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Psychological Bulletin
© 2023 American Psychological Association
ISSN: 0033-2909

https://doi.org/10.1037/bul0000392

The Conspiratorial Mind: A Meta-Analytic Review of Motivational and
Personological Correlates
Shauna M. Bowes1, Thomas H. Costello1, 2, 3, and Arber Tasimi1
1

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This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

2

Department of Psychology, Emory University
Sloan School of Management, Massachusetts Institute of Technology
3
Department of Psychology, University of Regina

A tidal wave of research has tried to uncover the motivational and personological correlates of conspiratorial
ideation, often studying these two classes of correlates in parallel. Here, we synthesize this vast and
piecemeal literature through a multilevel meta-analytic review that spanned 170 studies, 257 samples,
52 variables, 1,429 effect sizes, and 158,473 participants. Overall, we found that the strongest correlates of
conspiratorial ideation pertained to (a) perceiving danger and threat, (b) relying on intuition and having
odd beliefs and experiences, and (c) being antagonistic and acting superior. Considerable heterogeneity was
found within these relations––especially when individual variables were lumped together under a single
domain––and we identiﬁed potential boundary conditions in these relations (e.g., type of conspiracy). Given
that the psychological correlates of conspiratorial ideation have often been classiﬁed as belonging to one
of two broad domains—motivation or personality—we aim to understand the implications of such
heterogeneity for frameworks of conspiratorial ideation. We conclude with directions for future research
that can lead to a uniﬁed account of conspiratorial ideation.

Public Signiﬁcance Statement
This empirical “one-stop-shop” provides a comprehensive overview of the motivational and
personological correlates of conspiratorial ideation. We ﬁnd that most motivational and personological
variables reported in the literature were signiﬁcantly related to conspiratorial ideation, but effect sizes
varied considerably. We discuss the implications of our ﬁndings for future research that can leverage
our quantitative review to bridge motivation and personality and, ultimately, arrive at a uniﬁed
account of conspiratorial ideation.
Keywords: conspiratorial ideation, motivation, personality, psychopathology, individual differences
Supplemental materials: https://doi.org/10.1037/bul0000392.supp

Conspiratorial ideation is everywhere. Indeed, most surveyed
participants all over the world endorse at least one conspiracy theory
(CT; e.g., Atari et al., 2019; Goertzel, 1994; Kowalski et al., 2020;
Oliver & Wood, 2014; Swami, 2012; van Prooijen & Douglas,
2018). A growing number of psychologists have become interested
in illuminating conspiratorial ideation by looking at two key
questions: (a) What are the motivational correlates of conspiratorial
ideation? (b) What are the personological correlates of conspiratorial
ideation?
Although motivation and personality are deeply intertwined (e.g.,
Dweck, 2017; Grapsas et al., 2020; Strus & Cieciuch, 2017),

research in the domain of conspiratorial ideation has largely
pursued these two lines of work in parallel. As a result, there is
considerable heterogeneity across frameworks of conspiratorial
ideation and often little overlap between these frameworks. Some
frameworks emphasize the centrality of personological constructs
(e.g., general personality traits, see Goreis & Voracek, 2019),
whereas others do not mention personological constructs whatsoever (e.g., van Prooijen & Douglas, 2018). Moreover, both
personality and motivation span scores of discrete constructs that
have been examined, for the most part, in a piecemeal fashion in
relation to conspiratorial ideation. Here, we provide what is, to our
knowledge, the most comprehensive meta-analysis to date on this
exploding phenomenological workspace.

Shauna M. Bowes
https://orcid.org/0000-0003-3826-9147
The authors acknowledge funding from the Templeton Foundation (Grant
61379). The authors also thank Adele Strother and Kylee Novick for their
assistance with identifying studies to code and maintaining data ﬁles. Our
data ﬁles, code, and output ﬁles are available at https://osf.io/jxyfn/.
Correspondence concerning this article should be addressed to Shauna
M. Bowes, Department of Psychology, Emory University, 36 Eagle Row,
Atlanta, GA 30322, United States. Email: shauna.m.bowes@gmail.com

What Is Conspiratorial Ideation?
Although scholars continue to debate how best to distinguish
conspiracy theories from truth (and whether all conspiracy theories
are psychologically equivalent; see Brotherton, 2015; van Prooijen,
2018), there is considerable consensus surrounding the core features
of conspiracy theories. Broadly, conspiracy theories refer to causal
explanations of events that ascribe blame to a group of powerful
1

2

BOWES, COSTELLO, AND TASIMI

individuals (the conspirators) who operate in secret to form hidden
plans that beneﬁt themselves and harm the common good (e.g.,
Uscinski, 2019). Thus, the deﬁnitional recipe of conspiracy theories
involves three primary ingredients: (a) conspirators, (b) hidden
plans, and (c) malintent against others or society; this deﬁnitional
recipe holds whether conspiracy theories turn out to be true or not
(see Brotherton, 2015; van Prooijen, 2018). Conspiratorial ideation,
therefore, refers to a tendency to endorse conspiracy theories.

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An Exploding (and Piecemeal) Phenomenological
Workspace
Conspiratorial ideation is a rapidly expanding area of investigation.
From January 2020 to February 2023, for example, over 16,000
results on Google Scholar appeared when searching for “conspiratorial ideation” or “conspiracy belief ” or “conspiracy theory.” Similarly,
in a recent narrative review on the psychology of conspiratorial
ideation, the number of studies on conspiracy beliefs increased by
more than 150% in just 1 year alone (i.e., from 2020 to 2021; see Pilch
et al., 2023). Perhaps it may come as no surprise that a handful of
meta-analyses have already provided deep dives into the relations
between conspiratorial ideation and certain psychological variables
(e.g., paranoia, see Imhoff & Lamberty, 2018; control, see Stojanov
& Halberstadt, 2020) and domains (e.g., broadband personality traits;
Goreis & Voracek, 2019). Two meta-analyses—one peer-reviewed
(Stasielowicz, 2022) and the other posted as a preprint (Biddlestone
et al., 2022)—have become available since the initial submission of
our article and provide broad characterizations of the personological
and the motivational correlates of conspiratorial ideation.
The published meta-analysis examined the most common variables
assessed in relation to conspiratorial ideation (Stasielowicz, 2022;
see Table 1) and were typically personality traits or personological
phenomena. Broadly, their ﬁndings revealed that indices of
psychopathology (e.g., paranoia) were stronger correlates of
conspiratorial ideation than normal-range personality traits (e.g.,
extraversion). Although informative, this meta-analysis does not
shed light on a theoretical framework of conspiratorial ideation,
rendering it challenging to leverage their ﬁndings and revise theory
in the service of inspiring future research. Moreover, and as
previously noted, research on conspiratorial ideation is exploding.
Table 1
Previous Meta-Analytic Findings in Stasielowicz (2022)
Variable

k

r

Credibility interval
limits (95%)

Agreeableness
Cognitive ability
Conscientiousness
Extraversion
Narcissism
Neuroticism
Openness
Paranoia
Pseudoscientiﬁc beliefs
Religiosity
Schizotypy
Self-esteem

32
15
35
35
19
36
38
20
11
51
13
22

−.07
−.13
−.03
.02
.28
.04
.02
.34
.46
.14
.30
−.06

[−.11, −.02]
[−.18, −.07]
[−.06, .00]
[−.00, .04]
[.20, .36]
[.01, .07]
[−.03, .07]
[.28, .39]
[.32, .57]
[.10, .18]
[.18, .41]
[−.11, −.00]

Note. Bold indicates that the correlation is statistically signiﬁcant per
the credibility interval limits.

Because the landscape surrounding conspiratorial ideation is ever
shifting, there may very well be 12 different popular constructs
now1 than at the time this previous meta-analysis was conducted.
Focusing on commonly studied variables also does not reﬂect
the vast universe of personality dimensions (e.g., Mõttus et al.,
2020). Moreover, in trying to understand how people differ from
one another in their personality traits (and how these differences
might map onto conspiratorial ideation), it is important to consider
why people think, feel, and act the way they do. Thus, it would
be useful to also consider motivational constructs in the context
of conspiratorial ideation. After all, personality may be born out
of motivation (for more on this issue, see Dweck, 2017).
Drawing on a popular theory suggesting that a deprivation of three
motivational needs (epistemic, existential, and social) may lead
people to endorse conspiracy theories (see Douglas et al., 2017), a
recent preprint examined said motivational domains in relation to
conspiratorial ideation (Biddlestone et al., 2022; see Table 2). Broad
support for this tripartite motivational model was found in this metaanalytic work. Yet, several ﬁndings at the variable-level provided
“uncertain evidence” in support of the tripartite model per Bayesian
analyses, making it difﬁcult to draw ﬁrm conclusions about the
validity of this theory. There was also considerable heterogeneity
within the selected domains. For instance, the relation between the
domain of collective social motives and conspiratorial ideation was
small and positive, but the individual correlations within this domain
ranged from small and negative (e.g., low ingroup identiﬁcation)
to large and positive (e.g., perceived ingroup victimhood).
When considering the limitations of and heterogeneity present
in previous meta-analytic reviews, it becomes apparent that there
are several reasons why a comprehensive replication and extension of
prior ﬁndings is important in the space of conspiratorial ideation. Chief
among these reasons is that no meta-analysis to date has applied the
same set of search strategies, coding schemes, and analytic approaches
to both motivational and personological correlates of conspiratorial
ideation (or even examined them simultaneously). Although useful,
currently available meta-analyses are neither sufﬁciently comprehensive nor sufﬁciently precise to sustain meaningful conclusions
about the speciﬁcity, generalizability, magnitude, and heterogeneity
of relations between conspiratorial ideation and motivation and
personality. Given the considerable researcher degrees of freedom
present in meta-analytic reviews (see de Vrieze, 2018), comparing
across meta-analyses is fraught with opacity. This opacity makes it
important to adopt a uniﬁed approach, as presented here.

Bridging Motivation and Personality
To broaden beyond the aims of previous meta-analyses, the
current investigation seeks to bridge motivation and personality.
While we do not claim that our individual meta-analytic estimates
are necessarily more accurate than other reviews (e.g., Biddlestone et
al., 2022; Stasielowicz, 2022), our estimates of the relative explanatory
power of each variable, relative to other variables included in our
1

In our meta-analysis, we also identiﬁed that normal-range traits,
intelligence, and paranoia are commonly examined correlates of conspiratorial
ideation. That said, we additionally identiﬁed trust, self-reported intuition, selfreported rationality, cognitive reﬂection, anxiety, and social dominance
orientation as commonly assessed variables (see Results section). These
differences across meta-analyses reveal that the terrain surrounding
conspiratorial ideation is vast—and ever-changing.

CONSPIRATORIAL IDEATION META-ANALYSIS

Table 2
Previous Domain-Level Meta-Analytic Findings in Biddlestone
et al. (2022)

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Variable
Epistemic motives
Intuitive cognitive styles
Low general cognitive ability
Existential motives
Internal threats
External threats
Social motives
Individual
Relational
Collective

k

z

95% CIs

108
9

.16
.25

[.14, .18]
[.13, .36]

71
66

.13
.20

[.09, .16]
[.16, .24]

66
11
32

.21
.13
.10

[.18, .24]
[.01, .27]
[.02, .18]

Note. CI = conﬁdence interval. Bold indicates that the correlation is
statistically signiﬁcant per the conﬁdence intervals.

meta-analytic “map of the known world,” may be especially accurate.
After all, we use the same analytic approach, coding scheme, and
statistical decision-making processes for each variable.
It is essential to examine both motivation and personality in relation
to conspiratorial ideation, and this view is not just rooted in an aim
to be comprehensive for the sake of being comprehensive. Instead,
there is a strong theoretical foundation for considering motivation
alongside personality. Several lines of research are dedicated to
bridging motivation with personality (e.g., Bouchard & Johnson,
2021; Denissen & Penke, 2008; Duckitt & Sibley, 2009; Dweck,
2017; Grapsas et al., 2020; Jayawickreme et al., 2019), pointing to
the idea that independently examining motivation and personality
prevents critical insights onto important topics. Generally, research
shows that imposing strict theoretical boundaries between motivation
and personality is less well supported than is commonly supposed
(see Corr et al., 2013; Strus & Cieciuch, 2017).
There are multiple theories regarding how to integrate motivational
processes most effectively with personality traits, such as integrating
them into a circumplex model (e.g., Strus & Cieciuch, 2017) or into a
developmental framework (see Dweck, 2017). Nevertheless, these
various theories tend to share a distinction between descriptive (or
structural) and explanatory (or process-oriented) aspects of traits (e.g.,
Denissen & Penke, 2008; Jayawickreme et al., 2019; Mõttus et al.,
2020). Descriptive aspects of a trait broadly refer to the ways that
personality traits are measured (see Mõttus et al., 2020) and the
aggregation of individual, state-level behaviors (see Fleeson &
Jayawickreme, 2015). In essence, this level of a trait is the “what” of a
trait. The explanatory aspect of a trait, in turn, refers to the speciﬁc
cause of a speciﬁc behavior (see Mõttus et al., 2020) and the
cognitive, motivational, and affective processes that shape momentary information processing (see Jayawickreme et al., 2019). In
essence, this level of a trait is the “how” of a trait. Explanatory aspects
of a trait emphasize how the descriptive elements of a trait arise. Per
this distinction, motivations cause (e.g., Dweck, 2017) or are even
part-and-parcel (e.g., Fleeson & Jayawickreme, 2015) of traits.
By bringing together motivation and personality, it will be possible
to clarify what causes conspiratorial ideation and gain a deeper
understanding of how and why conspiratorial ideation predicts a host
of relevant outcomes (especially behaviors; see Dweck, 2017). With
this approach, we might be one step closer at designing effective
interventions for reducing conspiratorial ideation, as both the “what”

3

(descriptive/structural) and the “how” (explanatory/process-oriented)
will be considered by targeting broad areas of liability.
Further, by including motivational and personological variables
under the same meta-analytic roof, our review facilities comparisons
of the relative explanatory power of individual psychological
variables for conspiratorial ideation. Consistent with the classic
debate of lumping versus splitting in psychological science (see
Fiske, 2006), the domains of epistemic, existential, and social
motives represent lumping––a plethora of motives are joined
together under one heading. Through lumping these motives, we can
understand how shared processes bear on conspiratorial ideation.
Nevertheless, lumping variables together can wash out meaningful
signals at lower levels of analysis, including facet-level analyses
and even item-level analyses (see Mõttus et al., 2020). Thus, by
accounting for individual variables in addition to their broad
domains, it will be possible to gain actionable insights into the
relations between conspiratorial ideation and motives and traits. In
other words, we will be probing into individual variables for both
motivations (explanatory) and traits (descriptive). These comparisons across variables, rather than just domains, provide a rich
opportunity to replicate (and extend upon) previous research.
All in all, we suspect that an extension of previous meta-analytic
relations is needed to (a) clarify the relations between motivational
and personological variables and conspiratorial ideation and to
(b) illuminate sources of heterogeneity. We begin by describing
motivational and personological correlates of conspiratorial ideation, and then provide the ﬁndings from our meta-analysis, which
spanned 170 studies, 257 samples, 52 variables, 1,429 effect sizes,
and 158,473 participants. We conclude by outlining promising
directions for future research as we look forward to the possibility
of developing a uniﬁed theory of conspiratorial ideation.

Motivational Correlates of Conspiratorial Ideation
According to one popular perspective (Douglas et al., 2017),
people are drawn to conspiracy theories when they experience a
deprivation of the following three motivational needs:
1.

To form a reliable, certain, and stable view of the world
(epistemic motives).

2.

To feel safe and in control, particularly in the face of threat
(existential motives).

3.

To reinforce a superior, albeit fragile, image of oneself and
one’s ingroup (social motives).

In the following sections, we review these three motivational
domains and describe constructs that fall within each (e.g., Douglas
et al., 2017, 2019; Pierre, 2020; Sternisko et al., 2020; van
Mulukom, 2021; van Prooijen, 2019). We also describe the
deﬁnitions of relevant constructs according to these existing
organizational schemes.2 We sought to test theories surrounding
Of 34 motivational variables we reviewed, only ﬁve (15%) were placed
under more than one domain (e.g., alienation has been placed under both
existential and social motives in different reviews). Of these ﬁve constructs,
all were placed under one domain more than the others (e.g., alienation is
more often classiﬁed as social than existential). The remaining variables
were consistently placed under the same domain across frameworks of
conspiratorial ideation.
2

4

BOWES, COSTELLO, AND TASIMI

the psychology of conspiratorial ideation. As such, we coded
motivational variables according to frameworks of conspiratorial
ideation rather than frameworks of motivations per se (the latter of
which was adopted in a preprint; see Biddlestone et al., 2022). We
adopted this coding approach to test the heuristic value of the
tripartite motivational model and existing frameworks of conspiratorial ideation.

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Epistemic Motives
A drive to understand the everyday world is one reason why
people may be drawn to conspiracy theories. Identifying intuitive
explanations for ambiguous events, ﬁnding meaning in unpredictability and chaos, and maintaining one’s beliefs in the face of
contradiction correspond to epistemic motives (Douglas et al.,
2017). By relying on intuition, people can readily form accessible
explanations for uncertain situations and, in turn, generate a quick
understanding of the world. These intuitive understandings of the
world afford the opportunity for people to ﬁnd clarity and meaning
in their environment. To hold onto this intuitive and meaning-laden
understanding of the world, people may additionally strive to
uphold their beliefs rather than face additional uncertainty (see Kay
et al., 2009).
Conspiratorial ideation is related to reliance on intuition and
reduced analytical thinking. More precisely, conspiratorial ideation
manifests medium-to-large positive associations with measures of
intuitive thinking, including self-report measures of reliance on
intuition and quasibehavioral measures of intuition (e.g., susceptibility to pseudoprofound bullshit, susceptibility to the conjunction
fallacy; e.g., Brotherton & French, 2014; Čavojová et al., 2019;
Dagnall et al., 2017; Hart & Graether, 2018; Moulding et al., 2016;
Patel et al., 2019; Pennycook et al., 2015; van der Wal et al., 2018).3
Dovetailing with these ﬁndings, conspiratorial ideation is strongly
related to nonclinical delusion-proneness, indicating a propensity
to engage in intuitive and irrational thinking (e.g., Brotherton et al.,
2013; Dagnall et al., 2015). Regarding analytical thinking,
conspiratorial ideation is weakly-to-moderately negatively associated with self-report measures of rationality and cognitive reﬂection
(e.g., Barron et al., 2018; Castanho Silva et al., 2017; Ståhl & van
Prooijen, 2018; Swami et al., 2014), although these relations are
not always signiﬁcant (e.g., Ballová Mikušková, 2018; Patel et al.,
2019). Moreover, conspiratorial ideation and need for cognition
(i.e., preferences for complexity in thought; Cacioppo & Petty,
1982) are weakly-to-moderately negatively associated (e.g., Barron
et al., 2018; Ståhl & van Prooijen, 2018; cf. Miller et al., 2016).
These results raise the possibility that individuals prone
to conspiratorial ideation are motivated to understand the world
by engaging in intuitive, effortless thinking as opposed to rational,
effortful, and complex thinking.
An overreliance on intuition coupled with a drive to ﬁnd
meaning can contribute to identifying patterns where none exist
(i.e., illusory pattern perception; van Elk, 2015; Walker et al.,
2019) or identifying agency where none exists (i.e., hypersensitive
agency detection; see Douglas et al., 2016; Whitson & Galinsky,
2008). People prone to conspiratorial ideation are presumably also
prone to such patternicity; after all, conspiracy theories entail
identifying secret plotting by nefarious individuals (e.g., van
Prooijen, 2018). Bearing out this possibility, illusory pattern
perception tends to manifest large, positive correlations with

conspiratorial ideation (e.g., Moulding et al., 2016; Ståhl & van
Prooijen, 2018; van der Tempel & Alcock, 2015; van der Wal
et al., 2018; van Prooijen et al., 2018). Similarly, being overly
attuned to agency in others and the tendency to anthropomorphize,
also known as hypersensitive agency detection (i.e., Brotherton &
French, 2015; Douglas et al., 2016; Enders & Smallpage, 2019;
Imhoff & Bruder, 2014) and anthropomorphism, respectively,
are moderately positively associated with conspiratorial ideation
(e.g., Brotherton & French, 2015; Bruder et al., 2013; Douglas
et al., 2016).
Since conspiracy theories sometimes have the façade of being
evidence-based and can be supported by a variety of misleading
arguments (e.g., Dagnall et al., 2017; Goertzel, 1994), they may be
particularly appealing to those who are prone to maintain their
worldviews in the face of new evidence and tend to not think
effortfully. In support of these suppositions, conspiratorial ideation
is weakly-to-moderately and positively linked with dogmatism
(e.g., Čavojová et al., 2020) and moderately and negatively linked
with actively open-minded thinking (e.g., Erceg et al., 2022; Patel
et al., 2019; Stanovich & Toplak, 2019; Swami et al., 2014).
Given that conspiracy theories provide seemingly deﬁnite
explanations for largescale events, it has also been theorized that
conspiratorial ideation is related to strong motives for, and
the propensity to maintain, certainty (e.g., Douglas et al., 2017;
Kossowska & Bukowski, 2015). Desire for certainty entails
overlapping motivations, including need for cognitive closure
(i.e., the desire for any answer over uncertainty and preference for
order and structure; see Webster & Kruglanski, 1994) and
intolerance of ambiguity (i.e., the propensity to feel distressed by
information that is vague, open-ended, or uncertain; see Grenier
et al., 2005). Conspiratorial ideation tends to be positively related
with total scores on self-report inventories of need for closure
and intolerance of ambiguity; yet, most of these results are not
signiﬁcant and/or the effect sizes are small (e.g., Castanho Silva
et al., 2017; Golec de Zavala & Federico, 2018; Leman & Cinnirella,
2013; Marchlewska et al., 2018; Moulding et al., 2016; Swami
et al., 2014).
To summarize across all epistemic motives, conspiratorial
ideation appears to be related to inﬂexible cognitive styles,
including reliance on intuition, identifying patterns and agency
in their absence, and maintaining one’s views while being closeminded to alternative views. Still, individuals prone to conspiratorial ideation may also lack the cognitive abilities to evaluate
information accurately and critically (see Douglas et al., 2017,
2019).4 To address this possibility, scholars have directed attention
toward the relation between intelligence and conspiratorial
ideation. Across studies and measures of intelligence, there
appears to be a consistent negative relation between conspiratorial
ideation and general cognitive ability, although the magnitude of
these relations ranges from small to large (e.g., Adam-Troian et al.,
2019; Betsch et al., 2018; Čavojová et al., 2019; Dieckmann &
Johnson, 2019; Lantian et al., 2020; Pennycook et al., 2020;
3

Here and throughout, effect sizes were interpreted according to Gignac
and Szodorai’s (2016) guidelines for individual differences research: r = .10
is small, r = .20 is medium, and r = .30 is large.
4
A conspiracy theory is still a theory at the time of initial acceptance. As
such, the same psychological variables (e.g., low cognitive ability) that give
rise to conspiratorial ideation are theorized to be the same across conspiracy
theories, whether they turn out to be true or false (see van Prooijen, 2018).

CONSPIRATORIAL IDEATION META-ANALYSIS

Stieger et al., 2013; Swami & Furnham, 2012). Thus, it seems that
conspiratorial ideation may be related to reduced tendencies
and motivations to pursue complexity and a reduced ability to
make sense of complex information.

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Existential Motives
Another reason why people may be drawn to conspiracy theories
is to feel safe and in control, especially in the face of existential
threat (e.g., Douglas et al., 2017; van Prooijen, 2019). Thus,
conspiracy theories may appeal to those scoring high on existential
threat, as individuals are deprived of a sense of security and
power. For example, if the September 11th attacks were orchestrated
by the American government rather than an extremist group, then
people can spread the word and prevent such an attack from
happening again by voting for the “right” politicians.
Research reveals that conspiratorial ideation is moderately to
strongly and positively related to perceptions of existential threat
(e.g., Federico et al., 2018), such as perceiving that one’s nation
faces great threat (e.g., Cichocka, Marchlewska, & Golec de Zavala,
2016) and that one experiences more threat than others (e.g., Imhoff
et al., 2018). Existential threats can manifest in several ways, and
they often pertain to losing a sense of personal meaning and
confronting information that challenges one’s cherished beliefs
(e.g., van den Bos, 2009; van Prooijen, 2019). In addition to
perceiving more threat, conspiratorial ideation is moderately to
strongly and positively related to believing that the world is
inherently dangerous and unstable (e.g., Leone et al., 2019;
Moulding et al., 2016), perceiving one’s world with cynicism
rather than optimism (e.g., Bensley et al., 2020; Enders et al., 2020;
Swami, 2012; Swami et al., 2011; Vitriol & Marsh, 2018), and
feeling powerless (e.g., Biddlestone et al., 2020; Bruder et al., 2013;
Imhoff & Bruder, 2014; Jolley & Douglas, 2014; Moulding et al.,
2016; van Prooijen et al., 2018).
If people detect more threats in their environment and regard
the world as inherently dangerous, they are likely to (a) feel more
anxious, (b) perceive that they have less control, and (c) feel less
efﬁcacious. Research has examined how conspiratorial ideation
is related to all three of these possibilities. First, conspiratorial
ideation is related to experiencing more anxiety, including general
anxiety (e.g., Erceg et al., 2022; Grzesiak-Feldman, 2013; Šrol et al.,
2021) and death anxiety (e.g., Bruder et al., 2013; Stojanov &
Halberstadt, 2019), although these relations tend to be small.
Despite relatively consistent cross-sectional links between anxiety
and existential threat sensitivity and conspiratorial ideation, some
research shows that anxiety and existential threat sensitivity do
not seem to temporally precede conspiratorial ideation; such
results raise questions about whether and to what extent anxiety and
existential threat sensitivity are causes of conspiratorial ideation
(Liekefett et al., 2023).
When people experience threat and anxiety, they are likely
to perceive that they possess little to no control over their
environments. In line with this possibility, conspiratorial ideation
tends to manifest small-to-medium negative correlations with
perceptions of control (e.g., Bruder et al., 2013; Šrol et al., 2021;
Stone et al., 2018). Moreover, experimentally increasing a perceived
loss of control gives rise to greater conspiratorial ideation (e.g.,
Whitson et al., 2019; Whitson & Galinsky, 2008). Still, a recent
meta-analysis on the associations between experimentally induced

5

control and conspiratorial ideation indicated that the relationship
was small and not signiﬁcant (d = −.05, 95% CI [−.11, .02], k = 15,
N = 8,618; Stojanov & Halberstadt, 2020). This meta-analysis
raises the possibility that results from individual studies are
exaggerated and/or that there are potentially key, albeit overlooked,
moderators of the relations between conspiratorial ideation and
control.
Finally, although conspiratorial ideation appears to be only
weakly related to feeling that one possesses less control, research
indicates that conspiratorial ideation is related to feeling that one
possesses less efﬁcacy, or an ability to make changes in one’s
environment. Research demonstrates that conspiratorial ideation is
negatively related to multiple manifestations of efﬁcacy, such as
self-efﬁcacy (e.g., Ardèvol-Abreu et al., 2020; Lamberty & Leiser,
2019), external-efﬁcacy (e.g., Ardèvol-Abreu et al., 2020; Oliver &
Wood, 2014), and political-efﬁcacy (e.g., Lamberty & Leiser, 2019;
Molz & Stiller, 2021).

Social Motives
A third reason why people may be drawn to conspiracy theories
is that they afford opportunities to defend a positive image of
themselves and their ingroup (e.g., Douglas et al., 2019; Sternisko
et al., 2020). By endorsing a conspiracy theory that places blame
on others (often members of another group), people can retain a
sense of superiority, both at the individual and group levels (e.g.,
Cichocka, Marchlewska, & Golec de Zavala, 2016). Ascribing
blame to an outgroup for societal ills may reinforce notions that
one’s ingroup is blameless and superior. Thus, conspiracy theories
should be particularly compelling to those with a fragile sense-ofself and/or those who perceive outgroup threat.
Consistent with these ideas, conspiratorial ideation is moderately
and positively related to perceiving a largescale moral breakdown
in society (i.e., anomie; Brotherton et al., 2013; Bruder et al., 2013;
Imhoff & Bruder, 2014; Imhoff et al., 2018; Jolley et al., 2019;
Majima & Nakamura, 2020; Moulding et al., 2016) and feeling
alienated from others (e.g., Lamberty & Leiser, 2019; Leman &
Cinnirella, 2013; Swami et al., 2013). Conspiratorial ideation is also
weakly negatively related to healthy self-esteem, as a stable,
balanced, positive self-regard likely allays social threats to one’s ego
and buffers against feelings of alienation (e.g., Cichocka,
Marchlewska, & Golec de Zavala, 2016; Stieger et al., 2013;
Swami, 2012; van Prooijen et al., 2018).
Because conspiratorial ideation is related to a fragile sense-ofself, it should not only be related to less self-esteem but also to
more narcissism (i.e., nonclinical manifestations of the more
pernicious constellation of traits comprising narcissistic personality disorder; see Pincus et al., 2009). Narcissism comprises a
complex blend of overconﬁdence and vulnerability, meaning
that narcissistic individuals tend to boast while also needing
validation from others (e.g., Miller & Campbell, 2010). In line with
expectations, conspiratorial ideation is weakly-to-moderately and
positively related to narcissism (e.g., Bowes et al., 2021; Cichocka,
Marchlewska, & Golec de Zavala, 2016).
These results point to the possibility that people who endorse
conspiracy theories are motivated to stand out among their peers and
feel entitled to special recognition. That is, those who endorse
conspiracy theories may feel they possess secret knowledge
about “the truth” that others fail to see or are not knowledgeable

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6

BOWES, COSTELLO, AND TASIMI

enough to possess (e.g., Lantian et al., 2017). Thus, conspiratorial
ideation may be related to needs to stand out among one’s peers
(e.g., boastfulness) in conjunction with a tendency to distrust
one’s peers (e.g., vulnerable self-esteem). Research aligns with
these possibilities: conspiratorial ideation is moderately positively
related to a need for uniqueness (e.g., Díaz & Cova, 2020; Imhoff
et al., 2018; Imhoff & Lamberty, 2017; Lantian et al., 2017; Lyons
et al., 2019) and a general distrust of others (from peers to politicians
to institutions; e.g., Brotherton et al., 2013; Jolley & Douglas,
2014; Lantian et al., 2016; Leman & Cinnirella, 2013; Meuer &
Imhoff, 2021; Šrol et al., 2021; Stojanov & Halberstadt, 2019). This
general mistrust of others may be an important aspect of
conspiratorial ideation that turns people away from ofﬁcial
narratives and facilitates identifying a clear enemy (see Meuer
& Imhoff, 2021; Pierre, 2020). These data converge on an image of
conspiratorial ideation being linked to needs to valorize the self, as
conspiracy theorists may perceive that they are in possession
of special talents and knowledge while simultaneously feeling
skeptical of others.
A similar pattern of relations emerges when examining the
relations between conspiratorial ideation and perceptions of
one’s ingroup. If one believes that their group is exceptional,
superior, and deserving of greater recognition, then they will
likely perceive outgroups as threatening and inferior (e.g., Golec de
Zavala & Lantos, 2020). And indeed, people often target outgroup
individuals as the conspirators behind threatening events (e.g.,
Mashuri & Zaduqisti, 2014; van Prooijen & Song, 2021). These
conspiracy stereotypes may protect and valorize one’s ingroup
identity vis-à-vis outsourcing blame to nefarious outgroup saboteurs
(e.g., Jolley et al., 2020; van Prooijen & Song, 2021). Thus,
conspiratorial ideation should be related to (a) holding a positive
view of one’s ingroup and (b) holding a negative view of one’s
outgroup.
Looking at the ﬁrst point, conspiratorial ideation is positively
related both to collective self-esteem (e.g., Cichocka, Marchlewska,
Golec de Zavala, & Olechowski, 2016; Crocker et al., 1999; Swami
et al., 2018; Uenal et al., 2021) and to collective narcissism (e.g.,
Cichocka, Marchlewska, & Golec de Zavala, 2016; Cichocka,
Marchlewska, Golec de Zavala, & Olechowski, 2016; Kofta et al.,
2020; Marchlewska et al., 2019). Preliminary research indicates
that when statistically controlling for the overlap between collective
self-esteem and collective narcissism, there is a mutual suppressor
effect such that the positive relation for collective self-esteem and
conspiratorial ideation becomes negative whereas the positive
relation for collective narcissism becomes larger (Cichocka,
Marchlewska, Golec de Zavala, & Olechowski, 2016). These
results suggest that conspiratorial ideation is related to perceiving
one’s ingroup as inherently better than the outgroup, whereas it
is negatively related to healthy pride in one’s ingroup. Looking
at the ﬁrst point (i.e., holding a negative view of one’s outgroup),
conspiratorial ideation is strongly related to enhanced threat
perception of outgroup members (e.g., Cichocka, Marchlewska,
Golec de Zavala, & Olechowski, 2016; Díaz & Cova, 2020; Mashuri
et al., 2016; Uenal et al., 2021; van Prooijen & Song, 2021).
Given that conspiracy theories may help individuals reinforce
“legitimate” authorities while denigrating “illegitimate” others,
conspiratorial ideation should also be positively related to both
right-wing authoritarianism (RWA; see Grzesiak-Feldman, 2015)
and social dominance orientation (SDO; see Swami, 2012). RWA

reﬂects obsequious submission to established authority, adherence
to socially conservative norms, and aggression towards people who
transgress against these norms (e.g., Duckitt et al., 2010); SDO
reﬂects the tendency to prefer social hierarchies that maintain power
over lower status groups (e.g., Ho et al., 2015). Several studies
indicate that conspiratorial ideation is weakly-to-moderately and
positively associated with RWA (e.g., Bruder et al., 2013; Swami,
2012; Wood & Gray, 2019). Conspiratorial ideation also tends to
be weakly-to-moderately and positively related to SDO (e.g., Bruder
et al., 2013; Green & Douglas, 2018; Imhoff & Bruder, 2014;
Imhoff et al., 2018; Kerr, 2020; Lamberty & Leiser, 2019).

Personological Correlates of Conspiratorial Ideation
Personological constructs are relevant to a host of beliefs, from
political ideology (e.g., Fatke, 2017) to religiosity (e.g., Gebauer
et al., 2013) to determinism beliefs (e.g., Costello et al., 2020). As
such, psychologists have become increasingly interested in
illuminating the personological correlates of conspiratorial ideation
(e.g., Bowes et al., 2021; Goreis & Voracek, 2019; Stasielowicz,
2022). Below, we provide overviews of two key areas of research
on the personological correlates of conspiratorial ideation, one on
abnormal-range correlates and the other on normal-range personality correlates.

Abnormal-Range Correlates
Historically, there has been a focus on the intersection between
conspiratorial ideation and abnormal psychological processes.
Scholars have largely focused on two separable, albeit highly related,
domains of abnormality and their relations to conspiratorial ideation:
(a) personality disorders (i.e., enduring, inﬂexible, and stable patterns
of thought and behavior that deviate signiﬁcantly from cultural and
normative expectations, leading to marked impairment and distress;
see Sleep et al., 2019) and (b) psychopathology (i.e., a broad domain
comprising a heterogeneous array of emotional, behavioral, and
cognitive dysfunctions that collectively give rise to marked
impairment and distress; see Kotov et al., 2021).
Looking at personality disorders, scholars posited over 50 years
ago that conspiratorial ideation was fundamental to paranoid
personality (e.g., Hofstadter, 1964). This line of thinking has
carried over into modern frameworks of conspiratorial ideation, as
some scholars contend that paranoia is part-and-parcel of the
conspiracist worldview, meaning that it may be necessary to score
highly on measures of paranoia (e.g., distrust others, perceive
malintent in others) to be a conspiracy theorist (e.g., Brotherton &
Eser, 2015; Dagnall et al., 2015; van der Linden et al., 2021). As
a result, several studies examining the relations between conspiratorial ideation and personality disorder traits have focused on
paranoia, a deﬁning characteristic of paranoid personality disorder
(American Psychiatric Association [APA], 2013). Results support
both historical and contemporary accounts of the centrality of
paranoia to conspiratorial ideation, such that those who score higher
on measures of paranoia also report more conspiratorial ideation
(e.g., Brotherton & Eser, 2015; Bruder et al., 2013; Cichocka,
Marchlewska, & Golec de Zavala, 2016; van Prooijen et al., 2015).
Indeed, a recent meta-analysis on the relations between conspiratorial ideation and paranoia (Imhoff & Lamberty, 2018) indicated

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CONSPIRATORIAL IDEATION META-ANALYSIS

that conspiratorial ideation was strongly positively related to
paranoia (k = 11, N = 2,006, r = .36, 95% CI [.30, .46]).
In addition to paranoia, scholars have examined the relations
between conspiratorial ideation and schizotypal personality disorder
(schizotypy), as it is closely related to and imbued with paranoia
(e.g., Cicero & Kerns, 2010). Schizotypy is characterized by
odd and bizarre thinking styles, social awkwardness, ideas of
reference (e.g., events are nonrandom and personally meaningful),
and disorganized communication (e.g., unclear or strange patterns
of speech; see Raine, 1991). Schizotypal traits contribute to
holding anomalous beliefs (e.g., paranormal beliefs; see Hergovich
et al., 2008) and exhibiting decision-making biases (e.g., jumpingto-conclusions; see Hua et al., 2020) germane to conspiratorial
ideation (e.g., Bronstein et al., 2019; Bruder et al., 2013). As such,
some maintain that schizotypal features are fundamental to
the conspiracist worldview (e.g., Dagnall et al., 2015). In line
with this thinking, conspiratorial ideation manifests medium-tolarge positive correlations with total scores on schizotypy measures
as well as scores on lower order schizotypal facets, such as odd
and bizarre thinking styles (e.g., Barron et al., 2014, 2018; Dagnall
et al., 2015; Hart & Graether, 2018) and ideas of reference (e.g.,
Barron et al., 2018). Finally, conspiratorial ideation is not only
related to schizotypy speciﬁcally but also to tendencies to have
unusual experiences at large and seems reasonable given that
schizotypy encompasses broad tendencies to have unusual experiences (e.g., Dagnall et al., 2015; Stone et al., 2018).
It should be noted that conspiratorial ideation is not only related
to discrete personality disorders (e.g., schizotypy), but also to
a broad personality disorder liability. In the Diagnostic and
Statistical Manual of Mental Disorders, Fifth Edition (APA,
2013) alternative trait model (alternative model of personality
disorders), personality disorder traits are organized into ﬁve
domains reﬂecting the maladaptive extremes of the Big Five (e.g.,
John & Srivastava, 1999): negative affectivity (e.g., anxiousness,
emotional lability), detachment (e.g., intimacy avoidance, suspiciousness), antagonism (e.g., callousness, manipulativeness), disinhibition (e.g., impulsivity, irresponsibility), and psychoticism (e.g.,
eccentricity, perceptual dysregulation; e.g., Krueger et al., 2012).
Preliminary studies suggest that all ﬁve personality disorder
dimensions manifest medium-to-large positive associations with
conspiratorial ideation (e.g., Bowes et al., 2021; Swami et al., 2016).
Based on the ﬁndings described thus far, it may seem that
conspiratorial ideation is uniquely related to personality disorder
traits. Yet, there is a high degree of overlap between personality
disorder traits and psychopathological features (e.g., bipolar
disorder and borderline personality disorder; see Deltito et al.,
2001; Kotov et al., 2021). Moreover, personality dysfunction is as
strongly linked to indices of psychopathology as indices of
personality disorders (e.g., Sleep et al., 2019). Thus, conspiratorial
ideation may not be uniquely related to personality disorder traits
but, instead, to broad psychopathology liability. Clarifying the
extent that conspiratorial ideation bears on psychopathological
characteristics more generally presents many open and interesting
questions.
Psychopathological symptoms are often organized along two
higher order dimensions: internalizing (e.g., distress, fear, anxiety,
depression, low mood) and externalizing (e.g., antagonism,
substance abuse, antisociality, impulsivity, irresponsibility; see
Kotov et al., 2021) psychopathology.5 Consistent with the relations

7

between conspiratorial ideation and general personality disorder
dimensions (i.e., alternative model of personality disorders traits),
conspiratorial ideation is related to a range of internalizing and
externalizing features. Regarding internalizing features, conspiratorial ideation tends to manifest small positive associations with total
scores on depression symptom inventories (e.g., Bogart et al., 2010;
Grebe & Nattrass, 2012; Leone et al., 2018; Rose, 2017) and allied
negative mood states, including anger and hostility (e.g., Jolley &
Paterson, 2020; Marchlewska et al., 2019). Although no research
has examined symptoms of externalizing disorders per se, some
research has examined externalizing features in relation to
conspiratorial ideation; these studies indicate that conspiratorial
ideation is weakly-to-moderately and positively linked with selfreported physical aggression and a willingness to use violence
against others (e.g., Lamberty & Leiser, 2019) in addition to
justiﬁcations of the use of violence (e.g., burning 5th generation
mobile network towers to prevent spread of COVID-19; see Jolley &
Paterson, 2020).
Taken together, conspiratorial ideation appears to be related to
multiple manifestations of psychopathology. Even still, abnormalrange correlates do not sufﬁciently account for the fact that
conspiratorial ideation is pervasive and perhaps even universal (e.g.,
van Prooijen & Douglas, 2018). Thus, it is also important to consider
normal-range personality in the context of conspiratorial ideation.

Normal-Range Personality Correlates
Studies examining the associations between conspiratorial
ideation and normal-range personality are mixed (e.g., Bowes
et al., 2021; Brotherton et al., 2013; Imhoff & Bruder, 2014;
Stojanov & Halberstadt, 2019; Swami & Furnham, 2012). Research
suggests that the relations between Big Five traits and conspiratorial
ideation are highly heterogeneous in both magnitude and direction
(e.g., the published relations between agreeableness and conspiratorial ideation range from −.28, Swami et al. to .11, Orosz et al.,
2016). Recent meta-analytic examinations of the associations
between the Big Five traits and conspiratorial ideation reported
correlations that were either weak or not signiﬁcant (Goreis &
Voracek, 2019; Stasielowicz, 2022).
Beyond the Big Five, there is a model of general personality
(Honesty-Humility, Emotionality, Extraversion, Agreeableness,
Conscientiousness, Openness to Experience; HEXACO) that
includes variants of the standard Big Five dimensions as well
as a sixth honesty–humility dimension (e.g., greed avoidance,
sincerity; see Lee & Ashton, 2018). The HEXACO model of
personality is widely used given that it more comprehensively
captures personality adjectives cross-culturally than does the Big
Five model (e.g., Ashton & Lee, 2008). To our knowledge, only
two published studies have examined the associations between the
HEXACO domains and conspiratorial ideation (Bowes et al.,
2021; Jolley et al., 2019). Whereas relations between honesty–
humility and conspiratorial ideation were negative and small-tomoderate in magnitude, relations for the other HEXACO domains,
which largely align with the Big Five dimensions, were
inconsistent both in terms of their signiﬁcance and direction.
5

Features of psychosis (e.g., detachment, thought disorder) are separable
from internalizing and externalizing dimensions and tend to load on their
own dimension (see Kotov et al., 2021).

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BOWES, COSTELLO, AND TASIMI

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Additional work has burrowed into the relations between
humility and conspiratorial ideation by examining intellectual
humility––which is a manifestation of broad humility referring
to humility surrounding one’s beliefs, attitudes, and knowledge
(e.g., Van Tongeren et al., 2019)––and its relations with
conspiratorial ideation (Bowes et al., 2021; Bowes & Tasimi,
2022). In these studies, intellectual humility was weakly-tomoderately negatively related to conspiratorial ideation. In
aggregate, it seems that humility is a consistent, negative correlate
of conspiratorial ideation.

Present Investigation
Here, we sought to meta-analytically examine the full body of
currently available literature (including peer-reviewed journal articles,
dissertations and theses, and unpublished data) on the motivational
and personological correlates of conspiratorial ideation. We
aggregated and analyzed 52 variables in relation to conspiratorial
ideation. Not only did we want to provide a snapshot of the magnitude
of the relations between these motivational and personological
variables and conspiratorial ideation, but we also wanted to quantify
and examine sources of heterogeneity in these relations.
Meta-analysis allows for the identiﬁcation of the boundary
conditions driving heterogeneity, a necessary step in validating
theories of interest. For example, a substantial degree of
heterogeneity in the relation between threat and conspiratorial
ideation may suggest that only certain kinds of threats pertain to
conspiracy beliefs or that the effect does not generalize to certain
populations. Thus, by estimating the degree and sources of
substantive heterogeneity in the literature, we can offer new
insights concerning both variables that have been meta-analytically
examined in previous research and constructs that have been
understudied. What is more, there may be greater variation in
conspiratorial ideation relations within motivational domains then
there is across motivational domains; to our knowledge, our metaanalysis is the ﬁrst to address this issue.
To examine sources of heterogeneity, we included a theoretically informed moderator (conspiracy theory type), and we also
examined the potential for publication bias. Looking at conspiracy
theory type, there are two common ways of assessing people’s
beliefs in conspiracy theories within the literature: through
measures of speciﬁc or general conspiratorial ideation (e.g.,
Imhoff et al., 2022). Whereas measures of speciﬁc conspiratorial
ideation present a series of concrete, event-based conspiracy
theories (e.g., the U.S. government planned the 9/11 attacks to
retain power), measures of general conspiratorial ideation present
a series of abstract, decontextualized conspiracy theories (e.g.,
governments plan to harm their citizens to retain power). Although
measures of speciﬁc and general conspiratorial ideation are
theoretically similar and tend to be strongly positively interrelated
(e.g., Brotherton et al., 2013), there are important differences
between these measures. For example, belief in speciﬁc conspiracy
theories may be more skewed than belief in general conspiracy
theories (see Imhoff et al., 2022). Thus, the magnitude of the
relations between conspiratorial ideation and motivational and
personological constructs may vary across measures of conspiratorial ideation (e.g., Goreis & Voracek, 2019; Stasielowicz, 2022;
Stojanov & Halberstadt, 2020).

Method
Inclusion Criteria and Literature Search
To identify candidate studies, we started by searching references
from previous meta-analyses on conspiratorial ideation (e.g., Goreis
& Voracek, 2019; Imhoff & Lamberty, 2018; Stojanov &
Halberstadt, 2020). We next broadened our search through electronic
databases, speciﬁcally Google Scholar and APA PsycInfo,6 using a
series of Boolean phrases (e.g., ((“conspir* theor* OR conspire*
belie* OR conspire* idea*) AND open*)). For the complete list of
search terms we used, see Supplemental Table S1. Deﬁnitions of
and references for motivational and personological constructs
included in the meta-analysis are provided in Supplemental Tables
S2 and S3. See Figure 1 for an overview of the screening process.
We included studies that contained the words “conspiracy,”
“conspiratorial,” or “epistemically unwarranted beliefs” and allied
constructs (e.g., scientiﬁcally unsubstantiated beliefs) in the title or
abstract. We broadened our initial search to include studies
referencing epistemically unwarranted beliefs and allied constructs,
as conspiracy theories are often discussed and measured in the
larger context of epistemically unwarranted/questionable beliefs
(e.g., Lobato et al., 2014). Our inclusion criteria also included the
following: studies that (a) report an effect size (e.g., Pearson’s r) and
(b) measure a motivational or personological construct via selfreport or experimental paradigm (e.g., lab measures of illusory
pattern perception). Both published and unpublished (i.e., preprints,
theses, data sets) articles were eligible for inclusion. No exclusions
were made based on study population. Articles not written in
English were excluded. For studies that used multiple waves, we
included the correlations within waves (e.g., Wave 1 conspiratorial
ideation with Wave 1 variable of interest; Wave 2 conspiratorial
ideation with Wave 2 variable of interest; see Golec de Zavala &
Federico, 2018). In studies using pre–post designs (e.g., Orosz et al.,
2016), we included the correlations between baseline levels of
conspiratorial ideation and variables of interest at baseline, and we
did not include the correlations between experimentally induced
(post) levels of conspiratorial ideation and variables of interest.
The ﬁnal search was conducted in February 2022, yielding a
total of 3,721 unique results (after repeat titles were removed). The
methods sections of relevant studies were then screened for inclusion
to ascertain that both conspiratorial ideation and a relevant
motivational and/or personological construct were directly measured
(see Figure 1). We solicited the authors of 80 studies for additional
data concerning (a) observations that had not been reported in
the article (i.e., authors reported measuring relevant constructs but
did not report effect sizes in the article or Supplemental Materials) or
(b) additional information that was needed to calculate zero-order
correlations (e.g., only semipartial correlations were reported in the
article). If authors did not respond, two additional emails were sent.
We received 60 email responses (75%), yielding 28 data sets that met
our inclusion criteria (47%).

Data Coding
After removing duplicates and studies that were ineligible
for the meta-analysis, we ended up with a total of 170 studies
6
We searched for studies on COVID-19 conspiracy theories in PsyArXiv
and Google Scholar from May 2020 to early 2022.

CONSPIRATORIAL IDEATION META-ANALYSIS

9

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Figure 1
Flowchart of Screening Process

Note. k = number of studies; S = number of samples; ES = number of effect sizes.

(257 samples, 1,429 effect sizes) that met inclusion criteria. An
overview of all included articles, study characteristics, and effect
sizes can be found at https://osf.io/jxyfn/. Pearson’s r coefﬁcients
were coded from each study by the ﬁrst author and research
assistants.
For a variable to be included in the meta-analysis, there must have
been at least two effect sizes present across studies for said variable

(e.g., Goh et al., 2016). Based on inclusion criteria, we coded 52
motivational and personological variables from the eligible studies.
In addition to coding these variables, we coded for motivational
domain (i.e., epistemic, existential, social) and personological
domain (i.e., psychopathology, general/normal-range personality)
based on existing frameworks of conspiratorial ideation (e.g.,
Douglas et al., 2017, 2019; Goreis & Voracek, 2019).

10

BOWES, COSTELLO, AND TASIMI

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Moderators
We coded for potential moderators and examined whether
these moderators imposed boundary conditions on the relations
between conspiratorial ideation and motivational and personological constructs.7
Conspiracy Theory Type. As previously noted, endorsement
of conspiracy theories is often assessed in two ways: through
general conspiracy theories or speciﬁc conspiracy theories. In
addition to these approaches, some measures of conspiratorial
ideation assess conspiracy stereotypes, meaning that outgroup
members are perceived as conspirators behind an event, usually
due to pervasive stereotypes about said outgroup (e.g., Jewish
individuals seek world domination and subvert others to obtain
international power; see Swami, 2012). Moreover, measures of
conspiratorial ideation have assessed ﬁctitious conspiracy theories,
meaning they are not circulated in public life (e.g., that Red Bull
drinks are carcinogenic and this information is being hidden from
the public; see Swami et al., 2011), and conspiracy scenarios,
meaning individuals read about a conspiracy situation (e.g., death
of Princess Diana; see Jolley et al., 2019).
Thus, the following categories were coded: general (effect size
[ES] = 631, k = 96), speciﬁc (ES = 700, k = 103), ﬁctitious (ES =
16, k = 4), scenario-based (ES = 18, k = 8), stereotype (ES = 51,
k = 11), and mixed (e.g., measure contained both general and
speciﬁc conspiracies or study authors collapsed across measures
of general and speciﬁc conspiracy theories; ES = 13, k = 3). After
the outbreak of the COVID-19 pandemic, we also coded for
whether a measure assessed COVID-19 conspiracy theories
speciﬁcally (ES = 80, k = 19).
Post Hoc Moderators. After reviewing the literature, we coded
for four additional moderators: type of measure for general
personality, intelligence, efﬁcacy, and trust used in each study.
There is substantial variability across self-report measures of
broadband personality traits in terms of content coverage of each
of the ﬁve dimensions of the Big Five. For instance, the Ten-Item
Personality Inventory (TIPI; see Gosling et al., 2003) assesses
each personality dimension with a mere two items, whereas the
Neuroticism, Extraversion, Openness Personality Inventory–
Revised (see Costa & McCrae, 2008) assesses each dimension
with 48 items. The HEXACO Personality Inventory–Revised
(HEXACO PI-R; see Lee & Ashton, 2018) assesses six overarching
dimensions of personality rather than ﬁve, including modiﬁed
versions of the Big Five traits in addition to honesty–humility. The
following measures were coded as categorical variables: the
HEXACO PI-R (ES = 65, k = 6), TIPI (ES = 116, k = 12),
Neuroticism, Extraversion, Openness Personality Inventory–
Revised (Costa & McCrae, 2008; ES = 4, k = 1), Big Five Aspects
Scale (DeYoung et al., 2007; ES = 4, k = 1), International
Personality Item Pool-NEO Short-Form (Johnson, 2014; ES = 45, k
= 6), Five-Factor Model Rating Form (Samuel et al., 2013; ES = 5, k
= 1), the Big Five Inventory (BFI; John et al., 1991; ES = 76, k = 6),
the BFI-10 (Rammstedt & John, 2007; ES = 5, k = 1), the
Comprehensive Intellectual Humility Scale (CIHS; KrumreiMancuso & Rouse, 2016; ES = 10, k = 2), and the General
Intellectual Humility Scale (GIHS; Leary et al., 2017; ES = 10,
k = 2).
There was also signiﬁcant cross-study variation in measures used
to assess intelligence. Dimensions or types of intelligence can yield

differing correlations with various individual difference constructs,
including general personality traits (e.g., Reeve et al., 2006) and
personality disorder traits (e.g., psychopathy; Watts et al., 2016). In
post hoc analyses, we examined the dimension and type of
intelligence measured as a moderator in the relationship between
conspiratorial ideation and intelligence. We coded for the following:
general intelligence (i.e., total scores on performance-based
measures of intelligence; ES = 9, k = 5), matrix reasoning
(ES = 4, k = 3), numeracy (ES = 9, k = 7), verbal reasoning (ES = 7,
k = 3), base-rate neglect (ES = 1, k = 1), and self-reported
intelligence (i.e., self-placement on a distribution of percentiles,
ES = 8, k = 4).
In addition, we coded for the domain of efﬁcacy assessed, given
that there could be important variability across these domains in
their relations with conspiratorial ideation. We coded the following
domains: self-efﬁcacy (k = 6; ES = 11), external-efﬁcacy (k = 2;
ES = 6), and political-efﬁcacy (k = 4; ES = 9). Similarly, we coded
for the domain of trust assessed to examine whether there are
differences across domains of trust in relation to conspiratorial
ideation. We coded the following domains of trust: authority (k = 1,
ES = 2), combined (i.e., multiple forms of trust were combined
into a single score; k = 2, ES = 5), cultural (k = 1, ES = 1),
government/politics (k = 11, ES = 29), institutional (k = 9, ES = 21),
interpersonal (k = 17, ES = 36), medicine (k = 3, ES = 3), and
science (k = 2, ES = 2). All post hoc moderation results are in
Supplemental Tables S10–S13.

Data Analytic Plan
All analyses were conducted using the metafor package in R
(Viechtbauer, 2010).

Outliers
We generated data sets, wherein data were removed at the 95th and
99th percentiles of the distribution of the standardized residuals for
each meta-analytic model. All models were then run using data sets
with outliers removed. We note if the results changed (in terms of
statistical signiﬁcance and/or direction of the effect) when excluding
outliers. If the results did not change appreciably after removing
outliers, then we retained the full data set for our analyses (the models
with outliers removed are available at https://osf.io/jxyfn/).

Main Effects
Correlations were transformed using Fisher’s r-to-z transformation to normalize the sampling distribution of the Pearson’s r
coefﬁcients (Silver & Dunlap, 1987). Effect sizes were also
weighted according to the inverse of their variance (i.e., sampling
error) as it is the standard approach in meta-analysis (MarinMartinez & Sánchez-Meca, 2010).
7
We additionally coded for the predominate nation in each study
(e.g., >50% of the sample comprised participants from said nation), the
average age and gender in each sample, the sample composition of
each sample, political afﬁliation, the WEIRDness of each sample, and
predominate education in each sample. We also coded for the U.S. region
of each sample when such data were available. The descriptive statistics for
these constructs are reported in Supplemental Tables S4 and S5. Moderation
results for these variables are available in Supplemental Materials 1, 2,
Tables S6, S7, and S16–S21.

11

CONSPIRATORIAL IDEATION META-ANALYSIS

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We used a three-level random-effects model with restricted
maximum likelihood estimation (Assink & Wibbelink, 2016),
modeling the sampling variance for each effect size (Level 1),
within-sample variation across outcomes (Level 2), and betweensample variation (Level 3). By accounting for systematic variance
across outcomes from the same sample, we were better able to
account for correlated sampling errors (e.g., because of multiple
effect sizes drawn from the same sample; Van den Noortgate et al.,
2013) than previous meta-analyses (e.g., Goreis & Voracek, 2019;
Stasielowicz, 2022). In total, we calculated 52 meta-analytic
models (one for each variable of interest), with ks (studies) ranging
from 3 to 40 and Ns (sample size) from 578 to 67,236.

Heterogeneity
We quantiﬁed heterogeneity using several approaches. First,
Cochrane’s Q statistic is derived from the Q test and approximates
a χ2 distribution with k − 1 degrees of freedom. Interpretation of the
Q statistic represents the presence or absence of signiﬁcant betweenstudy heterogeneity. Although the Q statistic is a useful metric of
heterogeneity, it has poor power to detect heterogeneity when the
k is small and can be statistically signiﬁcant in the absence of true
heterogeneity when the k is large (Huedo-Medina et al., 2006). The
I2 statistic overcomes some of the Q statistic’s limitations, as it is
a metric of the proportion of total variation in the observed effect
that is due to between-study heterogeneity in the “true” effect
(Higgins & Thompson, 2002). We calculated I2 in Level 2 (I2(2)) and
Level 3 (I2(3)) of the model, to ascertain variation across outcomes
within sample and across samples, respectively, relative to the total
variance. In addition, we calculated H2 (Higgins & Thompson,
2002), which reﬂects the difference between Q and its expected
value when heterogeneity is absent. Importantly, H2 is not impacted
by the number of studies, affording comparisons of heterogeneity
across meta-analytic models. We interpreted H2 values according
to Higgins and Thompson’s (2002) benchmarks: H2 = 1 suggests
that the population of studies is homogeneous, whereas H2 > 1.5
suggests that heterogeneity is present. We also calculated τ21 and τ22 ,
which describe the within-sample and between-sample variances of
the true effect sizes in our data set. Alongside our reporting of
these variances, we computed the standard deviation of the true
pﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ
effect sizes, τ, which is calculated as τ21 + τ22 .

statistical signiﬁcance of the results or the accessibility of the
article; see McShane et al., 2016) using several analytic strategies.
First, we added the standard error or variance for each effect size as
a predictor in each meta-analytic model. This analytic approach is
closely linked to the PET-PEESE method used in two-level metaanalyses (Stanley & Doucouliagos, 2014). The precision-effect
test (PET; Stanley & Doucouliagos, 2014) is a meta-regression
technique in which the effect sizes are predicted from their
standard errors and weighted according to their precision estimates
(see Carter et al., 2019). If PET is signiﬁcant, then it is recommended
to follow-up with the precision-effect estimate with standard error
test (PEESE; see Carter et al., 2019). PEESE is the same as PET
except that the effect sizes are predicted from the squared standard
errors. The intercept of the regression in the PEESE model is the
estimated total effect controlling for publication bias (Stanley &
Doucouliagos, 2014). Although the performance of PET-PEESE
in multilevel meta-analytic models has not yet been adjudicated,
some consider it to be one of the best available methods to correct
for publication bias in meta-analysis (e.g., Lehtonen et al., 2018).
Nevertheless, PET-PEESE can yield unstable estimates if the ks
are low and/or if between-study heterogeneity is high (Carter et al.,
2019; Stanley, 2017). Given these limitations, we also examined
whether effect sizes were signiﬁcantly different between published
and unpublished results. We created a dichotomous variable (1 =
published; 2 = unpublished) and conducted subgroup analyses
using the method described earlier for categorical moderators
(published ES = 1,065, k = 146; unpublished ES = 364, k = 24).8

Transparency and Openness
We followed the Meta‐Analysis Reporting Standards guidelines
for reporting our meta-analytic results (Appelbaum et al., 2018). Our
data ﬁles, code, and output ﬁles are available at https://osf.io/jxyfn/.
This study was not preregistered.

Results
The full output of the results for each construct (e.g.,
heterogeneity, forest plots, moderator results) can be found at
https://osf.io/jxyfn/. Results and forest plots for each construct can
also be viewed through the following Shiny app at https://8cz637thc.shinyapps.io/ConspiracyMetaAnalysis/.

Moderator Analyses
For categorical moderators, we only included levels of a given
moderator variable if there were three or more effect sizes. A single
three-level random-effects model was ﬁtted to the data with the
categorical factor included to model the differences between the
subgroups (Viechtbauer, 2010). The intercept was removed to
model the effect size for each group. We examined signiﬁcant
moderation models based on an omnibus F-test. For models with a
signiﬁcant omnibus F-test, we next adjudicated whether effect sizes
were signiﬁcantly different based on t tests comparing each level
of the moderator.

Publication Bias
We also investigated publication bias (i.e., factors that may limit
the representativeness of a set of published studies, such as the

Study Characteristics
There were 170 studies, 257 samples, and 1,429 effect sizes
included in the present meta-analysis. On average, there were 12
studies, 16 samples, and 27 effect sizes per construct (Figure 2),
although it is evident there was considerable heterogeneity in terms
of the studies, samples, and effect sizes per construct. The lone
8
We also created funnel plots depicting the distribution of the effect sizes
by their precision (1/SE). The 95th and 99th percentile conﬁdence intervals
are included in the funnel plots to facilitate identiﬁcation of potential outliers
(these are available at https://osf.io/jxyfn/). Interpreting the magnitude of
publication bias from a funnel plot based upon visual inspection alone is
subjective and susceptible to error, however, and scholars caution against
interpreting funnel plots when effect sizes are signiﬁcantly heterogeneous
(Vevea & Woods, 2005). Thus, we do not describe these results but refer
readers to online materials at https://osf.io/jxyfn/.

12

BOWES, COSTELLO, AND TASIMI

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Figure 2
Boxplot of the Number of Studies, Samples, and Effect Sizes in the Meta-Analysis

Note. k = number of studies; S = number of samples; ES = number of effect sizes. The only outlier across all
three categories was “trust,” and it is denoted with a red X. Each point represents a variable assessed in the metaanalysis. See the online article for the color version of this ﬁgure.

outlier for number of studies, samples, and effect sizes was trust
(k = 40, S = 57, ES = 100).
Studies were conducted between 1994 and 2022 (M = 2017, SD =
3.82). Across constructs, there were 158,473 participants. Of 170
studies, 146 (S = 231) were published and 24 (S = 32) were
unpublished. Most studies included American participants (k = 77,
S = 103), followed by participants from the United Kingdom (k =
23, S = 33) and Poland (k = 12, S = 19). For studies that reported
their recruitment location within the United States, most reported
sampling from the Northeast (k = 5, S = 6) or West (k = 4, S = 5).
Most studies recruited from community samples (k = 117, S = 170)
followed by student samples (k = 48, S = 63). The average age
across samples was 32.29 years (SD = 9.82), and the average
percentage of females across samples was 56.4% (SD = 15.66).
Most studies included participants who identiﬁed as politically
Democratic (k = 9, S = 12), and most participants were college
educated (k = 86, S = 124). Most studies assessed speciﬁc
conspiracy theories (k = 103, S = 141) or general conspiracy
theories (k = 96, S = 141); the remaining studies assessed ﬁctitious
conspiracy theories (k = 4, S = 7), endorsement of conspiracy
scenarios (k = 8, S = 11), conspiracy stereotypes (k = 11, S = 19),
or a mixture of both speciﬁc and general conspiracy theories (k = 3,
S = 5). In addition, 158 studies assessed non-COVID-19 conspiracy
theories (S = 242) and 19 assessed COVID-19 conspiracy theories
(S = 21).
Regarding motivational and personological domains assessed
across studies, social motives were most frequently assessed (k = 88,
S = 126), followed by epistemic motives (k = 77, S = 115),
existential motives (k = 60, S = 81), psychopathology (k = 47, S =
63), and general personality traits (k = 33, S = 44). Regarding
constructs assessed across studies, the most commonly assessed

construct was trust (k = 40, S = 57), followed by Big Five traits
(ks ranged from 28 [conscientiousness, agreeableness, neuroticism]
to 31 [openness]; Ss range from 35 [agreeableness] to 41
[openness]), RWA (k = 27, S = 40), self-reported intuition and
cognitive reﬂection (ks were 23, Ss were 29 and 27), intelligence
(k = 22, S = 26), and anxiety, paranoia, and SDO (ks were 17, Ss
ranged from 22 [SDO] to 25 [anxiety]).

Outliers
None of the results appreciably changed in terms of statistical
signiﬁcance or effect size after removing outliers at either the 95th
or 99th percentiles of the distribution of effect sizes (mean change
in Pearson’s r after removing outliers was <.01 for both data sets).
Hence, we used the full data set for all subsequent analyses. Results
from data sets with outliers removed are available at https://osf.io/
jxyfn/.

Main Effects and Heterogeneity
The main effects, 95% conﬁdence intervals, and heterogeneity
statistics are presented in Tables 3 and 4.9 Descriptive statistics are
presented in Tables 5 and 6. For a rank-ordered presentation of
the results, see Figure 3. The meta-analytic estimates for
motivational constructs are depicted in Figure 4, and the metaanalytic estimates for personological constructs are depicted in
9

The statistical signiﬁcance of the main effects was unchanged after
employing a Benjamini and Hochberg (1995) correction for multiple
comparisons.

13

CONSPIRATORIAL IDEATION META-ANALYSIS

Table 3
Study Characteristics, Meta-Analytic Estimates, and Heterogeneity Statistics for the Motivational Constructs

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This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Construct
Epistemic
Self-reported rationality
Cognitive reﬂection
Need for cognition
Self-reported intuition
Bullshit receptivity
Conjunction fallacy
Delusion-proneness
Illusory pattern perception
Illusory agency detection
Anthropomorphism
Dogmatism
AOT
Intelligence
Need for closure
Intolerance of ambiguity
Existential
Existential threat
Belief in a dangerous world
Cynicism
Powerlessness
Anxiety
Death anxiety
Control
Efﬁcacy
Social
Anomie
Alienation
Individual self-esteem
Individual narcissism
Need for uniqueness
Trust
Collective self-esteem
Collective narcissism
Social threat
RWA
SDO

k

S

ES

N

r

95% CI

H2

Q

I2(2)

I2(3)

τ21

τ22

τ

21
23
10
23
8
7
5
12
5
4
9
6
22
13
5

25
27
11
29
9
9
5
23
8
6
9
11
26
15
6

37
39
13
41
12
28
14
47
9
7
18
14
39
24
10

9,717
16,387
12,477
13,238
5,076
3,423
1,851
6,019
4,363
1,255
8,510
5,645
12,276
11,583
1,818

−.15
−.17
−.14
.21
.26
.14*
.42
.24
.18
.40
.14
−.25
−.16
.10
.25

[−.20, −.09]
[−.23, −.11]
[−.24, −.04]
[.18, .25]
[.18, .34]
[.02, .25]
[.32, .51]
[.17, .30]
[.09, .27]
[.33, .46]
[.04, .24]
[−.35, −.15]
[−.21, −.11]
[.05, .15]
[.09, .40]

6.19
5.88
42.36
3.47
7.26
5.30
2.72
5.40
5.34
.41
20.71
10.85
3.93
3.62
4.40

265.93
268.51
563.62
183.29
99.10
176.44
52.10
300.83
57.02
9.84
390.76
165.88
192.34
110.88
54.03

15.2%
5.9%
25.0%
61.6%
14.1%
<1.0%
15.6%
50.4%
<1.0%
<1%
35.4%
6.5%
2.0%
<1.0%
<1.0%

73.1%
87.2%
70.4%
19.3%
69.6%
88.0%
60.0%
36.2%
78.5%
<1%
58.8%
85.6%
83.2%
79.8%
85.5%

.003
.001
.006
.007
.001
.000
.002
.015
.000
.000
.008
.002
.000
.000
.000

.015
.020
.016
.002
.007
.025
.007
.010
.008
.000
.013
.020
.011
.007
.027

.13
.14
.15
.09
.09
.16
.09
.16
.09
.00
.15
.15
.10
.08
.16

4
5
11
9
17
6
14
9

6
9
12
11
25
6
21
11

11
15
21
17
40
8
48
26

4,700
3,613
8,461
6,910
26,348
1,691
7,128
11,142

.34
.39
.31
.28
.19
.12
−.17
−.07

[.26, .43]
[.27, .50]
[.21, .41]
[.18, .38]
[.10, .28]
[.05, .19]
[−.21, −.12]
[−.22, .09]

24.93
6.44
31.74
3.37
20.12
.24
3.77
36.65

285.20
111.54
687.60
74.33
844.76
9.95
229.15
972.96

94.4%
15.8%
96.8%
10.7%
<1.0%
32.9%
29.2%
25.4%

<1%
70.9%
<1%
78.5%
96.6%
<1%
25.2%
73.3%

.014
.004
.046
.003
.000
.002
.004
.018

.000
.019
.000
.020
.045
.000
.007
.051

.12
.15
.21
.15
.21
.05
.10
.26

12
3
11
10
7
40
5
6
5
27
17

16
3
15
13
10
57
6
10
7
40
22

27
5
22
32
24
100
6
18
13
66
41

7,435
578
9,630
9,373
3,690
67,236
1,818
4,553
2,500
27,283
12,579

.34
.28
−.09
.22
.16
−.26
.22
.34
.56
.22
.20

[.28, .39]
[−.12, .67]
[−.14, −.04]
[.15, .30]
[.13, .18]
[−.30, −.22]
[−.02, .46]
[.22, .46]
[.30, .82]
[.17, .26]
[.13, .27]

2.29
2.22
2.81
3.35
.01
30.35
17.24
24.28
33.65
12.79
16.56

88.96
16.12
83.94
139.27
24.16
3135.42
109.44
455.11
450.43
910.15
720.07

17.3%
<1.0%
<1.0%
7.6%
4.9%
32.2%
46.6%
95.8%
39.4%
69.7%
63.2%

64.7%
89.7%
76.5%
82.5%
4.3%
65.7%
46.6%
<1.0%
58.3%
25.3%
31.5%

.002
.000
.000
.002
.000
.008
.024
.054
.048
.021
.021

.008
.054
.006
.016
.000
.016
.024
.000
.071
.007
.010

.10
.23
.08
.13
.02
.13
.22
.23
.35
.17
.18

Note. Bold indicates p < .001, italicized indicates p < .01. k = number of studies; S = number of samples; ES = number of effect sizes; CI = conﬁdence
intervals; AOT = actively open-minded thinking; RWA = right-wing authoritarianism; SDO = social dominance orientation. Positive correlations indicate
that conspiratorial ideation is related to more of a given construct, whereas negative correlations indicate that conspiratorial ideation is related to less of a
given construct.
* p < .05.

Figure 5. Herein, we provide a narrative overview of our ﬁndings;
granular details are provided in the main tables.

Motivational Correlates
Epistemic
Conspiratorial ideation was weakly and signiﬁcantly related to
less analytical thinking and need for cognition (rs ranged from −.14
[need for cognition] to −.17 [cognitive reﬂection]). Not only was
conspiratorial ideation related to less analytical thinking, but it was
also weakly-to-moderately related to more reliance on intuition (rs
ranged from .14 [conjunction fallacy] to .26 [bullshit receptivity])
and was strongly related to more delusion-proneness (r = .42).
There were also clear links between conspiratorial ideation and
patternicity, with effect sizes ranging from small to large (rs ranged
from .18 [illusory agency detection] to .40 [anthropomorphism]).
Consistent with the possibility that conspiratorial ideation may
align with motives to maintain one’s views, conspiratorial ideation

was weakly related to more dogmatism (r = .14) and moderately
related to less actively open-minded thinking (r = −.25).
Conspiratorial ideation was additionally related to motives to
identify certainty and avoid complexity (need for closure r = .10;
intolerance of ambiguity r = .25). Results indicated that conspiratorial ideation may also align with low cognitive ability, as
conspiratorial ideation was weakly negatively related to intelligence
(r = −.16). It should be noted that the relationship between
intelligence and conspiratorial ideation was signiﬁcantly larger when
assessing (a) verbal reasoning (b = −.21) than self-reported level of
intelligence, b = −.06; t(29) = 2.53, p < .05, and (b) general
intelligence (b = −.22) than self-reported level of intelligence,
t(29) = 2.47, p < .05. Heterogeneity was slightly reduced when
accounting for the domain of intelligence assessed (Δτ = .01).
The population of studies for each construct tended to be
heterogeneous (H2 ranged from 2.72 [delusion-proneness] to
42.36 [need for cognition]) apart from anthropomorphism (H2 =
.41). Between-sample heterogeneity tended to be large relative to

14

BOWES, COSTELLO, AND TASIMI

Table 4
Study Characteristics, Meta-Analytic Estimates, and Heterogeneity Statistics for the Personological Constructs

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Construct
Psychopathology
Schizotypy
Paranoia
Unusual experiences
Negative affect
Detachment
Antagonism
Disinhibition
Psychoticism
Physical aggression
Depression
Anger
Hostility
General personality
Humility
Emotionality/neuroticism
Extraversion
Agreeableness
Conscientiousness
Openness

k

S

ES

N

r

95% CI

H2

Q

I2(2)

I2(3)

τ21

τ22

τ

12
17
12
5
4
4
4
4
3
8
6
4

16
23
13
9
6
6
6
6
5
9
7
4

26
40
26
13
10
10
10
10
9
10
10
6

5,592
11,850
5,331
2,666
2,378
2,378
2,378
2,378
2,010
19,108
8,094
1,665

.38
.34
.35
.19
.23
.28
.26
.34
.19
.16
.17
.30

[.27, .49]
[.30, .39]
[.25, .44]
[.12, .25]
[.15, .31]
[.17, .39]
[.13, .39]
[.21, .47]
[.09, .29]
[.09, .29]
[.11, .23]
[.16, .44]

18.65
3.86
6.68
2.35
1.28
2.93
3.32
3.33
2.01
17.76
5.83
3.34

510.85
194.33
199.73
43.56
22.76
39.28
43.15
43.29
27.13
187.65
68.28
26.01

53.9%
22.8%
36.0%
75.2%
2.9%
<1%
<1%
4.2%
12.0%
<1.0%
54.4%
7.4%

40.8%
60.3%
55.4%
<1%
71.2%
86.9%
90.3%
86.2%
70.1%
93.1%
30.5%
81.8%

.029
.003
.011
.007
.000
.000
.000
.001
.002
.000
.004
.001

.022
.007
.017
.000
.005
.012
.017
.016
.010
.010
.002
.016

.23
.10
.17
.08
.07
.11
.13
.13
.11
.10
.08
.13

6
28
29
28
28
31

10
37
37
35
36
41

34
62
63
58
62
76

4,899
31,145
30,614
30,086
30,436
31,299

−.15
.05
.03
−.07
−.04*
.02

[−.19, −.12]
[.03, .07]
[.01, .05]
[−.11, −.04]
[−.07, −.00]
[−.02, .06]

3.91
1.13
1.92
4.31
4.76
9.36

166.78
132.07
183.68
308.05
356.93
787.72

80.5%
5.8%
8.4%
11.6%
11.3%
23.2%

<1%
57.9%
61.3%
78.0%
77.2%
70.5%

.007
.000
.000
.001
.001
.004

.000
.002
.002
.008
.008
.014

.08
.04
.05
.10
.09
.12

Note. Bold indicates p < .001, italicized indicates p < .01. k = number of studies; S = number of samples; ES = number of effect sizes; CI = conﬁdence
intervals. Positive correlations indicate that conspiratorial ideation is related to more of a given construct, whereas negative correlations indicate that
conspiratorial ideation is related to less of a given construct.
* p < .05.

within-sample variation (I2(3) ranged from 58.8% [dogmatism] to
88.0% [conjunction fallacy]); the exceptions were self-reported
rationality, illusory pattern perception, and anthropomorphism.
Overall, the standard deviation in true effects between observations
was smaller than the magnitude of the effect sizes, with the
exceptions of need for cognition (τ = .15), susceptibility to the
conjunction fallacy (τ = .16), and dogmatism (τ = .15).

Existential
Conspiratorial ideation was strongly related to perceiving
existential threats (r = .34), believing the world is dangerous
(r = .39), perceiving the world with cynicism (r = .31), and feeling
powerless (r = .28). In line with these ﬁndings, conspiratorial
ideation was weakly-to-moderately related to more anxiety
(anxiety r = .19; death anxiety r = .12) and was weakly, yet
signiﬁcantly, related to perceiving that one has less control (r =
−.17). In contrast, conspiratorial ideation was not signiﬁcantly
related to efﬁcacy (r = −.07), and the relation between efﬁcacy
and conspiratorial ideation did not signiﬁcantly vary by measure of
efﬁcacy after correcting for the false discovery rate (Benjamini &
Hochberg, 1995).
The population of studies for each construct tended to be
heterogeneous (H2 ranged from 3.37 [powerlessness] to 36.65
[efﬁcacy]) except for death anxiety (H2 = .24). Between-sample
heterogeneity tended to be small relative to within-sample variation
(I2(3) ranged from <1% [existential threat, belief in a dangerous
world, death anxiety] to 25.2% [control]); the exceptions were
belief in a dangerous world, powerlessness, anxiety, and control.
The standard deviation in true effects between observations tended
to be smaller than the magnitude of the effect sizes, with the
exceptions of efﬁcacy (τ = .26) and anxiety (τ = .21).

Social
Conspiratorial ideation was related to constructs pertaining to
feeling misunderstood by society and feeling isolated, as it was
strongly associated with more anomie (r = .34), less trust (r = −.26),
and more alienation (r = .28); nevertheless, the latter relationship
was not signiﬁcant. The relations between trust and conspiratorial
ideation did not signiﬁcantly differ across domains of trust. There
was also evidence that conspiratorial ideation is related to
a fragile sense-of-self, as it was weakly related to less individual
self-esteem (r = −.09), moderately related to more individual
narcissism (r = .22), and weakly related to more need for uniqueness
(r = .16). A similar pattern of results emerged when looking at
perceptions of one’s ingroup and outgroup. Speciﬁcally, conspiratorial ideation was moderately, albeit not signiﬁcantly, related to
more collective self-esteem (r = .22), and it was strongly related to
more collective narcissism (r = .34). Additionally, conspiratorial
ideation was strongly related to perceiving outgroup members as
threatening (r = .56) and moderately higher levels of RWA (r = .22)
and SDO (r = .20).
The population of studies for each construct tended to be
heterogeneous (H2 ranged from 2.22 [alienation] to 33.65 [social
threat]) except for need for uniqueness (H2 = .01). Between-sample
heterogeneity tended to be large relative to within-sample variation
(I2(3) ranged from 58.3% [social threat] to 89.7% [alienation]); the
exceptions were need for uniqueness, collective narcissism, RWA,
and SDO. The standard deviation in true effects between observations
was consistently smaller than the magnitude of the effect sizes.

Motivational Variables: Interim Summary
In sum, conspiratorial ideation was weakly and signiﬁcantly related
to less analytical thinking, need for cognition, and intelligence, more

176
18
23
10
17
7
9
9
20
2
2
10
10
20
13
3
69
5
6
11
10
9
3
12
5
153
11
3
16
14
9
53
1
5
3
21
12

151
18
16
3
24
5
17
8
12
7
5
8
3
17

10
4
87
5
8
8
6
13
5
26
21

172
14
—
4
18
13
45

2
6
6
41
26

Epistemic
Self-reported rationality
Cognitive reﬂection
Need for cognition
Self-reported intuition
Bullshit receptivity
Conjunction fallacy
Delusion-proneness
Illusory pattern perception
Illusory agency detection
Anthropomorphism
Dogmatism
AOT
Intelligence

Need for closure
Intolerance of ambiguity
Existential
Existential threat
BDW
Cynicism
Powerlessness
Anxiety
Death anxiety
Control
Efﬁcacy

Social
Anomie
Alienation
Individual self-esteem
Individual narcissism
Need for uniqueness
Trust

Collective self-esteem
Collective narcissism
Social threat
RWA
SDO

3
7
4
5
3

4
1
1
—
—
2
—
—
—
—
—
—

—
—
—
—
—

—
—
3
—
—
—
—
2
—
1
—

10
—
—
—
—
—
—
—
10
—
—
—
—
—

Scenario

1
—
—
1
—
—
—

1
1
3
—
1
1
1
—
—
—
—

—
2
20
1
—
1
—
9
—
9
—
24
—
1
1
—
—
—

11
1
—
—
—
—
—
—
5
—
—
—
—
1

2
—
—
—
—
—
2
—
—
—
—
—
—
—

Fictitious

CT type
Stereotype

—
—
—
4
5

19
—
—
—
5
1
2

—
—
—
—
—
—
—
—
—
—
—
—

1
—
175
—
—
—
1
4
—
1
—

—
—
6
—
—
—
—
6
—
—
—

18
1
7
—
2
1
—
2
—
—
—
—
1
1

—
—
—
—
—
—
—
—
—
—
—
—
—
—

6
18
13
63
36

335
26
5
20
27
23
95

23
10
13
11
15
21
16
35
8
47
26

332
36
32
13
39
10
28
15
47
9
7
18
12
37

No

COVID-19
Yes

Mixed

—
—
—
—
—
Auth = 2; comb = 5; cultural = 1;
govt = 29; inst = 21; inter = 35;
med = 3; science = 2
—
—
—
—
—

—
—
—
—
—
—
—
External = 8; political = 5;
self = 13

—
—
—
—
—
—
—
—
—
—
—
—
General = 6, matrix = 4;
numeracy = 8; verbal = 7;
self-report = 8
—
—

Measure type moderators

5
14
13
45
24

290
17
4
20
11
19
74

14
9
161
10
12
18
15
26
8
39
22

250
24
26
11
23
5
23
10
42
9
7
3
8
22

1
4
—
22
17

64
9
1
2
21
5
24

10
1
27
1
3
3
2
13
—
9
4

100
13
13
2
18
7
5
7
5
—
—
15
5
16

Unpub.

Pub. status
Pub.

Note. CT = conspiracy theory; Pub. status = publication status; Pub. = published; unpub. = unpublished; AOT = actively open-minded thinking; BDW = Belief in a Dangerous World; auth =
authority; comb = combined; govt = government; inst = institutions; inter = interpersonal; med = medical; RWA = right-wing authoritarianism; SDO = social dominance orientation. The number of
effect sizes is displayed for each level of the moderator.

Specific

General

Construct

Table 5
Descriptive Statistics for Each Moderator for the Motivational Constructs

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CONSPIRATORIAL IDEATION META-ANALYSIS

15

32
34
42

25

27

33

Agreeableness

Conscientiousness

Openness

1
—
1
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—

—
—
—
—
—
—

Fictitious

5
—
4
—
—
—
—
—
—
—
—
—
1

Stereotype

—

—

—

—

—
—

1
—
—
—
—
—
—
—
—
1
—
—
—

Scenario

1

1

1

1

1
1

1
—
—
—
—
—
—
—
—
—
1
—
—

Mixed

4

4

4

4

—
4

2
5
2
—
—
—
—
—
—
—
1
—

Yes

72

58

54

58

34
57

24
35
24
13
10
10
10
10
9
10
9
6

No

COVID-19

—
—
—
—
—
—
—
—
—
—
—
—
—
HEX = 14; CIHS = 10, GIHS = 10
HEX = 10, BFI = 14, BFI-10 = 1,
IPIP = 8, TIPI = 24, FFMRF = 1, BFI-10 = 1
HEX = 10, BFI = 14, BFI-10 = 1, IPIP = 8,
TIPI = 24, FFMRF = 1
HEX = 10, BFI = 14, BFI-10 = 1, IPIP = 8,
TIPI = 20; FFMRF = 1
HEX = 10, BFI = 14, BFI-10 = 1, IPIP = 8,
TIPI = 24; FFMRF = 1
HEX = 11, BFI = 14, BFI-10 = 1, IPIP = 13,
TIPI = 24, BFAS = 4, FFMRF = 1, NEO = 4

General personality measure

50

41

41

42

26
41

121
18
35
22
8
5
5
5
5
2
7
7
3

Pub.

26

21

17

21

8
21

60
8
5
4
5
5
5
5
5
7
3
3
3

Unpub.

Pub. status

Note. CT = conspiracy theory; General personality measure: HEXACO PI-R = HEXACO Personality Inventory–Revised; HEX = HEXACO PI-R; CIHS = Comprehensive Intellectual Humility Scale;
GIHS = General Intellectual Humility Scale; BFI = Big Five Inventory; IPIP = International Personality Item Pool-NEO Short-Form; TIPI = Ten-item Personality Inventory; FFMRF = Five-factor
Model Rating Form; BFI-10 = Big Five Inventory 10-item Version; BFAS = Big Five Aspects Scale; NEO = Neuroticism, Extraversion, Openness Personality Inventory–Revised; Pub. status =
publication status; Pub. = published; Unpub. = unpublished; HEXACO = Honesty-Humility, Emotionality, Extraversion, Agreeableness, Conscientiousness, Openness to Experience. The number of
effect sizes is displayed for each level of the moderator.

34

25
34

8
27

28

100
12
15
15
8
8
8
8
8
2
4
5
1

73
14
20
11
5
2
2
2
2
6
5
5
4

Psychopathology
Schizotypy
Paranoia
Unusual experiences
Negative affect
Detachment
Antagonism
Disinhibition
Psychoticism
Physical aggression
Depression
Anger
Hostility
General personality
Humility
Neuroticism

Extraversion

Specific

General

Construct

CT type

Table 6
Descriptive Statistics for Each Moderator for the Personological Constructs

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16
BOWES, COSTELLO, AND TASIMI

CONSPIRATORIAL IDEATION META-ANALYSIS

17

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This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Figure 3
Rank-Ordered Distribution of Meta-Analytic Correlations

Note. The size of the circles in the ﬁgure corresponds to the number of studies
included for that construct (i.e., larger circles reﬂect more studies). A negative
correlation indicates that the variable is related to less conspiratorial ideation,
whereas a positive correlation indicates that the variable is related to more
conspiratorial ideation. RWA = right-wing authoritarianism; SDO = social
dominance orientation; AOT = actively open-minded thinking. See the online
article for the color version of this ﬁgure.

dogmatism and need for certainty, more anxiety and less perceived
control, and less individual self-esteem. Conspiratorial ideation was
moderately and signiﬁcantly related to less open-minded thinking,
more reliance on intuition, more illusory pattern perception, less
trust, and more individual narcissism, RWA, and SDO. Finally,
conspiratorial ideation was strongly related to more delusion-proneness

and anthropomorphism, more existential threat sensitivity, belief
in a dangerous world, cynicism, and powerlessness, more anomie,
and more collective narcissism and social threat perception. The
population of studies for each construct tended to be heterogeneous,
and between-sample heterogeneity tended to be large relative to
within-sample variation for assessed motivational variables.

18

BOWES, COSTELLO, AND TASIMI

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Figure 4
Meta-Analytic Effects Weighted by Sample Size for Motivational Constructs

Note. The size of the circles in the ﬁgure correspond to the number of studies included for that construct (i.e., larger circles
reﬂect more studies). A negative correlation indicates that the variable is related to less conspiratorial ideation, whereas a
positive correlation indicates that the variable is related to more conspiratorial ideation. AOT = actively open-minded
thinking; RWA = right-wing authoritarianism; SDO = social dominance orientation. See the online article for the color
version of this ﬁgure.

Personological Correlates
Psychopathology
Conspiratorial ideation was signiﬁcantly and positively related
to all indices of psychopathology; effect sizes ranged from small

to large. Regarding paranoia and allied constructs, conspiratorial
ideation manifested large correlations with more paranoia (r = .34),
schizotypy (r = .38), and tendencies to have unusual experiences
(r = .35). Moreover, conspiratorial ideation was related to broad
personality disorder liability, as it manifested medium-to-large

Figure 5
Meta-Analytic Effects Weighted by Sample Size for Personological Constructs

Note. The size of the circles in the ﬁgure correspond to the number of studies included for that construct (i.e., larger circles
reﬂect more studies). A negative correlation indicates that the variable is related to less conspiratorial ideation, whereas a
positive correlation indicates that the variable is related to more conspiratorial ideation. See the online article for the color
version of this ﬁgure.

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CONSPIRATORIAL IDEATION META-ANALYSIS

19

p < .001. Heterogeneity was slightly reduced when accounting for
personality measure (Δτ = .02).

correlations with all general personality disorder dimensions (rs
ranged from .19 [negative affect] to .34 [psychoticism]). Conspiratorial ideation was also related to indices of externalizing and
internalizing. Speciﬁcally, conspiratorial ideation was weakly
associated with more physical aggression (r = .19), depression
(r = .16), and anger (r = .17), and it was strongly related to hostility
(r = .30).
The population of studies for each construct tended to be
heterogeneous (H2 ranged from 1.28 [detachment] to 18.65
[schizotypy]). Between-sample heterogeneity tended to be small
relative to within-sample variation (I2(3) ranged from <1%
[detachment, antagonism, depression] to 36.0% [unusual experiences]) with the exceptions of schizotypy, negative affect, and
anger. The standard deviation in true effects between observations
was consistently smaller than the magnitude of the effect sizes.

In sum, conspiratorial ideation was strongly related to all indices
of psychopathology, spanning internalizing, externalizing, and
personality disorder traits. In contrast, the correlations between
conspiratorial ideation and general personality traits were less-thansmall (rs < .10). The exception was humility, including both
honesty–humility and intellectual humility, as it was a small-tomoderate and negative correlate of conspiratorial ideation. The
population of studies for each construct tended to be heterogeneous,
and between-sample heterogeneity tended to be large relative to
within-sample variation for assessed personological variables.

General/Normal-Range Personality

Moderators and Publication Bias

Big Five personality traits, including openness (r = .02),
conscientiousness (r = −.04), extraversion (r = .03), agreeableness
(r = −.07), and neuroticism (r = .05), were weak correlates of
conspiratorial ideation; all relations, except for openness, were
signiﬁcant. The population of studies for each construct tended to
be heterogeneous (H2 ranged from 1.13 [neuroticism] to 9.36
[openness]). Between-sample heterogeneity was large relative to
within-sample variation (I2(3) ranged from 57.9% [neuroticism] to
78.0% [agreeableness]). The standard deviation in true effects
between observations mostly exceeded the magnitude of the
effect sizes, except for neuroticism (τ = .04).
The general personality measure variable signiﬁcantly moderated
the relations between conspiratorial ideation and neuroticism and
conscientiousness. Regarding neuroticism, its relationship with
conspiratorial ideation was signiﬁcantly larger when neuroticism
was assessed with (a) the IPIP (b = .10) than the HEXACO PI-R,
b = .01; t(52) = 2.59, p < .05, and (b) the IPIP than the TIPI, b = .04;
t(52) = 2.21, p < .05. Heterogeneity largely did not change
when accounting for personality measure (Δτ = .00). Regarding
conscientiousness, its relationship with conspiratorial ideation
was signiﬁcantly larger when conscientiousness was assessed
with the (a) HEXACO PI-R (b = −.14) than with the BFI, b = −.04;
t(52) = 2.30, p < .05, (b) the HEXACO PI-R than the IPIP, b = .01;
t(52) = 2.92, p < .01, and (c) the HEXACO PI-R than the
TIPI, b = .01; t(51) = 3.80, p < .001. Heterogeneity was slightly
reduced when accounting for personality measure (Δτ = .01).
Humility was a signiﬁcant, albeit small, negative correlate of
conspiratorial ideation, meaning conspiratorial ideation was related
to less humility (r = −.15). The population of studies for humility
was heterogeneous (H2 = 3.91). Between-sample heterogeneity
was small relative to within-sample variation (I2(3) < 1%), and the
standard deviation in true effects between observations did not
exceed the magnitude of the effect size (τ = .05) Personality
measure signiﬁcantly moderated the relationship between humility
and conspiratorial ideation such that the relationship was
signiﬁcantly larger when using the (a) HEXACO PI-R (b =
−.18) than the GIHS, b = −.06; t(31) = 3.66, p < .001; only assesses
the intrapersonal features of intellectual humility, and (b) the CIHS
(b = −.22; assesses emotional, interpersonal, and intrapersonal
features of intellectual humility) than the GIHS, t(31) = 5.42,

The descriptive statistics for each moderator for the motivational
and personological constructs are reported in Tables 5 and 6. The
conspiracy theory type moderation results and COVID-19
moderation results (Supplemental Tables S8 and S9) and the
publication bias results (Supplemental Tables S14 and S15) can be
found in the Supplemental Materials. Below, we discuss results
from models with both a signiﬁcant omnibus F value and a
signiﬁcant follow-up t test.10 The full moderation results are
available at https://osf.io/jxyfn/.

Personological Variables: Interim Summary

Motivational
Epistemic
Conspiracy Theory Type. Conspiracy theory type signiﬁcantly moderated the relations between conspiratorial ideation
and (a) cognitive reﬂection, (b) illusory pattern perception, (c)
actively open-minded thinking, and (d) need for closure. Cognitive
reﬂection was a stronger correlate of belief in speciﬁc conspiracy
theories (b = −.19) than general conspiracy theories, b = −.14;
t(37) = 2.37, p < .05. Similarly, actively open-minded thinking was
a stronger correlate of belief in speciﬁc conspiracy theories (b =
−.27) than general conspiracy theories, b = −.17; t(12) = 3.02, p <
.05. Turning to illusory pattern perception, the relationship between
conspiratorial ideation and illusory pattern perception was
signiﬁcantly stronger when assessing ﬁctitious (b = .35) conspiracy
theories than general (b = .17) conspiracy theories, t(43) = 2.05, p <
.05. The relationship between conspiratorial ideation and need for
closure, however, was stronger for general (b = .16) than speciﬁc
(b = .05) conspiracy theories, t(21) = 3.36, p < .01. Heterogeneity
was largely unchanged when accounting for conspiracy theory
type in the relations between cognitive reﬂection and illusory
pattern perception and conspiratorial ideation (Δτs were .00 and
.01, respectively). In contrast, heterogeneity was modestly reduced
when accounting for conspiracy theory type in the relations
between actively open-minded thinking and need for closure and
conspiratorial ideation (Δτs were .03 and .02, respectively).
10

The statistical signiﬁcance of the omnibus F statistics was unchanged
after employing a Benjamini and Hochberg (1995) correction for multiple
comparisons.

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20

BOWES, COSTELLO, AND TASIMI

The COVID-19 variable also signiﬁcantly moderated the
relationship between conspiratorial ideation and cognitive reﬂection, such that the relationship was stronger when assessing
COVID-19 (b = −.25) than non-COVID-19 (b = −.15) conspiracy
theories, t(37) = 2.33, p < .05. Yet, heterogeneity was largely
unchanged when accounting for conspiracy theory type in this
relation (Δτ = .00).
Publication Bias. There was no evidence for publication bias
in the relations between epistemic motives and conspiratorial
ideation when examining the publication status variable. Still,
regarding PET-PEESE, there was evidence for publication bias.
The PET test was signiﬁcant for cognitive reﬂection ( p < .05), but
the follow-up PEESE test indicated that the relationship between
cognitive reﬂection and conspiratorial ideation was still large,
negative, and signiﬁcant (intercept = −.26). The PET test was
also signiﬁcant for susceptibility to the conjunction fallacy ( p <
.01); the follow-up PEESE test indicated that the relationship
between conspiratorial ideation and susceptibility to the conjunction
fallacy was not signiﬁcant and was negative (intercept = −.02).

Existential
Conspiracy Theory Type. Conspiracy theory type signiﬁcantly moderated the relations between conspiratorial ideation
and belief in a dangerous world and control. First, the relation
between conspiratorial ideation and belief in a dangerous world
was larger for general (b = .45) than speciﬁc (b = .33) conspiracy
theories, t(12) = 7.91, p < .05. Regarding control, the relation
was signiﬁcantly larger when assessing (a) conspiracy stereotypes
(b = −.26) than general conspiracy theories, b = −.13; t(44) = 2.28,
p < .05, and (b) conspiracy stereotypes than speciﬁc conspiracy
theories, b = −.15; t(44) = 2.38, p < .05. Heterogeneity was slightly
reduced when accounting for conspiracy theory type in these
relations (Δτs were .01).
Publication Bias. There was no evidence for publication bias in
the relations between existential motives and conspiratorial ideation
when examining the publication status variable. Instead, the
relationship between conspiratorial ideation and efﬁcacy was
signiﬁcantly larger in unpublished (b = −.49) than published
(b = −.01) studies, t(24) = 2.39, p < .05. Heterogeneity was
modestly reduced when accounting for publication status in this
relation (Δτ = .04). No PET tests were signiﬁcant.

Social
Conspiracy Theory Type. Conspiracy theory type signiﬁcantly moderated the relations between conspiratorial ideation and
(a) anomie, (b) individual narcissism, (c) collective narcissism, (d)
social threat perception, (e) RWA, and (f) SDO. The conspiracy
theory type variable moderated the relations between conspiratorial
ideation and (a) anomie, (b) collective narcissism, (c) social threat
perception, (d) RWA, and (e) SDO such that the relations were
stronger when using measures of speciﬁc (bs ranged from .25
[SDO] to .67 [social threat]) than general (bs ranged from .14 [SDO]
to .29 [anomie]) conspiracy theories (ts ranged from 1.94 [RWA]
to 5.68 [social threat], dfs ranged from 15 [collective narcissism] to
63 [RWA], ps < .05). In contrast, the relation between individual
narcissism and conspiratorial ideation was signiﬁcantly larger

when using measures of general (b = .24) than speciﬁc (b = .19)
conspiracy theories, t(30) = 2.23, p < .05.
Moreover, the relations between conspiratorial ideation and
collective narcissism and social threat perception were signiﬁcantly
larger when using measures of conspiracy stereotypes (bs were .37
and .96) than general (bs were .16 and .21) conspiracy theories (ts
were 2.34 and 3.38, dfs were 15 and 10, ps < .01). Similarly, the
relationship between conspiratorial ideation and SDO was
signiﬁcantly stronger when using measures of conspiracy stereotypes (b = .53) than measures of general (b = .14) and speciﬁc (b =
.25) conspiracy theories (ts were 4.94 and 3.38, dfs were 38, ps <
.01). The COVID-19 variable also moderated the relation between
conspiratorial ideation and SDO, such that the relation was stronger
when using measures of COVID-19 (b = .42) conspiracy theories
than non-COVID-19 (b = .18) conspiracy theories, t(39) = 2.78,
p < .01.
By and large, heterogeneity was slightly reduced when
accounting for conspiracy theory type in the aforementioned
relationships (Δτ ranged from .00 [individual narcissism, RWA]
to .02 [anomie]). Heterogeneity was moderately reduced for
collective narcissism and social threat perception when accounting
for conspiracy theory type (Δτs were .06 and .09). Nevertheless, for
SDO, heterogeneity was largely unchanged when accounting for
the COVID-19 variable (Δτ = .00).
Publication Bias. There was little evidence for publication
bias when examining publication status as a moderator. In fact,
publication status signiﬁcantly moderated the relation between
conspiratorial ideation and RWA such that the relation was
stronger in unpublished (b = .30) than in published (b = .19) studies,
t(64) = 2.03, p < .05. Heterogeneity was slightly reduced when
accounting for publication status in these relations (Δτ = .01).
Nonetheless, the PET test was signiﬁcant for alienation and SDO
( ps < .05). The follow-up PEESE test indicated that the relation for
alienation was small, positive, and not signiﬁcant (intercept = .07)
and the relation for SDO was similarly, small, positive, and not
statistically signiﬁcant (intercept = .07).

Personological
Psychopathology
Conspiracy Theory Type. Conspiracy theory type signiﬁcantly moderated the relationship between conspiratorial ideation
and paranoia such that the relation was signiﬁcantly larger when
assessing (a) conspiracy stereotypes (b = .61) than speciﬁc
conspiracy theories, b = .29; t(36) = 3.13, p < .01, or (b) general
conspiracy theories (b = .36) than speciﬁc conspiracy theories,
t(36) = 3.17, p < .01; the relation between conspiratorial ideation
and paranoia was also signiﬁcantly larger when assessing
conspiracy stereotypes than general conspiracy theories, t(36) =
2.41, p < .05. Heterogeneity was slightly reduced when accounting
for conspiracy theory type (Δτ = .02).
Publication Bias. There was also evidence for publication
bias in the relation between paranoia and conspiratorial ideation
such that the relation was signiﬁcantly larger in published (b = .36)
than unpublished (b = .21) studies, t(38) = 2.91, p < .01. The
PET test was also signiﬁcant for paranoia ( p < .01); the follow-up
PEESE test indicated that the relationship between paranoia and

21

CONSPIRATORIAL IDEATION META-ANALYSIS

conspiratorial ideation was still positive, large, and statistically
signiﬁcant (intercept = .28).

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General/Normal-Range Personality
Conspiracy Theory Type. Conspiracy theory type signiﬁcantly moderated the relation between conspiratorial ideation and
extraversion, such that the relation was larger when using measures
of speciﬁc conspiracy theories (b = .05) than general conspiracy
theories, b = .01, t(60) = 2.34, p < .05. In addition, the COVID-19
variable signiﬁcantly moderated the relationship between conspiratorial ideation and openness. The relationship between openness
and conspiratorial ideation was signiﬁcantly larger when using
measures of COVID-19 conspiracy theories (b = −.16) compared
with non-COVID-19 (b = .03) conspiracy theories, t(74) = 2.94, p <
.01. Even still, heterogeneity was largely unchanged when
accounting for the conspiracy theory type and COVID-19 variables
in these relations (Δτ = .00).
Publication Bias. There were no signiﬁcant results for the
publication bias analyses.

speciﬁc conspiracy theories (b = .25) than for general conspiracy
theories, b = .20; t(349) = 2.92, p < .01. Neither the publication
status moderation results nor the PET-PEESE results were
signiﬁcant for the motivational domains.
Regarding the psychopathology domain, conspiracy theory
type and publication status signiﬁcantly moderated the relations
between the psychopathology domain and conspiratorial ideation.
Turning to conspiracy theory type, the relations between
conspiratorial ideation and the psychopathology domain were
signiﬁcantly stronger for conspiracy stereotypes (b = .55) than
other conspiracy theory measures (bs were .32 [general] and .26
[speciﬁc]; ts were 1.98 [general] and 2.47 [speciﬁc], dfs were 172,
ps < .05). Also, the relations between conspiratorial ideation
and the psychopathology domain were stronger for general (b =
.32) than speciﬁc (b = .26) conspiracy theories, t(172) = 3.38, p <
.001. There was also some evidence for publication bias, as
conspiratorial ideation was more strongly related to the psychopathology domain in published (b = .32) than in unpublished (b = .21)
studies, t(179) = 2.29, p < .05.

Discussion

Domain-Level Analyses
Meta-Analytic Correlations and Heterogeneity
To clarify whether relations were consistent across variables within
domain, we also conducted domain-level analyses. To do so, we
treated the individual variables, samples, and their interaction
(variable-by-sample) as random effects within the broader domain;
effect sizes were modeled as ﬁxed effects. This modeling allowed
us to calculate the average meta-analytic correlation within
domains. We did not examine general personality at the domainlevel, given that there is no interpretable “general personality
factor” in the literature. All variables within each domain were
coded in the same direction. For instance, in the epistemic domain,
measures of rational thinking, intelligence, and open-minded
thinking were recoded to reﬂect low rational thinking, intelligence,
and open-minded thinking. Across domains, the correlations were
medium, positive, and signiﬁcant (Table 7, Figure 6). Thus,
epistemic, existential, social, and psychopathology domains were
moderately related to more conspiratorial ideation. Heterogeneity
within each of the domains was large (H2 ranged from 9.06
[epistemic] to 22.22 [existential]).11

Moderation Results
First, turning to motivations, conspiracy theory type signiﬁcantly
moderated the relations between (a) the existential domain and
conspiratorial ideation and (b) the social domain and conspiratorial
ideation. Regarding the existential domain, the relations between
conspiratorial ideation and the existential domain were signiﬁcantly
smaller for measures that assessed a mix of conspiracy theories
(b = .08) than for measures of conspiracy stereotypes, b = .30;
t(182) = 2.22, p < .05. Regarding the social domain, the relations
between conspiratorial ideation and the social domain were
signiﬁcantly larger for conspiracy stereotypes (b = .46) than for
other measures of conspiratorial ideation (bs ranged from .14
[scenario] to .25 [general]; ts ranged from 3.28 [scenario] to 6.12
[general], dfs were 349, ps < .01). Moreover, the relations between
conspiratorial ideation and the social domain were larger for

The present investigation, which spanned 170 studies, 257
samples, 52 variables, 1,429 effect sizes, and 158,473 participants,
clariﬁes the motivational and personological correlates of conspiratorial ideation (and their magnitude), quantiﬁes the degree of
substantive differences across these constructs, and sheds light on
moderators that may account for said differences. Overall, this work
holds the potential to inform our understanding of conspiratorial
ideation and chart useful paths forward for future research,
especially when it comes to bridging motivation with personality.
Below, we summarize our ﬁndings and adopt a forward-looking
perspective concerning the remarkably vast and rich pattern of
psychological phenomena associated with conspiratorial ideation.

Motivational Correlates: Considering Epistemic,
Existential, and Social Motives
Our meta-analytic results largely support the tripartite motivational model of conspiratorial ideation (see Douglas et al., 2017). Of
34 epistemic, existential, and social variables, 31 (91%) were
signiﬁcantly related to conspiratorial ideation (see Table 3 and
Figure 4). Moreover, at the domain-level of analysis, the epistemic,
existential, and social motivational domains were all medium
correlates of more conspiratorial ideation. These ﬁndings suggest
that a deprivation of these motivational domains––broadly
construed––is related to more conspiratorial ideation. Overall, the
results corroborate the tripartite model’s core hypothesis that (a)
a need to understand one’s environment, (b) a need to feel secure
and safe in one’s environment, and (c) a need to maintain a
superior, but fragile, image of oneself and one’s ingroup predict
conspiratorial ideation when these needs are deprived. Consistent
with other research (Biddlestone et al., 2022), our ﬁndings reveal
that motivations at large are important, perhaps even essential,
pieces of the conspiratorial ideation puzzle.
11

The statistical signiﬁcance of the main effects and moderation results
for the domain-level analyses were unchanged after employing a Benjamini
and Hochberg (1995) correction for multiple comparisons.

22

BOWES, COSTELLO, AND TASIMI

Table 7
Study Characteristics, Meta-Analytic Estimates, and Heterogeneity Statistics for Motivation and Psychopathology at the Domain-Level
Domain

k

S

ES

N

r

95% CI

H2

Q

I2(2)

I2(3)

τ21

τ22

τ23

τ24

Epistemic
Existential
Social
Psychopathology

77
60
88
47

115
81
126
63

350
188
354
181

59,935
62,331
101,401
44,766

.21
.23
.25
.29

[.17, .26]
[.15, .30]
[.18, .31]
[.24, .34]

9.06
22.22
20.46
12.78

3520.36
4364.59
7595.69
2494.43

45.2%
35.2%
55.5%
80.7%

40.8%
56.4%
39.1%
11.8%

.007
.006
.014
.019

.006
.010
.010
.003

.005
.009
.000
.000

.004
.016
.014
.005

This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Note. Bold indicates p < .001. k = number of studies; S = number of samples; ES = number of effect sizes; CI = conﬁdence intervals. Correlations were
coded to be in the same direction within each domain. τ21 = sample; τ22 = outcome; τ23 = Sample × Outcome; τ24 = effect size.

Yet, results from our meta-analysis and a previous preprint
(Biddlestone et al., 2022) indicate that there is considerable
heterogeneity (and perhaps even statistical uncertainty; see
Biddlestone et al., 2022) in effect sizes within these motivational
domains. At the domain-level, heterogeneity statistics were
exceedingly large, and, at the variable-level, effect sizes within
domain often ranged from small and not signiﬁcant to large
and signiﬁcant. Hence, by lumping these constructs together, we
may lose important information about these granular relations.
Results from this meta-analysis suggest that getting an overall
“quick-and-dirty” snapshot of the domain-level relations is less
informative than a granular and more complex portrait of the
variable-level relations. Similarly, considering Meehl’s (1990)
observation that nearly all psychological constructs are interrelated
to some degree even in the absence of a meaningful connection
(i.e., a “crud factor”), statistical signiﬁcance does not shed light
on the meaning or substance of relations in adequately powered
meta-analyses. Hence, burrowing into the details, as we do below,
may be necessary to glean actionable insights concerning the
network and strength of interrelations between conspiratorial
ideation and motivation.
Of the three motivational domains delineated in the tripartite
motivational framework, the social domain was the best supported
in terms of the magnitude of effect sizes across variables. The

relations between social motives and conspiratorial ideation tended
to be medium-to-large, except for individual self-esteem, which
was a small, negative correlate of conspiratorial ideation. These
results collectively indicate that conspiratorial ideation is linked
to perceiving that one’s group is superior to outgroups and
that outgroups are threatening or immoral. It also seems that
conspiratorial ideation is uniquely related to viewing one’s ingroup
in an overly positive light rather than viewing one’s ingroup
in a positive light—after all, conspiratorial ideation was not
signiﬁcantly related to collective self-esteem. The relationship
between conspiratorial ideation and collective self-esteem, however,
was moderate, so additional research should disentangle feeling
positively toward one’s ingroup from feeling that one’s ingroup is
superior in the context of conspiratorial ideation.
What is more, the two largest correlations between conspiratorial
ideation and any of the motivational constructs assessed in our
meta-analysis were in the social domain. Trust was the largest
negative correlate of conspiratorial ideation and social threat
perception was the largest positive correlate. These two constructs
have not yet been directly meta-analytically investigated, and our
results illuminate their importance in the context of conspiratorial
ideation. The correlation between social threat perceptio

[The evaluation harness truncated this reference: showing the first 120000 of 215182 characters.]
</reference>

<statements>
1. Classic lay epistemic theory describes two tendencies it produces: “seizing” on early, readily available information, and “freezing” on the resulting judgment, preserving closure once it is achieved.
2. High need for closure fosters shallow, heuristic processing and a preference for information that fits existing beliefs, which can strengthen initial misinformation and reduce engagement with contradictory evidence or corrections.
3. A large body of work shows that need for closure is positively, though usually weakly to moderately, associated with endorsement of conspiracy explanations, which are a common form of misinformation.
4. Meta‑analytic syntheses find a small but reliable correlation between conspiracy beliefs and the desire for structure and closure, supporting the idea that such beliefs help cope with unsatisfied epistemic motives.
5. Its influence is largest under conditions of high uncertainty and low analytical or open‑minded thinking, where simple misinformation offers closure and individuals are less inclined to scrutinize it.
6. Conversely, chronically high need for closure combined with low rational or reflective thinking predicts more entrenched conspiratorial ideation and greater resistance to contradictory information.
7. Overall, the role of need for closure is to bias *how* people process and stick with information: it nudges them toward accepting the first plausible story that promises certainty and, once adopted, to resist revising that story—whether it is true or misinformation.
</statements>

Begin the assessment now. Output only the JSON list, without any conversational text or explanations.