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A generalized climate of distrust in political institutions is not functional to healthy democracies. With the advent of social media, recent scholarly efforts attempt to better understand people's conspiracy theory beliefs in inhibiting institutional trust. This study contributes to this literature by considering the direct antecedent effects of uncertainty avoidance and the moderating role of active social media use—SMU (i.e., interactional SMU, informational SMU, and political expressive SMU). The former is theorized to enable conspiracy theories to thrive, while the latter should cushion the negative effects of conspiracy beliefs on institutional trust. Relying on diverse survey data across different cultures from Europe, the Americas, and New Zealand (N = 11,958) and applying structural equation modeling, findings supported the hypothesized model. In high uncertainty‐avoidance societies, where less well‐known situations are perceived as uncomfortable or downright threatening, conspiracy beliefs proliferate and negatively impact institutional trust. Active SMU attenuates these effects. Via social media, citizens have the ability to strengthen social relationships (interactional SMU), keep themselves informed about the community (informational SMU), and engage in political self‐expression (political expressive SMU), which mitigate conspiracy‐belief negative effects on institutional trust. Future research implications and key limitations of the study are all discussed.
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Political Psychology, Vol. 0, No. 0, 2021
doi: 10.1111/pops.12754
0162-895X © 2021 The Authors. Political Psychology published by Wiley Periodicals LLC on behalf of International Society of Political Psychology
Published by Wiley Periodicals, Inc., 350 Main Street, Malden, MA 02148, USA, 9600 Garsington Road, Oxford, OX4 2DQ,
and PO Box 378 Carlton South, 3053 Victoria, Australia
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any
medium, provided the original work is properly cited.
Conspiracy Theories and Institutional Trust: Examining the Role
of Uncertainty Avoidance and Active Social Media Use
Silvia Mari
University of Milano- Bicocca
Homero Gil de Zúñiga
University of Salamanca
Pennsylvania State University
Universidad Diego Portales
Ahmet Suerdem
Istanbul Bilgi Universitesi
Katja Hanke
University of Applied Management Studies
Gary Brown
Royal Holloway University of London
Roosevelt Vilar
Massey University - Albany Campus
Diana Boer
University Koblenz- Landau, Campus Koblenz
Michal Bilewicz
University of Warsaw
A generalized climate of distrust in political institutions is not functional to healthy democracies. With the
advent of social media, recent scholarly efforts attempt to better understand people’s conspiracy theory beliefs
in inhibiting institutional trust. This study contributes to this literature by considering the direct antecedent
effects of uncertainty avoidance and the moderating role of active social media use— SMU (i.e., interactional
SMU, informational SMU, and political expressive SMU). The former is theorized to enable conspiracy theories
to thrive, while the latter should cushion the negative effects of conspiracy beliefs on institutional trust. Relying
on diverse survey data across different cultures from Europe, the Americas, and New Zealand (N= 11,958)
and applying structural equation modeling, findings supported the hypothesized model. In high uncertainty-
avoidance societies, where less well- known situations are perceived as uncomfortable or downright threatening,
bs_bs_banner
2Mari et al.
conspiracy beliefs proliferate and negatively impact institutional trust. Active SMU attenuates these effects. Via
social media, citizens have the ability to strengthen social relationships (interactional SMU), keep themselves
informed about the community (informational SMU), and engage in political self- expression (political expressive
SMU), which mitigate conspiracy- belief negative effects on institutional trust. Future research implications and
key limitations of the study are all discussed.
KEY WORDS: conspiracy beliefs, institutional trust, digital influence, social media use, cultural uncertainty avoidance
A significant body of literature argues for greater attention to the study of trust in political
institutions (e.g., Fukuyama, 1995; Putnam, 2001). Numerous scholars have also found that low
and sometimes decreasing levels of trust in many democratic institutions is becoming a widespread
conundrum (e.g., Twenge, Campbell, & Carter, 2014). Building citizens’ trust is fundamental to the
development and the consolidation of democracy, and the erosion of Institutional Trust (IT) may
endanger established democracies and the system of government. Detecting antecedents that may in-
hibit trust and identifying possible mechanisms to counteract these negative effects are increasingly
becoming vital. This article seeks to contribute to this goal. Primarily, the current study focuses on
a specific ITreducing factor: the tendency to believe in conspiracy theories (e.g., Douglas, Sutton, &
Cichocka, 2017). We examine how conspiracy beliefs (CBs), a mindset guiding attitudes and behav-
ior, may contribute to corrosion of trust in specific democratic institutions. The link between CBs
and trust is not novel in the social- psychological research, but trust is usually operationalized in this
literature at the interpersonal level, as trust in people at large (Abalakina- Paap, Stephan, Craig, &
Gregory, 1999). Because of a prevalent notion that CBs are trivial and inoffensive, research focusing
on the consequences of CBs, and its role on reducing IT, has largely been scarce (see Jolley, Mari,
& Douglas, 2020). CBs may feed into a climate of suspicion, which can destroy social capital, and
contributes to a general climate of distrust to pervade society at large, negatively affecting public
opinion’s views on political and government institutions.
First, this article considered the effects of culture in a cross- country sample of 11 democracies
and examined how a distrusting climate for democratic institutions promoted by CBs might hinge on
cultural values. Specifically, we theorized cultures with high uncertainty avoidance (Hofstede, 2001),
where less well- known situations are perceived as uncomfortable or downright threatening, may
harbor higher endorsement of beliefs in conspiracy theories and a stronger link between conspiracy
theories and IT. Second, the article aims to examine whether social media use (SMU) moderates the
CBs- IT relationship. It is well recognized that the Internet and social media have been involved in
the spread of CBs (Del Vicario et al., 2016). However, the role of Internet and social media should
not be monolithically considered negative per se. Rather, with respect to SMU, motives driving
Internet use represent significant individual differences (Gil de Zúñiga, Huber, & Strauß, 2018). For
instance, three specific ways of using social media are important positive predictors of prodemocratic
outcomes. As detailed later, interactional SMU explains social capital and informational and news
gathering, along with politically expressive online behaviors associated with political participation
(see Gil de Zúñiga, Molyneux, & Zheng, 2014; Yamamoto, Kushin, & Dalisay, 2015). We hypothe-
size that these forms of SMU, conceived as indicators of a general propensity towards active SMU
(Yu, 2016), buffer the CBs effects on IT.
Understanding Institutional Trust
Trust is a multidimensional construct. However, a definitional consensus has not yet been reached
(PytlikZillig & Kimbrough, 2016). McKnight and Chervany (2001), for instance, distinguished
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Conspiracy Theories and Institutional Trust
trust according to its target. In dispositional trust, the direct target is people in general, while in
institution- based trust— the focus in this study— the direct target is the environmental structure: po-
litical institutions.
Even though previous scholarship highlighted the gradual decrease in trust over time (Putnam,
2001), some authors have also debunked this decline as a myth. Indeed, some evidence shows that,
at least in Europe, the level of political trust has been generally low, with some fluctuations over
time due to prevalent political discourses not describing a stable decreasing trend (van de Walle, van
Roosbroek, & Bouckaert, 2008). In any case, to establish a civil society, building institutional trust
is viewed as essential, since it may promote collective participation in political, economic, and social
institutions and foster community involvement (Fukuyama, 1995; Putnam, 2001). Higher levels of
trust, additionally, may foster better provision of public services and encourage democratic practices
of cooperation and compliance without relying on coercion. Institutional distrust, on the other hand,
can hinder the success of policymaking, as showed also by the recent pandemic (Devine, Gaskell,
Jennings, & Stoker, 2020).
Drawing from the literature describing trust as an expectation of goodwill or benign intent from
the target of trust (Yamagishi & Yamagishi, 1994), Liu and colleagues (2018) developed the Global
Trust Inventory, a reliable instrument capable of measuring trust both within and across cultures.
Trust is conceptualized as a “system of meaning that encompasses both the sub- components of and
an overall grasp of the risks of opening oneself up to a range of dependencies on others” (p. 790).
In this interpretation, trust ranges from trust at the level of close interpersonal relationships up to
trust in local, national, and international bodies. The authors also differentiated trust in government
between representative (and thus partisan) institutions and order/implementation (impartial) insti-
tutions. Specifically, they developed a seven- factor model of trust, including— most relevant to the
current study— three targets of trust in governing institutions: trust in government, referring to the
representative/partisan governing bodies; trust in order/implementation government bodies (such as
the judiciary and election outcomes); and trust in security institutions (police and military). In the
current study, we will consider specifically trust in these institutions, since they cover a variety of
authorities at the country- level important for the effective functioning of a democracy (see Rothstein
& Stolle, 2008).
Some forms of trust are performance based, where citizens develop trust toward the institutions
that are perceived as effective, based on the assessment of past accomplishments (van de Walle &
Bouckaert, 2003). Askvik, Jamil, and Dhakal (2011) also described a social- identity- based form of
trust, which refers to institutions that are perceived to represent the interests and values of a specific
group in society. Other literature has focused on understanding the social, economic, and political
circumstances that can explain the shifts in trust over time (e.g., PytlikZillig et al., 2017). Here, we
argue that as IT is susceptible to individuals’ perception of sociopolitical climate: CBs endorsements
may impact overall IT levels.
Conspiracy Beliefs
Conspiracy theories may be defined as the tendency to explain prominent political and societal
events (e.g., the death of an eminent person) as due to a malevolent plot by hidden, powerful agents
aimed at some goal through systematic deception (e.g., Douglas et al., 2017; Goertzel, 1994). In
the social- psychology literature, CBs are generally measured through self- reported agreement with
a list of specific conspiracies. Research, however, has shown that endorsing one conspiracy theory
reinforces other conspiratorial ideas, enhancing the likelihood that one who believes in a specific
conspiracy will also believe in other conspiracies (Goertzel, 1994; Lewandowsky, Oberauer, &
4Mari et al.
Gignac, 2013), even despite the fact that these beliefs may contradict one another (Wood, Douglas,
& Sutton, 2012).
Subscribing to conspiracy theories can impact people in many ways (Jolley et al., 2020 for a
review). Along with research indicating some positive consequences of CBs, such as increase in
openness to political debate and attention to contradictions (e.g., Clarke, 2002), research has also
shown negative consequences of CBs, mainly linked to the political sphere (Ardèvol- Abreu, Gil de
Zúñiga, & Gámez, 2020; Thórisdóttir, Mari, & Krouwel, 2020). For instance, suspicious climate that
is generated by endorsing CBs can produce political disengagement (Lewandowsky et al., 2013),
violent political reactions (Mari et al., 2017), and even lower people’s intention to vote after expo-
sure to a conspiracy theory about government (Jolley & Douglas, 2014). Conspiracy theories may,
indeed, have insidious effects of which the individual may not be completely aware of (Douglas &
Sutton, 2008).
Conspirational processes may be informative about the origins of trust and distrust towards tar-
get political institutions. Research shows that conspiracy ideation may be characterized by a general
opposition to the mainstream, or distrust of society at large (Lewandowsky et al., 2013). Relevant
theoretical work maintains that in such beliefs, antiauthoritarian ideation is predominant, focusing
on challenging dominant societal power structures and providing counter- narratives to mainstream
understandings of the world (Harambam & Aupers, 2015; Sapountzis & Condor, 2013). Bartlett
and Miller (2010) asserted that, like populism more broadly, conspiracy theories serve to disrupt the
trust between people and their governments. This empirical link has also been established by other
experimental work. For instance, the presentation of a movie describing the moon landing as a gov-
ernmental plot diminished trust in government officials (Kim & Cao, 2016). Not only that, exposure
to conspiracies also augmented disillusionment with politicians and scientists (Jolley & Douglas,
2014). Thus, in line with these observations, we hypothesized that:
H1: The endorsement of general belief in conspiracy theories will be negatively associated to
trust toward specific governmental institutions (see Figure1 for theoretical model).
Figure 1. Summary of the main hypotheses.
Institutional
Trust
H2
H1
Conspiracy Beliefs Representative
Government
Security
System
Government
Bodies
Interactional
SMU
government
Informational
SMU Espressive
SMU
Active SMU
Cultural Index:
Uncertainty
Avoidance
H3
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Conspiracy Theories and Institutional Trust
Conspiracy Theories and Institutional Trust in the Digital Era
Aupers (2012) argued that “conspiracy culture evolved over the last decades from a deviant,
exotic phenomenon to a mainstream narrative that has spread through the media and is increasingly
normalized, institutionalized and commercialized” (p. 24). The Internet and social media may enable
minority ideas, like unverified rumors and conspiratorial ideas, to avoid being smothered by majority
social pressure or being filtered by mainstream media. False information, developed for minority
audiences, is particularly pervasive on social media, fostering collective credulity. Del Vicario and
colleagues (2016) showed that online social media enables the aggregation of people around com-
mon interests, worldviews, and narratives, acting as echo chambers with potential deleterious effects
on communities’ political polarization and trust. Thus, a deeper and balanced reflection on how new
technologies may inform debate is necessary, going beyond enthusiastic rhetoric describing how the
Internet and social media have contributed to interest in political debate (e.g., Bekkers, Beunders,
Edwards, & Moody, 2011).
Against this general trend in the literature, this study argues that certain specific active forms of
SMU, which tend to promote political engagement (Gil de Zúñiga et al., 2014), are able to cushion
the detrimental effects of CBs on IT. Indeed, research considering social media an extension of ev-
eryday life has shown that SMU may bring citizens into contact with the political realm and foster
a common sense of civic identity (Dahlgren, 2009). Interestingly, Yu (2016) distinguished between
passive and active forms of SMU. The former refers to content consumption not involving direct
interaction with others (e.g., reading posts), whereas active SMU involves content production (e.g.,
posting comments) that facilitate social interaction. Yu found that active SMU, conceived as self-
expression, was a positive driver of political participation. Civic engagement is strictly connected
to trust— both interpersonal and institutional— restoring a sense of community (Miranti & Evans,
2019) that helps satisfying basic needs, like social belonging and existential security need, some-
times eroded when subscribing to CBs (Douglas et al., 2017). Extending these observations, we
hypothesized that active SMU forms might be beneficial in counteracting the negative effects of CBs,
as contributing to the creation of social inclusion.
Here, we will focus on three specific types of active SMU as a possible buffer (i.e., moderator) of
the CBs- IT link. Zeroing in on the motivational bases of active SMU, Correa and colleagues (2010)
noted that people may approach the Internet and social media with different motivations, and these
count for more than the affordances of technology alone. Some people may use them to simply stay
in contact and interact with other individuals, thus contributing to creating a form of online social
capital (interactional motive) (Ardèvol- Abreu, Diehl, & Gil de Zuniga, 2018). According to Lin
(2008), the latter refers to the “resources embedded in one’s social networks, resources that can be
accessed or mobilized through ties in the network” (p. 51), and is useful to achieve personal goals.
Other people may want instead to use social media to actively stay informed about news and public
affairs (Huber, Gil de Zúñiga, Diehl, & Liu, 2019), thus having the chance to be exposed to dissimilar
political views and enriching openness of information (informational motive). The opportunity to re-
ceive such a large amount of information enhances the chance to be exposed to political information,
which in turn may promote an expressive motive of SMU (Yamamoto et al., 2015). Online political
expression, which serves identity motives, can take the form of forwarding e-mails and sharing or
commenting on information about politics and current events (Gil de Zúñiga, Diehl, Huber, & Liu,
2019).
Consumption of public- affairs information is positively associated with higher trust, whereas
consumption of information loosely available on social media is linked to lower trust levels (Ceron,
2015). Drawing from these observations, we reasoned that in the general population, those who
are motivated to use the Internet and social media in an active way (i.e., for interactional, infor-
mational, or expressive purposes), might be more trusting in institutions. Thus, we hypothesized
6Mari et al.
the moderation effect of an overall Active SMU factor (see Figure1) on the negative relationship
between CBs and IT (H2):
H2: For people engaging more (vs. less) in active SMU, the adverse effect of conspiracy beliefs
on IT might be then attenuated.
Indeed, the ability of people to build on relationships with others (interactional SMU), to keep
themselves informed about their community (informational SMU), and to engage in political self-
expression (expression SMU) might contribute to reducing the general suspicious atmosphere. The
individual may perceive themself as more included and supported by their community, thus contrib-
uting to less distrust towards authorities.
The Role of Culture: Uncertainty Avoidance
The theoretical SMU connections just described are generally conceived to fit people living in
democratic societies where access to social media allows active and free involvement in political
affairs (e.g., Loader & Mercea, 2011). However, some differences in the endorsement of CBs might
be ascribed to culture, a factor still overlooked in CBs literature (see, e.g., Troian et al., 2020 for
an exception). Hence, we also took into consideration the role of uncertainty avoidance (Hofstede,
2001) as a potential cultural source of CBs.
Hofstede’s (2001) conceptualization of culture has attained prominence in cross- cultural re-
search (Taras, Kirkman, & Steel, 2010). Among the six cultural value dimensions he proposed,
uncertainty avoidance refers to “the extent to which the members of a culture feel threatened by
uncertain or unknown situations” (Hofstede, 2001, p. 161; see also Hofstede, Hofstede, & Minkov,
2010). Cultures with high uncertainty avoidance tend to define a clear set of beliefs and rules that
seek to prevent ambiguous situations, and they do not tolerate unconventional behaviors. At the other
end of the spectrum, cultures with low uncertainty avoidance tend not to make efforts to eliminate
uncertainty, since they positively value a flexible future and reflect a more relaxed attitude to norma-
tive situations (Smith, 1992).
It stands to reason that a cultural preference for reducing uncertainty is likely to encourage the
endorsement of conspiracy theories, as this type of conspiratorial beliefs yield a nuanced way to deal
with unclear situations. Belief in conspiracy theories may fulfill existential motives (Douglas et al.,
2017), by managing uncertainty or anxiety over the external environment (Grzesiak- Feldman, 2013).
After all, trusting an unknown interaction partner implies a willingness to accept vulnerability in
dealing with such a target (Hetherington, 2005), therefore contributing to uncertainty acceptance.
We expect that:
H3: A high level of uncertainty avoidance within a culture might exert a negative influence on
IT, reducing it directly and indirectly, through the mediation of CBs.
All hypotheses presented are summarized in Figure1.
Method
The present data collection is part of a wider international cross- cultural study, the Digital
Influence Project, involving 22 countries from five continents. In the current study, we considered
only the data of 11 democracies, described culturally as relatively homogenous including Western
(European or Anglo countries) and Latin American societies, with all a Christian background.
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Conspiracy Theories and Institutional Trust
Additionally, since the importance of considering cross- culturally valid measures, we selected those
countries where the used measure of institutional trust was already proven to be cross- culturally valid
(Liu, Milojev, Gil de Zúñiga, & Zhang, 2018). We did not select the data from East Asian societies,
as the trust structure does not equate to those of Western societies (Zhang et al., 2019). The selected
items were translated from English into the country’s language, when necessary, by a panel of par-
ticipating scholars, who applied either the back translation (Behling & Law, 2000) or the committee
approach (Brislin, 1980). Data collection was conducted in September 2015, by a professional poll-
ing company, Nielsen, which provided the online panels in all involved countries through Qualtrics
(2014) software. In each country, a stratified quota sampling was employed. Gender, age, and geo-
graphic area were stratified such that sample demographics were representative for these variables
(e.g., matched the official census statistics).
The final sample includes N=11,958 (52.3% women, 2.1% missing values) participants, whose
average age was M=43.76, years SD= 15.71 (range 18– 94years). The represented 11 democra-
cies were: Argentina, Brazil, Chile, Spain, Italy, Poland, Estonia, Germany, New Zealand, United
Kingdom, and the United States. The demographics relative to each country are summarized in upper
panel of Table2.
Measures
From the Digital Influence Project, we selected the following self- report measures. Furthermore,
we tested measurement invariance for the key concepts, including SMU and IT, which we claimed
to be multidimensional. We employed the multigroup CFA (MGCFA) approach with R packages
Lavaan (Rossel, 2012), semTools (semTools Contributors, 2016), and MPlus 7 (Muthén & Muthén,
1998– 2012).
Conspiracy Beliefs
Drawing on previous research (Rose, 2017; Swami et al., 2016; see Ardèvol- Abreu et al., 2020),
three items measure a general conspiratorial vision of the world: “When one looks at the bigger pic-
ture, it is easy to see that many seemingly unrelated events form part of a larger plan, orchestrated
by powerful others acting in secrecy”; “Many significant world events have occurred as a result of
a conspiracy”; “Despite what the authorities say, large business and/or government routinely en-
gage in sinister, secret activities in the name of profit.” The items were pretested for comprehension
and cross- cultural validity in a cross- cultural pilot study carried out within the Digital Influence
Project. Participants answered on a 7- point agreement scale, ranging from 1=Completely disagree,
to 7=Completely agree. Overall Cronbach’s alpha was good (.81), ranging from .73 to .86 in coun-
try subsamples. We tested the three- item CBs scale for measurement invariance with MGCFA; de-
tails are presented in Table1 (upper panel). Full configural and metric invariances were reached.
Although rejecting full scalar invariance, by introducing cultural- specific modifications, we were
able to establish partial scalar invariance, which justifies mean comparisons (Fischer & Karl, 2019).
These findings confirm the good cross- cultural properties of the scale.
Active Social Media Use
The items of active SMU were adapted from previous research (Gil de Zúñiga et al., 2014) and
were introduced by the following statement: “People use social media for a variety of things. Listed
below are some more activities you may or may not have engaged in. Please tell us how often you
have been involved in the past twelve months in the following activities.” A list of activities followed,
8Mari et al.
which were conceived to measure three factors of active SMU: (1) SMU for active interaction (online
social capital) four items, e.g., “To find people to solve problems in my community”; (2) SMU for
information, three items, e.g., “To stay informed about current events and public affairs”; (3) SMU
for political expression, six items, e.g., “Posting or sharing thoughts about current events or politics.
Respondents answered on a 7- point frequency scale, ranging from 1=Never, to 7=All the time, with
2=Rarely, 3=Somewhat rarely, 4=Occasionally, 5=Somewhat frequently, 6=Frequently. The
three factors of SMU had a very good reliability: interactional SMU, overall alpha=.96 (range from
.94 to .97 in country subsamples), informational SMU, overall alpha=.88 (range from .79 to .91),
and political expressive SMU, overall alpha=.93 (range from .90 to .96). Measurement invariance
across countries for a three- factor structure was tested, and scalar invariance was established, as
shown in Table1 (middle panel), confirming the cross- cultural validity of the scale. Additionally, on
the whole sample, the three- factor model [χ2 (65)=4968.92, p<.001, RMSEA=.084, CFI=.966],
was compared to an alternative one- factor solution, where all the SMU items loaded on a single fac-
tor. The latter solution, however, obtained unsatisfactory fit indexes, χ2 (62)=38,540.45, p<.001,
RMSEA=.229, CFI=.731.
Institutional Trust
We used nine items relative to the trust toward fundamental state institutions. The items were
introduced by the following instructions: “Please rate your feelings of trust towards the following
people and organizations using the scale below.” Participants answered on a 7- point scale, ranging
from 1=Do not trust at all to 7=Trust completely. Then a list of state institutions followed, repre-
senting three factors: (1) Trust in Representative Government specified by three items, National
government, Local government, Prime Minister/President (partisan governing bodies); (2) Trust in
Governing Bodies, specified by four items, Judiciary, Government surveillance agencies, election
outcomes, tax system (nonpartisan government bodies); (3) Trust in Security forces, specified by two
Table 1. Measurement Invariance Across Countries: Conspiracy Beliefs Scale, Active Social Media Use Scale (Three-
Factor Model), and Institutional Trust Scale (Three- Factor Model)
Models χ2 (df) RMSEA Δχ2 (Δdf) CFI (ΔCFI)
Conspiracy Beliefs Scale
1. Configural invariance
(accept)
3.048 (1) .044 1.00
2. Metric invariance (accept) 180.092 (31) .067 177.044 (30) .99 (.01)
3. Scalar invariance (reject) 1201.949 (61) .132 146.96 (30) .89 (.10)
4. Partial scalar invariance
(accept)
370.005 (51) .076 113.042 (10) .97 (.02)
Active Social Media Use Scale, Three- Factor Model
1. Configural invariance
(accept)
6522.0 (682) .092 .957
2. Metric invariance (accept) 6996.9 (782) .088 474.9 (100) .955 (.003)
3. Scalar invariance (accept) 9045.0 (882) .095 2048.1 (100) .940 (.014)
Institutional Trust, Three- Factor Model
1. Configural invariance
(accept)
3737.0 (264) .114 .944
2. Metric invariance (accept) 4550.1 (324) .114 813.11 (60) .931 (.012)
3. Scalar invariance (reject) 7542.8 (384) .136 2992.65 (60) .884 (.048)
Note In the test of invariances level: accept=acceptance of invariance; reject=rejection of invariance.
Abbreviations: CFI, comparative fit index; RMSEA, root mean square error of approximation; Δ, the change in value com-
pared to previous model.
9
Conspiracy Theories and Institutional Trust
Table 2. Descriptive Statistics for the Country Subsamples and the Overall Samples
Variables
Country
Argentina Brazil Chile Estonia Germany Italy New Zealand Poland Spain
United
Kingdom United States Total Sample
N1145 1086 964 1168 1093 1041 1157 1060 1019 1064 1161 11,958
% Women 50.6 48.6 49.7 48.2 50.3 54.1 56.0 52.9 51.7 53.4 58.9 53.5
M SD M SD M SD M SD M SD M SD M SD M SD M SD M SD M SD M SD
Age 40.76 14.30 35.87 12.04 35.05 13.10 47.80 17.15 45.10 15.07 41.72 13.15 59.54 17.32 41.96 14.51 40.94 12.63 50.61 15.60 49.76 16.43 43.76 15.71
Socioeconomic
status
5.56 1.47 5.06 1.68 5.09 1.61 5.60 1.59 6.29 1.93 5.68 1.60 5.40 1.90 4.71 1.66 5.25 1.60 5.18 1.95 5.46 1.93 5.39 1.77
Conspiracy
beliefs
4.68 1.45 4.47 1.36 4.61 1.49 4.26 1.29 4.11 1.34 4.40 1.47 4.01 1.38 4.41 1.28 4.59 1.49 4.12 1.34 4.02 1.39 4.33 1.41
Interactional
SMU
3.33 1.69 4.03 1.70 3.53 1.68 2.47 1.34 2.62 1.67 3.50 1.72 2.47 1.46 3.32 1.58 3.27 1.69 2.21 1.55 2.38 1.53 2.99 1.70
Informational
SMU
4.52 1.44 5.08 1.26 4.77 1.32 4.11 1.54 3.56 1.71 4.38 1.46 3.63 1.59 3.94 1.41 4.18 1.56 3.01 1.75 3.41 1.72 4.04 1.64
Expressive SMU 2.98 1.54 3.47 1.57 3.01 1.50 2.02 1.06 1.90 1.32 2.96 1.57 2.01 1.21 2.66 1.47 2.98 1.53 1.96 1.39 2.21 1.39 2.55 1.51
Uncertainty
avoidance
index
86.00 / 76.00 / 86.00 / 60.00 / 65.00 / 75.00 / 49.00 / 93.00 / 86.00 / 35.00 / 46.00 / 68.29 18.33
Government trust 2.42 1.36 1.90 1.22 2.67 1.23 3.62 1.17 3.21 1.51 2.42 1.33 3.20 1.36 2.43 1.28 2.32 1.21 2.94 1.43 2.97 1.31 2.75 1.40
Government bod-
ies’ trust
2.58 1.24 2.54 1.29 2.95 1.29 4.13 1.32 3.58 1.33 2.99 1.35 3.96 1.32 2.98 1.32 3.04 1.31 3.65 1.41 3.30 1.29 3.26 1.41
Security system
trust
3.01 1.37 2.99 1.49 3.99 1.57 4.68 1.24 3.98 1.48 4.02 1.62 4.65 1.34 3.68 1.42 3.88 1.57 4.20 1.45 4.49 1.45 3.97 1.56
10 Mari et al.
items, Police and Military. The three factors of IT had a good reliability: trust in government, overall
alpha= .87 (range from .78 to .94 in country subsamples), trust in governmental bodies, overall
alpha=.86 (range from .82 to .87), trust in security, overall alpha= .77 (range from .69 to .77).
Additionally, as shown in Table1 (lower panel), we could establish metric invariance for this three-
factor scale which allows testing all correlation- based analyses.1 Also in this case, on the whole
sample, the hypothesized three- factor model, χ2 (17)=1292.61, p<.001, RMSEA=.082, CFI=.975,
was compared to and found superior to a one- factor solution, with all the trust items loading on a
single factor, which obtained poor fit indexes, χ2 (20)=5748.23, p<.001, RMSEA=.160, CFI=.889.
To sum up, results of measurement invariance tests showed that it is possible to make meaning-
ful mean comparisons for the CBs and SMU scales, and meaningful correlation- based analysis that
involves IT, across all societies.
Demographics
Along with age (in years) and gender (0 = men, 1 = women) of participants, we considered also
a measure of subjective social status, assessed through a single item: “On a scale of 1 to 10, with 10
being the people who are the most well off, and 1 being the people who are the least well off, where
would you describe your position?”
Cultural Uncertainty Avoidance
This index was gathered directly from the website of cultural values by Hofstede et al. (2010).
Within the same country, every respondent was assigned with the same index value, which was avail-
able for all the 11 considered countries (see Table2).2
Results
Descriptive Statistics and Correlations
Table2 summarizes the descriptive statistics of the key variables for the country subsamples
and the overall sample. Results showed that in each country, all participants slightly endorsed CBs
(i.e., they slightly agreed with the statements; ts<.01, from the midpoint 4), except for New Zealand
(95% CI: −07, .09) and the United States (95% CI: −06, .10), where the sample mean is not different
than the neutrality point (neither agree/nor disagree). Since we obtained scalar invariance for CBs
and SMU scales, we were able to run ANOVAs to compare means directly. Findings showed some
differences on the CBs means, F(10, 11,886)=33.68, p <.001, η2 = .03, with Argentina, Chile,
and Spain presenting the highest levels. When considering SMU, an ANOVA showed that Brazilian
participants reported the highest level in the three different types of use: for interactional SMU,
F(10, 11,875)=152.13, p<.001, η2=.11; for informational SMU, F(10, 11,875)=175.56, p<.001,
η2=.13; for expressive SMU, F(10, 11,875)=164.39, p<.001, η2=.12.
When considering correlations, the three factors of active SMU were positively intercorrelated
but distinct (the confidence interval built around the correlation values were far from including 1),
as well as the three factors of IT (see Table3). Additionally, CBs were significantly correlated with
all the considered variables. Importantly, the correlations between the CBs with the three dimensions
1The near scalar equivalence reported by Liu et al. (2018) was not required for present purposes as these do not involve mean
level comparisons across cultures for trust.
2We employed this method since the number of countries in the sample is not considered sufficient to apply hierarchical linear
modeling (see e.g., Bryan & Jenkins, 2015).
11
Conspiracy Theories and Institutional Trust
Table 3. Correlation Matrix Among Key Variables
Variables
1 2 3 4 5 6 7 8 9 10 11
1. Gender (0=men,
1=women)
1
2. Age −.102*** 1
3. Socioeconomic
status
−.039*** −.029*** 1
4. Conspiracy beliefs −.009 .009 −.100*** 1
5. Social media use:
Interaction
−.051*** −.151*** .085*** .107*** 1
6. Social media use:
Information
.072*** −.215*** .082*** .115*** .655*** 1
7. Social media
use: Political
expression
−.051*** −.191*** .074*** .120*** .680*** .555*** 1
8. Uncertainty avoid-
ance index
−.023* −.269*** −.062*** .138*** .269*** .262*** .244*** 1
9. Trust in
government
−.077*** .111*** .241*** −.215*** .050*** .037*** .026* −.196*** 1
10. Trust in govern-
ment bodies
−.070*** .128*** .241** −.258*** −.018 −.013 −.045*** −.221*** .737*** 1
11. Trust in security
system
−.056*** .167*** .151*** −.152*** −.035** .008 −.067*** −.200*** .496*** .661*** 1
*p<.05; **p<.01; ***p<.001.
12 Mari et al.
of IT were all negative, thus confirming Hypothesis 1. Further simple regression analyses, realized
on the 11 country subsamples, with CBs as the independent variable, showed its significant negative
effects in almost all the regressions, with the following exceptions: in Argentinean and Brazilian
subsamples regression coefficients for predicting both trust in representative government and trust
in the security system were not significant; in the Chilean subsample, predicting trust in the security
system was nonsignificant (see Table4).
Testing of Active Social Media Use’s Moderation
To test the main study hypothesis (H2), we tested a moderation model using structural equation
modeling (SEM). The hypothesis proposed that the effect of CBs toward institutional (dis)trust would
be moderated by active SMU. Here, the dependent variable, IT, was conceived as a latent factor, with
three different indicators: representative government, government bodies, and security- system trust.
Likewise, active SMU was modeled as a latent factor with three indicators (see Figure1) corre-
sponding to the three different forms of SMU: interactional, informational, and expressive SMU.
Consequently, the interaction term between CBs and active SMU was conceived as a latent factor
with three indicators as well. We added gender, age, and socioeconomic status as control covariates
even though this was not the central focus of the study. The analyses were run by implementing a
SEM model in R packages Lavaan (Rossel, 2012) and semTools (semTools Contributors, 2016)
using 1,000 bootstrapped samples for each.
The moderation SEM model fit the data very well: χ2 (56)=2268.785, p<.001, RMSEA=.059,
CFI=.955. Table5 presents the factor loadings of the latent constructs: All the indicators fit the
respective factor consistently and in a homogenous way. Table6 illustrates the results of the SEM
moderation model. The independent variable CBs was a negative predictor of IT whereas the la-
tent construct of active SMU was a positive predictor. The resulting latent factor of the interaction
between active SMU and CBs was significantly positive. The explained variance of the dependent
variable accounted for by the whole model was .162. We compared this model with a nested model
that did not include the interaction term [χ2 (32)=1796.835, p<.001, RMSEA=.074, CFI=.949],
finding that the latter performed worse than the hypothesized SEM moderation model. Furthermore,
Table 4. Conspiracy Beliefs as Determinant of Institutional Trust: Regression Analyses in Country Subsamples
Independent Variable:
Conspiracy beliefs
Dependent Variable
Trust in Representative
Government Trust in Governing Bodies Trust in Security System
Country Subsamples Βst R2Βst R2Βst R2
Argentina .003 .001 −.078** .006 −.018 .001
Brazil −.039 .002 −.082** .007 .015 .001
Chile −.126*** .016 −.103*** .011 −.024 .001
Estonia −.395*** .156 −.472*** .223 −.273*** .074
Germany −.201*** .041 −.232*** .054 −.150*** .022
Italy −.241*** .058 −.283*** .080 −.182*** .033
New Zealand −.253*** .064 −.315*** .099 −.246*** .061
Poland −.211*** .044 −.248*** .062 −.121*** .015
Spain −.177*** .031 −.200*** .040 −.122*** .015
United Kingdom −.188*** .035 −.238*** .057 −.133*** .018
United States −.226*** .051 −.262*** .069 −.113*** .013
**p < .01.
***p<.001.
13
Conspiracy Theories and Institutional Trust
the inspection of chi- square difference in nested models revealed that the additional path of the inter-
action term was significantly predictive of IT: χ2d(28)=471.95, p<.001.
The inspection of the interaction (Figure2) involved the estimate of conditional effects at three
values of the moderator: the mean, one standard deviation above the mean, and one standard de-
viation below the mean, using 1,000 bootstrapped samples. Findings revealed that the conditional
effect of CBs on representative government trust was negative at any level of the moderators and
significantly different from zero at α=.05, given the absence of zero from each bootstrap 95% con-
fidence interval (95% CI). For strong conspiracy theory believers, the negative effect of CBs on the
general latent factor of IT is reduced when people were also more active social media users. Finally,
the three control covariates (Table 6) all had a significant effect: older people, men, and higher
socioeconomic- status participants trusted their country’s governing institutions more.
Testing of Cultural Effects
Building on the previously tested moderation model, we inspected the effect of Hofstede’s un-
certainty avoidance index (H3), hypothesizing an indirect effect, through its effect on CBs, toward
the latent factor of IT, while also taking into account the uncertainty avoidance index’s direct effect.
We thus developed a SEM moderated mediation model that tested the complete model of Figure1.
The model considered the effects of the sociodemographic covariates (gender, age, and socioeco-
nomic status) as well. The model provided acceptable goodness- of- fit indexes: χ2 (66)=3201.8151,
Table 5. Factor Loadings of Latent Factors for SEM Moderation Model
Indicators B SE z- value p(>|z|) β
Latent factor: Trust (DV)
Government trust 1.000 .762
Government body trust 1.283 .014 89.472 .000 .969
Security system trust 1.016 .013 77.685 .000 .696
Latent factor: Active SMU (moderator)
Interactional SMU 1.000 .903
Informational SMU .788 .009 79.066 .000 .734
Expressive SMU .754 .010 81.710 .000 .766
Latent factor: Interaction conspiracy beliefs * SMU
Interaction indicator 1 1.000 .885
Interaction indicator 2 .737 .010 78.058 .000 .756
Interaction indicator 3 .818 .009 78.992 .000 .744
Note All the variables were modeled using three indicators.
Table 6. Results for SEM Moderation Model: Determinants of Latent Factor of Institutional Trust (H2 Testing)
Predictors B SE z- value p(>|z|) β
Conspiracy beliefs (CBs) −.181 .007 −26.112 .000 −.240
Latent factor: Active SMU −.014 .007 −2.197 .028 −.021
Latent factor: Interaction
CBs * Active SMU
.043 .005 9.348 .000 .090
Covariates
Gender (0=men,
1=women)
−.095 .019 −5.035 .000 −.045
Age .011 .001 18.124 .000 .164
Socioeconomic status .141 .006 25.660 .000 .236
Abbreviation: SMU, social media use.
14 Mari et al.
p < .001, RMSEA = .064, CFI = .938. As shown in Table 7, findings revealed a small positive
effect of the cultural index on CBs (explained variance: R2=.021). Uncertainty avoidance index
also diminished institutional trust. The overall addition of the cultural index slightly augmented
the explained variance of IT by the whole model (R2= .198). The conditional indirect effect was
very small, B=−.02, SE=.00, p<.001, β=−.032; the total effect [B=−.013, SE=.001, p<.001,
β=−.231] and was mainly due to the direct effect, B=−.012 SE=.001, p<.001, β=−.20.
Discussion
A generalized climate of institutional distrust may have severe consequences on community
well- being, citizens’ political engagement, and overall democratic welfare. This article investigated
how the endorsement of CBs contribute to the erosion of trust by augmenting the skepticism to-
ward the good intentions of public institutions and increasingly estranging citizens from trusting the
Figure 2. Hypothesis 2 testing: Moderating effect of active SMU latent factor on the relationship between conspiracy beliefs
and the latent factor of institutional trust. The conditional effects were estimated at three values of the moderator: the mean,
one standard deviation above, and one standard deviation below the mean, 1,000 bootstrapped samples.
15
Conspiracy Theories and Institutional Trust
government and its institutions. A central aim was also to investigate a direct effect of uncertainty
avoidance, as well as the other mechanisms that may attenuate such a negative effect on trust: Active
SMU.
Focusing first on CBs, in the present work we contributed to cross- cultural research on polit-
ical psychology in the following ways. A new and brief three- item scale was found to be partially
invariant across a remarkable number of democracies— 11— suggesting a possible methodological
extension of its use to other, less homogeneous societies. Its brevity is attractive since there is often
not enough room for long measures in large cross- cultural surveys. Additionally, some of the previ-
ous measures in the literature tend to be focused on specific conspiracy theories that may lack cross-
cultural validity. This is particularly relevant, as globalization and social media may be contributing
to the spread of specific conspiracy theories well beyond the country boundaries where they were
generated. The current measure, to the contrary, is general, focused to politics, and tries to depict an
overall mindset of skepticism toward unrevealed truths about the nasty plots of mysterious powerful
forces, which is easily understandable in different cultural settings.
Findings revealed that in the 11- country subsamples, endorsement of such beliefs was quite
generalized in the population, with the Latin- American democracies having the highest means.
Importantly, Hypothesis 1 was supported: CBs tended to induce distrust toward country’s authorities,
including both partisan and nonpartisan government bodies, and the security system, that is, toward
all the key institutions that preside over the functioning of the nation (Rothstein & Stolle, 2008).
These effects were generalized to almost all the considered countries, emphasizing that this link is
substantial and needs to be addressed by the involved authorities. Paradoxically, in Latin- American
countries of Argentina and Brazil (among those with the highest level of conspiratorial ideation),
these effects were nonsignificant when the target of trust was the representative government and
security systems. We might contend that the overt political instability that some of these countries
have been facing may affect more prominently the way people trust the authorities, so that it becomes
difficult to capture the subtle influence of generalized political CBs.
Another important aspect that our cross- sectional research points out is the necessity to estab-
lish a clear direction of the link between the CBs and IT. Sometimes research has found a reversed
pattern— compared to that one hypothesized and confirmed in the present research— but when con-
sidering more general measure of trust at large (e.g., Abalakina- Paap et al., 1999; Goertzel, 1994).
Recently, Freeman and Bentall (2017) theorized a framework in which low self- esteem, distrust of
Table 7. Results for SEM Moderated Mediation Model of Figure1: Inspection of Culture Uncertainty Avoidance Index
Effects (H3 Testing)
Predictors B SE z- value p(>|z|) β
DV: Conspiracy beliefs (CBs)
Cultural uncertainty avoidance index
(UAI)
.011 .001 15.730 .000 .145
DV: Latent factor of institutional trust
UAI −.012 .001 −20.826 .000 −.200
CBs −.167 .007 −22.870 .000 −.221
Latent factor: Active SMU .022 .007 3.027 .002 .032
Latent factor: Interaction CBs *
Active SMU
.038 .005 7.276 .000 .078
Control covariates
Gender (0=men, 1=women) −.116 .018 −6.299 .000 −.054
Age .008 .001 12.181 .000 .119
Socioeconomic status .135 .006 24.371 .000 .224
Abbreviations: DV, dependent variable in the specific part of model; SMU, social media use.
16 Mari et al.
authority, and smaller social networks (or context of marginalization) contributed to the incidence
of a specific conspiracy belief. As a short- term benefit, there will be a reduction in uncertainty but
also the confirmation and reinforcement of distrust beliefs, through access to homogeneous social
networks. In a similar vein, from another theoretical perspective, Harambam and Aupers (2015)
argued that conspiracy theories in the scientific domain may emerge in a context of widespread
scientific authority erosion. From these viewpoints, then, it might be plausible to contemplate that a
general climate of distrust may induce the development of more conspiracy theories. Alternatively,
the relationship might be more complex. For instance, when the institution is perceived as universally
inclusive, then trust will increase, but when an institution with a universalistic claim (i.e., judicial
system) is perceived to represent more particular identities, this may lead to the development of CBs
(see Askvik et al., 2011).
Hence, we believe that it seems plausible to posit a recursive link that needs to be further inves-
tigated in longitudinal research, where strong beliefs in conspiracy theories reinforce institutional
distrust on the one hand, whereas a distrusting climate at large fuels new CBs. However, it is import-
ant to distinguish between a general perception of (dis)trust toward the authorities versus the (dis)
trust focused on specific target institutions. On the one hand, general beliefs in conspiracy theories
may reinforce the distrust toward specific targets (e.g., state authorities), as we found in the current
study. On the other hand, a general distrustful climate toward people may reinforce specific CBs.
Future research should also consider these different levels of analyses to disentangle this quandary.
Our findings fully sustain the hypothesized moderation effect of Active SMU on the relationship
between CBs and IT (H2). Indeed, the SEM moderation model was supported, where active SMU
was modeled as a latent construct capturing the effects of forms of SMU useful to activate people
in the political realm (Yu, 2016). The interaction latent factor (between CBs and active SMU) was
indeed a significant predictor of IT. Despite the solid theoretical SEM approach employed, the ex-
plained variance in IT is small. Yet, when investigating such complex phenomenon in cross- cultural
research, even a low proportion of variance may be notable (see He & van de Vijver, 2012).
Active forms of SMU were found as precursors to other procivic attitudes and behaviors (Gil
de Zúñiga et al., 2014; Yamamoto et al., 2015). Among those who strongly endorsed conspiracy
theories, its negative effect on trust was cushioned when the individual actively used social media to
engage in the community and to participate in the public debate. Most likely, this is due to people’s
augmenting the sense of community inclusion— a psychological mechanism to further confirm in
future research. Our results are thus innovative in showing that proactive SMU may be used to fight
and challenge the effects of strong, sometimes insidious beliefs that thrive by exploiting the exact
same social media channels (e.g., Del Vicario et al., 2016). Public education efforts could aim to raise
awareness of the potential malevolent effects of Internet use. What seems clear is that future research
should continue to explore the useful distinction between active and passive forms of Internet use
and social media use (Yu, 2016) and to investigate whether these have opposing effects. For instance,
it would be interesting to compare the moderating effects of active SMU with using social media to
interact for purely leisure reasons, to check whether they may have the same, or rather the opposite,
effect in determining IT.
In this study, we also inspected the antecedent effects of culture attributes such as uncertainty
avoidance (Hofstede, 2001), referring to the extent to which a culture is intolerant of ambiguous sit-
uations and has created beliefs and rules that try to avoid such situations. The additional hypothesis
considered a possible direct and indirect effect of uncertainty avoidance, through an increase in CBs,
toward IT (H3). Our findings showed that such effects of a cultural climate of higher intolerance
of the unknown, although present and in the expected direction, contributed to (dis)trust in state
institutions in a limited way. Indeed, its effects and the explained variance are small. First, if more
countries are tested, a hierarchical linear model may be applied controlling directly for country ef-
fects at a higher level of analyses (Bryan, & Jenkins, 2015), which was not recommended with our
17
Conspiracy Theories and Institutional Trust
countries’ number. Also, the impact of other cultural indicators might be considered: for instance,
tightness- looseness, which reflects the way in which societies differ in the extensiveness of, and ad-
herence to, social norms (Gelfand et al., 2011). It is also worth noting that intolerance of uncertainty
may be investigated also from an individual viewpoint (e.g., Freeston, Rhéaume, Letarte, Dugas, &
Ladouceur, 1994). Indeed, trust in institution targets implies accepting that the relationship with the
target is unpredictable (see e.g., Hetherington, 2005); thus, the relationship may create uncertainty,
which can depend also on the perceived cultural climate.
This research also suggests that sociodemographic variables play an important role in deter-
mining trust. Trust in institutions is higher for older people, men, and higher social- status people.
This finding confirms past research, showing that people from higher social strata tend to express
greater support for the authorities and the system in which they live, as they are the ones who most
benefit from it (e.g., Anderson & Reichert, 1995; Liu et al., 2018). However, the picture provided
by our results also shows the other side of the coin. IT is lower for young people, women, and low
socioeconomic- status participants. In other words, trust in authorities is lower for the more vul-
nerable population segments. When people feel less empowered (Abalakina- Paap et al., 1999) or
anxious (Grzesiak- Feldman, 2013), they may more easily develop or accept conspiracy theories.
Thus, further research should consider sociodemographics as possible moderators of the CBs- IT
relationship. Indeed, the disadvantaged segments of the population, since threatened, might embrace
CBs to a higher level, thus exhibiting a higher distrust toward the institutions that govern them (see,
e.g., Douglas et al., 2017).
All in all, despite the limitations discussed in this section, findings of this study illustrated spe-
cific theoretical and empirical paths that shed light on how conspiracy theories may be useful to
depict the institutional distrust that festers in a social media era, across different democratic societies.
Albeit valuable CBs theoretical mechanisms have been clarified by this study, many important ques-
tions remain open, and we hope this work may inspire future research.
ACKNOWLEDGMENT
Correspondence concerning this article should be addressed to Homero Gil de Zúñiga, Department
of Political Science, University of Salamanca, Campus Miguel de Unamuno s/n, Salamanca, Castilla
y Leon 16802- 1503, Spain. E- mail: hgz@usal.es
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... Therefore, trust may also be a more complex psychological factor, influencing the relationship of other psychological factors with CT belief (cf. Mari et al., 2022;Miller et al., 2016). ...
... Differences between genders remain highly obscure with no real observable trend (cf. Dyrendal et al., 2021;Mari et al., 2022;Swami et al., 2011). Similarly, studies reported CT belief to be positively related to age (Van Prooijen, 2017), negatively related (Jensen et al., 2021;Mari et al., 2022), or not related at all . ...
... Dyrendal et al., 2021;Mari et al., 2022;Swami et al., 2011). Similarly, studies reported CT belief to be positively related to age (Van Prooijen, 2017), negatively related (Jensen et al., 2021;Mari et al., 2022), or not related at all . Differences in living areas which cause individuals to be more or less physically isolated from others have also been proposed to be predictive of CT belief. ...
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Public and scientific interest in why people believe in conspiracy theories (CT) surged in the past years. To come up with a theoretical explanation, researchers investigated relationships of CT belief with psychological factors such as political attitudes, emotions, or personality. However, recent studies have put the robustness of these relationships into question. In the present study, a prediction‐based analysis approach and machine learning models are deployed to detect and remedy poor replicability of CT belief associations. The analysis of a representative dataset with 2025 UK citizens supports the assumption that the current simplicity of the field's analysis routine, exhibiting high sample‐specificity and neglecting complex associations of psychological factors with CT belief, may obscure important relationships. The results further point towards key components of conspiratorial mindsets like general distrust and low socio‐political control. Important implications for building a coherent theory of CT belief are derived.
... The belief in conspiracy theories is harmful to democracy because it hampers rational political discussion and the decision-making process (McKay & Tenove, 2021). It also degrades trust in political institutions (Mari et al., 2022). Against this background, numerous studies focus on exploring the factors that predict conspiracy beliefs, such as right-wing ideology (e.g., Galliford & Furnham, 2017;Min, 2021;van Prooijen et al., 2015;Walter & Drochon, 2020) and right-wing authoritarianism (e.g., Hartman et al., 2021;Swami, 2012). ...
... Our findings offer support for media narratives and descriptive research about the role of conspiracy beliefs in right-wing protests, e.g., the January 6th insurrection. As mentioned, holding conspiracy beliefs is harmful to democracy because it hampers rational political discussion and the decision-making process (McKay & Tenove, 2021) and degrades trust in political institutions (Mari et al., 2022). As illustrated by other research (e.g., Galliford & Furnham, 2017;Walter & Drochon, 2020), this issue is greater for those with right-wing ideologies. ...
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Protest has long been associated with left-wing actors and left-wing causes. However, right-wing actors also engage in protest. Are right-wing actors mobilized by the same factors as those actors on the left? This article uses cross-national survey data (i.e., US, UK, France, and Canada) gathered in February 2021 to assess the role of misinformation, conspiracy beliefs, and the use of different social media platforms in explaining participation in marches or demonstrations. We find that those who use Twitch or TikTok are twice as likely to participate in marches or demonstrations, compared to non-users, but the uses of these platforms are more highly related to participation in right-wing protests than left-wing protests. Exposure to misinformation on social media and beliefs in conspiracy theories also increase the likelihood of participating in protests. Our research makes several important contributions. First, we separate right-wing protest participation from left-wing protest participation, whereas existing scholarship tends to lump these together. Second, we offer new insights into the effects of conspiracy beliefs and misinformation on participation using cross-national data. Third, we examine the roles of emerging social media platforms such as Twitch and TikTok (as well as legacy platforms such as YouTube and Facebook) to better understand the differential roles that social media platforms play in protest participation.
... Conspiracy theories also trigger political aggression: they are used as tools to derogate political opponents 17 , encourage political violence 18,19 , promote prejudice 18,20,21 and recruit terrorists 22 . More generally, conspiracy beliefs help to accelerate and consolidate mistrust of -and anxiety about -established institutions, including government 23,24 . Although a degree of healthy skepticism about official accounts of events should be encouraged, chronic skepticism becomes a problem as people ignore established facts and resist solutions to societal problems. ...
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... This study examines what predicts both general and specific conspiracy beliefs in the context of COVID-19. It is beneficial to consider conspiratorial thinking as another dependent variable not only because it allows researchers to see the difference between the two constructs but because conspiratorial thinking can show people's general tendency to endorse conspiracy theories that are not subject to specific contexts, time, and its microenvironment that such theories were built upon (Farhart et al., 2021), bolstering cross-cultural validity (Mari et al., 2022). ...
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