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Personality and Social Psychology Review
2015, Vol. 19(1) 3 –29
© 2014 by the Society for Personality
and Social Psychology, Inc.
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DOI: 10.1177/1088868314538548
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Article
Advancing an integrative view of the person is a major goal
in current personality research (see Barenbaum & Winter,
2008; Cervone, 2005; McAdams & Pals, 2006; Sheldon,
2004). Although personality traits have often been viewed as
central to the understanding of the person, the position of
personal values has generally been more peripheral (see, for
example, Bilsky & Schwartz, 1994; Buss, 1989; Hofstee,
1994). Some personality scholars have suggested the inclu-
sion of values in an integrative model of characteristics of
the individual (McAdams, 1996; McClelland, 1996; Shoda
& Mischel, 2006; Winter, John, Stewart, Klohnen, & Duncan,
1998), yet, little theoretical or empirical work has been
developed to accomplish this goal (Schwartz, 2011a). If
traits and values are to be combined into a unified model, a
starting point is to examine empirical links between person-
ality traits and personal values.
In this article, we review and clarify conceptual issues
regarding proposed models of relationships between person-
ality traits and values, and use meta-analysis to summarize
past findings regarding these relationships to advance a more
integrative understanding of the person. We make the follow-
ing contributions to the literature: First, we clarify defini-
tions and describe various views on the nature of the
relationships between traits and values; second, we propose
a conceptual underpinning for understanding which traits
should have stronger relationships with values and why; and
third, we offer empirical support for the distinction between
traits and values and explore their interrelations using meta-
analysis. We position our discussion and analyses within the
context of the most researched models of traits and values,
the Big Five (or Five-Factor) model and Schwartz’s (1992)
Value Theory (respectively).
Personality Traits and Personal Values
Personality traits are typically defined as descriptions of
people in terms of relatively stable patterns of behavior,
thoughts, and emotions (e.g., McCrae & Costa, 2003). The
Five-Factor Model (FFM) is the most researched taxonomy
of traits worldwide (e.g., Allik, 2005; McCrae & Costa,
1997); within this model, a large number of traits are com-
bined into five broad trait dimensions that load onto orthogo-
nal factors. The factors and descriptive traits for each are
provided in Table 1.
Personal values (e.g., achievement, security) are gener-
ally described as rather stable broad life goals that are impor-
tant to people in their lives and guide their perception,
judgments, and behavior (e.g., Rokeach, 1973; Schwartz,
1992). Values are organized in personal hierarchies of
538548PSRXXX10.1177/1088868314538548Personality and Social Psychology ReviewParks-Leduc et al.
research-article2014
1James Madison University, Harrisonburg, VA, USA
2Hong Kong University of Science and Technology, Clearwater Bay, Hong
Kong
3Royal Holloway University of London, Surrey, UK
Corresponding Author:
Laura Parks-Leduc, Department of Management, James Madison
University, 800 S. Main St., MSC 0205, Harrisonburg, VA 22807, USA.
Email: leduclm@jmu.edu
Personality Traits and Personal Values:
A Meta-Analysis
Laura Parks-Leduc1, Gilad Feldman2, and Anat Bardi3
Abstract
Personality traits and personal values are important psychological characteristics, serving as important predictors of many
outcomes. Yet, they are frequently studied separately, leaving the field with a limited understanding of their relationships.
We review existing perspectives regarding the nature of the relationships between traits and values and provide a conceptual
underpinning for understanding the strength of these relationships. Using 60 studies, we present a meta-analysis of the
relationships between the Five-Factor Model (FFM) of personality traits and the Schwartz values, and demonstrate consistent
and theoretically meaningful relationships. However, these relationships were not generally large, demonstrating that traits
and values are distinct constructs. We find support for our premise that more cognitively based traits are more strongly
related to values and more emotionally based traits are less strongly related to values. Findings also suggest that controlling
for personal scale-use tendencies in values is advisable.
Keywords
personality traits, personal values, meta-analysis
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4 Personality and Social Psychology Review 19(1)
importance, so that different people consider some values as
more important than others. The most widely used model of
values is the Schwartz’s (1992) Value Theory that identifies
10 broad values based on the motivations underlying them.
Descriptions of these values are provided in Table 2.
According to Schwartz’s theory and ample empirical evi-
dence, values are structured in a circle based on their inter-
relationships, such that values that are more positively
correlated are closer to one another and are thought to be
based on compatible motivations (see Figure 1).For exam-
ple, both self-direction and stimulation values are based on
the motivation for novelty and are therefore positively cor-
related and adjacent to one another in the value circle. Values
that emanate from opposite sides of the circle are negatively
correlated and are thought to be based on conflicting motiva-
tions. For example, self-direction values stem from the moti-
vation for independent thought and action that conflict with
the motivation to fulfill others’ expectations, the latter under-
lying conformity values. The 10 values can be further
grouped into four higher order types of values organized on
two bipolar dimensions: self-enhancement versus self-
transcendence, and openness to change versus conservation
(see Figure 1). This values structure has been examined in
more than 75 countries worldwide and has been found to be
largely universal (Schwartz, 2011b).
Although traits and values are conceptually similar,
researchers describe several distinctions between the two
Table 1. Five-Factor Model of Personality.
Construct Description: The extent to which individuals tend to be . . .
Openness to Experience . . .curious, intellectual, imaginative, creative, innovative, and flexible (vs. closed-minded,
shallow, and simple)
Agreeableness . . .helpful, good-natured, cooperative, sympathetic, trusting, and forgiving (vs. rude,
selfish, hostile, uncooperative, and unkind)
Extraversion . . . sociable, talkative, optimistic, ambitious, assertive, reward-seeking, outgoing, and
energetic (vs. introverted, shy, reserved, quiet, and unadventurous)
Conscientiousness . . .organized, responsible, dependable, neat, efficient, and achievement-oriented (vs.
disorganized, lazy, irresponsible, careless, and sloppy)
Emotional Stability . . . calm, self-confident, stable, resilient, and well-adjusted (vs. neurotic, nervous,
insecure, fearful, and anxious)
Table 2. Schwartz Value Taxonomy.
Construct Description/Items: Individuals who value this believe in the importance of . . .
Power . . . being in charge of people and resources and having money (social power, wealth, authority)
Achievement . . . socially recognized successes (ambition, competence)
Hedonism . . .sensual pleasure (fun, enjoying life)
Stimulation . . .having stimulating experiences (daring, exciting life)
Self-direction . . .independence of thought and action (creativity, freedom, independent, curious)
Universalism . . . promoting the welfare of all people and nature (equality, social justice, protecting the environment)
Benevolence . . .promoting the welfare of people you are close to (helpfulness, loyalty, honesty, forgiving)
Conformity . . .controlling impulses to fulfill others’ expectations (self-discipline, obedience)
Tradition . . .maintaining traditions (moderation, respect for tradition, devout)
Security . . .safety and security of self, family, and nation (family security, social order, clean)
Figure 1. The theoretical structure of values (Schwartz, 1992).
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Parks-Leduc et al. 5
constructs (for reviews, see Bilsky & Schwartz, 1994; Hitlin
& Piliavin, 2004; Parks & Guay, 2009). The most basic dif-
ference between traits and values is that traits are descriptive
variables whereas values are motivational variables. That is,
traits describe how individuals tend to feel, think, and
behave. They are therefore summaries of an individual’s
responses and behaviors. Unlike traits, values express a per-
son’s motivations that may or may not be reflected in behav-
ior (Roccas, Sagiv, Schwartz, & Knafo, 2002). For example,
a creative person (trait) tends to engage in creative thinking
and in creative acts; otherwise, this person would not be
labeled as having the trait of creativity. But valuing creativity
may or may not result in creative thinking or behavior.
Valuing creativity means that the person would like to be
creative and thinks that creativity is important, whether or
not he or she acts on this value. Hence, although it makes
sense to expect that most creative people will view creativity
as important in their lives, the trait and the value are not iden-
tical, and people can have different scores on a trait and a
value that share similar content.
Many researchers (e.g., Olver & Mooradian, 2003) also
propose the distinction that traits are more biologically based
(Goldberg, 1993; McCrae & Costa, 2008), whereas values
are more of a product of a person’s environment, including
culture, education, parental upbringing, and life events
(Rokeach, 1973). We believe that this theoretical distinction
has some merit, although it is most likely an oversimplifica-
tion, and additional research is needed to test the accuracy of
this claim. Although traits are known to be influenced by
genetics, they do vary somewhat by culture and are influ-
enced by environmental variables in addition to genetics
(e.g., Heine & Buchtel, 2009; Kandler, 2012). In addition,
research on heritability suggests that values have genetic ori-
gins in addition to environmental ones (Knafo & Spinath,
2011; Schermer, Vernon, Maio, & Jang, 2011). Understanding
the relationships between traits and values has the potential
to add clarity to continued research in this area.
The Nature of the Relationships
Between Traits and Values
Researchers differ in the way they view the nature of the
relationships between traits and values. They also differ on
how they believe traits and values fit within the overall con-
ceptualization of characteristics of the individual (which is
often broadly termed “personality,” even when it includes
characteristics beyond traits). Although both traits and val-
ues share a common heritage in the lexical hypothesis (the
idea that all important descriptors of an individual will be
encoded in language, and can therefore be culled from a dic-
tionary), the two constructs have been examined separately
since at least the 1930s, when Allport (1937) took pains to
remove values items from his research studies on personal-
ity. He referred to traits as temperament and values as char-
acter (Allport, 1937); these descriptors resurface at times
(see, for example, Cloninger, 1994), but it is not always clear
whether the term “personality” is a reference to temperament
only, or to both temperament (traits) and character (values).
Many researchers do not seem to distinguish between
traits and values; they adhere to the view that all meaningful
aspects of personality are subsumed under traits (Buss,
1989), or that traits and values are different ways of measur-
ing the same thing. Others blur the distinction between traits
and values. For example, the HEXACO personality inven-
tory (K. Lee & Ashton, 2004) is presented as a six-factor
model of personality traits. Yet it includes honesty, which
most values researchers would consider to be a value rather
than a trait. In contrast, others view traits and values as
entirely separate constructs that exist at the same level of
abstraction and prediction; these theorists tend to view psy-
chological needs as antecedents to both (e.g., Parks & Guay,
2009; Roccas et al., 2002). They also tend to define personal-
ity as the aggregate of traits only (not values).
Other researchers view traits and values as different com-
ponents of personality (e.g., Caprara, Alessandri, &
Eisenberg, 2012; Saroglou & Munoz-Garcia, 2008), drawing
on two integrative models of personality. The first model
suggests three levels of personality components, differing in
their level of contextualization (McAdams, 1995; see also
Sheldon, 2004, for a broader variation of this model). In this
model, traits are located in the first level as non-contextual-
ized components of personality, whereas values are part of
the second level of more contextualized elements of person-
ality (the third level has to do with one’s life narratives and
personal identity; McAdams, 1995).
The second integrative model suggests that traits are basic
tendencies that have a biological basis and that traits influence
characteristic adaptations, which include values (McCrae &
Costa, 2008). In this model, values are influenced both by
traits and by external influences, such as culture and life
events. Thus, values are influenced by traits but not solely
determined by them. To illustrate, if an individual is naturally
creative (trait), he or she might also value creativity as an
important life goal to pursue. But this relationship is not deter-
ministic—a person might value creativity even if he or she is
not creative, perhaps as a result of culture or upbringing.
Neither of the integrative models suggest any reason to
expect strong links between the levels of personality (i.e.,
McAdams, 1995; McCrae & Costa, 2008). Therefore, if
traits and values are related, the relationships are not likely to
be particularly strong. These models also both view traits as
antecedent to values (see also Wijnen, Vermeir, & Van
Kenhove, 2007). Yet, values might also influence traits
(Roccas et al., 2002). Specifically, as values motivate behav-
ior, if a value (e.g., benevolence) leads to recurrent behavior
(e.g., caring for one’s younger siblings), this recurrent behav-
ior will later become a trait, because traits include recurrent
patterns of behaviors.
To summarize, some researchers do not clearly distin-
guish between traits and values, some view them as distinct
and separate constructs, and some view them as loosely
related components at different levels of personality. This
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6 Personality and Social Psychology Review 19(1)
myriad of views, and the confusion it creates in the literature,
needs to be acknowledged. As meta-analysis relies on corre-
lations, we do not attempt to provide explanations regarding
the direction of relationships or superiority of one model
over the others. However, before integrating traits and values
into a comprehensive understanding of the individual, estab-
lishing the patterns and magnitudes of these relationships is
an important first step.
Two Sources for the Strength of the
Relationships Between Traits and
Values
Although the links between traits and values are not expected
to be strong, some of the traits of the FFM may be more
closely related to values than are others, as found in previous
research. Although researchers have developed hypotheses
for these relationships based strictly on content similarity, we
propose that the strength of the relationships between traits
and values may be based on two sources of similarities—
similarities in the nature of particular traits and values and
similarities in the content of particular traits and values.
Similarities in the Nature of Traits and Values
All values are inherently cognitive (see, for example, Schwartz
& Bilsky, 1987). Yet unlike values, traits may vary in the extent
to which they are based on cognition (recall that traits are
described as recurrent patterns of thought, behavior, and affect;
McCrae & Costa, 2003). Supporting the stronger cognitive
nature of values compared with traits, Roccas et al. (2002)
found that values predicted a cognitively based outcome better
than traits, and traits predicted an affectively based outcome
better than values. We expect that traits that are more cognitive
in nature will tend to have stronger relationships with values,
because values are cognitive in nature. In contrast, values are
not emotional variables—although they can elicit negative
emotions when they are violated, or positive emotions when
fulfilled (Locke, 1997; Schwartz, 1992; Sheldon & Elliot,
1999). We therefore expect weaker correlations with values for
traits that have a large emotional component.
Which traits in the FFM are the most cognitive and which
ones are the most affective? Using judges’ ratings of items
from multiple Big Five inventories, Pytlik Zillig, Hemenover,
and Dienstbier (2002) found that openness to experience had
a consistently strong cognitive component, and emotional
stability had a strong affective component. The remaining
three traits were all described primarily by behavioral items
(defined as overt, directly observable actions). This finding
suggests that openness to experience should have the stron-
gest relationships with relevant values, whereas emotional
stability should have the weakest. The remaining three traits
should fall in between. Note that although extraversion is
often defined as an affective trait, the typical measurement of
extraversion is primarily in behavioral rather than affective
terms, so we do not expect it to be similar to emotional stabil-
ity in its relationships with values.
Additional support for this premise comes from research
that examines the neuroscience of personality. Cloninger
(1994) developed a personality taxonomy that includes seven
major personality traits based on the different neurobiologi-
cal processes that occur in the brain during trait expression.
He retained Allport’s terms of temperament and character as
separate components of personality and defined tempera-
ment as “automatic associative responses to emotional stim-
uli that determine habits and moods, whereas character refers
to the self-aware concepts that influence our voluntary inten-
tions” (p. 266). The temperament traits relate to emotional
and automatic processes—activities that are primarily asso-
ciated with the mid-brain. The character traits involve the
frontal lobe (frontal cortex) to a greater degree than the tem-
perament traits, suggesting that the character traits are linked
to higher levels of cognitive processing. Neurobiological
research therefore supports the premise that traits vary in
terms of the extent to which they are affectively or cogni-
tively based. In a subsequent study, De Fruyt, Van De Wiele,
and Van Heeringen (2000) correlated Cloninger’s traits with
the Big Five. They found that emotional stability (neuroti-
cism in their study) was strongly correlated with one of
Cloninger’s temperament traits (mid-brain), supporting our
expectations for a weak correlation for emotional stability
with values. Openness to experience, extraversion, and con-
scientiousness all exhibited moderate positive correlations
with both temperament and character traits, whereas agree-
ableness showed a strong positive correlation only with a
character trait (frontal lobe), leading us to expect relatively
strong links for agreeableness with values.
In summary, the FFM traits vary in the extent to which
they are cognitively oriented, based on both research on the
item-level content of Big Five traits and research on the neu-
robiological processes involved in personality expression.
Taken together, we expect that openness to experience should
have the strongest links with values, followed by agreeable-
ness. Emotional stability should have the weakest links with
values, and conscientiousness and extraversion should fall
somewhere in between.
Similarities in the Content of Traits and Values
As research has demonstrated, the strength of relations
between traits and values should also be somewhat determined
by content similarity when comparing each trait with each
value. We briefly review previous hypotheses for expected
links between traits and values, focusing on links that have
been hypothesized by at least two of these previous articles.
Openness to experience. As stated above, we expect openness
to experience to have the strongest and most coherent pat-
terns of relations with values, as compared with the other
traits in the FFM. The content of this trait dimension is quite
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Parks-Leduc et al. 7
similar to the bipolar higher order value dimension of open-
ness to change versus conservation (see Figure 1), which
contrasts openness to new ideas and experiences with a pref-
erence for rigid rules of actions and thoughts (Rohan, 2000).
Hence, individuals who score highly on openness to experi-
ence are likely to value stimulation and self-direction and to
ascribe low importance to conformity, tradition, and security
values (Luk & Bond, 1993; Olver & Mooradian, 2003; Roc-
cas et al., 2002). We expect the relationship between open-
ness to experience and self-direction to be particularly strong,
as both relate to curiosity and creativity. Individuals who
score highly on openness to experience are also likely to
value universalism, as universalism values include tolerance
and openness to ideas and behaviors that are different from
what one is accustomed to (Olver & Mooradian, 2003; Roc-
cas et al., 2002; see also Schwartz, 1992). To summarize, we
expect openness to experience to exhibit relationships with
the following values: stimulation (+), self-direction (+), uni-
versalism (+), conformity (−), tradition (−), and security (−).
Agreeableness. Agreeable individuals are oriented toward
helping others and cooperating with them (e.g., Graziano &
Eisenberg, 1997; John & Srivastava, 1999). This orientation
is similar to the motivation underlying benevolence values,
which aims to enhance the well-being of people in one’s
immediate social environment (family, friends, etc.). Coop-
eration with others requires some willingness to adapt to
group norms as well. Conformity values express the motiva-
tion to fulfill the expectations of others in one’s social groups.
Similarly, tradition values express the motivation to maintain
the customs, traditions, and hierarchy of one’s social groups.
Therefore, both conformity and tradition are likely to be pos-
itively related to the cooperative aspect of agreeableness
(Luk & Bond, 1993; Olver & Mooradian, 2003; Roccas et
al., 2002). In contrast, power values express the motivation
for dominance and control, sometimes at the expense of oth-
ers. They are therefore incongruent with agreeableness
(Olver & Mooradian, 2003; Roccas et al., 2002). We thus
expect agreeableness to exhibit relationships with the fol-
lowing values: benevolence (+), conformity (+), tradition
(+), and power (−).
Extraversion. Extraverts need stimulation. They are highly
energetic, ambitious, assertive, and reward-seeking (e.g.,
Costa & McCrae, 1992; John & Srivastava, 1999). This ten-
dency to seek rewards and to be ambitious is highly compat-
ible with achievement values (Luk & Bond, 1993; Roccas et
al., 2002). In addition, being energetic and having a high
need for stimulation are highly compatible with stimulation
values (Bilsky & Schwartz, 1994; Luk & Bond, 1993; Roc-
cas et al., 2002). We therefore expect extraversion to be
related to achievement (+) and stimulation (+) values.
Conscientiousness. This trait dimension describes socially
prescribed impulse control that facilitates task and
goal-directed behavior (e.g., Fiske, 1994; Hogan & Ones,
1997; John & Srivastava, 1999). McCrae and John (1992)
suggested that conscientiousness has two major components,
each compatible with different values. The first is a proactive
aspect of conscientiousness, which is related to the motiva-
tion for success according to social standards (Costa &
McCrae, 1988). This motivation is also expressed in achieve-
ment values (Luk & Bond, 1993; Roccas et al., 2002). The
second aspect of conscientiousness is inhibitive and is related
to the motivation for impulse control (Costa & McCrae,
1988), expressed in conformity values (Olver & Mooradian,
2003; Roccas et al., 2002). Hence, conscientiousness should
be related to achievement (+) and conformity (+) values.
Emotional stability. People who score highly on this trait tend
to be less prone to negative affect (Costa & McCrae, 1988;
John & Srivastava, 1999). They are not easily distressed and
have healthy coping strategies (Gunthert, Lawrence, &
Armeli, 1999). As this trait is primarily affective, and as val-
ues do not tend to have direct relations to well-being or dis-
tress (Roccas et al., 2002; Sagiv, Roccas, & Hazan, 2004),
this trait is likely to be unrelated to values.
Sinusoid Patterns of Correlations
According to values theory (Schwartz, 1992, 1996), if theory
predicts that a certain variable (such as religiosity) is associ-
ated with a certain value (such as tradition), this variable
should also exhibit positive relations with compatible types
of values (those that are adjacent to it on the circle; in this
example, conformity, security, and benevolence) and nega-
tive relations with conflicting types of values (those that are
opposite to it on the circle; in this example, hedonism and
stimulation). Because the value circle is based on a motiva-
tional continuum, related variables should have a systematic
pattern of correlations with the entire value system. The vari-
able of interest should be most positively related to the value
that is most clearly positively linked with it, and the correla-
tions should become less and less positive as one moves
around the circle and away from that value, eventually mov-
ing to negative relationships. The negative relationships
should reach their maximum with the value on the circle that
directly opposes the value with the strongest positive corre-
lation. If one graphs the correlations, with the values pro-
vided on the graph from left to right in order as one moves
clockwise around the circle, the subsequent line should form
a sinusoid curve (a sine wave, with one major peak and one
major valley).
We expect openness to experience, agreeableness, and
extraversion to display a sinusoidal pattern of correlations
with the full set of values. Specifically, the highest positive
correlation should be with the corresponding value accord-
ing to the research reviewed above, and the correlations with
other values should decrease monotonically going around
the circle of values, creating a sinusoid shape. We do not
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8 Personality and Social Psychology Review 19(1)
expect this pattern with conscientiousness, because it should
be most positively related to two non-adjacent values
(achievement and conformity).
Possible Moderators
What might affect the strength of relations between traits and
values? We consider five moderators, starting with modera-
tors based on theoretical considerations followed by modera-
tors based on methodological issues.
Culture
Culture is often defined as a shared system of meaning (e.g.,
Smith & Bond, 1998), and cultures differ in the meanings
they attribute to events. Different cultures may result in dif-
ferent trait–value relations. Of the possible cultural dimen-
sions that one could consider, individualism versus
collectivism and tightness versus looseness seem to have the
potential to moderate the relationships between traits and
values.
Individualism versus collectivism is the most studied cul-
tural dimension (Taras, Kirkman, & Steel, 2010). According
to Hofstede (1980), individualistic cultures emphasize indi-
viduality—the uniqueness of the individual and his or her
right to pursue personal goals. In contrast, collectivistic cul-
tures emphasize the importance of one’s group and, as a
result, the obligations to one’s group. Cultures also differ in
strength—in the pervasiveness of social norms and in the tol-
erance to deviant behavior from those norms (Pelto, 1968).
Tight societies have a culture with very strong norms and
severe sanctions for the violation of those norms, whereas
loose cultures have more ambiguous norms and are more
permissive of possible deviance (Gelfand, Nishii, & Raver,
2006; Gelfand et al., 2011). Cultures that are tighter or more
collectivistic are thus likely to encourage more normative
value endorsement, whereby individuals within the culture
would be more likely to subscribe to the dominant values of
the culture, rather than those consistent with the individual’s
traits. In contrast, members of looser cultures or more indi-
vidualistic cultures might be more likely to endorse values
that are consistent with their individual personality traits,
leading to higher correlations between values and traits in
more individualistic or looser cultures (for a similar argu-
ment regarding the links between values and behavior, see
Roccas & Sagiv, 2010).
Alternatively, the relationships between traits and values
may be universal as they may stem from the same psycho-
logical processes across cultures. Indeed, although ample
research demonstrates that the means of measures of values
and traits vary cross-culturally (see, for example, Allik,
2012, regarding traits; Schwartz, 2011b, regarding values),
the links between the two systems may be universal, just as
the intercorrelations among traits and those among values
are largely universal (see, for example, McCrae & Costa,
1997; Schwartz, 2011b). Finding that these relationships are
universal would support the view that the links between traits
and values are based on processes that are largely unaffected
by culture. This moderator analysis is therefore particularly
interesting, as its results may inform our fundamental under-
standing of the relationships between traits and values.
Values Instruments
Traits and values have been measured by different instru-
ments, which makes results difficult to generalize because
differences across studies may be the result of using different
scales that assess traits or values in a somewhat different
fashion. However, the variety of scales used, particularly for
traits, meant that few studies used the same measures. As a
result, we could not conduct fully hierarchical moderator
analyses considering both the traits measure and the values
measure. For values, however, most studies used one of two
instruments: the Schwartz Value Survey (SVS; Schwartz,
1992) or the Portrait Values Questionnaire (PVQ; Schwartz
et al., 2001). We therefore conducted a basic moderator anal-
ysis using the values instrument as a moderator.
The PVQ was developed from the SVS with the intention
of creating an instrument that was less abstract and less cog-
nitively complex. Rather than rating the importance of each
value, respondents read descriptions of individuals (i.e., por-
traits) in terms of values and rate the extent to which the
described person is similar to them. An important difference
between these instruments for the purposes of the current
investigation involves how directly they measure values. The
SVS measures values directly, because participants rate
abstract goals in terms of how important they are as a guiding
principle in their lives. Unlike the SVS, in the PVQ, partici-
pants read a description of a person and rate how similar that
person is to them. The description of the person includes two
sentences. Often, one sentence describes the person in terms
of a goal that is important to him or her. This is a direct mea-
sure of a value. For example, the first part of an item that
measures security values is “It is important to her to live in
secure surroundings.” Yet the other sentence sometimes
involves trait-like elements. For example, the second sen-
tence of the item above is “She avoids anything that might
endanger her safety.” As the PVQ has trait-like elements, it is
likely to result in inflated trait–value correlations compared
with the SVS.
Personality Instruments
Although 11 personality instruments were utilized in the
studies that we examine, two were used frequently enough to
include them in a moderator analysis: the Neuroticism,
Extraversion, and Openness to Experience (NEO; Costa &
McCrae, 1992) and the Big Five Inventory (BFI; John,
Donahue, & Kentle, 1991). Arguably the best-validated of
personality inventories, the NEO is commercially available
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Parks-Leduc et al. 9
with differing versions based on age and gender, and it is
widely used in a variety of settings (John & Srivastava,
1999). McCrae and Costa developed the NEO initially from
the work of previous personality researchers, most notably
Cattell. They later added Agreeableness and
Conscientiousness, creating the NEO-PI-R. This inventory
provides 240 items measuring six facets each for each of the
five factors. Items are provided in sentence form, with par-
ticipants rating their level of agreement (or disagreement).
McCrae and Costa subsequently developed a short version
(60 items; the NEO-FFI) that only assesses the five factor-
level constructs. Although it is not identical, the NEO-PI-R
and the NEO-FFI are substantially correlated (John &
Srivastava, 1999), hence we group them together in our mod-
erator analysis.
Researchers developed the BFI (John et al., 1991) in an
effort to achieve some convergence among differing views of
the content of the factors of the Big Five, which were con-
ceptualized somewhat differently by different researchers.
Ten judges with psychology backgrounds reviewed the lit-
erature on all the existing versions of the Big Five, and cat-
egorized 300 items from the Adjective Check List (ACL)
into five categories. The researchers then retained the items
for which there was a high level of agreement and from there,
culled the list down to 44 representative items. Because
adjectives can sometimes have more than one meaning, they
created short phrases for items (John & Srivastava, 1999).
The BFI and the NEO are highly correlated but not exactly
the same; corrected correlations range from .83 (Extraversion)
to .97 (Agreeableness; John & Srivastava, 1999). Because
the NEO and the BFI are highly correlated and because both
rely on longer descriptions (sentences or phrases), we expect
them to yield fairly similar results.
Statistical Adjustments for Values Scale Use
Values research requires a somewhat different approach to
data analysis compared with traits. People make decisions
about how to behave not based on the absolute importance of
a value but rather on its importance relative to other values. In
other words, we cannot predict behavior based solely on how
high a person’s score is on benevolence values; we need to
know how high it is relative to other values that the person also
endorses. Moreover, individuals differ in their use of the scale
such that some people tend to attribute high importance to val-
ues across items, and some low. Schwartz (1992) therefore
recommended controlling for mean importance of values. Due
to these theoretical reasons, we anticipate that the expected
trait–value relations will be more accurate when scale-use ten-
dency of values is controlled. Whereas the majority of studies
controlled for scale use in the correlation matrix, some reported
only the zero-order correlations (in some cases, these studies
subsequently controlled for scale use in their regression equa-
tions or path estimates, which would typically be viewed as
more critical to hypothesis testing).
Other Moderators
Many studies are conducted with university students, who
are a more homogeneous group than the general population
and can therefore generate somewhat different results in
studies compared with the general population (Peterson,
2001). We therefore examined study population as a poten-
tial moderator. Because the studies included varied greatly in
sample size, we also tested whether sample size moderates
trait–value correlations. Finally, as is often done in meta-
analyses, we tested whether publication status moderates
trait–value relations to account for a possible publication
bias.
Meta-Analytic Method
Literature Search
To locate articles for inclusion, we conducted searches using
major electronic databases such as PsycINFO. We used the
keywords “personality,” “traits,” and “values” to search for
related articles. We additionally scanned the reference sec-
tions from the articles produced by the initial search to see
whether additional studies could be located in this fashion.
For studies located that did not include correlations tables,
we contacted authors to request their raw data. Finally, we
contacted researchers in this domain to request unpublished
studies and posted requests for data on related list serves.
Studies were collected up until April 2013; the search yielded
88 possible studies.
Inclusion criteria. We restricted our meta-analysis to the dom-
inant taxonomies for categorizing traits and values reviewed
above—the FFM and the Schwartz values theory (see Tables
1 and 2), and to those studies that examined traits and values
at the individual (rather than group) level. One study (Wijnen
et al., 2007) divided openness to experience into two facets,
labeled “self-rated intelligence” and “creativity.” Correla-
tions were averaged across these facets to create a factor-
level correlation for the meta-analysis. One study (von
Collani & Grumm, 2009) grouped values into four broader
categories rather than using the 10 value types; it was elimi-
nated from our study (results of analyses for the four higher
order value dimensions are available in supplementary files
at http://psr.sagepub.com/supplemental).
Some studies were excluded because they did not provide
the necessary quantitative data for a meta-analysis.
Specifically, 8 studies did not include a correlation matrix
(and we were unable to obtain a correlation matrix from the
author[s]); two studies included only significant correlations;
and 1 study used canonical correlations. These were
excluded. This yielded a total of 60 studies (listed in Table
3), including 29 from published articles, 1 book chapter, 25
unpublished data sets, 2 data sets from conference presenta-
tions, and 3 samples from dissertations. Several studies had
very large sample sizes; 10 studies had samples of more than
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10 Personality and Social Psychology Review 19(1)
Table 3. Studies Included in the Meta-Analysis; Possible Moderators.
Study NPersonality measure Values measure Country
Sample
population
Method of
analysisaPublication status
1. Arthaud-Day, Rode, and
Turnley (2012)
582 IPIP SVS United States Students Partialled Published article
2. Bardi (2005) 103 BFI SVS United Kingdom Students Partialled Unpublished
3. Bardi (2008) 677 TIPI SVS United Kingdom Students Partialled Unpublished
4. Bardi, Buchanan, Goodwin,
Slabu, and Robinson (2014)
136 BFI SVS United Kingdom Police trainees Partialled Published article
5. Bardi, Bull, and Brown (2008) 65 BFI SVS United Kingdom Students Partialled Unpublished
6. Bardi and Guerra (2011) 163 BFI SVS World Students Partialled Published article
7. Bardi and John (2006) 110 BFI SVS United Kingdom Students Partialled Unpublished
8. Bardi, Lee, Hofmann-Towfigh,
and Soutar (2009) (a)
128 BFI SVS United Kingdom Students Partialled Published article
9. Bardi et al. (2009) (b) 196 BFI SVS United Kingdom Students Partialled Published article
10. Bardi, Levontin, and John
(2011)
586 BFI, NEO, and
Saucier’s mini-
markers
SVS and PVQ United States Students Partialled Unpublished
11. Bardi, Loader, Keen, and
Martin (2004)
232 BFI SVS World Students Partialled Unpublished
12 Barrick, Giluk, Shaffer, and
Stewart (2006)
126 PCI PCVS United States Students Correlations Unpublished
13. Barrick et al. (2005) 166 PCI SVS United States Students Correlations Unpublished
14. Blickle, Schlege, Fassbender,
and Klein (2006)
226 NEO SVS Germany 76 white-collar
criminals; 150
managers
Correlations Published article
15. Burns and Postlethwaite
(2007)
159 PCI SVS United States Students Correlations Unpublished
16. Caprara, Schwartz, Capanna,
Vecchione, and Barbaranelli
(2006)
4,349 BFQ PVQ Italy General
population
Unknown Published article
17. Caprara and Vecchione (2006) 944 BFQ PVQ Italy General
population
Correlations Published article
18. Caprara, Vecchione, and
Schwartz (2009)
576 BFQ PVQ Italy Students Unknown Published article
19. Cohrs, Kielmann, Maes, and
Moschner (2005)
512 NEO SVS World General
population
Partialled Published book
chapter
20. Collins and Blum (2011) 199 IPIP SVS United States Students Centered Unpublished
21. Dirilen-Gumus (2010) (a) 386 BFI PVQ United States Students Unknown Published article
22. Dirilen-Gumus (2010) (b) 382 BFI PVQ Turkey Students Unknown Published article
23. Dirilen-Gumus, Cross, and
Donmez (2012)
278 BFI PVQ United States General
population and
Students
Correlations Published article
24. Dollinger, Leong, and Ulicni
(1996) (a)
275 NEO RVS United States Students Standardized Published article
25. Dollinger et al. (1996) (b) 198 NEO RVS United States Students Standardized Published article
26. Goldberg (2008) 698 IPIP SVS United States General
population
Partialled Unpublished
27. Haslam, Whelan, and Bastian
(2009)
180 IPIP SVS Australia Students Partialled Published article
28. Knafo (2007) 278 Saucier’s mini-
markers
SVS Israel Students Correlations Unpublished
29. Kusdil (2000) (a) 147 NEO SVS United Kingdom General
population
Partialled Dissertation
30. Kusdil (2000) (b) 329 NEO SVS Turkey General
population
Partialled Dissertation
31. Lonnqvist and Versakalo
(2005)
498 NEO SVS Finland Military (Reserve
Officer School)
Correlations Unpublished
32. Lonnqvist and Walkowitz
(2010)
120 Short Five PVQ Germany Students Correlations Unpublished
33. Luengo Kanacri, Rosa, and Di
Giunta (2012)
563 BFQ PVQ Italy General
population and
Students
Correlations Published article
(continued)
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Parks-Leduc et al. 11
Study NPersonality measure Values measure Country
Sample
population
Method of
analysisaPublication status
34. Luk and Bond (1993) 114 NEO SVS China Students Partialled Published article
35. MyPersonality—100 items
(Kosinski & Stillwell, 2011)
2,986 NEO SVS World Internet Partialled Unpublished
36. MyPersonality—20 items
(Kosinski & Stillwell, 2011)
1,487 NEO SVS World Internet Partialled Unpublished
37. MyType (Wilson, Gosling, &
Graham, 2012)
15805 BFI PVQ World Internet Correlations Unpublished
38. Olver and Mooradian (2003) 255 NEO and Saucier’s
mini-markers
SVS United States Students Correlations Published article
39. Parks (2007) 367 IPIP RSVS United States Students Correlations Dissertation
40. Parks (2008) 74 IPIP RSVS United States Employees Correlations Unpublished
41. Parks-Leduc, Pattie, Pargas,
and Eliason (2014)
420 IPIP RSVS United States Students Correlations Unpublished
42. Poling, Woehr, Gorman, and
Arciniega (2006)
266 Saucier’s Unipolar
Markers
PVQ United States Students Correlations Conference
paper
43. Roccas, Sagiv, and Porat
(2007)
217 Saucier’s mini-
markers
PVQ Israel Students Partialled Unpublished
44. Roccas, Sagiv, Schwartz, and
Knafo (2002)
246 NEO SVS Israel Students Partialled Published article
45. Saroglou and Munoz-Garcia
(2008)
256 NEO SVS Spain Students Partialled Published article
46. Stankov (2007) 1,255 IPIP SVS United States Students Unknown Published
article
47. Steca, Monzani, and Greco
(2011)
4,285 BFQ PVQ Italy General
population
Unknown Unpublished
48. Sverdlik and Sagiv (2007) 272 Saucier’s mini-
markers
SVS Israel Students Partialled Unpublished
49. Trapnell (2007) 249 BFI PVQ Canada Students Partialled Unpublished
50. Uziel, Sagiv, and Roccas (2007) 170 Saucier’s mini-
markers
SVS Israel Students Unknown Unpublished
51. Vecchione, Alessandri,
Barbaranelli, and Caprara
(2011)
1,675 Unique to study PVQ Italy General
population
Correlations Published article
52. Vecchione, Caprara, Schoen,
Castro, and Schwartz (2012)
(a)
981 BFQ PVQ Italy General
population
Partialled Published article
53. Vecchione et al. (2012) (b) 352 BFQ PVQ Spain General
population
Partialled Published article
54. Vecchione et al. (2012) (c) 190 NEO PVQ Germany General
population
Partialled Published article
55. Vecchione and Mebane (2007) 1,089 BFQ PVQ Italy General
population
Correlations Published article
56. Wijnen, Vermier, and Van
Kenhove (2007)
311 Mervielde’s Big Five
Scale
SVS Belgium Students Correlations Published article
57. Wolfradt and Dalbert (2003) 212 NEO SVS Austria 104 students;
107 general
population
Correlations Published article
58. Xu (2005) 126 IPIP SVS United States
and China
Employees Correlations Conference
paper
59. Yik and Tang (1996) 216 Unique to study SVS Hong Kong Students Correlations Published article
60. YourMorals.org (Graham et
al., 2011)
7,543 BFI SVS World Internet Correlations Unpublished
Note. BFI = Big Five Inventory; BFQ = Big Five Questionnaire; IPIP = International Personality Item Pool; NEO = Neuroticism, Extraversion, and Openness to Experience; PCI =
Personal Characteristics Inventory; PCVS = Pairwise Comparison Values Survey; PVQ = Portrait Values Questionnaire; RSVS = Revised Schwartz Value Survey; SVS = Schwartz
Value Survey; TIPI = Ten Item Personality Inventory.
a.Method of analysis refers to how the researcher(s) presented the correlations. While some researchers just provide the correlations without statistical adjustment, many
values researchers control for scale use by partialling out the mean value score or via some other method.
Table 3. (continued)
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12 Personality and Social Psychology Review 19(1)
1,000 participants. The largest 4 data sets were data gathered
from web sites and social networks—MyType (N = 15,805;
Wilson, Gosling, & Graham, 2012), YourMorals.org (N =
7,543; Graham et al., 2011), and 2 from MyPersonality.org
(N = 2,986 and 1,487; Kosinski, Stillwell, & Graepel, 2013).
MyType and MyPersonality.org can be accessed from
Facebook and include a variety of surveys designed to tell
people more about themselves, including a Myers–Briggs
test, a Big Five personality traits test, the SVS, and others.
MyType surveys have been taken by more than 17,000 users.
YourMorals.org is a site developed by social psychologists to
enhance the study of various topics related to moral, social,
and political psychology; it also includes a variety of sur-
veys, including a Big Five measure and the SVS (Graham,
Haidt, & Nosek, 2009; Graham et al., 2011).
Meta-analytic procedure. Meta-analytic procedures were
based on Hunter and Schmidt (2004). We corrected correla-
tions for unreliability and sampling error (SPSS syntax
adopted from Field & Gillett, 2010). Two studies collected
data on traits or values using more than one scale. This
yielded two correlations that were not independent (because
they came from the same respondents). For one of these stud-
ies (Bardi & John, 2006), composite correlations were calcu-
lated before inclusion in the meta-analysis. Composites were
calculated based on formulas provided by Hunter and
Schmidt (2004). Because composite calculations require that
intercorrelations between all scales be provided, we were
unable to perform the same procedure for the other study
(Olver & Mooradian, 2003). For this study, therefore, the
average correlations were calculated and these were included
instead.
Most studies reported coefficient alpha reliabilities, but
a few did not. When possible, correlations were corrected
individually. When reliability estimates were not provided,
artifact distribution was used to provide a mean reliability;
this was then used to correct for unreliability (see Table 4
for average reliabilities). None of the studies reported reli-
ability estimates accounting for transient error, and as a
result, they are likely to overestimate the true reliability of
the scales. No corrections were made for range restriction,
as data were not available to calculate range restriction on
values. Past research on traits has found little evidence of
range restriction, however, and the same is likely to be true
of values.
Moderator analyses. Hunter and Schmidt (2004) recom-
mended hierarchical moderator analyses when a sufficient
number of studies exists. If moderators are related and the
analyses are not hierarchical, failing to conduct hierarchical
moderator analyses can lead to false conclusions (i.e., mod-
eration could be attributed to the wrong construct). However,
the number of studies was insufficient to perform hierarchi-
cal moderator analyses considering all moderators. As a
result, we conducted separate moderator analyses for each of
the moderators, but we are cautious in our conclusions. Our
cultural moderators were modeled as continuous variables;
all other moderators were categorical.
Culture. The primary studies included in the meta-
analysis were conducted in 13 countries in North America,
Europe, and Asia. This provided cross-cultural variabil-
ity that enabled us to consider whether cultural differences
could create a moderator effect, that is, whether trait–value
relationships might vary by culture. Several studies were
conducted across multiple countries and cultures; these were
removed from this set of analyses.
To conduct the individualism/collectivism moderator
analysis, studies were assigned a number representing their
level of individualism versus collectivism, based on data
from Hofstede (1980; for previous use of this method, see
Bardi & Guerra, 2011; Suh, Diener, Oishi, & Triandis, 1998).
Based on his empirical data, Hofstede assigned culture scores
ranging from 1 to 100, with 1 representing very high collec-
tivism and 100 indicating very high individualism. For
example, the United States is very individualistic and has a
score of 91. Spain has a score of 51, about the middle of the
scale. Hong Kong, with a much more collectivist culture, has
a score of 25. Our studies were skewed toward the high end
of the scale; the majority of the studies were conducted in
countries with moderate to high individualism scores.
Because this moderator was modeled as a continuous vari-
able, weighted least squares (WLS) regression was used for
the moderator analysis rather than sub-grouping, as recom-
mended by Steel and Kammeyer-Mueller (2002). With WLS
regression, the correlation is considered the dependent vari-
able, and the moderator the independent variable, in a regres-
sion analysis (with each study weighted by the inverse of the
sample error variance). Significant betas indicate that mod-
eration has occurred.
Table 4. Average Reliabilities (Coefficient α).
Construct Reliability
Openness to experience .76
Agreeableness .73
Extraversion .78
Conscientiousness .80
Emotional stability .81
Power .72
Achievement .76
Hedonism .72
Stimulation .73
Self-direction .67
Universalism .78
Benevolence .72
Conformity .68
Tradition .63
Security .65
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Parks-Leduc et al. 13
To examine the tightness/looseness of culture as a mod-
erator, studies were assigned a tightness score based on data
from Gelfand and colleagues (2011), with higher scores rep-
resenting a tighter culture. For example, Turkey had a rela-
tively high score of 9.2, representing strong cultural norms.
Israel, in contrast, scored a 3.1, suggesting more acceptance
of behavior that is inconsistent with cultural norms. Included
studies were fairly normally distributed in terms of this cul-
tural moderator; most were in the middle, whereas a few
studies were at either end of the range. As in the previous
analysis, WLS regression was used to conduct the moderator
analysis.
Values instruments. The SVS has a list of 56 (Schwartz,
1992) or 57 (Schwartz, Sagiv, & Boehnke, 2000) value
items (e.g., social power, daring) that participants rate as a
guiding principle in their own life on a 9-point scale, from
−1 (opposed to my principles) to 0 (not important) to 7 (of
supreme importance). The scale is asymmetric to capture
discriminations between values, as all values are desirable
in society (Schwartz & Bardi, 2001). Rather than rating the
importance of each value, respondents to the PVQ (Schwartz
et al., 2001) read two-sentence descriptions of individu-
als (i.e., portraits) in terms of values and rate the extent to
which the described person is similar to them. There are
two versions of the questionnaire—one for males and one
for females—to allow for gender-specific pronouns. Sample
items include “He likes to be in charge and tell others what to
do. He wants people to do what he says” (power); “She looks
for adventures and likes to take risks. She wants to have an
exciting life” (stimulation). The PVQ includes 40 descriptive
“portraits” (value items); respondents indicate how much the
described person is similar to them on a 6-point scale ranging
from 1 (very much like me) to 6 (not like me at all). A total
of 30 studies used the SVS, and 18 used the PVQ (1 of those
used the shortened, 20-item version of the PVQ, but was still
included).
Personality instruments. As stated previously, 11 studies
using the NEO (Costa & McCrae, 1992) and 14 studies using
the BFI (John et al., 1991) were included in this moderator
analysis. The NEO includes either 240 or 60 items depending
on whether or not it is examining facets. A sample item is “I
am a productive person who always gets the job done” (John
& Srivastava, 1999); participants rate their level of agree-
ment/disagreement with the statement. The BFI includes 44
short statements such as “Is original, comes up with new
ideas,” for which participants utilize a 5-point scale to rate
their level of agreement/disagreement in terms of how well
the statement describes them.
Statistical adjustments to control for values scale use. To
control for scale-use tendency, researchers often partial out
the overall mean score of values. Twenty-eight of the stud-
ies included in the meta-analysis clearly used a partialling
method, and 22 clearly reported zero-order correlations (we
were unable to code some studies due to missing information
in the articles; these were eliminated from this analysis). Not
all studies controlled for participants’ scale-use tendency in
the same way: The majority reported correlations after par-
tialling out the personal mean value score, but 1 study sub-
tracted the mean value score from each value domain score
(Collins & Blum, 2011), and 2 studies subtracted the mean
value score from each value domain score and then divided
that difference by the standard deviation of the scores (Doll-
inger, Leong, & Ulicni, 1996). Given that they were intended
to fulfill the same purpose and probably would have resulted
in similar correlations, we treated these methods as suf-
ficiently similar to group them together for the moderator
analyses.
Meta-Analytic Results
Individual Correlation Estimates
Tables 5 through 9 provide the results of the main meta-anal-
ysis (one table for each trait). As expected, traits and values
are related in consistent ways. Openness to experience and
agreeableness, in particular, exhibit several strong relation-
ships with values. The meta-analysis reveals that openness to
experience is strongly correlated with self-direction (ρ =
.52); has moderate positive relationships with stimulation
(ρ = .36) and universalism values (ρ = .33); and has a moder-
ate negative relationship with tradition, conformity, and
security values (ρ = −.31, −.27, and −.24, respectively).
Agreeableness relates most strongly with benevolence val-
ues (ρ = .61). It also has moderate relationships with power
(ρ = −.42), universalism (ρ = .39), conformity (ρ = .26), and
tradition values (ρ = .22).
Extraversion and conscientiousness exhibit fewer signifi-
cant relationships (and no strong relationships) with the
Schwartz value domains. Extraversion demonstrates moder-
ate relationships with stimulation, power, achievement, and
hedonism values (ρ = .36, .31, .31, and .20, respectively).
Conscientiousness is moderately related to security (ρ = .37),
conformity (ρ = .27), and achievement values (ρ = .17).
Finally, emotional stability did not demonstrate any signifi-
cant relationships with the values domains. In total, 18 of the
50 correlations yielded generalizable relationships (those for
which the 80% credibility interval around ρ did not include
zero; see Table 10 for a summary of these relationships).
Eleven of the 50 relationships have 90% confidence intervals
(CI; around mean r) that do not include 0 (see Tables 5-9 for
mean r and 90% CIs).
The strength of the relationships between traits and values
was generally consistent with our theoretical expectations, as
the more cognitively based traits tended to have more and
stronger relationships with values, and the primarily affec-
tive trait (emotional stability) was unrelated to values. The
specific relationships were also largely consistent with
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14 Personality and Social Psychology Review 19(1)
expectations: The 14 predicted relationships all generalized,
and 4 relationships generalized that we did not hypothesize
(agreeableness with universalism; extraversion with power
and hedonism; and conscientiousness with security). If we
define “strong” relationships as those with a rho greater than
.50 (see Cohen, 1988), then 2 of the 50 relationships are
strong: agreeableness with benevolence (ρ = .61), and open-
ness to experience with self-direction (ρ = .52). With only 2
strong relationships out of 50 (after correcting for statistical
artifacts), traits and values are clearly distinct constructs. If
we rely on the more conservative mean r, then none of the
relationships would be classified as strong (the strongest
would be agreeableness with benevolence; mean r = .45). In
nearly every case, the percentage of variance accounted for
by statistical artifacts was small, resulting in generally wide
credibility intervals. This indicates that moderators are likely
present in the data, suggesting the need for a more fine-tuned
analysis of the data.
Sinusoidal Pattern of Correlations
Schwartz (1992, 1996) suggested that correlations between
values and any other variable should be represented graphi-
cally with a sinusoidal curve. In this type of analysis, values
are listed on the horizontal axis in order (i.e., moving around
the circle) and the correlations with the other variable of
interest are then plotted on the vertical axis. Figures 2 to 6
provide plots of the meta-analytic estimates (rho) of the rela-
tionships between traits and values. With the exception of
emotional stability, which does not exhibit any significant
Table 5. Meta-Analytic Results for Openness to Experience and Values.
Ten-factor value domains k N Mean rρSDρCVLL CVUL CILL CIUL % Var
Power 52 54,274 −.04 −.06 .11 −.20 .08 −.27 .15 13
Achievement 54 54,747 .08 .11 .12 −.04 .26 −.12 .34 11
Hedonism 53 54,165 .07 .09 .12 −.06 .24 −.14 .32 11
Stimulation 51 53,692 .27 .36 .13 .20 .52 .11 .61 8
Self-Direction 55 54,959 .37 .52 .11 .38 .66 .31 .74 11
Universalism 53 54,165 .25 .33 .10 .20 .46 .12 .53 12
Benevolence 54 54,747 .10 .13 .11 −.01 .27 −.08 .34 13
Conformity 55 54,959 −.20 −.27 .16 −.48 −.07 −.59 .04 6
Tradition 51 53,692 −.21 −.31 .15 −.50 −.12 −.60 −.02 8
Security 54 54,377 −.17 −.24 .17 −.45 −.02 −.56 .09 6
Note. Bolded mean r values have a 95% confidence interval that does not include 0. Bolded ρ values have an 80% credibility interval that does not include
0. k = number of studies; N = total number of individuals across all studies; Mean r = the average of the uncorrected correlations; ρ = the estimated true
score correlation; SDr = standard deviation of mean r; SDρ = the standard deviation of the corrected correlations; CVLL and CVUL = lower and upper
bounds, respectively, of the 80% credibility interval; 90% CV = the 90% Credibility Value—this is the upper limit of the 80% credibility interval; CILL and
CIUL = lower and upper bounds, respectively, of the 95% confidence interval around the corrected mean correlation; % Var = the percentage of variance
that was accounted for by statistical artifacts (sampling error and unreliability of measures).
Table 6. Meta-Analytic Results for Agreeableness and Values.
Ten-factor value domains k N Mean rρSDρCVLL CVUL CILL CIUL % Var
Power 54 54,599 −.31 −.42 .21 −.70 −.15 −.84 .00 3
Achievement 55 54,946 −.18 −.24 .24 −.54 .07 −.71 .23 3
Hedonism 53 54,165 −.08 −.11 .11 −.24 .03 −.32 .10 13
Stimulation 51 53,692 −.04 −.05 .11 −.19 .09 −.26 .17 13
Self-Direction 55 54,959 −.04 −.07 .19 −.31 .18 −.45 .32 5
Universalism 54 54,364 .29 .39 .12 .23 .54 .15 .62 9
Benevolence 56 55,072 .45 .61 .17 .39 .82 .28 .94 4
Conformity 55 54,959 .18 .26 .11 .12 .39 .05 .47 14
Tradition 51 53,692 .15 .22 .12 .08 .37 .00 .45 13
Security 54 54,377 .00 .00 .17 −.22 .22 −.34 .34 6
Note. Bolded mean r values have a 95% confidence interval that does not include 0. Bolded ρ values have an 80% credibility interval that does not include
0. k = number of studies; N = total number of individuals across all studies; Mean r = the average of the uncorrected correlations; ρ = the estimated true
score correlation; SDr = standard deviation of mean r; SDρ = the standard deviation of the corrected correlations; CVLL and CVUL = lower and upper
bounds, respectively, of the 80% credibility interval; 90% CV = the 90% Credibility Value—this is the upper limit of the 80% credibility interval; CILL and
CIUL = lower and upper bounds, respectively, of the 95% confidence interval around the corrected mean correlation; % Var = the percentage of variance
that was accounted for by statistical artifacts (sampling error and unreliability of measures).
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Parks-Leduc et al. 15
relationships with values, the pattern shows the expected
sinusoid patterns as predicted by the values theory. Especially
for openness to experience and agreeableness, one clear peak
and one clear valley is observed such that the relationships
increase and decrease monotonously as one moves around
the circle. Conscientiousness, as anticipated, has two peaks.
Even the weaker meta-analytic effects provide meaningful
information, as they follow the sinusoidal pattern predicted
by the structure of a circle, so even effects that do not gener-
alize are interesting within the larger picture of how values
relate to other variables.
Moderator Analyses
Given the volume of data involved, we present our findings
in an abbreviated format in Tables 11 to 15. Additional data
regarding moderator analyses are available from the first
author.
Culture. The WLS regression results for individualism/col-
lectivism as a moderator are summarized in Table 11. We
proposed that more individualistic cultures would allow indi-
viduals greater flexibility in choosing values, such that they
would be more likely to choose values consistent with their
traits. Thus, we expected that trait–value relationships would
be stronger in more individualistic cultures. However, only 4
of the 50 regression equations were significantly moderated
by individualism/collectivism. The relationships for which
the moderator effect was significant were agreeableness with
hedonism and emotional stability with achievement, stimula-
tion, and self-direction. None of these were hypothesized to
be related, and none were strong relationships in the main
Table 7. Meta-Analytic Results for Extraversion and Values.
Ten-factor value domains k N Mean rρSDρCVLL CVUL CILL CIUL % Var
Power 54 54,599 .23 .31 .17 .09 .52 −.02 .63 5
Achievement 55 54,946 .23 .31 .16 .10 .52 −.01 .63 6
Hedonism 53 54,165 .16 .20 .09 .09 .32 .02 .39 15
Stimulation 51 53,692 .28 .36 .07 .27 .45 .22 .50 22
Self-Direction 55 54,959 .12 .17 .17 −.05 .38 −.16 .49 6
Universalism 54 54,364 −.05 −.05 .15 −.25 .14 −.35 .24 7
Benevolence 56 55,072 −.04 −.05 .25 −.37 .26 −.54 .43 3
Conformity 55 54,959 −.13 −.17 .20 −.42 .09 −.56 .23 4
Tradition 51 53,692 −.18 −.25 .20 −.51 .01 −.64 .15 4
Security 54 54,377 −.04 −.05 .17 −.27 .17 −.39 .29 6
Note. Bolded mean r values have a 95% confidence interval that does not include 0. Bolded ρ values have an 80% credibility interval that does not include
0. k = number of studies; N = total number of individuals across all studies; Mean r = the average of the uncorrected correlations; ρ = the estimated true
score correlation; SDr = standard deviation of mean r; SDρ = the standard deviation of the corrected correlations; CVLL and CVUL = lower and upper
bounds, respectively, of the 80% credibility interval; 90% CV = the 90% Credibility Value—this is the upper limit of the 80% credibility interval; CILL and
CIUL = lower and upper bounds, respectively, of the 95% confidence interval around the corrected mean correlation; % Var = the percentage of variance
that was accounted for by statistical artifacts (sampling error and unreliability of measures).
Table 8. Meta-Analytic Results for Conscientiousness and Values.
Ten-factor value domains k N Mean rρSDρCVLL CVUL CILL CIUL % Var
Power 54 54,599 .04 .05 .09 −.07 .17 −.13 .23 17
Achievement 55 54,946 .12 .17 .11 .02 .31 −.05 .39 12
Hedonism 54 54,391 −.15 −.19 .15 −.38 .00 −.49 .11 6
Stimulation 51 53,692 −.12 −.16 .18 −.38 .07 −.50 .19 5
Self-direction 55 54,959 .01 .01 .24 −.29 .31 −.45 .47 3
Universalism 54 54,364 −.01 −.02 .18 −.26 .22 −.38 .35 4
Benevolence 56 55,072 .05 .07 .16 −.14 .28 −.25 .39 6
Conformity 55 54,959 .20 .27 .11 .13 .41 .05 .49 12
Tradition 51 53,692 .07 .10 .12 −.05 .25 −.13 .33 13
Security 54 54,377 .27 .37 .19 .14 .61 .01 .74 5
Note. Bolded mean r values have a 95% confidence interval that does not include 0. Bolded ρvalues have an 80% credibility interval that does not include
0. k = number of studies; N = total number of individuals across all studies; Mean r = the average of the uncorrected correlations; ρ = the estimated true
score correlation; SDr = standard deviation of mean r; SDρ = the standard deviation of the corrected correlations; CVLL and CVUL = lower and upper
bounds, respectively, of the 80% credibility interval; 90% CV = the 90% Credibility Value—this is the upper limit of the 80% credibility interval; CILL and
CIUL = lower and upper bounds, respectively, of the 95% confidence interval around the corrected mean correlation; % Var = the percentage of variance
that was accounted for by statistical artifacts (sampling error and unreliability of measures).
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16 Personality and Social Psychology Review 19(1)
meta-analysis (the strongest was agreeableness with hedo-
nism, ρ = −.11). Graphing the line resulting from each of the
regression results shows that in each case, the slope was
positive, and that the line crosses the x-axis (such that the
relationship goes from negative to positive as the culture
goes from more collectivistic to more individualistic). The
results do not support our premise that the relationship
between personality and values is stronger in more individu-
alistic cultures.
We also expected that looser cultures would allow for
stronger relationships between traits and values. For tight-
ness/looseness of culture, the results (Table 12) indicate that
this aspect of culture significantly moderated 7 of the 50
relationships: openness to experience with hedonism; agree-
ableness with universalism and security; extraversion with
tradition; conscientiousness with power and universalism;
and emotional stability with power. Of those 7 significant
effects, none were hypothesized relationships, although one
relationship was moderate in strength and generalized in the
main meta-analysis (agreeableness with universalism; ρ =
.39). For this relationship, the slope was positive and the line
did not cross zero, suggesting that as the culture gets tighter,
the relationship between the trait and the value gets stronger
(counter to our expectations). Of the remaining six signifi-
cant effects, all crossed zero. Three were negative, suggest-
ing that as the culture became tighter, the relationships
between traits and values went from positive to negative. The
other three were positive, indicating that as the culture
became tighter, the relationships went from negative to posi-
tive. Thus, the results of the tightness/looseness moderator
do not suggest a consistent effect of culture on these
relationships.
In sum, none of the hypothesized relationships (from the
main analyses) showed evidence of moderation in our cul-
tural moderator analyses. Those relationships that showed
evidence of cultural moderation did not provide results that
were either systematic or supportive of our hypothesis. The
number of studies (which ranged from 41-47) was quite
Table 9. Meta-Analytic Results for Emotional Stability and Values.
Ten-factor value domains k N Mean rρSDρCVLL CVUL CILL CIUL % Var
Power 52 54,274 .02 .03 .08 −.07 .13 −.13 .18 21
Achievement 54 54,747 −.01 −.01 .10 −.14 .12 −.21 .19 14
Hedonism 53 54,165 .01 .01 .05 −.05 .08 −.09 .12 35
Stimulation 51 53,692 .01 .02 .13 −.14 .18 −.23 .27 9
Self-direction 55 54,959 −.01 −.01 .09 −.13 .11 −.19 .18 18
Universalism 53 54,165 −.03 −.03 .07 −.12 .05 −.16 .10 25
Benevolence 54 54,747 −.01 −.01 .10 −.14 .11 −.20 .18 14
Conformity 55 54,959 −.04 −.05 .05 −.12 .01 −.15 .04 43
Tradition 51 53,692 −.02 −.03 .04 −.09 .02 −.12 .05 53
Security 54 54,377 −.02 −.03 .08 −.13 .07 −.18 .12 24
Note. Bolded mean r values have a 95% confidence interval that does not include 0. Bolded ρ values have an 80% credibility interval that does not include
0. k = number of studies; N = total number of individuals across all studies; Mean r = the average of the uncorrected correlations; ρ = the estimated true
score correlation; SDr = standard deviation of mean r; SDρ = the standard deviation of the corrected correlations; CVLL and CVUL = lower and upper
bounds, respectively, of the 80% credibility interval; 90% CV = the 90% Credibility Value—this is the upper limit of the 80% credibility interval; CILL and
CIUL = lower and upper bounds, respectively, of the 95% confidence interval around the corrected mean correlation; % Var = the percentage of variance
that was accounted for by statistical artifacts (sampling error and unreliability of measures).
Table 10. Summary of the Main Meta-Analysis Results (ρ).
Openness to Experience Agreeableness Extraversion Conscientiousness Emotional stability
Power −.06 −.42 .31 .05 .03
Achievement .11 −.24 .31 .17 −.01
Hedonism .09 −.11 .20 −.19 .01
Stimulation .36 −.05 .36 −.16 .02
Self-direction .52 −.07 .17 .01 −.01
Universalism .33 .39 −.05 −.02 −.03
Benevolence .13 .61 −.05 .07 −.01
Conformity −.27 .26 −.17 .27 −.05
Tradition −.31 .22 −.25 .10 −.03
Security −.24 .00 −.05 .37 −.03
Note. Generalizable results (in bold) refer to results for which the 80% credibility interval does not include 0.
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Parks-Leduc et al. 17
modest to detect moderation using regression. With more
studies, and studies from a wider range of countries, there
may be greater potential for finding meaningful moderation
effects by culture. Nevertheless, the current evidence does
not support the idea that culture meaningfully moderates the
relationships between traits and values.
Values instruments. Results of the analyses using the value
instrument (SVS or PVQ) are provided in Table 13. Credi-
bility intervals were still generally wide, and the percent
variance accounted for relatively small, after taking into
account the values scale that was used. We conducted a
series of z tests to determine whether the 95% CI overlapped
Figure 2. Plot of relationships between openness to experience and values.
Note: Pow = Power, Ach = Achievement, Hedn = Hedonism, Stim = Stimulation, Sdir = Self-direction, Univ = Universalism, Benv = Benevolence, Conf =
Conformity, Trad = Tradition, Scty = Security.
Figure 3. Plot of relationships between agreeableness and values.
Note: Pow = Power, Ach = Achievement, Hedn = Hedonism, Stim = Stimulation, Sdir = Self-direction, Univ = Universalism, Benv = Benevolence, Conf =
Conformity, Trad = Tradition, Scty = Security.
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18 Personality and Social Psychology Review 19(1)
when comparing the two types of studies; results indicate
that 29 of the 50 relationships are significantly different
between studies using the SVS versus studies using the
PVQ. Thus, the values measure appears to act as a
moderator. As additional evidence, more of the relationships
generalize when we separate the studies based on values
measure used (i.e., the credibility intervals are more narrow
and less likely to include 0; so there is more similarity within
Figure 5. Plot of relationships between conscientiousness and values.
Note: Pow = Power, Ach = Achievement, Hedn = Hedonism, Stim = Stimulation, Sdir = Self-direction, Univ = Universalism, Benv = Benevolence, Conf =
Conformity, Trad = Tradition, Scty = Security.
Figure 4. Plot of relationships between extraversion and values.
Note: Pow = Power, Ach = Achievement, Hedn = Hedonism, Stim = Stimulation, Sdir = Self-direction, Univ = Universalism, Benv = Benevolence, Conf =
Conformity, Trad = Tradition, Scty = Security.
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Parks-Leduc et al. 19
each of the two groups of studies than there is across all
studies). While 18 relationships generalized in the overall
analysis, 24 relationships generalized when using just the
SVS, and 24 relationships generalize when using just the
PVQ. This pattern suggests that the PVQ and the SVS are
not measuring entirely the same content, and researchers
should bear this in mind in future research. Although the
intention in developing the PVQ was to develop a measure
with identical content compared with the SVS, slight differ-
ences in the coverage of content may be present. For
example, the value item “wisdom” from the SVS (part of
universalism) is not covered in the PVQ. This is probably
the value item that relates most strongly to valuing intellect,
and therefore, its absence from the PVQ may have weak-
ened the relationships of the PVQ’s universalism with the
trait openness; indeed, the PVQ’s universalism was more
weakly linked with trait openness compared with the SVS’s
universalism. In general, however, as we expected, the PVQ
had stronger relationships with traits than the SVS. Specifi-
cally, of the 15 hypothesized relationships, 10 were stronger
Table 11. Personality and Values; Individualism/Collectivism of Culture as a Moderator.
Openness to experience Agreeableness Extraversion Conscientiousness Emotional stability
kβR2kβR2kβR2kβR2kβR2
Power 44 −.01 .00 45 .14 .02 45 −.09 .01 45 −.07 .00 44 .20 .04
Achievement 46 .16 .03 47 .25 .06†47 −.03 .00 47 .16 .02 46 .38 .14*
Hedonism 45 −.07 .01 45 .30 .09* 45 −.04 .00 46 .14 .02 45 .21 .04
Stimulation 43 −.13 .02 43 −.07 .01 43 −.03 .00 45 .06 .00 43 .34 .12*
Self-direction 47 .14 .02 47 −.14 .02 47 −.05 .00 47 −.06 .00 47 .31 .10*
Universalism 45 .08 .01 46 −.04 .00 46 .08 .01 46 −.08 .01 45 −.03 .00
Benevolence 46 −.01 .00 47 −.02 .00 47 .20 .04 47 .11 .01 46 −.16 .02
Conformity 47 .00 .00 47 −.05 .00 47 .16 .03 47 .00 .00 47 −.09 .01
Tradition 43 .08 .01 43 .19 .03 43 .10 .01 43 .14 .02 43 −.20 .04
Security 46 .05 .00 46 .17 .03 46 .16 .03 46 .02 .00 46 −.01 .00
Note. k = the number of studies. β = the standardized beta weight of the independent variable (individualism/collectivism).
†Significant at p < .10.
*Significant at p < .05.
Figure 6. Plot of relationships between emotional stability and values.
Note: Pow = Power, Ach = Achievement, Hedn = Hedonism, Stim = Stimulation, Sdir = Self-direction, Univ = Universalism, Benv = Benevolence, Conf =
Conformity, Trad = Tradition, Scty = Security.
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20 Personality and Social Psychology Review 19(1)
with the PVQ compared with 5 that were stronger with the
SVS, probably because the PVQ includes some trait-like
elements in its items.
Personality instruments. Results of this moderator analysis are
presented in Table 14. As with the values scales, the modera-
tor analysis with personality scales yielded generally wide
credibility intervals and results that did not account for a
large percentage of variance. We again conducted a series of
z tests to determine whether the 95% CIs overlapped; results
indicate that 30 of the 50 relationships are significantly dif-
ferent. Contrary to our expectations, therefore, the personal-
ity measure significantly moderated the observed
relationships between personality and values. In addition,
more of the relationships generalized when using just the
BFI, although this was not true for the NEO (although this
could be a result of combining two different versions of the
NEO). Relationship with values also tended to be stronger
for the BFI as compared with the NEO, although we would
not have predicted this a priori, and it is not clear why this
should be the case. Given that the NEO and the BFI were
developed using different methods, perhaps it is not surpris-
ing that the results would differ.
Statistical adjustments to control for values scale use. Abbrevi-
ated results of this moderator analysis are provided in Table
15. The z test showed that 37 of the 50 relationships were
significantly different when using different methods, so sta-
tistical adjustments act as a moderator. As further evidence,
28 of the 50 relationships generalized when limiting our
Table 12. Personality and Values; Tightness/Looseness of Culture as a Moderator.
Openness to experience Agreeableness Extraversion Conscientiousness Emotional stability
kβR2kβR2kβR2kβR2kβR2
Power 42 .14 .02 43 −.27 .07†43 .06 .00 43 −.32 .10* 42 .39 .15*
Achievement 44 −.01 .00 45 −.27 .07†45 .22 .05 45 −.20 .04 44 −.01 .00
Hedonism 43 .33 .11* 43 −.29 .08†43 .10 .01 44 −.24 .06 43 .11 .01
Stimulation 41 .30 .09†41 −.05 .00 41 .19 .04 41 .17 .03 41 .08 .01
Self-direction 45 .03 .00 45 .25 .06 45 .27 .07†45 .22 .05 45 −.16 .03
Universalism 43 −.01 .00 44 .40 .16* 44 −.11 .01 44 .44 .19* 43 −.06 .00
Benevolence 44 .26 .07†45 .21 .05 45 −.08 .01 45 .02 .00 44 −.17 .03
Conformity 45 −.01 .00 45 −.16 .03 45 −.19 .03 45 −.14 .02 45 −.08 .01
Tradition 41 −.19 .04 41 −.31 .09†41 −.33 .11* 41 −.14 .02 41 −.21 .04
Security 44 −.11 .01 44 −.36 .13* 44 −.17 .03 44 −.12 .02 44 .19 .04
Note. k = the number of studies. β = the standardized beta weight of the independent variable (tightness/looseness of culture).
†Significant at p < .10.
*Significant at p < .05.
Table 13. Meta-Analytic Rho (and SD-rho) for Personality and Values; Values Measure as Moderator.
Openness to experience Agreeableness Extraversion Conscientiousness Emotional stability
SVS PVQ SVS PVQ SVS PVQ SVS PVQ SVS PVQ
ρSDρρSDρzρSDρρSDρzρSDρρSDρzρSDρρSDρzρSDρρSDρz
Power −.11 .13 −.03 .06 2.82 −.26 .15 −.53 .17 5.56 .14 .10 .43 .07 11.8 .06 .09 .05 .09 .37 .05 .06 .01 .08 1.82
Achievement .13 .15 .11 .06 .63 −.07 .16 −.36 .21 5.02 .20 .12 .39 .15 4.55 .22 .09 .12 .11 3.24 −.05 .04 .02 .12 2.39
Hedonism .08 .05 .09 .14 .29 −.10 .13 −.12 .08 .64 .14 .06 .25 .08 4.97 −.14 .10 −.22 .17 1.81 .03 .05 .01 .06 1.17
Stimulation .33 .10 .38 .13 1.38 −.03 .12 −.06 .10 .91 .30 .06 .40 .05 6.06 −.08 .05 −.21 .21 2.58 −.10 .05 .10 .10 7.86
Self-direction .51 .12 .54 .09 .98 −.02 .19 −.10 .19 1.40 .12 .14 .19 .18 1.41 .04 .14 −.01 .29 .68 −.08 .05 .05 .07 6.87
Universalism .37 .09 .30 .10 2.39 .29 .11 .45 .07 6.03 .06 .12 −.13 .12 5.24 .01 .14 −.03 .21 .71 .01 .04 −.05 .07 3.30
Benevolence .10 .11 .16 .10 1.91 .46 .16 .71 .06 7.70 .12 .12 −.20 .24 5.28 .14 .09 .01 .18 2.86 −.03 .05 0 .12 1.01
Conformity −.20 .14 −.32 .15 2.73 .28 .09 .26 .10 .69 .01 .10 −.29 .16 7.14 .30 .09 .25 .12 1.52 −.05 .03 −.06 .05 .77
Tradition −.22 .11 −.38 .13 4.30 .27 .11 .20 .11 2.09 −.07 .10 −.40 .12 9.65 .12 .10 .08 .13 1.11 −.03 .04 −.04 .05 .71
Security −.17 .17 −.28 .15 2.30 .14 .14 −.09 .12 5.94 .08 .13 −.13 .15 4.88 .28 .09 .44 .20 3.19 .01 .04 −.06 .07 3.86
Avg % Variance 18% 9% 14% 8% 20% 8% 22% 5% 55% 17%
Note. Generalizable results (bolded ρ) refer to results for which the 80% credibility interval does not include 0. The number of studies for the SVS ranged from 27 to 30
(N ranged from 19,276 to 20,183); for the PVQ there were 18 studies (N = 32,707). The z test is used to test for whether the 95% confidence intervals overlap (Hunter &
Schmidt, 1990); z > 1.96 indicates that the scores are significantly different at p ≤ .05; z > 2.56 indicates that the scores are significantly different at p ≤ .01. SVS = Schwartz
Value Survey (Schwartz, 1992); PVQ = Portrait Values Questionnaire (Schwartz et al., 2001). SDρ = the standard deviation of the corrected correlations; Avg % Variance = the
average percent variance accounted for.
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Parks-Leduc et al. 21
analyses to studies using the partialling method, and 22 rela-
tionships generalized with studies using zero-order correla-
tions. In comparing the methods, some relationships were
stronger when partialling, some were stronger when using
zero-order correlations, and some were about the same across
the two methods. However, “stronger” does not necessarily
mean better or more accurate. As the partialling method has
strong theoretical support, partialling out the mean value
score should provide a clearer picture of the relationships
because correlations that are controlled for scale use are
more accurate.
Other moderators. We also examined study population, sam-
ple size, and publication status as potential moderators.
However, the three moderators were confounded with one
another, as several of the larger studies were based on unpub-
lished data from Internet studies involving the general popu-
lation. None of these moderator analyses yielded clear
results; in all three sets of analyses, some differences emerged
between the subgroups, but across the 50 correlations, no
subgroup was clearly superior to another. Given that the
results are not particularly meaningful, in the interest of
space, we have not included details from these analyses
Table 14. Meta-Analytic Rho (and SD-rho) for Personality and Values; Personality Measure as Moderator.
Openness to experience Agreeableness Extraversion Conscientiousness Emotional stability
BFI NEO BFI NEO BFI NEO BFI NEO BFI NEO
ρSDρρSDρzρSDρρSDρzρSDρρSDρzρSDρρSDρzρSDρρSDρz
Power −.08 .05 −.14 .20 .83 −.50 .23 −.46 .05 .63 .33 .13 .09 .02 6.77 .09 .04 .04 .11 1.24 −.02 .06 .02 .02 2.28
Achievement .10 .08 −.05 .14 3.05 −.38 .25 −.14 .15 2.93 .27 .05 .10 .08 5.94 .18 .08 .16 .09 .56 −.09 .03 −.06 .02 2.94
Hedonism .01 .07 .04 .07 1.04 −.14 .05 −.19 .10 1.46 .19 .04 .10 .08 3.28 −.29 .09 −.18 .06 3.65 −.02 .04 .05 .03 4.90
Stimulation .31 .08 .22 .09 2.35 −.08 .07 −.15 .08 2.06 .36 .04 .27 .04 5.08 −.25 .16 −.15 .03 2.27 .07 .15 −.11 .02 4.42
Self-direction .52 .08 .39 .11 3.29 −.17 .13 −.13 .07 .98 .11 .08 −.04 .09 4.34 −.11 .19 −.08 .06 .56 .02 .11 −.03 .05 1.51
Universalism .33 .05 .39 .08 2.10 .39 .04 .21 .10 5.39 −.05 .15 −.07 .04 .48 −.11 .15 −.12 .11 .19 .01 .00 .03 .04 1.58
Benevolence .13 .03 .05 .11 2.24 .68 .10 .32 .14 6.96 −.15 .30 .01 .08 1.90 −.02 .15 .08 .07 2.18 .07 .07 −.04 .06 4.13
Conformity −.29 .10 −.32 .11 .70 .31 .04 .22 .12 2.39 −.21 .20 −.09 .06 2.13 .30 .04 .25 .05 2.71 −.04 .02 −.04 .00 .00
Tradition −.29 .08 −.28 .08 .28 .30 .05 .21 .11 2.19 −.28 .21 −.12 .10 2.41 .14 .05 .04 .07 3.56 −.02 .02 −.02 .00 .00
Security −.25 .10 −.33 .06 2.48 −.01 .18 −.03 .00 .42 −.06 .18 −.02 .06 .78 .50 .14 .17 .09 7.14 −.08 .04 .03 .03 7.86
Avg % Variance 20% 23% 15% 30% 13% 41% 15% 34% 46% 77%
Note. Generalizable results (bolded ρ) refer to results for which the 80% credibility interval does not include 0. Fourteen studies used the BFI (N =
25,776); for the NEO, the number of studies ranged from 8 to 11 (N ranged from 6,289 to 6,974). The z test is used to test for whether the 95%
confidence intervals overlap (Hunter & Schmidt, 1990); z > 1.96 indicates that the scores are significantly different at p ≤ .05; z > 2.56 indicates that the
scores are significantly different at p ≤ .01. BFI = Big Five Inventory (John, Donahue, & Kentle, 1991); NEO = Neuroticism, Extraversion, and Openness to
Experience, NEO-PI-R or NEO-FFI (Costa & McCrae, 1992). SDρ = the standard deviation of the corrected correlations; Avg % Variance = the average
percent variance accounted for.
Table 15. Meta-Analytic Rho (and SD-rho) for Personality and Values; Method as Moderator.
Openness to Experience Agreeableness Extraversion Conscientiousness Emotional stability
Partialled Corr.s Partialled Corr.s Partialled Corr.s Partialled Corr.s Partialled Corr.s
ρSDρρSDρzρSDρρSDρzρSDρρSDρzρSDρρSDρzρSDρρSDρz
Power −.10 .12 −.05 .08 1.68 −.57 .18 −.25 .13 7.13 .30 .19 .26 .09 0.95 .07 .09 .03 .09 1.53 −.03 .08 .07 .03 5.78
Achievement .03 .11 .17 .07 5.36 −.37 .24 −.12 .14 4.57 .21 .13 .34 .10 3.96 .14 .07 .19 .16 1.34 −.07 .08 .01 .07 3.69
Hedonism −.01 .07 .14 .04 9.22 −.16 .08 −.07 .12 2.95 .17 .07 .20 .09 1.25 −.27 .11 −.15 .15 3.11 0 .04 .02 .05 1.49
Stimulation .28 .08 .39 .09 4.31 −.12 .08 .01 .06 6.21 .34 .06 .35 .05 0.61 −.27 .13 −.09 .14 4.45 .08 .14 −.08 .06 5.09
Self-direction .46 .10 .55 .09 3.31 −.21 .13 .05 .08 8.59 .05 .12 .25 .10 6.36 −.16 .14 .14 .15 7.17 .05 .08 −.08 .07 6.06
Universalism .33 .07 .33 .15 0 .35 .12 .37 .10 0.63 −.12 .08 .07 .14 5.55 −.16 .12 .11 .10 8.50 0 .04 −.03 .05 2.23
Benevolence .10 .09 .14 .11 1.35 .59 .21 .59 .09 0 −.21 .21 .16 .15 7.26 −.04 .13 .20 .08 8.02 .05 .08 −.07 .06 5.94
Conformity −.33 .11 −.18 .16 3.74 .27 .09 .27 .12 0 −.26 .14 .01 .18 5.76 .27 .07 .33 .09 2.56 −.04 .05 −.07 .05 2.09
Tradition −.32 .09 −.24 .14 2.24 .25 .09 .25 .13 0 −.32 .18 −.10 .16 4.34 .11 .08 .16 .08 2.09 −.02 .03 −.06 .05 3.20
Security −.30 .11 −.16 .15 3.36 −.09 .10 .15 .13 7.07 −.14 .11 .09 .17 5.45 .45 .20 .33 .14 2.43 −.06 .09 0 .06 2.75
Avg % Variance 17% 20% 12% 17% 12% 15% 14% 16% 30% 44%
Note. Generalizable results (bolded ρ) refer to results for which the 80% credibility interval does not include 0. Partialled refers to studies that partialled out the mean value
score; corr.s = studies that just provided the straight correlation. SDρ = the standard deviation of the corrected correlations; Avg % Variance = the average percent variance
accounted for. There were 24 to 28 studies that clearly partialled out the mean value score (N ranged from 26,761 to 28,015) and 21 to 22 studies that clearly reported a
straight correlation (N ranged from 15,698 to 15,910). The z test is used to test for whether the 95% confidence intervals overlap (Hunter & Schmidt, 1990); z > 1.96 indicates
that the scores are significantly different at p ≤ .05; z > 2.56 indicates that the scores are significantly different at p ≤ .01.
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22 Personality and Social Psychology Review 19(1)
(additional details regarding these moderator analyses are
available on request from the first author).
Discussion
The current article presents the first meta-analysis of the
relationships between personality traits and personal values,
focusing on the most studied models of traits and values—
FFM and the Schwartz (1992) value theory. The results show
meaningful relationships, most of which were predicted a
priori and generally follow the sinusoidal pattern predicted
by the values circle. As we expected, the strength of these
relationships was a product of two factors: the nature of the
traits (more cognitively based traits have stronger relation-
ships with values) and content overlap between the traits and
values. The pattern of results also suggests that although val-
ues and traits are related, the two constructs are distinct.
Moderator analyses suggest that the choice of instrument
(for both traits and values) sometimes affects the results.
Hypothesized links tend to be stronger when using the PVQ
to measure values as compared with the SVS, and when
using the BFI to measure personality as compared with the
NEO. Furthermore, relationships are more consistent with
theory when response tendencies for values are statistically
controlled. Additional moderator analyses do not support the
idea that culture (individualism vs. collectivism and tight-
ness vs. looseness cultural dimensions) affects these relation-
ships. We next elaborate on the specific meta-analytic results
and discuss their theoretical and practical implications. We
then discuss some limitations and point to important future
directions for research.
Trait–Value Associations
In discussing the findings of associations between traits and
values, we refer both to the strengths of the links found and
to the patterns of associations. With regard to the latter, as
values are structured in a circle, relations with other vari-
ables should generally follow a sinusoidal pattern of gradual
change in correlations as one moves around the circle.
Openness to experience. We expected this trait to have the
strongest correlations with values based on the nature of
openness as the most cognitively based trait and on the over-
lap in content between openness and values. And indeed, of
the five traits, openness to experience had some of the stron-
gest correlations with values, showing the clearest pattern of
correlations and with an almost perfect sinusoidal pattern of
correlations. Individuals scoring high on openness to experi-
ence tend to value novelty (self-direction and stimulation
values) and particularly novel ideas (self-direction) and bro-
admindedness (universalism values). In contrast, individuals
who score low on openness to experience tend to value main-
taining the world as it is and the safety it provides (tradition,
conformity, and security values).
Agreeableness. Agreeableness is also strongly related to val-
ues. Individuals who score high on agreeableness tend to
value being prosocial, particularly toward people in their
close environment (benevolence values) but also toward
people in society in general (universalism values).They also
tend to value restraining their impulses to fit in (conformity
and tradition), possibly to facilitate getting along with others.
In contrast, individuals who score low on agreeableness tend
to value having resources and being dominant (power val-
ues). Similar to openness, agreeableness had a perfect sinu-
soidal pattern of correlations with values.
Extraversion. As we expected, extraversion correlated less
strongly with values than did openness and agreeableness,
but these correlations are nevertheless theoretically mean-
ingful and generally follow a sinusoidal pattern. Individuals
who score high on extraversion tend to value excitement and
variety (stimulation values), as well as value enhancing their
own interests through dominance, success, and having fun
(power, achievement, and hedonism values).
Conscientiousness. Conscientiousness is the only trait that
was not expected to have a sinusoidal pattern of correlations
with values; instead, it was expected to have two peaks of
correlations with values that are not adjacent to one another
in the value circle (i.e., conformity and achievement). Its cor-
relations with values generally followed the expected pat-
tern, but it was most strongly associated with security values.
Hence, this meta-analysis established that conscientious
people tend to value order, adherence to rules, and the avoid-
ance of risks. They also tend, to a lesser degree, to value fit-
ting in(conformity) and having socially recognized
accomplishments (achievement). In general, however, con-
scientiousness is less strongly associated with values com-
pared with openness and agreeableness.
Emotional stability. As expected, emotional stability did not
correlate with values. This is consistent with our premise that
an affectively based trait should not be strongly related to
values, which are a cognitively based construct. Our meta-
analysis also confirms the idea expressed in a review on val-
ues and well-being (Sagiv et al., 2004) that values are not
directly related to well-being.
Moderators
Culture. Our analyses were the first to examine cross-cultural
differences in the relationships between traits and values.
The moderator analyses showed little evidence for a cultural
effect on the strength of trait–value relationships, although a
larger sample size is needed before drawing firm conclu-
sions. Still, the occasional and unsystematic cultural effects
found may suggest that although people in various cultures
vary on their levels of traits (e.g., Costa, Terracciano, &
McCrae, 2001) and values (e.g., Schwartz, 2011b),
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Parks-Leduc et al. 23
the relationships between traits and values remain largely
consistent across cultures, at least in the current range of cul-
tures (see John, Naumann, & Soto, 2008, for traits; Schwartz,
2011b, for values) and for the cultural variables that we con-
sidered. Additional dimensions of culture do exist and could
also be considered, although we tested those that we believed
were most likely to moderate these relationships. As more
samples accumulate, the statistical power for answering this
important question will increase.
Survey instrument. Using the PVQ to measure values often
results in stronger hypothesized trait–value correlations. The
PVQ scale may inflate correlations between the two con-
structs because its items often include trait-like components.
Should researchers continue to use it? If an important part of
a study is to measure values alone without any traces of
traits, strivings, or preferences (all exist in parts of some
items), and if distinguishing between values and these other
characteristics of the person is important, then researchers
might want to use the SVS rather than the PVQ. In all other
instances, the PVQ should be adequate for use, and it has
some clear advantages over the SVS (detailed in Schwartz,
2005). A newly constructed measure of values (Schwartz et
al., 2012) builds on the PVQ and fewer of its items have trait-
like components compared with the PVQ, but it is still not
completely trait-free. Researchers may also wish to bear in
mind that the content of the two instruments may sometimes
be slightly different.
Similarly, the choice of personality instrument is likely to
have an impact on the strength of the observed relationships
between traits and values. As with the values measure,
researchers should choose personality measures based on a
particular study’s purpose and design. We also encourage
researchers to evaluate personality instruments at the item
level to determine whether the scale is accurately measuring
traits or whether it also includes some value-laden items. We
did not expect, a priori, for the BFI to exhibit stronger rela-
tionships with values as compared with the NEO—We can-
not therefore say at this point which personality instrument
yields more accurate results, just that the relationships
differ.
Statistical adjustments to control for values scale use. Control-
ling for how respondents use the rating scales in statistical
analyses of correlations should result in more accurate cor-
relations between traits and values. Such treatment of the
data is in line with the understanding that values exist in a
system of values; therefore, the important element in linking
to another variable is not so much the absolute importance
given to the value but rather its importance compared with
all other values—its prioritization over other values in one’s
value system. This consideration leads to the important rec-
ommendation for researchers to control for scale-use ten-
dency in values when correlating values with other
variables.
Theoretical Implications
The research literatures on personality traits and personal
values share a common heritage: research on both sets of
constructs originated with a reliance on the lexical hypoth-
esis for identifying relevant content. The lexical hypothe-
sis proposes that meaningful differences in the
characteristics of individuals are encoded in language,
such that a review of the dictionary for terms describing
individuals will yield a comprehensive list of important
characteristics (Goldberg, 1993; McCrae & Costa, 1997;
Schwartz, 1994). When Allport (1937) undertook his study
of personality traits based on the lexical hypothesis, he
stated that personality traits should be non-evaluative and
was explicit in his efforts to remove evaluative terms that
related to an individual’s “character,” or values. Until quite
recently, that separation of values and traits has led the two
sets of constructs to be studied mostly independently of the
other.
Traits and values are independently examined as impor-
tant predictors of a multitude of outcome variables in numer-
ous contexts in various areas such as educational psychology
(e.g., Knafo & Schwartz, 2004; Poropat, 2009), organiza-
tional psychology (e.g., Berson, Oreg, & Dvir, 2007; Lim &
Ployhart, 2004), health psychology (e.g., Bergin, 1991;
Terracciano & Costa, 2004), political psychology (e.g.,
Saucier, 2000; Schwartz, Caprara, & Vecchione, 2010), envi-
ronmental psychology (e.g., Grunert & Juhl, 1995;
Ramanaiah, Clump, & Sharpe, 2000), sports psychology
(e.g., Courneya & Hellsten, 1998; M. Lee, Whitehead,
Ntoumanis, & Hatzigeorgiadis, 2008), occupational psychol-
ogy (e.g., Gottfredson, Jones, & Holland, 1993; Sagiv, 2002),
social psychology (e.g., Cohrs, Moschner, Maes, &
Kielmann, 2005; Sibley & Duckitt, 2008), and others. Only
recently have researchers started to explore the combined
effects of traits and values on various outcomes (see, for
example, Parks & Guay, 2012; Roccas et al., 2002). The
present article offers the first meta-analysis of the relation-
ships between personality traits and personal values, thereby
clarifying these relationships. The results demonstrate that
traits and values are related in predictable ways based both
on the extent to which the trait is cognitively based and on
the extent to which the contents of traits and values are con-
ceptually similar.
As noted previously, researchers tend to adhere to one of
three basic views of traits and values: (a) They are different
ways of measuring the same thing; (b) they are unique and
separate constructs at the same level of abstraction; and (c)
they are both part of a hierarchy of personality, but they exist
at different levels in that hierarchy. This meta-analysis
clearly demonstrates that the first viewpoint is inaccurate. If
traits and values were different ways of measuring the same
thing, then the correlations between them should have been
much stronger, demonstrating convergent validity. Yet only
18 of the 50 relationships generalized, and of those, only 2
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24 Personality and Social Psychology Review 19(1)
were strong relationships. The pattern of results therefore
clearly demonstrates that although values are meaningfully
linked to traits, the two constructs are distinct.
A review of the traits–values literature provides additional
evidence in support of this premise; many studies have
examined the differential impact of traits and values on vari-
ous outcomes and constructs, providing evidence of diver-
gent validity. For example, Roccas and colleagues (2002)
found that values and traits have different patterns of correla-
tions with religiosity (associated primarily with values but
not traits) and with positive affect (associated primarily with
traits but not values). Other researchers have replicated these
findings with subjective well-being and life satisfaction
(associated primarily with traits; Haslam, Whelan, & Bastian,
2009; Saiz, Alvaro, & Martinez, 2011) and with religiosity
and spirituality (associated primarily with values; Saiz et al.,
2011; Saroglou & Munoz-Garcia, 2008). Parks and Guay
(2012) found that traits and values have differential relation-
ships with the motivational processes of goal content and
striving. Finally, several studies have shown that values are
better predictors of voting preference and choice than are
traits (Caprara, Schwartz, Capanna, Vecchione, &
Barbaranelli, 2006; Caprara, Vecchione, & Schwartz, 2009;
Dirilen-Gumus, Cross, & Donmez, 2012). Clearly, these are
not just different ways of measuring the same thing, and
including both traits and values in the same study has the
potential to improve predictions of a wide array of
outcomes.
As the different views on the nature of the relationships
between traits and values can cause confusion in the litera-
ture, researchers who study traits and values should state
their underlying assumptions and provide a consistent theo-
retical conceptualization connecting their work with other
trait–value studies that conceptualize the link in a similar
way. As an example, the HEXACO personality inventory
(K. Lee & Ashton, 2004) is a six-factor model that includes
Honesty–Humility (not included in our study because it is
not a Big Five inventory). The Honesty–Humility factor
seems to largely tap values; the developers of the scale state
that the common adjectives used to define the factor are
“Sincere, honest, faithful/loyal, modest/unassuming, fair-
minded” (Ashton & Lee, 2007, p. 154). These descriptors
overlap considerably with values items; “honest” and
“loyal” are both benevolence items on the SVS, whereas the
tradition scale includes the item “humble” (Schwartz, 1992,
p. 7), which seems quite similar to modest and unassuming.
Fair-minded would seem to fit with universalism values,
which are concerned with equality and fairness in society
(Schwartz, 1992). If one is of the opinion that traits and val-
ues are both aspects of personality, then the HEXACO scale
may be a legitimate method for measuring personality.
However, if a researcher views personality as an aggregate
of traits (and not values), then this scale may not be appro-
priate for measuring personality. We therefore encourage
researchers to make explicit their assumptions and
definitions.
Limitations
It is important to outline the unavoidable limitations of this
meta-analysis, which stemmed largely from lack of suitable
studies. First, the reliability corrections, as stated previously,
were based only on coefficient alpha, which does not take
into account transient error. As a result, they are likely to be
overestimates of the true reliability. Second, information was
not available to determine whether range restriction occurred
in the data, although we do not think that range restriction is
a large issue in the studies examined here. Third, many of
these studies were conducted in different languages, using
translated scales. Given the number of studies available and
the fact that not all studies indicated the language, we made
no attempt to control for differences caused by the language
of the instrument. Fourth, not enough studies were available
in each category to enable conducting hierarchical moderator
analyses, making it difficult to pinpoint which construct is
causing the moderation, because moderators may be corre-
lated (as noted above). Fifth, focusing exclusively on studies
that used the FFM for traits and the Schwartz (1992) value
circle for personal values led us to eliminate some studies
that might be worth including when a sufficient number of
such studies is available. Sixth, we examined only factor-
level scores for traits, as most studies did not include facet-
level scores. Finally, as noted, the moderator analyses
regarding culture are likely to provide clearer results with
more studies, especially studies of people from collectivist
cultures. When more studies accumulate, a meta-analysis
can be conducted that overcomes these limitations.
Future Directions
This meta-analysis points to the importance of three broad
future directions that would enhance the integrative under-
standing of the person: (a) incorporating more elements of
the person in one study to enhance the understanding of the
structure of enduring psychological characteristics of the
person, (b) examining causal directions of different charac-
teristics of the person to enhance the understanding of life-
span development of the person, and (c) integrating research
from other domains, such as neuroscience, to further inform
and develop our understanding of the constructs of traits and
values and how they are related.
Incorporating more elements of the person in the same
study. This meta-analysis established links between two
enduring characteristics of the person: traits and values.
However, more elements should be included in the same
study, and the simultaneous relationships among multiple
elements should be established empirically. In addition to
traits and values, these could include goals, needs, beliefs,
attitudes, and temperaments, among others. Some work has
been conducted in this direction, mainly examining two
types of constructs at a time (e.g., Calogero, Bardi, & Sutton,
2009; Goodwin, Polek, & Bardi, 2012; Roberts & Robins,
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Parks-Leduc et al. 25
2000), but much more work is needed as well as the inclu-
sion of more constructs.
Longitudinal directions of relations between enduring characteris-
tics of the person. Although this meta-analysis provides an
understanding of how traits and values relate to one another, it
represents a “snapshot” of those relationships at one point in
time, which may not reflect how the two influence one another
across time. Theorists have suggested mechanisms for recip-
rocal effects of traits and values (Caprara et al., 2006; Roccas
et al., 2002), and several researchers have begun to theorize
and examine the possible interrelations between the two (e.g.,
Bilsky & Schwartz, 1994; Olver & Mooradian, 2003; Roccas
et al., 2002; Schermer et al., 2011). Traits are often considered
more innate; hence, one could argue that if one of these were
to influence the other, it would be traits. Alternatively, one
could argue that values influence traits—for example, when
someone becomes a parent, the value domains of benevolence
and security could become more important to them. This
should change their behavior, and that behavioral change
might, over time, lead to modest changes in traits. We do not,
at this point, fully understand the reciprocal nature of these
relationships over time, yet this is an important step for gain-
ing an integrative view of the person and understanding how
this integration comes about. We therefore encourage research-
ers to study this question in longitudinal research.
Integrating other research domains. The question of how traits
and values are related may be more easily answered if we
search broadly in the research literature for other ways to
understand these constructs. Both traits and values are psy-
chological constructs—they represent complex processes
taking place within the brain. A better understanding of those
neural processes may inform our understanding of how traits
and values relate to one another, how much they influence
one another, and how much they are influenced by genetics
(nature) versus environment (nurture). For example, the
frontal lobe develops later in life than the mid-brain, not
reaching full maturity until early adulthood (Sowell, Thomp-
son, Holmes, Jernigan, & Toga, 1999). This fact suggests
that psychological processes involving the frontal lobe might
be more influenced by external influences into early adult-
hood, whereas those that are processed primarily in the mid-
brain may be less prone to such influence. If this is true, then
stating that traits represent nature and values represent nur-
ture is overly simplistic, because traits themselves appear to
vary in the extent to which they involve the frontal lobe ver-
sus the mid-brain. Understanding at a more fundamental
level how traits and values are related to one another should
help move the field forward in developing a more integrated
conceptualization of characteristics of the individual.
Conclusion
The past decade has seen initial attempts to clarify the simi-
larities and differences between traits and values and a
preliminary exploration of the links between them. This
meta-analysis establishes, for the first time, the relationships
between personality traits (of the most widely used trait
model—the FFM) and personal values (of the most widely
used value model—the Schwartz value theory). It also estab-
lishes for the first time a conceptual underpinning for under-
standing these relationships, as more cognitively based traits
demonstrate stronger relationships with values, and more
emotionally based traits exhibit weaker (or no) relationships
with values. We now know that openness to experience and
agreeableness are the most strongly and coherently related to
values; extraversion and conscientiousness also have some
meaningful relations to values; and emotional stability is
generally unrelated to values. We also have established that
traits and values are distinct constructs and that their rela-
tionships show little variation cross-culturally. Our modera-
tor analyses also resulted in a recommendation for researchers
to control for scale-use tendency in values, and to consider
carefully which survey instrument to use as some measures
(i.e., the PVQ and the BFI) tend to yield stronger trait–value
relationships than do others. The findings from this meta-
analysis will enable researchers to use traits and values more
effectively in their studies. Moreover, this new knowledge
has prepared the ground for developing models that advance
our integrative understanding of the person.
Acknowledgment
We wish to thank Frank Schmidt and In-Sue Oh for their feedback
on various meta-analytic issues we faced in developing this article.
Also, we are extremely grateful to the many researchers who shared
their unpublished data sets with us for this study.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect
to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, author-
ship, and/or publication of this article.
Supplemental Material
The online supplemental material is available at http://pspr.
sagepub.com/supplemental.
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