Intelligence and personality

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42 Intelligence and Personality
Colin G. DeYoung
Intelligence and personality have often been viewed as distinct psychological
domains that intersect only to a very limited degree. However, research over the
last four decades suggests the possibility that, both conceptually and empirically,
intelligence could be integrated with larger models of personality. Such an integra-
tion may allow a more unified conception of the structure and sources of individual
differences. Since the previous edition of this handbook, the prospect for integrating
intelligence with personality has been strengthened by new research clarifying the
relation of intelligence to broad taxonomies of personality. The first purpose of this
chapter is to explore the conceptual relation of intelligence to personality.
The second is to review empirical research on the relation of intelligence to a wide
range of personality traits.
Following a presentation of working definitions for intelligence and personality,
the chapter reviews arguments for and against three of the most common distinctions
that are drawn between intelligence and personality. These three dichotomies pro-
vide an overview of the major conceptual issues at stake. Given the amount of
thought that has been devoted to the conceptual relation of intelligence to person-
ality, this chapter cannot hope to be comprehensive. Additional perspectives can be
found in three excellent edited collections (Collis & Messick, 2001; Saklofske &
Zeidner, 1995; Sternberg & Ruzgis, 1994). Additionally, the chapter discusses
whether intelligence can be located within the Big Five model (John, Naumann, &
Soto, 2008). Finally, the Big Five personality dimensions serve to organize a review
of empirical associations of intelligence with various personality traits, with
a separate section at the end for associations with sociopolitical orientation.
Definition of Intelligence
In this chapter, “intelligence,”without a modifier, is used to refer to general
intelligence, often known as the g-factor, the ability to perform well on a wide variety
of challenging cognitive tasks (Spearman, 1904). Intelligence contributes to solving
problems (including problems of comprehension) through thinking and reasoning, and
it is well measured by IQ and similar tests (Gottfredson, 1997a; Neisser et al., 1996).
General intelligence occupies the apex of a hierarchy of more specific cognitive
abilities that are all related to each other. At levels of the hierarchy below g, divisions
can be made among narrower forms of intelligence, which are empirically distinct
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despite being correlated with each other (Carroll, 1993; Johnson & Bouchard, 2005a,
2005b). In this chapter, it will be necessary to refer to a distinction between the two
major types of ability at the level of the intelligence hierarchy immediately below g.
These have often been referred to as crystallized and fluid intelligence, but I will refer
to them as verbal and nonverbal intelligence, for several reasons.
Researchindicates that the difference between these two factors is not best captured
by the terms “fluid”and “crystallized,”which were originally developed based on the
theory that some abilities (those called “fluid”) were genetically determined and
uninfluenced by experience or education, whereas other abilities (those that “crystal-
lized”over time) relied on knowledge or skill acquired from experience (Horn &
Cattell, 1966). Factor analyses of the most extensive test batteries available show that
individual differences in ability do not covary according to how much they depend on
acquired knowledge but rather according to whether they require solving problems
using stimuli that are verbal or nonverbal (Johnson & Bouchard, 2005a,2005b;
Johnson, Nijenhuis, & Bouchard, 2007; Major, Johnson, & Deary, 2012). Johnson
and Bouchard (2005a) labeled the nonverbal factor “perceptual,”but nonverbal
memory and reasoning tasks were also encompassed by this factor, and “nonverbal”
seems a more adequately inclusive label. (Their model also identifies a third factor at
the same level of the hierarchy, representing the ability to rotate three-dimensional
images mentally, but this is a much smaller factor than the other two.)
Both verbal and nonverbal intelligence are determined by a combination of innate
ability and acquired knowledge and skills. Verbal intelligence cannot be entirely
crystallized (dependent on experience) because it is just as heritable (that is, its
variation among people is genetically influenced) as nonverbal intelligence, even
after controlling for g(Johnson & Bouchard, 2007; Johnson et al., 2007). Even
vocabulary tests (often held up as prototypically “crystallized”) usually require
people to reason fluidly about the meaning and relations of words and concepts in
order to articulate appropriate definitions on the fly, given that most people do not
memorize dictionaries. Complementarily, nonverbal intelligence is obviously not
entirely fluid (independent of experience) because it is influenced by environmental
factors in studies of heritability (Johnson & Bouchard, 2007; Johnson et al., 2007),
and it has increased in the populations of industrialized nations on a timescale too
short to be due to genetic change (a phenomenon known as the Flynn effect, after its
discoverer). In fact, the Flynn effect for nonverbal (“fluid”) intelligence is consider-
ably greater than that for verbal intelligence (Pietschnig & Voracek, 2015).
Most tests traditionally considered to measure crystallized intelligence are verbal,
whereas most tests traditionally considered to measure fluid intelligence are nonverbal.
Thus, most past findings regarding fluid and crystallized intelligence and personality
can be translated effectively into a verbal-nonverbal framework for the present review.
Definition of Personality
Personality is a broader concept than intelligence, as can be seen in the
following definition by McAdams and Pals (2006):
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Personality is an individual’s unique variation on the general evolutionary design
for human nature, expressed as a developing pattern of dispositional traits,
characteristic adaptations, and integrative life stories, complexly and differentially
situated in culture. (p. 212)
This definition highlights three distinct levels at which personality can be described:
characteristic adaptations, life stories, and traits. Characteristic adaptations and life
stories both describe the individual’s adaptation to their particular sociocultural
context (e.g., as a lawyer), with characteristic adaptations reflecting different strate-
gies and goals that one has adopted and life stories reflecting one’s narrative
descriptions of one’s history and identity (DeYoung, 2015a). Traits describe rela-
tively stable patterns of behavior, motivation, emotion, and cognition (Pytlik Zillig,
Hemenover, & Dienstbier, 2002; Wilt & Revelle, 2015) that are not bound to
a particular sociocultural context but could be observed in any such context (e.g.,
argumentativeness). This is not to say that all traits will have the same average
scores, or identical manifestations, in all cultures, nor that all traits can be observed
in any situation, but rather that any trait can be observed in a range of situations in
any culture (DeYoung, 2015a). Traits will be the primary level of focus in this
chapter. For this reason, vocational interests will not be discussed, despite their
relevance to intelligence and related personality traits (Ackerman & Heggestad,
1997), as they are more like characteristic adaptations than traits, in their cultural
specificity.
A central project in personality psychology has been the development of
a comprehensive taxonomy of traits. Research based both on trait descriptors
drawn from the natural language (as represented in dictionaries) and on large
collections of existing personality questionnaires has provided evidence for a five
factor solution, leading to a taxonomy known as the Five Factor Model or Big Five
(Goldberg, 1990; John et al., 2008; Markon, Krueger, & Watson, 2005; Waller,
DeYoung, & Bouchard, 2016). This model includes the broad trait domains of
Extraversion, Neuroticism, Agreeableness, Conscientiousness, and Openness/
Intellect, each of which will be defined in its own section below. The Big Five are
substantially genetically influenced (Rieman, Angleitner, & Strelau, 1997), and the
genetic factor structure of the Big Five appears to be invariant across European,
North American, and East Asian samples, suggesting the biological universality of
this model (Yamagata et al., 2006).
Personality traits are hierarchically organized, with more specific traits (e.g.,
talkativeness, sociability, enthusiasm) varying together, such that one can deduce
the presence of broader traits (e.g., Extraversion, for the three traits just mentioned)
that account for their covariance. Higher-order traits may exist above the Big Five
(DeYoung, 2006; Digman, 1997), but they appear to be minimally related to intelli-
gence (DeYoung et al., 2008). For the present purpose, therefore, they are of less
interest than levels of trait structure below the Big Five. Each Big Five domain
comprises a large number of lower-level traits, called facets, with no consensus as to
how many facets exist for each domain. Additionally, research suggests the existence
of a level of personality structure between the Big Five and their facets. In two
samples, two genetic factors were necessary to account for the shared genetic
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variance among the facets within each of the Big Five (Jang et al., 2002). If the Big
Five were the next level above the facets, only one genetic factor should have been
necessary for each domain.
In factor analysis of phenotypic data, using fifteen facets for each domain, two
factors similar to the genetic factors were found for each of the Big Five (DeYoung,
Quilty, & Peterson, 2007). These factors were then characterized empirically by their
correlations with more than 2,000 items from the International Personality Item Pool
(Goldberg, 1999). Of particular relevance for intelligence, the two factors in the
Openness/Intellect domain clearly differentiated between Openness to Experience
and Intellect, with Openness reflecting aesthetically oriented traits related to engage-
ment in sensation and perception (e.g., “Believe in the importance of art”;“See
beauty in things that others might not notice”) and Intellect reflecting intellectual
interest or engagement (e.g., “Avoid philosophical discussions”–reversed) and per-
ceived intelligence (e.g., “Am quick to understand things”).
Importantly, traits are probabilistic entities. Each of the Big Five encompasses
many subtraits, and a high score on a Big Five trait indicates an increased likelihood
of high scores on its various subtraits but is not deterministic. This entails that people
scoring high in Intellect will, on average, score higher in Openness than people
scoring low in Intellect. However, the correlation between Openness and Intellect is
far from perfect, which means that some people will score high in Intellect but only
moderate or low in Openness and vice versa. Distinguishing these two aspects of the
broader Openness/Intellect domain from the Big Five turns out to be crucial for
understanding the empirical relation of intelligence to personality, as explained
following a discussion of their conceptual relation.
The Conceptual Relation of Intelligence to Personality
Given a broad definition of personality, like the one presented in the section
“Definition of Personality,”the possibility of describing intelligence as a personality
trait seems clear. Indeed, some early theorists considered personality to include
intelligence (Cattell, 1950; Guilford, 1959). However, most theorists have not
considered intelligence to be part of personality, instead asserting either that intelli-
gence (as defined in the section “Definition of Intelligence”) is unrelated to person-
ality (e.g., Eysenck, 1994) or that intelligence and personality are related but
nonetheless categorically distinct (e.g., Chamorro-Premuzic & Furnham, 2005).
The large body of empirical evidence reviewed in the latter half of this chapter
rules out the possibility that intelligence is unrelated to personality. A number of
personality traits show consistent and meaningful relations to intelligence. Thus, the
important contrast is between the view that intelligence is a personality trait and the
more common view that intelligence is fundamentally different from personality
traits.
Three dichotomies seem to be largely responsible for the view that intelligence
and personality may be related but should be considered categorically distinct.
(Because many researchers have advanced similar dichotomies, with slight
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variations, what follows represents a distillation of many viewpoints.) First,
a distinction is often made between cognitive and noncognitive traits, with intelli-
gence considered to be cognitive and personality considered to be
noncognitive. Second, intelligence and personality differ in their typical methods
of measurement: Intelligence is usually assessed using ability tests, whereas person-
ality is usually assessed by questionnaire. Third, the difference in typical measure-
ment corresponds to a conceptual distinction in which intelligence is often
considered to reflect “maximal performance”(i.e., performance when individuals
are trying their hardest), whereas personality is considered to reflect “typical beha-
vior”(Cronbach, 1949). The following section reviews arguments for and against the
validity of these dichotomies.
The cognitive/noncognitive dichotomy is widely used, but the evidence against it
is strong enough that even some of the people who popularized it have acknowledged
that it is a “misnomer”(Duckworth, 2009, p. 279). The distinction between cognitive
and noncognitive fails because almost all traits have cognitive attributes (even when
“cognitive”is used to designate something like “conscious thought”rather than
referring to any form of information processing), though these are more prominent in
some traits than in others. In a study of common Big Five questionnaires, items
describing cognitive traits were found in all five domains, with Openness/Intellect
containing the most such items and Extraversion and Neuroticism containing the
fewest (Pytlik Zillig et al., 2002). Examples of cognitive attributes are easily
provided, even for traits that might be considered relatively less cognitive:
Neuroticism is associated with rumination, compulsive thinking about possible
threats (Nolan, Roberts, & Gotlib, 1998); Agreeableness is associated with “social-
cognitive theory of mind,”understanding and reasoning about the mental states of
others (Allen et al., 2017; Nettle & Liddle, 2008). Personality includes stable
patterns of cognition, in addition to behavior, motivation, and emotion. Duckworth
(2009; Duckworth & Yeager, 2105) suggests that psychologists may continue to
employ this problematic dichotomy because “cognitive”is a convenient shorthand
for “cognitive ability.”“Noncognitive,”therefore, is used as shorthand to indicate all
variables other than cognitive ability or intelligence, even though many of those
other variables have cognitive attributes. Thus, the existence of the cognitive/non-
cognitive dichotomy appears to reflect imprecise use of language rather than a strong
theoretical assertion that intelligence is categorically distinct from personality.
The second dichotomy involves methods of measurement. Historically, research
on intelligence has been separated from research on personality by the fact that
personality has typically been assessed by questionnaire, whereas intelligence has
typically been assessed by ability tests. These two research traditions thus represent
two paradigms, in Kuhn’s(1970) original sense, separated from each other by
differing sets of conventional scientific practices. Nonetheless, most psychologists
would not assert that different methods of measurement, in and of themselves, justify
a categorical distinction between the constructs that have been measured. (Whether
the differences in measurement are necessary because of an underlying conceptual
distinction is a separate question and the focus of the third dichotomy, discussed later
in the current section.) Psychometricians warn against confusing constructs with
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measures (e.g., Jensen, 1998; Loevinger, 1957). Personality traits are not identical to
scores on personality questionnaires, just as intelligence is not identical to an IQ
score. In both cases, the measures merely provide estimates of what researchers
typically want to investigate –namely, latent traits, actual patterns of human
functioning that persist over time –and these cannot be measured without error.
Multiple methods can be used to measure a single latent trait; each method may
incorporate different sources of error or bias, and one method may be better than
another for the purposes intended, but nonetheless each can be said to measure the
same latent trait. For example, given our working definition of intelligence as
a general mental ability, one should expect it to be best measured by ability tests,
but one could also measure it, albeit less accurately, using questionnaires that require
self-, peer, or observer ratings of subjects’mental ability (this approach is discussed
in more detail in the section “Openness/Intellect”). Differences in typical methods of
measurement, therefore, would not usually be seen as sufficient to rule out the
possibility that intelligence is part of personality.
What makes the issue of measurement more complicated, however, is the possi-
bility that the different types of measures typically used for intelligence and person-
ality correspond to a valid dichotomy between maximal performance and typical
behavior. If intelligence really involves only maximal performance, and if person-
ality really involves only typical behavior, then one would be forced to conclude that
intelligence and personality are categorically distinct. Our working definition of
intelligence can be read to imply that maximal performance is what matters.
However, some theorists have questioned the sharpness of the distinction between
maximal performance and typical behavior (e.g., Ackerman, 1996). This distinction
is blurred by the fact that ability can affect typical behavior, as illustrated by the fact
that IQ scores are good predictors of outcomes that depend on typical behavior –
including job success, academic performance, and health (Deary, 2012). If being
intelligent did not typically entail that one often used one’s intelligence, IQ would be
unlikely to predict real-world outcomes. Because the complexity of the world always
outstrips our simplified mental models (Peterson & Flanders, 2002), intelligence will
often be expressed in typical behavior (Gottfredson, 1997b). Even idle thoughts
seem likely to be different for those high as opposed to low in intelligence. Any
ability for which there is frequent demand or possibility for application will influence
typical behavior, and tests of that ability will provide indices of both maximal
performance and typical behavior. This is not to say that maximal performance is
identical to typical behavior –underachievers who fail to make the best use of their
abilities are a clear counterexample –but a case can be made that intelligence, as
a trait, entails typical behavior as well as maximal performance, even while acknowl-
edging that ability and typical behavior are not the same thing.
The idea that personality involves only typical behavior has also been contested.
The personality research framework provided by the lexical hypothesis has generally
not excluded abilities. Traits that describe ability have been included in all selections
of personality descriptors from natural languages (though more in some than others;
John et al., 2008), and these have not fallen exclusively within the Openness/Intellect
domain in factor analysis. For example, empathy is a component of Agreeableness
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that involves the ability to detect the mental states of others, and many components
of Conscientiousness, such as self-discipline and patience, can be considered abil-
ities. Large differences in outcome may be evident when people are trying their
hardest to be patient, rather than not attempting to restrain themselves, and some
people may be more successful in the attempt than others. Abilities thus appear to be
relatively common within the Big Five.
One complement to the observation that numerous personality traits involve
abilities is the idea that ability tests could be used to measure traits other than
intelligence (Ackerman, 2009; Cattell & Birkett, 1980; Cattell & Warburton, 1967;
Wallace, 1966; Willerman, Turner, & Peterson, 1976). For example, tests of the
ability to detect and understand others’mental and emotional states might be reason-
able measures of at least some facets of Agreeableness (Allen et al., 2017; Nettle &
Liddle, 2008), and tests of the ability to remain calm under stress might be good
measures of Neuroticism. Personality includes many abilities that could potentially
be measured by tests of maximal performance, and better progress may be made in
this area if such tests are designed to reflect theories regarding the key underlying
processes involved in different personality traits (e.g., DeYoung, 2015a). In creating
such tests, one must remember that, because of the differences in method, correla-
tions between questionnaires and tests measuring the same trait are unlikely to be
very high, even if the tests are valid.
Having reviewed arguments for and against the three dichotomies commonly used
to separate intelligence from personality, one can conclude that viewing intelligence
as a personality trait is a viable, if relatively uncommon, conceptual strategy. Many
personality traits appear to involve both cognitive processes and abilities, two
categories that have sometimes been considered exclusive to intelligence. One
might argue that maximal performance (relative to typical behavior) is more impor-
tant in intelligence than in other traits, but this suggests a difference of degree
between intelligence and other traits, rather than a qualitative or categorical differ-
ence. The question of whether intelligence should be considered a personality trait
thus remains open.
Intelligence in the Big Five
The previous section raised the question of whether intelligence can be
considered part of personality. Given the potential viability of an affirmative answer,
another important question is whether intelligence can be integrated with models of
personality, like the Big Five, that are derived from questionnaire measures and
attempt to provide comprehensive taxonomies of traits. Any trait model that would
claim comprehensiveness should presumably include intelligence. Based on lexical
and questionnaire studies, verbal descriptions of intelligence fall within the Intellect
aspect of the Openness/Intellect domain in the Big Five.
The compound label “Openness/Intellect”reflects a history of debate about how
best to characterize the content of this domain, with some researchers preferring
“Openness to Experience”(e.g., Costa & McCrae, 1992a) and others “Intellect”
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(e.g., Goldberg, 1990). This debate was largely resolved conceptually by the obser-
vation that “Openness”and “Intellect”describe two central aspects of the larger
domain (DeYoung, 2015b; DeYoung et al., 2007; Johnson, 1994; Saucier, 1992;
Woo, Chernyshenko, Longley et al., 2014). Lexical studies made it clear that both
aspects are represented in natural language and appear within a single Big Five factor
(e.g., Goldberg, 1990; Saucier, 1992). Many words describe Intellect –intellectual,
intelligent, philosophical, erudite, clever –and many words describe Openness –
artistic, perceptive, poetic, fantasy-prone. Additionally, many words could character-
ize people high in Intellect or Openness or both –imaginative, original, innovative.In
fact, Saucier (1992,1994)proposedthat“Imagination”might be a better single label
for the domain as a whole, given the existence of both intellectual and aesthetic forms
of imagination. This broad sense of “imagination”seems appropriate for a traitdomain
that has, as its central characteristic, the disposition to detect, explore, appreciate, and
utilize both abstract and sensory information (DeYoung, 2015a,2015b). Importantly,
general measures of Openness/Intellect (such as the Revised NEO Personality
Inventory; NEO PI-R; Costa & McCrae, 1992b; the Trait Descriptive Adjectives;
Goldberg, 1992; or the Big Five Inventory; John et al., 2008; Soto & John, 2017)
contain content reflecting both Openness and Intellectand they predict other variables
very similarly, no matter which label their authors prefer (e.g., DeYoung, Peterson, &
Higgins, 2005).
In studies of the Big Five in languages other than English, less agreement about
the nature of the factor corresponding to Openness/Intellect has emerged, relative to
the other four factors. In a Dutch study, for example, this factor was most strongly
characterized by descriptors of unconventionality (Hofstee et al., 1997). (Content
related to unconventionality also appears in the English Openness/Intellect factor but
less predominantly.) However, these differences between languages appear to be
related primarily to criteria for variable selection. In Dutch and Italian lexical
studies, for example, descriptors related to abilities were intentionally undersampled,
leading to the exclusion of many terms that might reflect intellectual ability (John
et al., 2008). Additionally, in a six-factor lexical solution that has been proposed as
a slight modification of the Big Five, the content of Openness/Intellect was more
consistent across all languages (Ashton et al., 2004). Thus, the relative lack of
consensus about the content of Openness/Intellect appears to have been due to
methodological issues. The current state of lexical research suggests that
Openness/Intellect encompasses a range of trait descriptors related to intellectual
and aesthetic curiosity, creativity, imagination, and ability –including descriptors of
intelligence.
As measured by questionnaires, therefore, intelligence can be located within the
Big Five. Despite this semantic fit, objections have been raised because intelligence
tests do not behave quite like questionnaire ratings of descriptors of intelligence. If
multiple cognitive ability tests are factor analyzed with personality questionnaires,
they tend to form a sixth factor, rather than grouping with questionnaire variables
reflecting Openness/Intellect (McCrae & Costa, 1997). However, this result may be
due to one or two artifacts, the first of which is the presence of two distinct sources of
method variance in these factor analyses. In addition to substantive trait variance, all
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of the ability tests share method variance that they do not share with any question-
naire variables and vice versa. This shared variance inflates the intercorrelations
within each type of measure, relative to their correlations with the other type, and
inclines the two types of measure to form separate factors, regardless of what they
share substantively.
A second possible artifact resembles what Cattell (1978) called a “bloated
specific factor,”which could result from the inclusion of many intelligence tests
in factor analysis of broad personality questionnaires. A bloated specificfactor
is one that appears only because measures of a single lower-level trait are
overrepresented in the pool of variables to be factor analyzed. Their large
number will tend to cause them to form a separate factor, even when the
other factors recovered are at a higher level of the trait hierarchy and one of
them should subsume the lower-level trait in question. As an analogy, consider
what would happen if one included many scales measuring anxiety in a factor
analysis with the thirty facets of the Big Five measured by the NEO PI-R.
When this is done, one sometimes finds a sixth factor for anxiety, in addition to
the usual general Neuroticism factor (Oltmanns & Widiger, 2016). This anxiety
factor should be considered a bloated specific factor because the location of
anxiety as a lower-level trait within Neuroticism is well established (John et al.,
2008; Markon et al., 2005).
The existence of distinct method variance for intelligence tests and questionnaires,
plus the possibility of bloated specific factors, makes interpretation ambiguous for
results of joint factor analyses of tests and questionnaires. The factor-analytic results
summarized by McCrae and Costa (1997) could be taken to indicate that intelligence
falls outside of the Big Five (which would imply that descriptors of intelligence do
not measure intelligence as much as they measure some other construct), or they can
be challenged by the argument that an adequate factor analysis would need to take
method variance into account. Unfortunately, there’s a catch to the latter argument:
Modeling method variance in intelligence is complicated by the fact that the relevant
method factor would consist of the variance shared among cognitive ability tests –
but this is exactly the definition of g. Thus, for intelligence, method variance is
thoroughly confounded with substantive variance. One alternative way to test the
location of intelligence within the Big Five in factor analysis is to use a single IQ
score or other index of g, rather than multiple ability tests, because then there are no
other tests with which it can share method and hence no separate method factor.
When this is done, intelligence loads primarily and substantially (>0.30) on the
Openness/Intellect factor, supporting the integration of intelligence as a lower-level
trait within the Big Five personality hierarchy (DeYoung, Grazioplene, & Peterson,
2012).
The idea that intelligence could be a lower-level trait in the personality hierarchy
might strike some as odd, given the obvious importance of intelligence in human
functioning and the number of cognitive abilities that make up the hierarchy below g.
Nonetheless, the location of descriptors of intelligence within the Big Five seems
clear. As noted in the section “Definition of Personality,”the existence of Openness
and Intellect as two correlated but separable aspects of Openness/Intellect was
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supported by factor analysis of fifteen facet scales in this domain, and empirical
characterization of the Intellect factor by correlations with thousands of person-
ality items indicated that it includes at least two facets, intellectual or cognitive
engagement and perceived intelligence or cognitive capacity (DeYoung et al.,
2007; Smillie et al., 2016, appendix). In the Big Five personality hierarchy, there-
fore, intelligence appears to be at a relatively low level: one facet out of at least two
within Intellect, which is itself one of two aspects of the broader Openness/Intellect
domain (Figure 42.1; DeYoung, 2015b). This structural finding highlights the great
complexity of the personality hierarchy, in terms of how many different patterns of
emotion, motivation, cognition, and behavior it encompasses. Intelligence is not
unique in being an extremely important and multifaceted construct that is, none-
theless, relatively narrow when compared with traits like the Big Five that repre-
sent very broad regularities in personality. Anxiety, for example, appears to be one
facet of the Withdrawal aspect of Neuroticism (DeYoung et al., 2007, 2016)and
thus exists at the same level of the personality hierarchy as intelligence. The
relative breadth of a trait places no limitation on its importance to human beings
and seems to place little limitation on the extent to which it may be further
subdivided.
Having located intelligence within the personality hierarchy conceptually, we can
turn in more depth to the question of how it relates empirically to the Big Five and
their lower-order traits. Its putative position within Intellect suggests that it should be
most strongly related to questionnaire measures of Intellect and to general measures
of the Openness/Intellect domain but less strongly to specific measures of Openness
and to other Big Five domains. Having asserted that ability tests are better measures
of intelligence than questionnaires are, this chapter will continue to focus on these
tests and, when “intelligence”is discussed in relation to empirical work, it has been
measured by ability tests, unless otherwise noted.
Figure 42.1 Hierarchical structure of the Openness/Intellect trait domain (from
DeYoung, 2015b).
Levels of the hierarchy are labeled at left. Facets are arranged such that those
closest together are most strongly related and those farthest apart are least related
(DeYoung et al., 2012). Facet labels represent categories of facets and are not
indivisible entities; no consensus exists as to the exact number and identity of
facets. Apophenia is the tendency to detect patterns or causal connections where
none exist.
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Openness/Intellect
Several thorough reviews of associations between intelligence and per-
sonality have been published (Ackerman, 2009; Chamorro-Premuzic & Furnham,
2005;Eysenck,1994; Zeidner & Matthews, 2000), but until recently only one had
been meta-analytic (Ackerman & Heggestad, 1997), and this meta-analysis
included only three studies reporting the correlation of Openness/Intellect with g.
In the previous version of this chapter (DeYoung, 2011), I informally meta-
analyzed nine additional studies that had been published since 1997 and found
a very similar correlation to Ackerman and Heggestad (r = .3). A more recent
dissertation provides an impressively comprehensive meta-analysis of the relation
of intelligence to personality, analyzing effects from more than 900 studies, and
serves as an important source for my discussion in this chapter (Stanek, 2014).
Unfortunately, the dissertation is currently under embargo, and the results are being
updated for publication (Stanek, personal communication, June 2018). Therefore,
I will not be citing exact numbers from this meta-analysis but will provide
approximations and assessments of how well it supports conclusions from already
published data.
One additional complication is that this meta-analysis includes many studies using
non-Big Five questionnaires, whenever possible categorizing scales from those
measures within the Big Five or their aspects and facets and including them in meta-
analytic estimates of associations with constructs from the Big Five hierarchy. This
has the potential to introduce noise and attenuate correlations if any scale categor-
izations are inaccurate or merely approximate. Nonetheless, it provides the most
extensive analysis to date of intelligence-personality associations and confirms that,
of the Big Five, Openness/Intellect shows by far the strongest association with
intelligence, with a correlation around 0.25. Although this correlation is moderate
in magnitude (Hemphill, 2003), it is consistent with the possibility of including
intelligence as a facet of Openness/Intellect, given the lack of shared method. Note
that the average correlation between facets of Openness/Intellect in the NEO PI-R,
which do share method, is only 0.28 (Costa & McCrae, 1992b).
Both Stanek’s(2014) meta-analysis and research using a purpose-built measure of
the Intellect and Openness aspects (the Big Five Aspect Scales; BFAS; DeYoung
et al., 2007) confirm that Intellect is more strongly related to intelligence than
Openness is. Whereas the correlation of intelligence with Intellect is about 0.35,
that with Openness is only in the range of about 0.15 to 0.20 (DeYoung et al., 2012,
2014; Kaufman et al., 2016; Stanek, 2014). Further, when Intellect and Openness are
used as simultaneous predictors, only Intellect is uniquely associated with intelli-
gence (DeYoung et al., 2012, 2014; Woo, Chernyshenko, Stark, & Conz, 2014). This
pattern is consistent with the idea that intelligence can be seen specifically as a facet
of the Intellect aspect of Openness/Intellect within the Big Five.
It is also consistent with research based on scales that were not explicitly designed
to measure Intellect and Openness but that measure facets of these two traits
(DeYoung et al., 2012; Mussel, 2013). Scales measuring components of Intellect
can be categorized as measuring either intellectual engagement or perceived
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intelligence. Commonly used scales measuring intellectual engagement include
Typical Intellectual Engagement (TIE; Goff & Ackerman, 1992), Need for
Cognition (NFC; Cacioppo et al., 1996), and the Ideas facet of the NEO PI-R
(Costa & McCrae, 1992b). The Ideas facet is much more strongly correlated with
TIE (r= 0.77; Ackerman & Goff, 1994) and NFC (r= 0.78; Cacioppo et al., 1996)
than with any of the other NEO PI-R facets (Costa & McCrae, 1992b). Like Ideas,
TIE and NFC have been found to be substantially associated with intelligence
(Ackerman & Heggestad, 1997; Cacioppo et al., 1996; Espejo, Day, & Scott,
2005; Frederick, 2005; Gow et al., 2005; Hill et al., 2013).
Whereas Ideas is the only NEO PI-R facet that is a good marker of Intellect
(DeYoung et al., 2007; DeYoung et al., 2012), four NEO PI-R facets are good
markers of Openness; listed from largest to smallest loading, they are Aesthetics,
Fantasy, Feelings, and Actions.
1
(The sixth Openness/Intellect facet, Values, does
not mark either Openness or Intellect strongly and is discussed below in the section
“Sociopolitical Orientation.”) In studies that consider the NEO PI-R facets indivi-
dually, Ideas typically predicts intelligence more strongly than do the four Openness
facets (DeYoung et al., 2005, 2009, 2012; Furnham et al., 2007; Holland et al., 1995;
McCrae, 1993; Moutafi, Furnham, & Crump, 2003, 2006). Further, a behavioral
genetic study found that a genetic factor influencing intelligence tests was marked
strongly by Ideas but not by the facets that reflect Openness (Wainwright et al.,
2008).
Measures of perceived intelligence are less standardized than measures of intel-
lectual engagement, with some involving Likert-ratings of descriptors of intelligence
and others involving more direct estimations of intelligence with reference to
a normal distribution or percentiles. Nonetheless, a number of studies have examined
their association with performance on intelligence tests, and a meta-analysis of forty-
one such studies found a correlation of 0.33 (Freund & Kasten, 2012). Again, this
effect size is consistent with the location of intelligence within the personality
hierarchy depicted in Figure 42.1, but it also clearly indicates that self-reported
intelligence should not be used as a proxy for tested intelligence (Freund & Kasten,
2012; Paulhus, Lysy, & Yik, 1998). Other-ratings of intelligence fare somewhat
better, though they have been less well studied. Teacher-ratings of intelligence
strongly predict student IQ, with reported correlations ranging from about 0.45 all
the way up to 0.80 (Alvidrez & Weinstein, 1999; Brickenkamp, 1975, cited in
Ostendorf & Angleitner, 1994; Pedulla, Airasian, & Madaus, 1980). Additional
research is necessary on how well intelligence can be rated by others who are not
teachers, such as friends or family members.
The relative lack of accuracy for self-ratings of intelligence suggests the utility of
studying discrepancies between self-rated and tested intelligence (Ackerman, Beier,
1
That the NEO PI-R contains only one Intellect facet and four Openness facets is an idiosyncrasy of that
instrument and does not constitute evidence that Intellect is not central to the larger Openness/Intellect
domain. The facets of the NEO PI-R were derived rationally, rather than empirically, and its authors
have argued against Intellect as a valid interpretation of content in this domain (Costa & McCrae,
1992a; McCrae & Costa, 1997). As noted above, however, considerable evidence in both lexical and
questionnaire research indicates that Intellect is just as central to the larger domain as Openness.
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& Bown, 2002; Paulhus & John, 1998). Self-reported intelligence may reflect
a combination of actual intelligence and inaccurate self-perception that could be
due to over- or underconfidence. Indeed, self-esteem predicts the tendency to rate
one’s intelligence more highly than is warranted by one’s tested intelligence
(Gabriel, Critelli, & Ee, 1994). Gender is another predictor of self-rated intelligence,
with men rating themselves higher than women do, even though no gender difference
exists in general intelligence (Johnson & Bouchard, 2007; Syzmanowicz &
Furnham, 2011). Men also score higher on Intellect and measures of intellectual
engagement than women do (whereas women score higher in Openness), suggesting
that men’s tendency to be overconfident in their intelligence might also encourage
them to be more intellectually engaged (Costa et al., 2001; Weisberg, DeYoung, &
Hirsh, 2011). In addition to the male tendency to exaggerate intelligence, there is also
a female tendency to underestimate (Kaufman, 2012; Steinmayr & Spinath, 2009;
Syzmanowicz & Furnham, 2011).
So far in this section we have considered associations with general intelligence
only. Studies that have examined verbal and nonverbal intelligence separately con-
sistently show that Openness/Intellect is more strongly correlated with verbal than
nonverbal intelligence (Ackerman & Heggestad, 1997; Ashton et al., 2000; Austin,
Deary, & Gibson, 1997; Baker & Bichsel, 2006; Bates & Shieles, 2003; Beauducel
et al., 2007; DeYoung et al., 2005, 2014; Holland et al., 1995; Stanek, 2014). This
differential association has led many researchers to theorize that Openness/Intellect
causes increased “crystallized”intelligence through increased motivation to learn
and through investment in educational pursuits (Chamorro-Premuzic & Furnham,
2005; von Stumm & Ackerman, 2013).
The most thoroughly elaborated theory of this type is the Openness-Fluid-
Crystallized-Intelligence (OFCI) model, which hypothesizes a number of develop-
mental influences of Openness/Intellect on intelligence and vice versa (Ziegler et al.,
2012). (Note, however, that OFCI does not distinguish between the Openness and
Intellect aspects and refers to the broader Big Five dimension of Openness/Intellect
as “Openness.”) The OFCI’senvironmental success hypothesis posits that higher
intelligence leads to higher Openness/Intellect because success in the intellectual
domain leads to greater interest and engagement in that domain. The OFCI’s
environmental enrichment hypothesis posits a causal effect in the other direction,
in which heightened curiosity associated with Openness/Intellect leads to greater
exposure to complex environments, which encourages the development of (fluid)
reasoning ability and, in turn, the greater acquisition of (crystallized) knowledge.
Although the developers of OFCI recognize that what has traditionally been called
“fluid”intelligence can be influenced by environmental factors (as in their environ-
mental enrichment hypothesis), they nonetheless conflate verbal tests with “crystal-
lized”intelligence, and many of the other developmental investment theories do too
(Chamorro-Premuzic & Furnham, 2005; von Stumm & Ackerman, 2013). The
problem with interpreting the stronger correlation of Openness/Intellect with verbal
than nonverbal intelligence as evidence of a developmental investment process is
that, as discussed in the section “Definition of Intelligence,”verbal intelligence
cannot be equated to crystallized intelligence. Because both verbal and nonverbal
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intelligence are influenced by a mix of genetic and environmental forces, their
differential associations with Openness/Intellect are uninformative regarding the
causal relations between Openness/Intellect and intelligence.
To begin to elucidate such causal relations requires longitudinal data, preferably in
a genetically informative sample that can help to rule out likely genetic confounds.
One very lengthy longitudinal (but not genetically informative) study found no
support for the idea that Openness/Intellect is related to change in intelligence over
time, using IQ at ages eleven and seventy-nine years (Gow et al., 2005). Although
Openness/Intellect, assessed at seventy-nine, was correlated with IQ at both ages (r=
0.32 at age eleven and 0.22 at age seventy-nine), it ceased to predict IQ at age
seventy-nine after controlling for IQ at age eleven. Consistent with the argument that
intelligence is a facet of Openness/Intellect, Gow and colleagues concluded that the
variance shared between Openness/Intellect and intelligence probably just reflects
the same stable trait of intelligence across the life span. A smaller longitudinal study,
with more limited assessment of intelligence, did find some association of Openness/
Intellect (rated by parents at age seventeen) with change in intelligence between the
ages seventeen and twenty-three (Ziegler et al., 2012). Clearly, additional research is
needed and genetically informative samples, such as in twin studies, would be
a useful next step.
The differential association of Openness/Intellect with verbal and nonverbal
intelligence can be clarified by separating the Openness and Intellect aspects. In
the previous version of this chapter (DeYoung, 2011), I noted a pattern in which
facets from the NEO PI-R that are markers of Openness appeared to be more weakly
associated with nonverbal intelligence than did the Ideas facet (a marker of Intellect),
whereas they had similar strength of association with verbal intelligence.
Subsequently, we confirmed this pattern with the BFAS, finding in two samples
that Intellect was almost equally strongly associated with both verbal and nonverbal
intelligence, whereas Openness was associated only with verbal intelligence
(DeYoung et al., 2014). Another study similarly found that Intellect but not
Openness predicts nonverbal intelligence (though it did not assess verbal intelli-
gence) (Nusbaum & Silvia, 2011). These findings were also supported by meta-
analysis (Stanek, 2014) and explain why total Openness/Intellect is associated more
strongly with verbal than with nonverbal intelligence, as well as casting further doubt
on developmental theories that rely on this differential association. It also supports
locating intelligence within Intellect taxonomically, given its relation to both the
verbal and the nonverbal subfactors.
The question remains, however, as to why the Openness aspect is related to verbal
but not nonverbal intelligence and remains related to verbal intelligence even after
controlling for Intellect (DeYoung et al., 2014). One possible answer to this question
was provided by a study demonstrating (1) that Intellect and Openness showed
a double dissociation, whereby Intellect predicted working memory and Openness
predicted implicit learning, and (2) that implicit learning was specifically associated
with verbal ability but not with g(i.e., with its unique variance, as opposed to its
variance shared with g) (Kaufman et al., 2010). Implicit learning refers to the ability
to detect and learn patterns in sensory information automatically without conscious
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awareness. Given that Openness is associated with the tendency to perceive and
enjoy patterns in sensory information, implicit learning is a sensible candidate as one
of its functional substrates (DeYoung, 2015b). This implicit-learning ability may
also facilitate language learning, much of which involves detecting statistical reg-
ularities in speech.
The link between intelligence and Intellect is reinforced by studies of working
memory and brain function. Intelligence is very strongly associated with working
memory, the ability to maintain and manipulate information in short-term memory,
despite distraction (Kovacs & Conway, 2016). Further, the brain systems in the
prefrontal cortex (PFC) and parietal cortex that support both working memory and
intelligence overlap substantially, supporting the theory that working memory is one
of the primary cognitive substrates of intelligence (Deary, Johnson, & Penke, 2010).
Not surprisingly, therefore, Intellect appears to be associated with working memory
capacity and also with its neural substrates (DeYoung et al., 2009; Kaufman et al.,
2010). A neuroimaging study of brain activity during a difficult working memory
task found that Intellect predicted neural activity associated with better working
memory performance, in both the left frontal pole (most anterior region) of the PFC
and a region of the medial PFC involved in monitoring performance and detecting
the likelihood of error (DeYoung et al., 2009). The left frontal pole has been strongly
implicated in g(e.g., Gläscher et al., 2010), and, indeed, when controlling for
intelligence, the association between Intellect and neural activity in this area was
attenuated, suggesting that this association reflects the fact that questionnaire mea-
sures of Intellect partially capture actual intelligence. The association between
Intellect and neural activity in medial PFC, however, remained significant after
controlling for intelligence, suggesting that this association might reflect the ten-
dency toward cognitive engagement and effort that is also captured by Intellect.
People who are more motivated to do well in cognitive tasks may be more likely to
expend energy on monitoring their ongoing performance to detect and avoid errors.
A recent study inspired by this finding tested experimentally the hypothesis that
Intellect is partly associated with performance on cognitive tasks because those
higher in Intellect exert more effort (Smillie et al., 2016). Using a dual-task para-
digm, this study showed that those high in Intellect were more susceptible to
decrements in cognitive performance when required to engage in an additional
secondary task, indicating that they were allocating more of their available cognitive
resources to the primary task than were those low in Intellect. These results suggest
that, although Intellect is associated with intelligence, this may not be exclusively
due to differences in ability; Intellect reflects motivation as well as ability in the
intellectual domain.
Another trait that falls within Openness/Intellect in lexical studies is creativity
(Saucier, 1992), and both Openness/Intellect and intelligence are consistently posi-
tively associated with creativity, whether the latter is measured by trait-descriptive
questionnaires, by real-world achievement, or by measures of creative ability in the
laboratory, such as divergent thinking (Feist, 1998; Kaufman et al., 2016; Silvia,
2008). Another chapter provides in-depth review of the association of intelligence
with creativity (see Chapter 45, by Plucker, Karwowski, & J. C. Kaufman, this
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volume). Creativity has often been considered a personality trait, which provides yet
another reason to endorse the possibility of considering other cognitive abilities,
including intelligence, as personality traits. In Figure 42.1, creativity could be listed
with innovation and imagination in the central facet category of the Openness/
Intellect domain, with relations to both Openness, primarily for artistic creativity,
and Intellect, primarily for scientific creativity (Kaufman et al., 2016).
One personality trait positively associated with both creativity and Openness is
often (though not always) weakly negatively related to intelligence; this is apophe-
nia, the tendency to detect patterns or causal connections where none in fact exist
(DeYoung et al., 2012; Miller & Tal, 2007). The word “apophenia”was coined to
describe the central symptoms of psychosis –hallucinations and delusions (Brugger,
2001) –but milder apophenia is a common phenomenon, including things like
mistakenly thinking that one has heard one’s name in a crowd, seeing faces in
inanimate objects, and holding superstitious beliefs, such as astrology. A more
common label for apophenia is “positive schizotypy,”referring to characteristics
associated with schizotypal personality disorder and risk for schizophrenia. People
high in Openness are more likely to experience apophenia presumably because they
detect more patterns in general and some of those patterns are Type I errors.
Intelligence, however, should facilitate screening out false positives from real
patterns, thus encouraging lower levels of apophenia. Despite their weak or negative
correlation, intelligence and apophenia both load positively on the general
Openness/Intellect factor and can potentially be considered peripheral facets of
that Big Five dimension, with apophenia as a facet of Openness and intelligence as
a facet of Intellect (Figure 42.1; DeYoung et al., 2012, 2016).
Extraversion
Extraversion comprises a set of lower-level traits related to approach
behavior and positive affect, including assertiveness, talkativeness, drive, sociabil-
ity, activity level, and positive emotionality. Extraversion appears to represent the
manifestation in personality of sensitivity to rewards, both anticipated and received
(DeYoung, 2015a; Wacker & Smillie, 2015). Meta-analyses of many studies shows
that Extraversion is negligibly related to intelligence, with a correlation of 0.05 or
less (Stanek, 2014; Wolf & Ackerman, 2005). Further, any weak positive association
of intelligence with Extraversion might be artifactual, simply reflecting
Extraversion’s positive correlation with Openness/Intellect (DeYoung, 2006;
Digman, 1997) rather than a real association with intelligence specifically.
Another possibility is that any weak associations of Extraversion with intelligence
could reflect individual differences in low-level cognitive processes that are them-
selves only weakly related to intelligence. For example, Extraversion has been found
to predict better short-term memory (Zeidner & Matthews, 2000), although it does
not typically predict working memory, in which information in short-term memory
must be manipulated or maintained despite distraction (DeYoung et al., 2005, 2009).
Extraversion may be related to some aspects of intelligence test-taking, rather than to
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actual intelligence. Faster speed of test-taking and a lack of persistence during tests
have been associated with Extraversion but results are equivocal (Chamorro-
Premuzic, & Furnham, 2005; Doerfler & Hornke, 2010). In general, the cognitive
correlates of Extraversion seem to be moderated by contextual factors, such as
sensory stimulation and incentives (Eysenck, 1994; Pickering, 2004; Zeidner &
Matthews, 2000). Perhaps because it primarily reflects basic positive emotional
and motivational tendencies, Extraversion appears to be related to the stylistic
ways in which people solve problems that require intelligence, while predicting
their ability to solve them correctly only slightly, if at all.
Neuroticism
Neuroticism encompasses a variety of traits reflecting the tendency to
experience negative emotion, including anxiety, depression, irritability, panic, and
insecurity. It appears to reflect the primary manifestation in personality of sensitivity
to threat and punishment (DeYoung, 2015a; Gray & McNaughton, 2000).
Neuroticism exhibits a small but reliable negative correlation with intelligence, in
the range of −0.10 to −0.15 (Ackerman & Heggestad, 1997; Stanek, 2014). This
correlation is likely to be due to the facts that negative emotion typically interferes
with higher cognition, in part by interrupting the functions of the PFC (Fales et al.,
2008; Keightley et al., 2003), and that neurotic individuals are more likely to
experience anxiety under the pressures of testing situations (Ackerman &
Heggestad, 1997). Measures specifically designed to assess test anxiety are nega-
tively correlated with intelligence, r=−0.33 (Ackerman & Heggestad, 1997). The
most likely reason that this correlation is considerably stronger than the correlation
of intelligence with Neuroticism is that traits are probabilistic, such that not everyone
high in Neuroticism will experience a lot of test anxiety. Individuals who are high in
Neuroticism and generally anxious may nonetheless be nonanxious while taking
tests because of their particular histories and characteristic adaptations. (Similarly,
individuals scoring low in Neuroticism, who are not generally anxious, may none-
theless be anxious about taking tests for reasons related to their personal histories.)
Neuroticism is not inevitably associated with test anxiety, but the substantial correla-
tion between the two (r≈0.5; Ackerman & Heggestad, 1997) means that high levels
of Neuroticism increase the probability of anxiety during tests, which presumably
leads to the small negative correlation between Neuroticism and intelligence. Hence
the association of Neuroticism with intelligence is probably mediated by test anxiety
(Moutafi, Furnham, & Tsaousis, 2006).
Longitudinal studies suggest a link between Neuroticism and change in IQ that
may indicate a substantive association, rather than just a confounding by test anxiety.
One such study, which assessed a large cohort at eleven years old and again at
seventy-nine, found a small negative correlation (r=−0.18) of Neuroticism with
change in IQ over that sixty-eight-year span (Gow et al., 2005), suggesting either that
Neuroticism influences the development of intelligence or that it is linked to age-
related declines in intelligence. The latter possibility is further supported by
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a longitudinal study of more than 600 adults over seventy-one years old, which found
that Neuroticism predicted a steeper rate of cognitive decline over seven years
(Chapman et al., 2012).
Agreeableness
Agreeableness reflects traits involved in altruism and cooperation, contrast-
ing empathy, politeness, kindness, and humility with callousness, rudeness, aggres-
sion, and dishonesty. Meta-analysis has consistently indicated that Agreeableness is
not associated with intelligence (Ackerman & Heggestad, 1997; DeYoung, 2011;
Stanek, 2014). However, like Openness/Intellect, the two major subfactors or aspects
of Agreeableness show differential association with intelligence. The aspects of
Agreeableness are Compassion, reflecting the tendency to experience and express
empathy, sympathy, and concern for others, and Politeness, reflecting the tendency to
avoid being rude or belligerent and to refrain from manipulating or taking advantage
of other people. (The term “compassion”is sometimes used more specifically to
describe the desire to help others, explicitly differentiating this from “empathy,”
defined as sharing others’emotions, but Compassion in the Big Five hierarchy
encompasses both of these things.) Whereas Compassion reflects emotional concern
for others, Politeness seems to be less based in emotional connection and more in
following social rules and inhibiting belligerent or socially disruptive impulses.
Research that separates Compassion and Politeness shows that, although
Politeness is unrelated to intelligence, Compassion is positively related to intelli-
gence, and more strongly to verbal than nonverbal ability, just like Openness, with
correlations around 0.2 (DeYoung et al., 2014; Stanek, 2014). One possible expla-
nation for this pattern is psychometric: Compassion is correlated with Openness,
which may lead to an artifactual correlation with intelligence. Indeed, one study
found that Compassion did not remain significantly associated with intelligence
after controlling for Openness (DeYoung et al., 2014). However, another possible
explanation is that Openness and Compassion share some of their underlying
mechanisms. Openness involves the capacity for imagination, in the sense of
simulating experience, such as an imagined future or a fictional world.
Compassion also involves the capacity for imagination because, to understand
what others are experiencing (known as “mentalizing ability”), one must imagine
the world from their perspective.
Openness, Compassion, mentalizing, and imagination have all been linked to the
brain’s so-called default network, an extensive brain system involved in self-directed
thought (in contrast to attention directed toward external stimuli) and in the simula-
tion of experience in episodic memory, prospection, and mentalizing (Allen et al.,
2017; Andrews-Hanna, Smallwood, & Spreng, 2014; Beaty et al., 2016). Further, the
subnetwork of the default network that is most strongly linked to mentalizing ability
is also linked to language processing, potentially helping to explain why Compassion
and Openness are specifically linked to verbal intelligence (Andrews-Hanna et al.,
2014).
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Although Politeness appears not to be related to intelligence, aggression, which is
a facet of Politeness (reversed), often is found to be negatively related to intelligence
(Ackerman & Heggestad, 1997; DeYoung et al., 2008; Frisell, Pawitan, &
Långström, 2012; Huesmann, Eron, & Yarmel, 1987; Séguin et al., 1999).
However, results are inconsistent and meta-analysis suggests little association
(Stanek, 2014), which may be due to the existence of different measures, types,
and severities of aggression. Some questionnaire measures of aggression include
being rude or pushy as instances of aggression, rendering the construct similar to
Politeness, which is not correlated with intelligence. The examples of negative
correlation cited above tend to focus on physical aggression, and perhaps it is
physical aggression specifically that is linked to low intelligence.
Consistent with an association with physical aggression, intelligence is negatively
associated with the broader trait of externalizing behavior, which includes antisocial
behavior, impulsivity, and drug abuse, in addition to aggression (DeYoung et al., 2008;
Krueger et al., 2007; Raine et al., 2005; Séguin et al., 1999). Among the Big Five,
Agreeableness and Conscientiousness show the strongest (negative) correlations with
externalizing behavior (Miller & Lynam, 2001). Behavioral genetic research suggests
that the association between externalizing behavior and intelligence is genetically
based (Koenen et al., 2006). Many questions remain regarding the association of
aggression and antisocial behavior with intelligence, which will hopefully be clarified
by future research that distinguishes between different types of aggression.
When components of Agreeableness such as detecting the emotional states of
others or facilitating harmonious social relations are measured by ability tests rather
than questionnaires, they are correlated with intelligence (Mayer, Salovey, & Caruso,
2004; Mayer, Roberts, & Barsade, 2008; Roberts, Schulze, & MacCann, 2008). This
finding has emerged primarily from work on emotional intelligence, which has been
defined as “the ability to engage in sophisticated information processing about one’s
own and others’emotions and the ability to use this information as a guide to
thinking and behavior”(Mayer, Salovey, & Caruso, 2008, p. 503). Many question-
naires have been developed to assess emotional intelligence, but they reflect
a diverse and rather incoherent collection of different conceptualizations of the
construct (Mayer, Salovey, & Caruso, 2008; Roberts et al., 2008). Of more interest
are ability tests that have been developed to assess emotional intelligence, most
prominently the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT),
which comprises a battery of subtests that involve tasks like identifying emotions
in facial expressions or judging how best to manage others’emotions in social
situations. Despite psychometric limitations (Barchard, 2003; Brody, 2004), the
MSCEIT can be considered an encouraging example of the assessment of personality
using ability tests rather than questionnaires. Scores on the MSCEIT are consistently
associated with intelligence, with a correlation of about 0.3 (Mayer et al., 2004;
Roberts et al., 2008). Like Openness and Compassion, the MSCEIT appears to be
more strongly associated with verbal intelligence than with nonverbal intelligence
(Mayer et al., 2004; Roberts et al., 2008).
Despite the fact that the MSCEIT is at least moderately related to intelligence, its
primary association with the Big Five is with Agreeableness, rather than with
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Openness/Intellect. Across a number of studies, scores on the MSCEIT have been
found to be correlated with Agreeableness in the range of 0.20 to 0.30 (Mayer et al.,
2008; Roberts et al., 2008). They are also correlated with Openness/Intellect, but
more weakly, in the range of 0.10 to 0.20. Correlations with Extraversion,
Neuroticism, and Conscientiousness are lower still (Mayer et al., 2004, 2008;
Roberts et al., 2008). Thus, emotional intelligence has roughly the same magnitude
of relation to Agreeableness that intelligence has to Openness/Intellect and self-
reported intelligence. The ability to recognize and manage emotions effectively in
social situations can potentially be considered a component of Agreeableness and
one that is positively associated with general intelligence. One study found that most
of the variance in the MSCEIT could be accounted for by g, Agreeableness, and
gender (Schulte, Ree, & Carretta, 2004), suggesting that emotional intelligence
might reasonably be considered a compound of Agreeableness and general
intelligence.
Conscientiousness
Conscientiousness describes the tendency to be organized, self-disciplined,
responsible, and hardworking, as opposed to lazy, messy, impulsive, and distractible.
It appears to reflect the ability and tendency to prioritize nonimmediate or abstract
goals, leading to the exertion of effort to pursue goals or follow rules (DeYoung,
2015a). Among the Big Five, it is the best predictor of both academic and occupa-
tional success, as well as health and longevity (Roberts et al., 2014). In fact, the only
psychological trait that predicts these outcomes more strongly is intelligence.
Interestingly, however, intelligence and Conscientiousness are nearly unrelated,
and it may even be that Conscientiousness is weakly negatively related to intelli-
gence, although the evidence is somewhat inconsistent (Ackerman & Heggestad,
1997; DeYoung, 2011; Stanek, 2014).
One potential explanation for a weak negative association of intelligence with
Conscientiousness is provided by a theory of compensation (Chamorro-Premuzic &
Furnham, 2005; Moutafi, Furnham, & Paltiel, 2004). People who are unintelligent
may be more orderly in order to avoid complexity that they find difficult to manage
because of their low intelligence. Similarly, they may tend to work extra hard, so as
to accomplish tasks that could be performed more quickly or easily by someone more
intelligent. Given that intelligence and Conscientiousness both predict academic and
occupational success substantially but independently, this theory is plausible.
Evidence suggests, however, that it may be onlyone aspect of Conscientiousness that
is negatively associated with intelligence and therefore a candidate as a compensatory
mechanism. The two aspects of Conscientiousness are Orderliness and Industriousness
(DeYoung et al., 2007), and meta-analysis suggests that Orderliness is weakly nega-
tively correlated with intelligence, whereas Industriousness is positively related to
intelligence (Stanek, 2014). A positive association of Industriousness with intelligence
is consistent with the finding, noted in the previous section, that externalizing behavior is
negatively correlated with both intelligence and Conscientiousness. When comparing
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the aspects of Conscientiousness, externalizing problems are more strongly associated
with Industriousness than with Orderliness (DeYoung et al., 2016). Impulsivity is a core
feature of externalizing problems related to Conscientiousness, and it too has been found
to correlate negatively with intelligence (Kuntsi et al., 2004; Lynam et al., 1993; Vigil-
Colet & Morales-Vives, 2005). (Note that some forms of impulsivity are more strongly
associated with Neuroticism or Extraversion than with Conscientiousness, and different
forms of impulsivity may be differentially associated with intelligence; DeYoung &
Rueter, 2016; Whiteside & Lynam, 2001).
Conceptually, Conscientiousness is clearly linked to the tendency to forgo
immediate rewards, in favor of longer-term goals. Normatively, people discount
rewards that are delayed (Frederick, Loewenstein, & O’Donoghue, 2002), but
the strength of this delay discounting shows considerable variability and has the
characteristics of a stable personality trait (Kirby, 2009). Delay discounting is
typically measured through a series of choices between smaller, more immediate
rewards and larger, delayed rewards, with similar outcomes obtained whether
these choices are hypothetical or actually result in reward (Shamosh & Gray,
2008). A meta-analysis of twenty-four studies indicated a correlation of −0.23
between delay discounting and intelligence (Shamosh & Gray, 2008). In one
study, this association was partially mediated by working memory capacity and
by neural activity in the same frontopolar region of the PFC discussed in relation
to Intellect (Shamosh et al., 2008). Delay discounting is positively correlated
with questionnaire measures of impulsivity (Hinson, Jameson, & Whitney, 2003;
Ostaszewski, 1996; Richards et al., 1999; Swann et al., 2002) but only weakly
correlated with Conscientiousness, with a correlation around −0.1 (Mahalingam
et al., 2014).
Finally, in both childhood and adulthood, ratings of intelligence and Intellect in
questionnaires are associated positively with Conscientiousness, and especially with
Industriousness (Costa & McCrae, 1992a; DeYoung et al., 2007). In adults, this
association does not prevent Intellect descriptors from loading primarily on a broader
Openness/Intellect factor. In preschool-age children, however, this association
appears to be strong enough that traits reflecting Intellect may group with
Conscientiousness in factor analysis, rather than with traits that reflect Openness,
such as perceptual sensitivity and enjoying low intensity sensations, which form
their own separate factor (De Pauw, Mervielde, & Van Leeuwen, 2009; Shiner &
DeYoung, 2013).
A link between Intellect and Conscientiousness may reflect their related biological
substrates in the PFC (Shamosh et al., 2008). The lateral PFC is responsible for
maintaining focus on nonimmediate goals and inhibiting impulsive responses
(Bunge & Zelazo, 2006; Rueter et al., 2018), functions associated with
Conscientiousness, but it is also responsible for manipulating information in work-
ing memory, functions associated with Intellect and intelligence (DeYoung et al.,
2005, 2009). These two classes of PFC function, one more stabilizing and the other
more flexible and exploratory, may be in tension, though both have been described as
“executive function.”As the PFC is developing rapidly in young children, differ-
ences in overall state of development might cause Intellect and Conscientiousness to
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covary (Shiner & DeYoung, 2013). After the PFC is more fully developed, however,
the functional similarity of Intellect and Openness, as forms of exploratory cogni-
tion, may link Intellect more strongly with Openness than with Conscientiousness.
Further, Conscientiousness and intelligence appear to be related to two distinct
neural networks that both have nodes in lateral PFC: a goal priority network and
a cognitive control network, respectively (Rueter et al., 2018). At biological, beha-
vioral, and psychometric levels of analysis, the relation of intelligence to
Conscientiousness and related traits is a pressing topic for investigation in person-
ality psychology.
Sociopolitical Orientation
Although culturally specific social and political attitudes are clearly char-
acteristic adaptations rather than traits, a general tendency toward conservatism
versus liberalism (broadly defined) is a trait that might be found in any culture and
that has been studied along with related traits such as right-wing authoritarianism
and traditionalism (Bouchard et al., 2003; Koenig & Bouchard, 2006). Sociopolitical
orientation receives a separate section here because it cannot easily be categorized
within any one of the Big Five. Conservatism, authoritarianism, and traditionalism
are associated negatively with Openness/Intellect but also positively with
Conscientiousness and particularly Orderliness (Carney et al., 2008; Hirsh et al.,
2010; Goldberg & Rosolack, 1994). Additionally, conservatism is associated nega-
tively with the Compassion aspect of Agreeableness but positively with the
Politeness aspect (Hirsh et al., 2010; Osborne, Wootton, & Sibley, 2012).
Sociopolitical orientation thus appears to reflect a complex blend of multiple basic
traits and this blend is consistent with the characterization of the core of conserva-
tism as dislike of change and uncertainty, plus anti-egalitarianism, and the core of
liberalism as openness to change, plus egalitarianism (Hirsh et al., 2010; Jost, 2017).
(Note, however, that openness to change and egalitarianism are distinct dimensions
that are nearly uncorrelated among people who are not politically engaged; Malka,
Lelkes, & Soto, 2017.)
In keeping with their negative association with Openness/Intellect, conservatism
and authoritarianism are negatively associated with intelligence. A meta-analysis
estimates this correlation at around −0.15 for conservatism and −0.30 for author-
itarianism (Onraet et al., 2015). However, the correlation with conservatism varies
as a function of sample characteristics, such as age and the quality of assessment,
and a number of studies find correlations of conservatism with intelligence in the
range of −0.20 to −0.35 (e.g., Bouchard et al., 2003; Deary, Batty, & Gale, 2008;
Koenig & Bouchard, 2006; Ludeke, Rasmussen, & DeYoung, 2017). Longitudinal
studies have even found that childhood or adolescent IQ negatively predicts
conservatism in adulthood (Block & Block, 2006; Hodson & Busseri, 2012).
Like Openness and Compassion (but in the opposite direction), conservatism is
more strongly related to verbal than nonverbal intelligence (Ludeke et al., 2017;
Onraet et al., 2015).
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In the NEO PI-R, the Values facet of Openness/Intellect assesses liberal versus
conservative sociopolitical attitudes and an alternative measure of this facet has been
labeled “Liberalism”(Goldberg, 1999). The Values facet seems to behave most like
the Ideas facet in its association with intelligence and working memory, typically
showing stronger correlations than the four Openness facets (Chamorro-Premuzic
et al., 2005; DeYoung et al., 2005, 2009). However, Values does not clearly mark
either the Intellect or the Openness aspect of Openness/Intellect, potentially because
liberalism represents a compound of Openness/Intellect with other traits (DeYoung
et al., 2007; Hirsh et al., 2010).
Liberalism is characterized by appreciation of diverse points of view and embrace
of change, which may be facilitated by intelligence and working memory in part
because change and consideration of diverse perspectives produce higher levels of
complexity in experience. Such complexity may be difficult to manage for those of
lesser intelligence (note the similarity of this argument to the one described in the
“Conscientiousness”section regarding the compensatory negative association
between Orderliness and intelligence; Orderliness is a strategy for reducing com-
plexity). Further, liberalism is characterized by concern for the welfare of others, as
reflected in its association with Compassion, and Compassion is also positively
correlated with intelligence. Thus, most of the personality traits correlated with
liberalism are correlated in the same direction with intelligence, which may reflect
the fact that sociopolitical orientation is best considered to be a blend or compound of
several basic traits, rather than a basic trait itself.
Nonlinear and Interactive Associations of Personality and
Intelligence
Thus far, all associations of intelligence with other traits considered in this
chapter have been linear and nonmultiplicative. A few studies, however, have
examined more complex effects. Analyses of two large samples (N> 1000) and
one larger still (N> 70,000) suggested an absence of nonlinear associations between
intelligence and personality (Austin et al., 2002; Reeve, Meyer, & Bonaccio, 2006),
but analysis of the even larger Project TALENT sample (N> 360,000) found
a number of nonlinear associations, which could be important when considering
the extremes of the intelligence distribution (Major, Johnson, & Deary, 2014).
Participants both high and low in intelligence scored lower on Orderliness than
those intermediate in intelligence. Additionally, two scales that showed nonlinear
effects in opposite directions reflected the two major aspects of Extraversion:
Sociability (corresponding to Enthusiasm) was lower at both extremes of intelli-
gence, whereas Leadership (corresponding to Assertiveness) was higher at both
extremes. This suggests the existence of substantive associations of Extraversion
with intelligence, despite the absence of a linear relation, which might be suppressed
if the two aspects are not considered separately.
In addition to nonlinear effects, there may also be important multiplicative or
interactive effects of intelligence, in which the effect of intelligence differs depending
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on the level of other traits or vice versa. For example, intelligence may influence the
effects of Neuroticism, as suggested by studies of interactions between Neuroticism
and intelligence in predicting various outcomes. One such study found that leadership
performance was predicted by this interaction (Perkins & Corr, 2006): For individuals
high in Neuroticism, intelligence was positively associated with performance,
whereas for those low in Neuroticism, intelligence was unrelated to performance.
Another study found a similar effect for the interaction of Neuroticism and intelli-
gence, among military conscripts, in predicting performance, physical health, and
adjustment to military life (Leikas et al., 2009). Those high in Neuroticism showed
poor performance, health, and adjustment only if they were low in intelligence.
Intelligence, therefore, may act as a buffer for neurotic individuals, allowing them
to cope with stressors despite heightened sensitivity to negative affect.
Intelligence has also been found to interact with Openness/Intellect in several studies.
In a study of 180 psychology students, Openness/Intellect predicted vocabulary only at
low levels of intelligence, suggesting that those who are highly intelligent do not need to
make any particular effort to learn new words, whereas those who are relatively unin-
telligent will learn new words only if they are high in Openness/Intellect and hence
curious and motivated to explore new information (Ziegler et al., 2012). (Because the
vocabulary test in this study used a multiple-choice format designed to prohibit deduction
of the correct answer, it was more reasonable as a measure of learned “crystallized”
information than vocabulary tests that require spoken definitions of words.) A similar
finding emerged in a sample of 836 Chinese secondary students, in which nonverbal
intelligence interacted with Openness/Intellect to predict academic performance in Math,
Chinese, and English (Zhang & Ziegler, 2015). Again, there was a positive correlation of
performance with Openness/Intellect only for those low in intelligence, suggesting that
the motivation associated with Openness/Intellect can compensate for low intelligence in
challenging cognitive tasks, like schoolwork. Two studies in Germany, however, did not
replicate this effect and instead found interactions of intelligence with Conscientiousness
in predicting academic performance (Bergold & Steinmayr, 2018). In these samples,
intelligence predicted performance more strongly in those high rather than low in
Conscientiousness, suggesting that, among students low in Conscientiousness, highly
intelligent students may fail to achieve up to their full potential or that, among relatively
unintelligent students, being more conscientious may not lead to much improvement in
grades. Given the disparities in results across different studies, additional research on the
interaction of intelligence with other personality traits is clearly warranted.
Conclusions and Future Directions
Intelligence can be viewed either as a construct that is categorically distinct
from personality or as one construct within the larger domain of personality. Neither
viewpoint is supported by incontrovertible evidence, but I believe that psychology
would benefit from the conceptual integration of intelligence and personality. The
mandate of personality psychology is to understand the whole person as a coherent
entity (DeYoung, 2015a; McAdams & Pals, 2006), and this goal can be furthered by
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consideration of intelligence as a personality trait. In discussing the relation of
intelligence to Openness/Intellect, Saucier (1994, p. 294) wrote, “Intelligence is
prone to suck in, or perturb the orbit of, any construct that comes near it.”This
assertion evokes an image of personality traits as small planets orbiting a massive
sun of intelligence. Framed grandiosely, one purpose of this chapter is to propose
a Copernican revolution, whereby intelligence is now simply one trait among many,
orbiting the central concept of personality. As mentioned in the section “The
Conceptual Relation of Intelligence to Personality,”this proposal is not entirely
novel but similar proposals in the past have not been much heeded. Given recent
developments in understanding the difference between Openness and Intellect and
their differential association with intelligence, the time may have come when this
revolution is sufficiently empirically supported to gain traction.
The major conceptual barrier to integrating intelligence and personality is the old
distinction between maximal performance and typical behavior. I suggest that this
dichotomy, although intuitively appealing, may ultimately fail to distinguish person-
ality from intelligence, both because individual differences in intelligence entail
individual differences in typical behavior and because many personality traits
encompass abilities other than intelligence. Broad personality traits reflect pervasive
regularities in human functioning, and such regularities are likely to reflect types of
challenge that are common in everyday life (DeYoung, 2015a; Nettle, 2006). Any
such challenge provides an opportunity, or even a demand, for the application of
relevant ability, ensuring that ability will be intimately tied to typical behavior. From
this perspective, underlying most traits is both a motivational component –how
likely the relevant mechanism is to be engaged –and an ability component –how
likely the mechanism is to succeed when engaged (DeYoung, 2015a).
A full integration of intelligence with personality requires locating intelligence
within hierarchical trait taxonomies, like the Big Five model. In the Big Five,
descriptors of intelligence are located within the Intellect aspect of the broader
domain of Openness/Intellect. As reviewed in this chapter, this location is strongly
consistent with the patterns of correlation of intelligence tests with trait question-
naires. Having located intelligence within Intellect one can address what is perhaps
a more interesting question: Are there personality traits other than Intellect that are
associated with intelligence and, if so, why? Utilizing the Big Five framework, this
chapter reviewed what is known about these associations and highlighted a number
of empirical questions that should be addressed in future research.
Particularly interesting are the associations of intelligence with Agreeableness and
Conscientiousness. As typically measured in Big Five questionnaires, both show little or
no association. However, some of their lower-level aspects and facets, as well as
conceptually related constructs such as delay discounting and emotional intelligence,
do show significant associations with intelligence. Agreeableness reflects the mechan-
isms by which we are able to cooperate with others and Conscientiousness reflects the
mechanisms by which we are able to follow rules and work toward distant goals.
Understanding exactly how intelligence relates to these sophisticated psychological
functions is of paramount importance for understanding personality as a coherent system.
The relatively strong association of intelligence with Compassion (the strongest of any
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trait from the Big Five hierarchy outside the Openness/Intellect domain) is particularly
interesting and warrants further study. It may be relevant for understanding the well-
established negative correlation between intelligence and prejudice (Hodson & Busseri,
2012; Onraet et al., 2015).
Given that individual differences in the intelligence hierarchy below gappear to
cluster according to whether they involve verbal or nonverbal operations, rather than
according to whether they are crystallized or fluid (Johnson & Bouchard, 2005a,
2005b) and that Intellect is related to nonverbal intelligence almost as strongly as to
verbal intelligence, new theories regarding the causal and developmental links
between Openness/Intellect and intelligence probably need to be developed.
Clearly, genetic versus experience-dependent aspects of intelligence are still of
interest, but investigating them will be more challenging now that one cannot simply
assume that any verbal tests assess crystallized intelligence while nonverbal tests
assess fluid intelligence. One promising approach to experience-dependent abilities
is to investigate domain-specific knowledge, while controlling for verbal and non-
verbal intelligence (e.g., Ackerman, 2000). To test developmental theories ade-
quately will require longitudinal, genetically informative designs.
Our understanding of personality generally and intelligence specifically will be
enriched by considering how the psychological functions and biological systems that
underlie intelligence are related to and interact with those that underlie other
personality traits. A biological layer can be added to all of the questions raised in
this chapter. In each case, we know relatively little about how the biological systems
that underlie intelligence (Deary, Penke, & Johnson, 2010; Santarnecchi,
Emmendorfer, Pascual-Leone, 2017) interact with the biological systems that under-
lie other personality traits (Allen & DeYoung, 2017). Pinpointing specific genetic
and neurobiological mechanisms involved in the association of intelligence with
other traits is an important project that has barely begun.
This project may be usefully guided by a cybernetic perspective on personality, in
which traits are presumed to reflect variations in parameters of mechanisms that
contribute to human goal pursuit (DeYoung, 2015a). In this framework, a key
function associated with Openness/Intellect is to generate interpretations of the
world through cognitive exploration, with Openness more oriented toward compre-
hending correlational patterns of association (such as those manifest in sensory
experience) and Intellect more oriented toward comprehending causal and logical
structure (DeYoung, 2015b; Kaufman et al., 2010). With this in mind, one can
understand intelligence –a“capability for comprehending our surroundings”
(Gottfredson, 1997a, p. 13) –as an important mechanism for interpretation of the
causal and logical structure of experience, one that is complemented by intellectual
engagement and by the aesthetic interests and abilities encompassed by Openness.
Acknowledgment
Because this chapter is an updated version of my chapter in the previous
edition of this handbook, I would like, once again, to thank the people who read
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drafts of the chapter in the previous edition and provided helpful feedback: Tom
Bouchard, Wendy Johnson, Niels Waller, Auke Tellegen, Aldo Rustichini, Raymond
Mar, and Jacob Hirsh. Any remaining errors or infelicities are my own and may even
have been introduced as I revised the chapter for this new edition.
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