctional Model 13
Then, our results differed from prediction of the model
regarding both the health and the moral values profiles.
While the tenants of the sociofunctional model aggre-
gate these profiles in one contamination-disgust-rejection
profile, our findings show that they may refer to two dis-
tinct profiles. Specifically, unlike the health profile, anger,
and not disgust, mediated the link between moral values
threat and moral rejection. As already mentioned, threat
to moral values could trigger moral disgust while threat
to health would trigger physical disgust (Simpson, Carter,
Anthony, & Overton, 2006). Since moral disgust resembles
anger (Lee & Ellsworth, 2013), this is not surprising that
anger rather than disgust was found to mediate the link
between values threat and moral rejection. On this basis,
we explored whether anger was better at mediating the
threat-behavioral intention link than global prejudice.
This was not the case. Thus, although moral disgust resem-
bles anger, it is probably not the same. Future research on
prejudice linked to disgust should however differentiate
between physical and moral disgust to clarify this point.
Finally, our data remain silent about the reciprocity
by inability-pity-prosocial behaviors profile. It is worth
mentioning that items reflecting this kind of threat were
extremely difficult to formulate, even with the help pro-
vided by the authors of the model. Thus, it is possible
that we failed to capture this threat. Another possibility is
that the relevance of this threat depends on the cultural
context. The original data were collected in the USA when
this threat could be more important than in France, where
the two studies were run.
To sum up, the present studies replicate basic find-
ings of the model on the threat-emotion links (Cottrell
& Neuberg, 2005) and successfully show the direct links
between threats (emotions) and behavioral intentions.
Regarding mediation analyses, findings only partially
support the threat-emotion-behavioral intention profiles
as described in the sociofunctional model. Even if the
health-disgust-rejection, the safety-fear-escape, and the
moral-guilt-repair profiles emerged, the obstacle-anger-
aggression profile failed. This gap raises a question about
the validity of the model because this profile involves the
majority of the specific threats listed in the model (i.e., 6
on 11 specific threats). Thus, future research will have to
check the validity of this profile, as well as the conditions
that make such a profile emerge, or whether it should be
considered as a theoretical mirage. Although the results
of these studies are interesting by themselves, we must
acknowledge that our reliance on a correlational design
and on the self-reported measures limit our conclusions
about the causal role of threat and the mediational role of
emotions. Thus, an important next step for this research
would be to more appropriately test the hypothesized
causal chain by manipulating the treat and measuring
actual, instead of reported, behavior.
Notes
1 These five profiles represent prototypical reactions
to perceived threat posed by outgroups. It is worth
noting that secondary emotions (with the resulting
emergence of secondary behavioral motivation) can
also emerge when the perceived threat implies the
presence of another threat (see Cottrell & Neuberg,
2005). For instance, a threat of contamination, leading
to disgust, should also imply a threat to move freely
(due to potential contamination) which would induce
anger (and potential aggressive tendencies) toward
members of the outgroup. However, these secondary
emotions are beyond the scope of this article and will
not be exposed in details.
2 Anger and fear were each measured with two items. In
contrast, disgust, pity, and guilt were each measured
with only one item because of an error (that was cor-
rected in Study 2).
3 We performed a principal component analysis that
showed that the 12 items saturated on one unique fac-
tor explaining 70, 33% of the total variance.
4 Again, we performed a principal component analysis.
Results showed that two factors emerged explaining
respectively 54% and 31% of the total variance. Vari-
max rotation showed that 3 of the 4 items saturated
on the first factor. However, one of the health items
weakly saturated one this factor (.07). After exclusion of
this item (see Item Health 1 in Appendix 1), one unique
factor emerged explaining 68% of the total variance.
5 For each category of items, we performed a principal
component analysis. For obstacle category, results
revealed one main factor explaining 66% of variance
(saturation coefficients > .59). For behavioral inten-
tion linked to obstacle threat, one main factor explain-
ing 39% of variance (saturation coefficients > .32).
6 A principal component analysis performed for con-
tamination category showed that two factors emerged
explaining respectively 54% and 28% of the variance,
corresponding to the threat to health and the threat
to values. This was the same for behavioral intention
linked to contamination threat. Results revealed two
factors explaining respectively 46% (behavioral inten-
tion linked to health threat factor) and 30% of variance
(behavioral intention linked to values threat factor).
Additional File
The additional file for this article can be found as follows:
Appendix. Items of perceived threats, emotions and
behavioral intentions in Study 2. DOI: https://doi.
org/10.5334/irsp.169.s1
Competing Interests
The authors have no competing interests to declare.
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How to cite this article: Aubé, B., and Ric, F. (2019). The Sociofunctional Model of Prejudice: Questioning the Role of Emotions
in the Threat-Behavior Link.
International Review of Social Psychology
, 32(1): 1, 1–15, DOI: https://doi.org/10.5334/irsp.169
Published: 10 January 2019
Copyright: © 2019 The Author(s). This is an open-access article distributed under the terms of the Creative Commons
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