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Personality and Individual Differences 49 (2010) 306–316
Contents lists available at ScienceDirect
Personality and Individual Differences
j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c
a t e / p a i d
The nature of the relationship between personality traits and
political attitudes
Brad Verhulst a, Peter K. Hatemi b,c,*, Nicholas G. Martin b
a Department of Political ScienceStony Brook University, Stony
Brook, NY 11794-4392, USA
b Queensland Institute of Medical Research, Genetic
Epidemiology 300 Herston Road, Q 4029, Australia
c Department of Political Science University of Iowa, 344
Schaeffer Hall, Iowa City, Iowa 52242-1498, USA
a r t i c l e i n f o
Article history:
Received 29 October 2009
Received in revised form 3 November 2009

Accepted 4 November 2009
Available online 9 December 2009
Keywords:
Personality
Ideology
Attitudes
Politics
Genes
0191-8869/$ - see front matter � 2009 Elsevier Ltd. A
doi:10.1016/j.paid.2009.11.013
* Corresponding author. Address: University of Io
City, Iowa 52242-1498, USA. Tel.: +1 319 335 2347.
E-mail address: [email protected] (P.K. H
a b s t r a c t
Building upon a series of works by Thomas J. Bouchard, Lindon
J. Eaves, Hans J. Eysenck and other con-
temporaries, we present strong evidence that the assumed causal
relationship between personality
and left–right ideology is too simplistic. We suggest the
relationship is not predictive and instead is better
understood by dividing the overarching left–right ideological
spectrum into more meaningful attitude
dimensions. In doing so, we find that Psychoticism is strongly
related to conservative positions on Pun-
ishment, Religious, and Sex attitudes, whereas Social
Desirability is related to liberal positions on the
same attitudes. Furthermore, the nature of the covariance
between Psychoticism and social attitudes is
due to a common genetic influence, while covariance between
Social Desirability and these attitudes
in females is largely a function of common shared
environmental covariance.

� 2009 Elsevier Ltd. All rights reserved.
1. Introduction
Psychologists, geneticists, and political scientists have long at-
tempted to identify and explain the associations between
person-
ality and political preferences (Adorno, Frenkel-Brunswik,
Levinson, & Sanford, 1950; Eysenck, 1954; McCloskey, 1958).
Most
of these early attempts to link personality traits with political
atti-
tudes portrayed conservatism as a pathology and focused on
con-
necting conservatives with negative personality traits (e.g.
Adorno et al., 1950; Altemeyer, 1981; Altemeyer, 1996). Such a
view is exemplified by McCloskey (1958), who labeled
conserva-
tives as:
‘‘. . .social isolates, . . . people who think poorly of themselves,
who suffer personal disgruntlement and frustration, who are
submissive, timid, and wanting in confidence, who lack a clear
sense of direction and purpose, who are uncertain about their
values, and who are generally bewildered by the alarming task
of having to thread their way through a society which seems to
them too complex to fathom” (37).
Focusing on the causal connection between negative personality
traits and conservatism and positive traits with liberalism
contin-
ues to dominate research in this area, though the language has
be-
come more subtle (see Block & Block, 2006; Jost, Glaser,
Kruglanski,
& Sulloway, 2003; Jost et al., 2008). For example, researchers

have
ll rights reserved.
wa, 344 Schaeffer Hall, Iowa
atemi).
worked very hard to demonstrate that the positively valued
Open-
ness to Experience dimension has a strong and consistent
negative
relationship with political conservatism (see Gosling, Rentfrow,
&
Swann, 2003; Jost, Federico, & Napier, 2009; McCrae, 1996;
Mondak
& Halperin, 2008; Van Hiel, Kossowska, & Mervielde, 2000;
Van
Hiel, Pandelaere, & Duriez, 2004). Recent work however, has
also
demonstrated that Neuroticism is positively associated with
economic liberalism (Leeson & Heaven, 1999; Riemann,
Grubich,
Hempel, Mergl, & Richter, 1993), though these findings are
often
dismissed or downplayed in favor or a more positive view of
liber-
alism and negative view of conservatism.
The connection between personality and politics historically
rested on the assumption that causality runs from personality
traits to political attitudes. This seems plausible as personality
is
widely understood as some combination of innate dispositions
and personal experiences that, in general, guides behavior in a
sta-
ble predictive manner (Bouchard, 1994; Cattell, 1957; Eysenck,
1990; Eysenck, 1991; Tellegen et al., 1988; Winter &

Barenbaum,
1999). This is not to say behavior is predetermined by
personality;
rather, environmental circumstances provide the impetus for
behaviors, and personality predispositions increase or decrease
the probability of behavior only if the action is appropriate for a
specific situation (Bandura, 2001; Caprara & Cervone, 2000;
Mis-
chel & Shoda, 1998). Political attitudes, on the other hand, have
typically been viewed as much more capricious (Converse,
1964).
Although a plethora of research on attitudes suggest that they
can be quite stable over time, rather than being perceived as
per-
sonal dispositions, political attitudes are typically portrayed as
http://dx.doi.org/10.1016/j.paid.2009.11.013
mailto:[email protected]
http://www.sciencedirect.com/science/journal/01918869
http://www.elsevier.com/locate/paid
B. Verhulst et al. / Personality and Individual Differences 49
(2010) 306–316 307
preferences related to the immediate social environment and are
thus perceived as entirely context dependent.
Such a view of attitudes, combined with the widely held
assumption that, unlike personality, parental-offspring correla-
tions of attitudes were entirely functions of cultural
transmission
(e.g., Niemi & Jennings, 1991; for an exception see Martin et
al.,
1986), reinforced the belief that personality traits were causally
prior to social and political attitudes. However, such an
assumption

was unfounded, as the heritability of social and political
attitudes
has been established and replicated across populations
(Bouchard
& McGue, 2003; Eaves, Eysenck, & Martin, 1989; Martin et al.,
1986; Waller, Kojetin, & Bouchard, 1990).
Indeed, the genetic covariation between social attitudes and
personality was explored over 30 years ago. Eaves and Eysenck
(1974) identified a genetic relationship between personality and
conservatism. Typical of a Nature Letter, however, while
profound
and novel, they offered only brief discussion on why this
relation-
ship existed. And, unfortunately, these findings went largely
unad-
dressed for several decades, with the exception of a handful of
scholars. Among these, Bouchard, Lykken, McGue, Segal, and
Telle-
gen (1990) continued to pursue this question (e.g., Bouchard,
1997;
Bouchard, 2009; Bouchard & McGue, 2003; Waller et al.,
1990).
This work has led to a paradigm shift in the connection between
personality and politics.
Combining Religiousness, Authoritarian dispositions, and tradi-
tional Conservatism into a core attitude/world view system,
Bou-
chard (2009, p. 36) drew on other contemporaries (e.g., Saucier,
2000), and synthesized a theory that more accurately integrated
attitude dimensions and personality traits. Such a synthesis im-
plies that whatever relationship exists between personality and
political attitudes cannot be strictly causal; rather, it seems
likely
that the relationships among political attitudes and personality

traits are in part expressions of the same underlying genetic
liabil-
ity. Verhulst, Hatemi, and Eaves (2009) provided strong support
of
such a position and offered the first replication of Eaves and
Ey-
senck’s (1974) findings presented some 35 years earlier. Using
a
large US twin sample (over 6000 pairs), they found that the vast
majority of the covariance between Psychoticism and
Militaristic/
Defense attitudes was due to a common underlying genetic
influence.
Building upon a series of works by Bouchard, Eaves, Eysenck
and others, we examine the assumptions made in the existing
lit-
erature regarding the causal connection between personality
traits
and political attitudes. Specifically, we estimated the genetic
and
environmental sources of covariation between personality traits
and political attitudes and extended the findings of Verhulst
et al. (2009) by focusing on specific attitudinal dimensions of
polit-
ical attitudes and personality traits in a very large sample of
Aus-
tralian Twins.
2. Methods and results
Data were collected from 1988 to 1990 by mailed surveys to
two large cohorts of adult Australian twins enrolled in the
volun-
teer Australian Twin Registry. Each participant completed a
Health
and Lifestyle Questionnaire (HLQ), which contained items on

socio-
political attitudes, personality traits, and wide variety of health-
re-
lated and sociodemographic measures (Eaves et al., 1989; Eaves
et al., 1999; Martin, 1987; Truett et al., 1994). Using only
respon-
dents who completed the political and personality measures, the
sample consists of 20,559 individuals from 5402 families; this
in-
cludes 7234 individual twins, comprising 3254 complete same
sex pairs and 363 unlike sex pairs. The mean age of the entire
sam-
ple was 38.6 (SD = 15.5), while the mean age of the twin
respon-
dents was 34.1 (SD = 14.0). Regarding sex, 57.7% were female
in
the greater population, while in the twin sample 63.8% were fe-
male. For more details on the sample, including ascertainment
and response rates, see Hatemi, Medland, Morley, Heath, and
Mar-
tin (2007).
2.1. Measures
Personality traits were measured by the short form of the Re-
vised version of the Eysenck Personality Questionnaire (EPQ-R-
S,
Eysenck & Eysenck, 1997; Eysenck, Eysenck, & Barrett, 1985)
with
sub-scales for Extraversion, Psychoticism, Neuroticism and
Social
Desirability.
Extraversion is comprised of two central components: affiliation
or sociability, which includes valuing interpersonal bonds and
being warm and affectionate, highly sociable and expressive,

and
agency or impulsiveness, which includes goal-oriented
behavior,
ambition, dogmatism, social dominance, leadership, aggression
and assertiveness (Depue & Collins, 1999). Psychoticism is
posi-
tively related to authoritarianism, risk taking, impulsivity,
tough-
mindedness, practicality, magical ideation, and religiosity and
neg-
atively related to openness to experience. A careful inspection
of
the items that comprise the Psychoticism scale used in this
paper
(as presented in Appendix 1) suggest that the factor is
character-
ized by low levels of introspection and a preoccupation with
rules
and regulations. Neuroticism is associated with feelings of
inferior-
ity, unhappiness, anxiety, dependence, hypochondria, guilt,
emo-
tional instability, and obsessiveness (Eysenck & Eysenck,
1985).
The additional sub-factor of Social Desirability (often dubbed
the
‘‘lie” scale), was also included in the analyses and is
characterized
by social acquiescence or conformity and lack of self-insight
(Fran-
cis, Brown, & Pearson, 1991).
To maximize the empirical validity of the personality dimen-
sions, items were dropped from the personality scales if they
were
explicitly related to one of the attitude dimensions or if they did

not contribute to the intended trait. The nature of the
dimensions
remained unchanged, however. The empirical validity problem
is
most evident with the Psychoticism scale. Although the
Psychoti-
cism sub-scale is established in the extant literature, in many
re-
cent cases it has less than ideal levels of inter-item reliability.
This is most likely because the Psychoticism scale was
developed
in the 1950s, and then revised in the mid 1980s. Thus, the tech-
niques available to assess reliability when the scales were
created
were impoverished. Retaining items that do not meaningfully
con-
tribute to the latent factor introduces error into the model.
There-
fore, dropping these specific items increased the precision with
which we can estimate the trait and the confidence we have in
our analyses.
Another common problem that plagues the study of personality
and politics is the clear distinction between attitudinal items
and
personality items. The tautology problem is more common in
other
personality measures, like the NEO-PI-R Openness to
Experience
scale where several items explicitly tap political concepts (see
Costa & McCrae, 1992). Remaining cognizant of this problem,
we
identified three items in the Psychoticism scale that had also the
possibility of overlapping with attitudinal items. Specifically,
the
items ‘‘Would being in debt worry you?” and ‘‘Do you think

people
spend too much time safeguarding their future with savings and
insurances?” potentially overlap with economic political
attitudes,
while ‘‘Do you think marriage is old-fashioned and should be
done
away with?” potentially overlaps with both social and religious
political attitudes. Importantly, the factor loadings of these
items
are not overwhelming and measures of fit do not decline with
the removal of these items. Removing potentially tautological
items is not meant to fundamentally alter the concept, but rather
ensure that the items that comprise the construct are not inher-
ently political. In other words, this should ensure that the
observed
308 B. Verhulst et al. / Personality and Individual Differences
49 (2010) 306–316
relationship is between the traits and not a function of similar
items.
Political and social attitudes were assessed utilizing a 50-item
index of political and social issues contemporary at the time of
the survey (see Posner, Baker, Heath, & Martin, 1996). In a
Wilson
and Patterson (1968) format, respondents indicated if they
agreed,
disagreed, or were uncertain about their attitudes towards a
wide
range of issues across several ideological dimensions (e.g.,
Death
Penalty, Bible Truth, Legalized Prostitution, Immigration,
Stiffer Jail
Terms, etc.). Of these 50 items, 26 of the most explicitly

political
items were used to construct four political attitude dimensions:
Religious, Sex, Out-groups and Punishment dimensions (see
details
below). To facilitate comparisons between this study and
similar
others, we also created a Liberal–Conservative ideology
measure
using all 50 items as the scale was intended and commonly
found
in the extant literature (see Wilson & Patterson, 1968). A
complete
list of the items can be found in Appendix 2.
Unlike personality, there is no consensual model or theory of
socio-political attitudes. Although there is wide agreement on a
general, abstract left–right spectrum, the attitudes that comprise
this spectrum remain elusive and insofar as specific attitude
facets
go, they remain underdeveloped (see Bouchard, 2009; Eagly &
Chaiken, 1993). As such, to identify the attitude factors, we
relied
heavily on the face validity of the scales and the empirical
results.
2.2. Preliminary analysis
A confirmatory factor analysis (CFA) with missing data was
con-
ducted specifying the four personality factors and the four
political
ideology attitude factors identified above (see Appendices 1 and
2
for the specifics of the CFA). For the personality traits, higher
scores
indicated higher levels of the traits, and for the ideological

dimen-
sions higher scores indicated the liberal position. The model fit
sta-
tistics for this class of Confirmatory Factor Models are
impoverished, especially for relatively complex factor models
such
as those estimated in this paper. To compensate for this, we
esti-
mated a comparable non-nested model with list-wise deletion,
where the factor loadings and the factor correlations were
essen-
tially unchanged. In this model the RMSEA was 0.044, the CFI
was 0.870, and the TLI was 0.917. These fit indices suggest that
the model fits the data very well. As such, we are confident in
the factor structure we estimate.
2.3. Phenotypic correlations between personality traits and
ideological
dimensions
We limited our analyses to the relationships between person-
ality traits and ideological dimensions to those relationships
that had correlations greater than 0.20. This decision was based
on the increased reliably of disentangling covariance between
the phenotypic traits (Cohen, 1988). The first stage of our anal-
ysis focused on identifying the phenotypic relationships be-
tween the personality traits and the social attitudes (see
Table 1). The correlations between our attitude dimensions
and personality traits were much larger than those reported
for correlations between overall Conservatism–Liberalism
(ideol-
ogy) and personality traits in other studies (see Carney, Jost,
Gosling, & Potter, 2008; Verhulst et al., 2009). Further, the
gen-
eral ideology scale also was highly correlated with several per-
sonality dimensions.

As can be seen in Table 1, several relationships stand out. Most
notably, Psychoticism was strongly related to more conservative
Religious, Sex and Punishment attitudes in both sexes. This spe-
cific pattern of relationships was consistent with the original re-
search on the Authoritarian personality (Adorno et al., 1950)
and the magnitude is consistent with the relationship between
authoritarianism and general conservatism (Altemeyer, 1998;
Stenner, 2005). We expected that Psychoticism, by virtue of its
theoretical relationship with Authoritarianism, would be associ-
ated with Religious, Sex, and Punishment attitudes, as these
atti-
tudes are central to the concept of Authoritarianism (see
Bouchard, 2009).
These same political attitudes were also correlated with Social
Desirability in both sexes, although in the opposite (liberal)
direc-
tion and to a lesser extent. Although the personality and politics
literature has generally ignored the connection between Social
Desirability and ideological or attitudinal dimensions, this is
the
second study to link Social Desirability with liberal social
attitudes
in very large genetically informative samples (see Verhulst et
al.,
2009). Thus, it appears that an empirical relationship exists,
even
though the theoretical justifications for this relationship are not
yet resolved.
As a point of comparison with other personality and politics
studies, we also examined the relationship between the additive
50-item general ideology scale and the four personality traits.
The general ideology dimension was also highly related to
Psychot-

icism and Social Desirability. The most interesting feature of
the
pattern of correlations between the general ideology dimension
and the personality traits mirrored the Religious and Sex
attitudes.
Items along these dimensions comprised the majority of the
items
in the scale, and thus appeared to drive the relationships
observed
between the general ideology factor and the separate personality
traits. Importantly, by narrowly focusing in the general ideology
factor the relationships between extraversion and neuroticism
and the political attitudes, which we discuss below, would be
obscured.
The relationship between Neuroticism and liberal Out-group
attitudes also corresponds with recent findings in the emerging
lit-
erature within the personality and politics sub-field.
Specifically,
Neuroticism has been linked with liberal economic ideological
atti-
tudes in several samples and is consistent with Verhulst et al.
(2009) analysis of US twins. Importantly, attitudes on
immigration
were part of the US economic ideology dimension in that study,
but
here in our Australian population they were part of the Out-
group
dimension.
Finally, we found a relationship between Extraversion and con-
servative Sex attitudes in these analyses. Very few
contemporary
studies in the personality and politics literature have found
signif-

icant relationships between Extraversion and attitudinal or ideo-
logical predispositions. However, our finding is consistent with
an older literature showing Extraversion to be positively related
to Authoritarianism and Conservatism (Eysenck & Wilson,
1978;
Pearson & Greatorex, 1981; Ray, 1980; for a recent replication
see Carney et al., 2008). Subsequent analyses often failed to
repli-
cate these earlier findings. We believe part of the failure to
repli-
cate these relationships is due to the left–right generalization of
attitude factors. However, greater Extraversion has been long
established as a significant influence on sex drive, earlier age of
first intercourse, promiscuity, orgasm, and other activities
(Cooper,
Agocha, & Sheldon, 2000; Eysenck, 1976; Miller et al., 2004;
Schenk
& Pfrang, 2005). Thus, regarding the relationship between
Extra-
version and the Sex attitudes factor, the direction of the
correlation
is in the opposite direction than expected. At first glance it
appears
for Australians, the relationship between Extraversion and atti-
tudes on sex are quite different from the relationship between
Extraversion and actual sexual behavior. Future studies are
needed
to replicate this finding.
2.4. Genetic analyses
Structural equation models incorporating genetic, shared and
unique environmental sources of covariation allowed us to ex-

Table 1
Phenotypic correlations between personality and attitude
dimensions for male (N = 3449) and female (N = 6066) twins.
Psychoticism Extraversion Neuroticism Social Desirability
Female twins
Religious attitudes �.534 �.124 �.003 .273
Sex attitudes �.601 �.266 �.049 .359
Out-group attitudes �.106 �.080 .204 .211
Punishment attitudes �.451 �.047 .094 .282
General ideology �.566 �.177 .001 .357
Male twins
Religious attitudes �.496 �.035 .008 .237
Sex attitudes �.570 �.196 �.033 .318
Out-group attitudes �.004 �.010 .166 .100
Punishment attitudes �.421 .047 .021 .231
General ideology �.495 �.061 �.008 .261
Note: Higher scores on the Personality factors denoted higher
levels of the traits. Higher scores on the attitude factors denote
more liberal responses for all attitude
dimensions. All relationships except that between Psychoticism
and Out-group attitudes were statistically significant at .01 or
better. However, conventional levels of
statistical significance do not focus our attention on
substantively meaningful relationships. Here we focus only on
significant relationships where the effect size is medium or
larger (correlations greater P.20 in bold; see Cohen, 1988).
Table 2
Between co-twin correlations by zygosity.
MZM MZF DZM DZF DZOS

Personality traits
Psychoticism .536 .615 .381 .414 .370
Extraversion .516 .488 .193 .212 .211
Neuroticism .367 .438 .142 .213 .085
Social Desirability .383 .520 .318 .394 .267
Social attitudes
Religious .592 .632 .506 .513 .536
Sex .592 .668 .452 .558 .505
Out-groups .600 .559 .482 .402 .361
Punishment .567 .587 .407 .339 .433
General ideology .631 .675 .517 .552 .524
N (twin pairs) 646 1385 384 839 363
(2010) 306–316 309
plore the nature of the relationships among personality and
attitudes dimensions. Table 2 provides the twin correlations
separated by zygosity and sex for the personality traits and so-
cio-political attitude dimensions. The correlations between MZ
twins were substantially larger than the correlations between
same-sex DZ twins, providing initial support for the presence of
genetic influences and reason to explore structural models to
quantify those influences. However, the MZ–DZ correlation
differ-
ences were much greater for most personality dimensions than
for the political attitude sub-factors, suggesting significant
shared
environmental influences on the attitude dimensions. For com-
pleteness we also tabulate the correlations for the DZ opposite-
sex pairs. For most variables the correlations for opposite-sex
DZ twins were similar to the correlations for same-sex DZ
twins,
but for Social Desirability and attitudes to Out-groups the
DZOS

correlation was a bit lower, suggesting that familial effects on
these scales were somewhat different in males and females for
these constructs. For simplicity we therefore present results of
separate analyses of male and female twins, omitting the oppo-
site-sex pairs.
Results of estimating the genetic and shared and non-shared
environmental variance components for each measure alone,
using
maximum likelihood estimation in Mx (Neale, Boker, Xie, &
Maes,
2003), are presented in Table 3. Components of variance due to
Additive Genetic (A), Common environmental (C), and Unique
Environmental (E) influence are tabulated (for detailed explana-
tions of the methodology and theory, along with limitations and
recent criticisms see Medland & Hatemi, 2009; Neale & Cardon,
1992).
The results were largely consistent with the expectations based
on the twin correlations and the long-standing personality
litera-
ture. Specifically, Psychoticism, Extraversion, and Neuroticism
were characterized by large additive genetic and unique
environ-
mental components, while the common environmental
component
was not significant. For Social Desirability, the common
environ-
ment variance was statistically significant but the additive
genetic
component for males was not. In contrast, in both sexes, the
addi-
tive genetic, shared and unique environmental variance compo-
nents for almost all the attitude scales were significant. The
shared environment variance accounted for large portions of the
variance in social attitudes. Importantly, the variance
components

of the general ideology scale are very similar to those of both
the
Sex and the Religious factors. The only attitude that differed
from
this trend was Punishment attitudes, where the common
environ-
ment variance was not significant for females.
2.5. Cholesky decomposition
The preceding steps were necessary to examine the complex
relationships between personality traits and political attitude
dimensions. Several of the personality dimensions were
correlated
with different attitude dimensions at the phenotypic level. Our
main interest, however, lay in exploring the nature of the
pheno-
typic relationships. As such, we undertook a series of bivariate
Cholesky decompositions (see Fig. 1) to evaluate the sources of
covariation. The constraints and model specifications are
explained
in detail in Medland and Hatemi (2009). Since we wished to
know
how much of the variance in attitudes could be explained by
per-
sonality, we put the personality factors first in our analyses.
Tables 4 and 5 display the standardized path coefficients from
the Cholesky analyses for females and males, respectively.
Cells
with dashes indicate that the paths were constrained to zero.
This
was done where the univariate variance decomposition models
de-
scribed in the previous section did not account for a statistically
reliable portion of the variance in the trait. These constraints
pre-

vented model instability arising from very small sources of
shared
variance.
As is shown in Table 4 for males and Table 5 for females, the
relationships between Psychoticism and Religious, Sex, and
Pun-
ishment attitudes were largely due to additive genetic
covariation.
Performing a simple algebraic transformation of the path coeffi-
cients, we found that the majorities of the covariation between
Psychoticism and Punishment, Sex, and Religious attitudes was
due to genetic covariance.
Table 3
Estimated variance components for personality and ideology
dimensions, separately by variable.
Males Females
a2 c2 e2 a2 c2 e2
Psychoticism .559 (.51, .60) – .441 (.39, .49) .602 (.57, .63) –
.399 (.37, .43)
Extraversion .503 (.45, .55) – .497 (.45, .55) .474 (.44, .51) –
.526 (.49, .56)
Neuroticism .362 (.30, .42) – .638 (.58, .70) .438 (.40, .48) –
.562 (.52, .60)
Social Desirability .141 (.00, .36) .230 (.03, .29) .629 (.57, .70)
.368 (.23, .51) .141 (.01, .27) .490 (.46, .53)
Religious attitudes .151 (.00, .32) .435 (.28, .57) .415 (.37, .46)
.226 (.12, .34) .393 (.29, .49) .381 (.35, .41)
Sex attitudes .271 (.11, .45) .316(.15, .46) .413 (.37, .46) .212
(.11, .32) .443 (.34, .53) .346 (.32, .37)

Out-group attitudes .268 (.11, .44) .336 (.18, .47) .395 (.35, .44)
.311 (.19, .44) .244 (.13, .35) .445 (.41, .48)
Punishment attitudes .285 (.11, .47) .277 (.10, .43) .438 (.39,
.61) .491 (.36, .61) .089 (.00, .21) .420 (.39, .45)
General ideology .212 (.06, .37) .408 (.29, .54) .380 (.35, .42)
.244 (.15, .31) .420 (.34, .51) .335 (.31, .36)
Note: Estimates in italics are not significant.
a c e
A11 to the
Personality
Trait
C11 to the
Personality
Trait
E11 to the
Personality
Trait
Personality Trait
and Social
Attitudes A12 to the
Social
Attitude
A22 to the
Social

Attitude
C12 to the
Social
Attitude
C22 to the
Social
Attitude
E12 to the
Social
Attitude
E22 to the
Social
Attitude
Personality
Trait
Social
Attitude
A1 A2 C2C1 E1 E2
Fig. 1. General Cholesky model.
Table 4
Bivariate cholesky results for personality traits and social
attitudes for males.

a c e
Psychoticism and Religious Attitudes .758 – .653
(.72, .79) (.62, .69)
�.476 .615 – – �.201 .596
(�.52, �.43) (.58, .65) (�.24, �.16) (.57, .563)
Psychoticism and Sex Attitudes .757 – .654
(.72, .79) (.62, .69)
�.539 .562 – – �.249 .577
(�.58, �.49) (.52, .60) (�.29, �.21) (.55, .61)
Psychoticism and Punishment Attitudes .760 – .650
(.73, .79) (.61, .69)
�.332 .680 – – �.260 .600
(�.39, �.28) (.65, .71) (�.31, �.22) (.57, .63)
Psychoticism & Ideology .756 – .655
(.72, .78) (.62, .69)
�.486 .632 – – �.192 .572
(�.53, �.44) (.59, .67) (�.24, �.15) (.54, .60)
Extraversion and Sex Attitudes .715 – .700
(.67, .75) (.66, .74)
�.182 .757 – – �.108 .619
(�.24, �.12) (.73, .78) (�.15, �.06) (.59, .65)
Neuroticism and Out�Group Attitudes .610 – .792
(.55, .66) (.75, .83)
.183 .764 – – .061 .615
(.11, .26) (.73, .79) (.02, .11) (.58, .65)
Social Desirability and Religious Attitudes .386 .495 .778
(.08, .60) (.23, .62) (.74, .82)
.362 .138 .106 .651 .055 .642
(.03, .56) (.00, .49) (�.16, .36) (.52, .72) (.01, .10) (.61, .68)

49 (2010) 306–316
Table 5
Bivariate cholesky results for personality traits and social
attitudes for females.
a c e
Psychoticism & Religious Attitudes .783 – .622
(.76, .80) (.60, .65)
�.508 .615 – – �.209 .567
(�.54, �.48) (.59, .64) (�.24, �.18) (.55, .59)
Psychoticism & Sex Attitudes .783 – .623
(.76, .80) (.60, .65)
�.564 .594 – – �.246 .518
(�.59, �.53) (.57, .62) (�.27, �.22) (.50, .54)
Psychoticism & Punishment .787 – .617
(.77, .80) (.59, .64)
�.390 .658 – – �.231 .601
(�.43, �.35) (.63, .68) (�.26, �.20) (.58, .62)
Psychoticism & Ideology .783 – .623
(.76, .80) (.60, .65)
�.580 .586 – – �.170 .540
(�.61, �.55) (.56, .61) (�.20, �.14) (.52, .56)
Extraversion and Sex Attitudes .691 – .723
(.66, .72) (.70, .75)
�.265 .776 – – �.109 .562
(�.31, �.22) (.76, .79) (�.14, .08) (.54, .58)

Neuroticism and Out�Group Attitudes .664 – .748
(.63, .69) (.72, .77)
.204 .726 – – .094 .650
(.16, .25) (.70, .75) (.06, .13) (.63, .67)
Social Desirability and Religious Attitudes .498 .520 .694
(.35, .61) (.40, .61) (.67, .72)
.117 .428 .339 .555 .051 .614
(�.05, .28) (.28, .54) (.20, .50) (.41, .65) (.02, .08) (.59, .64)
Social Desirability and Sex Attitudes .502 .518 .693
(.36, .62) (.39, .61) (.67, .72)
.123 .405 .435 .539 .095 .577
(�.03, .28) (.27, .51) (.30, .60) (.35, .63) (.07, .13) (.55, .60)
Social Desirability and Punishment Attitudes .504 .517 .692
(.37, .61) (.40, .61) (.67, .72)
.057 .671 .355 .000 .096 .642
(�.11, .21) (.59, .72) (.22, .47) (�.31, .31) (.06, .13) (.62, .66)
Social Desirability and Out�Group Attitudes .517 .505 .691
(.38, .63) (.37, .60) (.67, .72)
.011 .563 .290 .393 .080 .662
(�.17, .18) (.44, .67) (.13, .47) (.00, .53) (.05, .11) (.64, .69)
Social Desirability and Ideology .515 .506 .692
(.38, .63) (.38, .60) (.67, .72)
.096 .450 .504 .450 .070 .572
(�.06, .25) (.33, .55) (.36, .69) (.00, .58) (.04, .10) (.55, .60)
Note: Estimates in italics were not significant. Again,
parameters with a lower confidence bound of zero should be
interpreted as not statistically significant.
Table 4 (continued)

a c e
Social Desirability and Sex Attitudes .384 .497 .778
(.10, .60) (.24, .62) (.74, .82)
.445 .274 .137 .548 .104 .631
(.11, .67) (.00, .49) (�.16, .38) (.39, .65) (.06, .15) (.60, .67)
Social Desirability and Punishment Attitudes .399 .484 .779
(.00, .61) (.21, .63) (.74, .82)
.035 .543 .299 .416 .086 .659
(�.64, .65) (.00, .70) (.04, .60) (.00, .60) (.04, .14) (.62, .70)
Social Desirability and Ideology .397 .486 .779
(.00, .61) (.21, .63) (.74, .82)
.179 .427 .323 .549 .066 �.612
(�.53, .58) (.00, .59) (.09, .68) (.00, .68) (.02, .11) (�.65,
�.58)
Note: Estimates in italics were not significant. To solve
estimation problems in a limited number of models we bounded
the parameters to have a lower confidence bound of
zero. Thus, parameters with a lower confidence bound of zero
should be interpreted as not statistically significant.
(2010) 306–316 311
Importantly, although the paths from Psychoticism to the
attitude dimensions (A12) were quite strong for each attitude
dimension, these paths were still smaller than the paths
accounting for the unique influence (A22) on the attitude
dimen-
sions. Thus, although there was a strong relationship between
Psychoticism and each attitude dimension, the majority of the
additive genetic variance in the attitude dimensions was not ac-
counted for by the genetic influences on Psychoticism. The

vari-
ance shared between the unique environmental component of
Psychoticism and the attitude dimensions were minimal (paths
E12), while the residual unique environmental variance in the
attitude dimensions were uniformly high (paths E22), which is
not surprising since they include measurement error. This pat-
tern of results did not vary substantially by sex. Again, the pat-
49 (2010) 306–316
tern of relationships for the general ideology scale mimicked
the
relationships for the Religious and Sex attitudes with Psychoti-
cism. Specifically, the phenotypic relationship between general
ideology and Psychoticism appeared to be driven by the additive
genetic influence.
Similar relationships existed between Extraversion and Sex
attitudes as well as between Neuroticism and Out-group atti-
tudes. In both cases, the connections between the personality
traits and the attitude dimensions were primarily accounted for
by the additive genetic covariance between the constructs rather
than by any environmental covariance. Again, this pattern of re-
sults was remarkably consistent across sexes. In both cases, the
phenotypic relationships were much smaller than the relation-
ships observed between Psychoticism and the attitude dimen-
sions. As such, there were correspondingly smaller paths A12 in
these models.
The relationship between Social Desirability and each attitude
dimension (Sex, Punishment, and Out-groups) deviated slightly
from the pattern of relationships identified for the other
personal-
ity traits. Specifically, for females both the additive genetic and

common environment variance components were significant for
Social Desirability. Thus, this necessitated estimating Cholesky
models with common environmental pathways. To ensure that
the male model was broadly comparable with the female model,
we estimated the same parameters even though the additive ge-
netic variance in Social Desirability was not statistically
significant
when it was measured alone in males.
The Cholesky results for Social Desirability were generally con-
sistent across sexes. Specifically, the relationships between
Social
Desirability and the attitude dimensions rested primarily in the
common environmental covariances. For females, the common
environmental covariations (paths C12) between Social
Desirabil-
ity and the attitude dimensions were substantively large and sta-
tistically significant for all political attitudes. Furthermore, the
additive genetic covariances (paths A12) were substantively
small
and statistically not significant for all political attitudes. The
pat-
tern for males was only slightly different. For the Religious and
Punishment attitude dimensions, the common environmental
covariances (paths C12) were statistically significant and
substan-
tively large. For Sex attitudes, however, the common
environmen-
tal covariance was much smaller and not statistically
significant.
Furthermore, for Religious and Sex attitudes, the additive
genetic
covariances with Social Desirability were statistically
significant.
Remember, however, that the additive genetic component was
not statistically significant for Social Desirability in the

univariate
models for males. Furthermore, we had many more female than
male twins, giving us greater power to detect significant results
in the female sample.
While single population based results should be accepted with
caution, the current results are broadly consistent with analyses
on data from an equally large US twin sample (see Verhulst
et al., 2009). Specifically, the current study replicated the
findings
from a completely separate population of twins in a different
country, and therefore increases generalizability of the effects.
Fi-
nally, as with the other personality traits, the result for the gen-
eral ideology factor mirrored the Religious attitude factor.
Specifically, for both males and females, the primary source of
covariance between Social Desirability and any of the attitude
factors was common environmental covariance rather than addi-
tive genetic covariance.
3. Discussion
The results in this paper offer a more fine grained explanation
for the relationship between personality traits and social atti-
tudes than that captured by looking only at the Conservatism–
Liberalism super factor (ideology). Specifically, ideology was
strongly and negatively correlated with Psychoticism and posi-
tively correlated with Social Desirability. These same relation-
ships were also seen with the Religious, Sex, and Punishment
attitude sub-factors but not with the attitudes toward Out-
groups, where the correlation with Psychoticism was negligible.
In addition we also saw a modest (��0.2) negative correlation
between Extraversion and liberal attitudes to sex and a positive
correlation (�0.2) between Neuroticism and liberal attitudes to
Out-groups. All these correlations were remarkably consistent
between sexes.

Consistent with the existing literature, we showed that individ-
ual differences in both personality traits and political attitudes
could
be decomposed into genetic and environmental variance compo-
nents. For personality traits environmental influences were
over-
whelmingly unique to the individual, except for Social
Desirability
where there was an important component of shared
environmental
influence. For attitudes, on the other hand, we saw substantial
genet-
ic influences, but large components of shared environmental
vari-
ance as well. However, the common environmental covariance
is
likely to be confounded in some part by assortative mating (see
Eaves et al., 1999; Eaves & Hatemi, 2008). Indeed, the spousal
corre-
lations for Social Desirability was 0.25 and ranged from 0.45 to
0.65
for the attitudinal dimensions (p < .001, N = 3535). Finally,
using a
multivariate genetic model, we demonstrated that the
phenotypic
relationships between personality and attitudes were primarily
functions of a single source of covariance, genetic in the case of
the
correlations of Psychoticism, Neuroticism, and Extraversion
with
attitude dimensions in both males and females, and shared
environ-
ment for correlations between Social Desirability and attitudes.
In line with our expectations, Psychoticism was strongly related
to more conservative positions on Religious, Sex, and

Punishment
attitude dimensions. This finding is consistent with previous
theo-
rizing that suggests these attitude dimensions should be central
to
Authoritarian concerns, and that Authoritarianism, Traditional
Conservatism, and Psychoticism are intertwined (Adorno et al.,
1950; Bouchard, 2009).
The correlations between Psychoticism and the attitudinal
dimensions we demonstrate in this paper are larger than those
presented in other similar papers using other omnibus person-
ality theories; however, the reported relationships are consis-
tent with the theoretical relationship between Psychoticism
and various measures of Authoritarianism, like Adorno et al.’s
(1950) F scale, Altemeyer’s (1981, 1996) RWA scale, and Feld-
man’s (2003) Social Conformity–Autonomy Scale. Notably,
both
the F and the RWA scales have been strongly criticized for
including explicit political content in the measurement of
Authoritarianism, while the development of the Social Confor-
mity–Autonomy scale goes to great lengths to remove any
explicitly political content from the measurement of authoritar-
ianism, and thus avoid confounding the personality trait with
attitudinal preferences. Therefore, the magnitude of the rela-
tionships between the attitudinal variables and Psychoticism
are not unexpected.
A similar, but substantially weaker relationship existed be-
tween Extraversion and more conservative attitudes on the Sex
attitude dimension. This finding is opposite to what might be
ex-
pected based on Extraversion’s relationship to mode liberal
sexual
behavior (see Cooper et al., 2000). However, such a finding is
in line

with older studies of conservatism and personality (see Eysenck
&
Wilson, 1978; Pearson & Greatorex, 1981; Ray, 1980). We see
two
possible explanations for this relationship. First, there was a
rea-
sonably large correlation between Psychoticism and
Extraversion
(r = 0.37). As such, the relationship between Extraversion and
Sex
attitudes that we observed may have been a function of the very
(2010) 306–316 313
strong relationship between Psychoticism and Sex attitudes.
Alter-
natively, as noted above, Extraversion has two sub-factors:
affilia-
tion/sociability and agency/impulsiveness. Thus, the phenotypic
relationship may have been driven by the agency/impulsiveness
sub-factor. We leave it to future research to disentangle these
possibilities.
On the other hand, the more Neurotic our twins were, the more
‘‘liberal” their attitudes toward Out-groups (e.g. immigration,
mul-
ticulturalism). This echoed the relationship found between
Neurot-
icism and more liberal attitudes on economic issues in a large
US
sample, as the Australia Out-group dimension and the US Eco-
nomic dimension shared one important item in particular – atti-
tudes to immigration (see Verhulst et al., 2009).

One of the most interesting, but least explored, personality
traits in the context of political attitudes is Social Desirability.
The higher respondents scored on this dimension, the more
likely
they were to support liberal positions on Religious, Sex, and
Pun-
ishment attitudes. Overall the relationships between attitudes
and Social Desirability were the opposite of the relationships
be-
tween Psychoticism and attitudes, though substantially weaker.
In this study, as in Verhulst et al. (2009), Social Desirability
corre-
lated with more liberal social attitudes.
In sum, the relationships between Psychoticism, Extraversion,
and Neuroticism and all attitude dimensions (Sex, Punishment,
and Religious) were largely driven by common genetic influ-
ences. For Social Desirability the pattern that emerged was
the vast majority of covariation between Social Desirability
and each attitude dimension was due to the similarity in shared
environment, though this effect was less consistent in males.
Regardless of the source of covariance between personality
and attitude dimensions, the overwhelming portion of individ-
ual differences remained unique to each trait, with one excep-
tion – Psychoticism and Sex attitudes shared some 40% of
their covariance.
Of central importance to our findings, the relationships between
personality traits and political ideologies were not simple or
uni-
form: different attitude dimensions correlated with different
per-
sonality traits to varying degrees. Importantly, if we had
focused
only on the relationship between the general ideology factor and
the personality traits we would have missed several key

relation-
ships, including the relationship between Neuroticism and more
liberal attitudes, which seemed to be restricted to economic or
group competition attitude dimensions. Furthermore, the
intrigu-
ing relationship between Extraversion and Sex attitudes would
also have gone unnoticed. Recent research on personality and
pol-
itics has missed these findings because it focused only on the
gen-
eral ideological factor.
Do you prefer to go your own way rather than act by the rules?
Do you stop to think things over before doing anything?
Would you take drugs which may have strange or dangerous eff
Do good manners and cleanliness matter much to you?
Would you like other people to be afraid of you?
Is it better to follow society’s rules than go your own way?
Are you a talkative person?
Are you rather lively?
Do you enjoy meeting new people?
ects?
Our analysis has brought together the foundational contribu-
tions of H.J. Eysenck to personality and attitudes
dimensionality,
and the genetic studies of attitudes initiated by L.J. Eaves and
N.G. Martin and further developed by T.J. Bouchard.
Bouchard’s
(2009) argument that combining Authoritarianism,
Religiousness
and Conservatism implies that whatever relationship exists be-
tween personality and attitudes, is not that one predicts the
other,
but that both traits contain elements that are simply different
rep-
resentations of the same constructs. Such a position is supported

by the results we show here.
The finding that the majority of covariation between Psychot-
icism and attitudes is due to genetic variance provides strong
evidence that a simple environmentally driven causal theory
from personality to politics is not suitable for such a complex
relationship. It is important to keep in mind that genes are mul-
tifaceted: there is no specific gene for a personality trait or for
a
political attitude, even if individual genes can be associated
with
specific attitudes or personality traits. However, the
relationship
between Social Desirability and the attitude dimensions exhib-
ited a remarkably different pattern of results. The locus of the
relationship in this case rested on shared environmental influ-
ences on the two traits. Due to the significant spousal correla-
tions for both Social Desirability and socio-political attitudes, it
is likely that some part of the shared environmental covariance
is attributed to assortative mating. The result provides some
support for existing social science expectations about the
impor-
tance of environmental influences for the relationship between
personality traits and social attitudes (see Mondak & Halperin,
2008). The social nature of Social Desirability makes the
connec-
tion between this personality trait and the associated social atti-
tudes reasonable. However, this environmental relationship is
the exception to our understanding of personality and politics
based on our findings here and in other studies (see Verhulst
et al., 2009).
These analyses should be seen as the beginning of a new stage
in the research connecting personality and politics. At this
point,
we know that the patterns of relationships are more complex

than
those suggested by previous models. That is, we cannot assume
causality, nor focus only on a single left–right ideological
spectrum.
Future research focusing on both active and passive gene–
environ-
ment covariation using extended kinship designs, and gene–
envi-
ronment interaction models are underway to further explore
these patterns.
Appendix 1. Confirmatory factor structure of the EPQ
Psychoticism Extraversion Neuroticism Social
Desirability
.57
�.31
.79
�.42
.38
�.46
.66
.71
.60
(continued on next page)
Appendix A (continued)
Psychoticism Extraversion Neuroticism Social

Desirability
Can you usually let yourself go and enjoy yourself at a lively
party? .76
Do you usually take the initiative in making new friends? .69
Can you easily put some life into a rather dull party? .81
Do you tend to keep in the background on social occasions?
�.83
Do you like mixing with people? .73
Do you often take on more activities than you have time for?
.26
Do you like plenty of bustle and excitement around you? .60
Do you like doing things in which you have to act quickly? .57
Are you mostly quiet when you are with other people? �.75
Do other people think of you as being very lively? .81
Can you get a party going? .80
Would you call yourself happy-go-lucky? .49
Does your mood often go up and down? .69
Do you ever feel ‘just miserable’ for no reason? .64
Are you an irritable person? .62
Are your feelings easily hurt? .65
Do you often feel ‘fed-up’? .72
Would you call yourself a nervous person? .63
Are you a worrier? .75
Would you call yourself tense or ‘high-strung’? .65
Do you worry too long after an embarrassing experience? .62
Do you suffer from ‘nerves’? .59
Do you often feel lonely? .66
Are you often troubled about feelings of guilt? .66
If you say you will do something, do you always keep your
promise? .49
Were you every greedy by helping yourself to more than your
share? �.63
Have you ever blamed someone for what was really your fault?

�.59
Are all your habits good and desirable ones? .59
Have you ever taken anything that belonged to someone else?
�.68
Have you ever broken or lost something belonging to someone
else? �.55
Have you ever said anything bad or nasty about anyone? �.71
As a child, were you ever ‘fresh’ towards your parents? �.51
Have you ever cheated at a game? �.70
Have you ever taken advantage of someone? �.76
Do you always practice what you preach? .57
Do you sometimes put off until tomorrow what you ought to do
today?
�.36
Appendix 2. Confirmatory factor structure of the Australian
socio-political attitude index
Religious Sex Out-groups Punishment
Bible Truth .84
Divine Law .74
Sabbath Observance .74
Church Authority .76
Divorce �.60
Evolution Theory �.55
Condom Machine �.86
Abortion �.78
Legalized Prostitution �.69
Casual Sex �.64
Chastity .63
Birth Control �.51
Surrogate Mothers �.50
Test Tube Babies �.44

Gay Rights �.54 �.46
Asian Immigration �.79
Multiculturalism �.73
49 (2010) 306–316
Appendix 2 (continued)
Religious Sex Out-groups Punishment
White Superiority .64
Conservationists �.49
Apartheid .46
Foreign Ownership �.34
Stiffer Jail Terms .82
Strict Rules .68
Death Penalty .59
Caning .48
Teenage Delinquency �.44
Note: In addition to the 26 items above, the following items
comprise the 50-item general conservatism scale: Privatization,
Medicare, Trade Unions, Patriotism, Voluntary
Euthanasia, Nuclear Power, Working Mothers, Inborn
Conscience, Government Welfare, Socialism, Herbal Remedies,
Charity Work, Suicide, Licensing Laws, Fluoridation,
Royalty, Women Judges, Disarmament, Censorship, White Lies,
Teenage Dole, Private Schools, Chiropractors, Defense
Spending, Legalized Modern Art. The items excluded
from the attitudinal factors did not contribute to the latent
attitudes and were thus omitted from the traits.

(2010) 306–316 315
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REGULAR ARTICLE
Personality Psychology: Lexical Approaches, Assessment
Methods, and Trait Concepts Reveal Only Half
of the Story—Why it is Time for a Paradigm Shift
Jana Uher
Published online: 8 February 2013
# The Author(s) 2013. This article is published with open access
at Springerlink.com
Abstract This article develops a comprehensive philosophy-of-
science for person-
ality psychology that goes far beyond the scope of the lexical

approaches, assessment
methods, and trait concepts that currently prevail. One of the
field’s most important
guiding scientific assumptions, the lexical hypothesis, is
analysed from meta-
theoretical viewpoints to reveal that it explicitly describes two
sets of phenomena
that must be clearly differentiated: 1) lexical repertoires and the
representations that
they encode and 2) the kinds of phenomena that are represented.
Thus far, personality
psychologists largely explored only the former, but have
seriously neglected studying
the latter. Meta-theoretical analyses of these different kinds of
phenomena and their
distinct natures, commonalities, differences, and interrelations
reveal that personality
psychology’s focus on lexical approaches, assessment methods,
and trait concepts
entails a) erroneous meta-theoretical assumptions about what
the phenomena being
studied actually are, and thus how they can be analysed and
interpreted, b) that
contemporary personality psychology is largely based on
everyday psychological
knowledge, and c) a fundamental circularity in the scientific
explanations used in trait
psychology. These findings seriously challenge the widespread
assumptions about the
causal and universal status of the phenomena described by
prominent personality
models. The current state of knowledge about the lexical
hypothesis is reviewed, and
implications for personality psychology are discussed. Ten
desiderata for future
research are outlined to overcome the current paradigmatic

fixations that are substan-
tially hampering intellectual innovation and progress in the
field.
Keywords Personality. Meta-theory. Methodology. Lexical
hypothesis . Lexical
approach . Traits . Personality assessment . Philosophy of
science . Big five model . Five
factor model
Integr Psych Behav (2013) 47:1–55
DOI 10.1007/s12124-013-9230-6
J. Uher (*)
Comparative Differential and Personality Psychology, Freie
Universität Berlin, Habelschwerdter
Allee 45, 14195 Berlin, Germany
e-mail: [email protected]
Science provides a special way of constructing knowledge about
the world. Unlike
nonscientific knowledge construction, science provides a way of
thinking simulta-
neously about phenomena and the means of producing
knowledge about them—this
presupposes meta-theory and methodology (Althusser and
Balibar 1970; Toomela
2011). Meta-theory refers to the philosophical assumptions
about the theoretical
nature of the phenomena to be studied and to the questions that
are asked about
them. Methodology refers to the ways (i.e., approaches) in
which these questions can
be answered and to the techniques (i.e., methods) that can

therefore be used (Sprung
and Sprung 1984).
All sciences have meta-theories. They determine which
elements of real
phenomena can be reduced to precisely those subsets of
elements that are
considered relevant to and defining of concrete scientific
phenomena and the
ways in which they can be reduced (Althusser and Balibar 1970,
p. 84, analysing
the philosophy of science of Marx 1867; Køppe 2012; Weber
1949). Meta-
theories determine what is considered data in a particular field
(in a particular
historical time; Kuhn 1962), and how the thus-defined data can
be analysed and
interpreted (Køppe 2012; Wagoner 2009). Hence, the first step
of reducing real
elements into facts is already a theoretical decision (Weber
1949, p. 173). “Alles
Faktische ist schon Theorie”—all facts are already theory
(Goethe 1907, p. 127).
In other words, “it is the theory which decides what can be
observed” (Einstein
to Heisenberg in 1926, cited in Heisenberg 1989, p. 10). Meta-
theories and
methodologies are the rules that govern the effective practices
of sciences.
Therefore, they should be explicated to enable researchers to
constantly scruti-
nise all levels from epistemology and ontology up to the
specific theories about
the phenomena studied (Toomela 2011). This also includes
rethinking the very
reduction of real phenomena into scientific phenomena (Utz

2005).
Contemporary psychology largely follows meta-theory and
methodology im-
plicitly, sometimes even “blindly” (Toomela 2011, p. 22)—this
occurs in partic-
ular when research methods are decided first and research
questions are adapted
to the methods rather than vice versa (Omi 2012; Westen 1996).
“The under-
standing that research methodology comprises an essential part
of scientific
theories about phenomena that are studied is not always brought
into the center
of theoretical reasoning” (Toomela 2009, p. 45). Ignoring the
meta-theoretical
assumptions underlying particular methods can result in
mismatches between
methods and research questions that hamper the scientific
understanding and
the explanations of the phenomena being studied—and thus
scientific progress
(Loftus 1996; Toomela and Valsiner 2010; Weber 1949). More
profoundly, a
priori decisions on methods preclude posing the primary
question of what the
phenomena to be studied actually are (Toomela 2011).
These meta-theoretical and methodological challenges are
characteristic of con-
temporary personality psychology and of taxonomic personality
research in particular
(Uher 2008a, b, 2011a, b; Uher, Methodological approaches to
personality taxono-
mies: The Behavioural Repertoire x Environmental Situations
Approach—A non-

lexical alternative, unpublished). The “discovery” of five major
dimensions of indi-
vidual differences is considered a milestone in modern Western
psychology (De Raad
1998; Digman 1990; Goldberg 1990). This “break through” was
made possible by the
assumption that people encode in their everyday languages all
those individual
2 Integr Psych Behav (2013) 47:1–55
differences that they perceive as most salient in everyday
encounters and that they
consider to be socially relevant. This so-called lexical
hypothesis, first articulated by
Galton (1884), has provided a stringent rationale for using the
lexica of human
languages as finite sources of information to unravel a few
major dimensions of
individual differences (Allport and Odbert 1936; Cattell 1943).
In English and some
other languages, the reduction of the pertinent lexical
repertoires to five major
dimensions has received the most support in Western scientific
communities
(Goldberg 1993; John et al. 1988). The lexical hypothesis also
suggests that enquiring
about the everyday psychological ideas that people develop of
themselves and of
other individuals could be a suitable method for the scientific
measurement of
personality (Block 2010; Westen 1996). Assessments by
laypeople have become
the standard methods of investigation (Baumeister et al. 2007;

Matthews et al.
2003) and the “primary source of data” in personality
psychology (Schwarz 1999,
p. 93). The assumptions expressed in the lexical hypothesis
might also contribute to
the fact that the prevailing strategies of the scientific
explanation of individual
differences largely follow structures that are deeply rooted in
everyday psychology.
In spite of its enormous importance as one of the most widely
used theoretical
assumptions to have guided personality psychology (Ashton and
Lee 2005), the
lexical hypothesis has remained untested (Toomela 2010a;
Westen 1996), and still
today, its statements have been considered only partially. This
article systematically
explores the meta-theoretical assumptions that underlie this
hypothesis. It starts by
highlighting the explicit reference of the lexical hypothesis to
two sets of phenomena
that must be clearly differentiated; these are, on the one hand,
people’s lexical
repertoires and the representations that these repertoires encode,
and, on the other
hand, the kinds of phenomena that are perceivable in everyday
life and that are being
represented. Thus far, personality psychology has focused
primarily on just one of
these two sets—on lexically encoded representations—but has
failed to systemati-
cally investigate the second set, namely, the kinds of
phenomena that are being
perceived and represented.

This article elaborates the distinct natures of the different kinds
of phenomena to
which the lexical hypothesis refers and explores their
commonalities, differences, and
interrelations from a philosophy-of-science perspective. This
allows for scrutiny to be
applied to the phenomena that are being lexically encoded and
sheds new light on the
fundamental questions of which kinds of phenomena can
actually be captured by
assessments—and which ones cannot. These analyses reveal that
erroneous meta-
theoretical assumptions underlie the established beliefs about
what these phenomena
actually are. They show that contemporary personality
psychology is largely based on
everyday psychological knowledge. Furthermore, the present
meta-theoretical anal-
yses allow us to scrutinise the prevailing psychological strategy
of explaining indi-
vidual differences—explicitly or implicitly—by assuming the
existence of “traits”.
The philosophy-of-science perspective identifies explanations
based on trait concepts
as fundamentally circular. These findings seriously challenge
the established assump-
tions about the causal and universal status of the phenomena
described by prominent
personality models.
Various researchers have carefully crafted serious concerns
about the established five
factor models of personality (e.g., Block 1995, 2001, 2010;
Eysenck 1992; McAdams
1992; Westen 1996), about assessment data and their
interpretation (e.g., Brower 1949;

Integr Psych Behav (2013) 47:1–55 3
Michell 1997, 2003; Omi 2012; Rosenbaum and Valsiner 2011;
Schwarz 2009; Trendler
2009; Valsiner 2012), and about the explanations provided by
trait psychology (e.g.,
Allport 1961; Bock 2000; Cervone et al. 2001; Lamiell 2003;
Mischel and Shoda 1994,
1995). This article moves these critical objections coherently to
meta-theoretical and
methodological levels of consideration. It expands them
substantially from the
philosophy-of-science perspective and elaborates a fundamental
critique of the lexical
approaches, assessments by laypeople, and trait concepts that
currently dominate per-
sonality psychology. It closes by outlining 10 desiderata for
future research to overcome
the limitations revealed in the analyses and to stimulate new
directions in the field.
Lexical Encodings—Constructs and Representations
The lexical hypothesis states that people encode in their
everyday languages all those
differences between individuals that they perceive to be salient
and that they consider
to be socially relevant in their everyday lives. Encodings about
differences within
individuals over time are not explicitly mentioned, however (see
below). Among the
many phenomena that individuals can perceive, recurrent
patterns are particularly

meaningful because such patterns may allow predictions of
future events while facing
the uncertainty of the future. Individuals therefore seek to
identify recurrent patterns
in their experiences with their personal world (Kelly 1955). To
describe, explain, and
to predict the likely occurrences of events, people construct and
represent their
experiences in private ideas (Valsiner 2012). These ideas are
called subjective or
individual representations (Jovchelovitch 2007; Moscovici
1984). Representations
referring to experiences with one’s own person and the—
especially social—world are
called personal constructs in personality psychology (Kelly
1955).
To communicate their perceptions and mental constructs of what
they perceive and
to negotiate socially shared meanings in order to cope with the
world collectively,
groups of individuals create and use social constructs. These
constructs are called
intersubjective or social representations (Jovchelovitch 2007) or
folk concepts in
personality psychology (Tellegen 1993). Constructs and
representations referring to
the perceptions of persons are called personality constructs. The
lexical hypothesis
states that, over time, socially shared constructs of self- and
other-perception become
encoded in the natural human languages. Pertinent lexical
encodings reflect the body
of everyday psychological ideas, beliefs, values, and practices
that people have
developed about individuals (Block 2010; Wagner et al. 1999;

Westen 1996).
What is Constructed and Represented—Phenomena and Patterns
What is it that is constructed and represented as “personality”?
Psychological defi-
nitions of personality—a few prominent ones picked out of
many—provide the first
insights into what scientific psychologists construct as
personality. Some frequently
cited definitions refer fairly generally and descriptively to
personality as
those characteristics that account for a person’s consistent
patterns of feeling,
thinking, and behaving (Pervin and John 1997, p. 4) or as
an individual’s characteristic patterns of thought, emotion, and
behaviour,
together with the psychological mechanisms–hidden or not–
behind those pat-
terns (Funder 2004, p. 5).
These definitions include psychological and behavioural
phenomena. Allport
(1937) also included psychophysical systems and environmental
adaptivity by defin-
ing personality as
the dynamic organization within the individual of those
psychophysical systems
that determine his unique adjustments to his environment (p.

48).
Eysenck (1947) furthermore specified genetic and
environmental causality, bio-
logical systems, and ontogenetic development when he defined
personality as
the sum-total of the actual or potential behaviour-patterns of the
organism, as
determined by heredity and environment; [that] originates and
develops through
the functional interaction of the four main sectors into which
these behaviour-
patterns are organized: the cognitive sector (intelligence), the
conative sector
(character), the affective sector (temperament), and the somatic
sector
(constitution) (p. 25).
McCrae and Costa (2008) extended the scope of consideration
by conceptualising
particular personality constructs as reflecting “universals” of
human nature that are
“invariant across human cultures” (McCrae and Costa 1997, p.
510), and thus also
potentially phylogenetic in origin (McCrae 2009).
These definitions are sufficient for highlighting fundamental
issues. First, they
refer descriptively to particular patterns (e.g., those described
as “characteristic”
and “consistent”) and to the different kinds of phenomena in
which these patterns
occur (e.g., physiological, psychological, and behavioural
phenomena). Second,
they include assumptions about the causation of the described

patterns in the
described phenomena by other kinds of phenomena internal to
the individual
(e.g., psychological phenomena) and/or external (e.g.,
environmental conditions)
considering various explanatory perspectives (e.g., proximate,
adaptive, ontoge-
netic, phylogenetic). Astonishingly, there is no mention of
people’s lexical
encodations and representations of individual differences
although these are
central to the lexical hypothesis.
From philosophy-of-science perspectives, the different kinds of
phenomena
studied with regard to personality must be clearly differentiated.
This is essential
because interrelations among them can be untangled only if they
are explored
each in their own right and if a priori assumptions about
specific interrelations
are avoided. This is rarely done in psychology. Behaviourists
have focused too
much on external conditions and behaviours, but have largely
ignored psycho-
logical phenomena. Subsequent researchers have tried to
overcome the limita-
tions of behaviourism and have therefore focused strongly on
psychological
phenomena and on individuals’ representations of their world,
but behaviour
has faded into the background. The prevailing investigative
strategies are preoc-
cupied with causal processes and the conditions in which
behavioural phenomena

occur—especially psychological ones—with the result that clear
differentiations
of psychological and behavioural phenomena are missing.
The meta-theoretical definition of behavioural phenomena as
“external activities
or externalisations of living organisms that are functionally
mediated by the environ-
ment (Millikan 1993) in the present” (Uher, What is behaviour?
And (when) is
language behaviour? A meta-theoretical definition, unpublished)
allows such differ-
entiations. This definition highlights the intrinsic relatedness of
behaviour to proper-
ties of the immediate external environment that are defined as
environmental
situations and emphasises that it is inherently bound to the
present. Externality
differentiates behaviour from thoughts, emotions, and other
psychological phenom-
ena, which are also bound to the present (Gillespie and Zittaun
2010; Toomela 2010a;
Valsiner 1998, 2012) but are internal to the individual (Toomela
2008). This meta-
theoretical definition generally defines all behavioural
phenomena without specifying
particular ones (e.g., goal-directed action or response) because
many of these con-
cepts include a priori assumptions about causally related
internal processes (e.g.,
psychological phenomena) and external conditions in the
environment (e.g., partic-

ular stimuli) that are separate kinds of phenomena. To scrutinise
which kinds of
phenomena people can perceive in everyday life and construct
as personality, it is
helpful to first specify the particular patterns referred to in
definitions of personality.
Defining Patterns
For scientific definitions, the notions of “a person’s consistent
patterns”, “individual
characteristics”, and “individual uniqueness” are surprisingly
vague. They do not
specify what is meant to be “consistent” with what, nor do they
indicate which patterns
are considered “different, “unique”, and “characteristic” and
why. Moreover, they fail to
mention within-individual variability and structural
complexity—both within and be-
tween individuals. This is remarkable because these patterns
refer to phenomena (e.g.,
those of the psyche and of behaviour) that are heterogeneous,
complex, dynamic, and
thus highly fluctuating. In such phenomena, differences among
individuals are neces-
sarily apparent at any given time (Uher 2011a) and
determinations of meaningful
consistency—both within and between individuals—are matters
of mere convention.
Meta-theoretical analyses help to carve out basic criteria for
determining which patterns
can be considered specific to particular individuals, and thus
different from others,
which ones cannot, and why. So what does individual-
specificity mean?

Probabilistic Patterns In the steadily fluctuating flow of events
in highly dynamic
phenomena, individuals necessarily show considerable within-
individual variability
over time. Consequently, they can be characterised only by
probabilistic patterns.
What types of probability1 are able to describe these patterns?
First, events of
psychological and behavioural phenomena are not random, such
as events in throws
of dice. There are no equipossible elementary events in well-
defined sample spaces
that can be studied in repeated experiments as in Laplacian
theory. Moreover, the
1 For the present meta-theoretical analyses, theories considering
subjectivistic probabilities of the occur-
rences of events (e.g., degrees of belief; Gillies 2000; Rychlak
1968) will not be considered here (for
reasons described in detail below).
events are not independent from one another—this applies to
events of the same
phenomenon (e.g., several smiles) as well as to events of
different phenomena (e.g., a
smile and a laugh). Rather, different events may co-occur and
even depend upon one
another, particularly if the phenomena are functionally similar
or related. Their events
need not be exclusively disjunctive (e.g., smiles and laughs).
Thus, finite (limiting)
frequencies, which are defined as empirical occurrences relative

to all possible
occurrences (von Mises 1928), are inadequate for describing
individual probabilities
in psychological and behavioural phenomena.
The concept of propensity probabilities seems to be better
suited for this purpose.
Propensities are considered properties of physical objects or
situations that are assumed
to cause empirical frequencies, even if only single-case
observations are made (Popper
1959). They are therefore conceived also as properties of
repeatable conditions that
determine empirical frequencies in the long run (Gillies 2000).2
But this very assump-
tion precludes the idea that propensity probabilities can be
applied to individuals
because their defining property as living systems is the fact that
they undergo continuous
changes during ontogenetic development. This is true for the
molecules in their bodies
and the phenomena constructed as personality alike. In fact,
personality is assumed to
develop and change gradually over the course of the lifespan
(e.g., Caspi and Roberts
2001; Cattell 1950; Soldz and Vaillant 1999). This implies that
the individual’s empirical
frequencies cannot converge (i.e., stabilise) in the long run as
may be true for physical
systems. By contrast, the probabilities themselves change over
time—an idea typically
not considered by theories of propensity probabilities (cf.
Gillies 2000; Popper 1959).
Further differences are essential. In psychological and
behavioural phenomena,

there are no discrete events such as there are in coin tosses.
Well-defined natural
entities on which probability estimations could be based are
lacking. Instead, it is the
scientists who must decide which entities of real phenomena
make up particular
scientific phenomena. The ways in which they define entities as
categories depend
not only on the phenomena themselves, but also on the purposes
of their reduction
(Weber 1949). Moreover, the processual character and
microgenetic development of
many psychological and behavioural phenomena (Rosenthal
2004) entails that their
occurrences can be construed as frequencies only in some cases.
In other cases, they
may be construed more accurately as durations of nonfixed and
often highly variable
length (or as latencies, which are durations with specified start
times).
Consequently, in fluctuating phenomena such as those of the
psyche and of
behaviour, events can be considered only by their empirical
occurrences (i.e., in
terms of frequencies and durations) relative to particular time
periods. This new
probability type will therefore be called a time-relative
probability. For example, in
observations of free play in a kindergarten group, a time-
relative probability of
10 min per hour of observation time during which a child plays
by him/herself may
be determined for a particular 5-year-old child. The time
periods in which time-
relative probabilities are determined must be specified

precisely—both in terms of the
occasions and spans of time in which the data were collected to
determine the
probabilities and in terms of historical times in the individual’s
ontogeny. Both are
2 The concept of propensity probabilities reifies observed
properties into causal entities of an unkown and
undefined kind. As such, the explanatory strategy is inherently
circular and faces the same challenges as
those elaborated for trait psychology in this article.
essential to define individual-specificity. For example, the 10
min per hour probabil-
ity could have been determined from 20 h of regular observation
obtained across a
time period of 2 weeks; the ontogenetic stage of the individual
is specified by an age
of 5 years, which can be categorised as early childhood.
This new probability type enables ratio-scaled quantifications
that are essential for
quantitative comparisons across time and situational contexts
and between individuals,
groups, populations, and species (Uher, Meta-theoretical
foundations of objectivity
versus subjectivity in quantifications of behaviour and
personality; An integrative
meta-theoretical framework for research on individual
behaviour in context—situa-
tions, populations, species, both unpublished). It also allows for
the merging of

concepts of averages across occasions, as studied in personality
research, with concepts
of ranges, especially maxima, as studied in intelligence and
achievement research3
(Ackerman 1994), and concepts of variability in terms of
differences between consec-
utive occasions (i.e., fluctuations) as studied in physiological
and behavioural research
(De Weerth et al. 1999). For example, the child’s time-relative
probability could be on
average 10 min per hour, ranging from 5 to 20 min per hour on
a daily basis; the
magnitude of day-to-day variability (for comparable occasions
across the days) as
indicated by the coefficient of variation could be CV=0.5. This
coefficient specifies
the standard deviation standardised by the mean (because the
standard deviation is
sensitive to the sample mean) to allow for comparisons between
different samples (for
an overview of methods of analyses of variability, see van Geert
and van Dijk 2002).
Such comprehensive analyses of patterns are important because
within-individual var-
iability in psychological and behavioural phenomena is
pronounced and bears theoret-
ical and empirical importance. For example, within-individual
variability can indicate
ongoing processes and can reflect phenomena that are important
for explaining changes
and development (van Geert and van Dijk 2002, p. 344).
Moreover, within-individual
variability often substantially exceeds between-individual
variability (Shweder and
Sullivan 1990; Uher, An integrative meta-theoretical framework

for research on indi-
vidual behaviour in context—situations, populations, species,
unpublished).
Differential Patterns Time-relative probabilities that
characterise all individuals in
the same way cannot be individual-specific. If all children in
the observed group have
the same time-relative probability of self-playing, then these
probabilities cannot
characterise any one of them individually. Time-relative
probabilities can reflect
individual uniqueness only if they deviate from those of other
individuals of a
particular reference group of interest (e.g., a social group,
culture, or species)—that
is, if they are differential. This is the case if the determined
time-relative probabilities
differ between children such that their individual averages vary
interindividually, for
example, between 2 min and 30 min per hour, their individual
ranges vary, for
example, between 15 min and 50 min, and their individual
within-individual varia-
bilities vary, for example, between CV=0.3 and 1.3.
The concept of time-relative probabilities presupposes that the
number of occa-
sions and periods of time considered for the probability
estimations are comparable
3 Personality research is often distinguished from intelligence
research in American psychology. In
European traditions (e.g., Cattell, Eysenck, Stern, Pawlik),
intelligence and achievement are considered
inherent parts of an individual’s personality.

between individuals. This is important when considering the
effects of aggregation on
the reliability of probability estimations (cf. Spearman 1910)
and when taking into
account the fact that the individuals’ probabilities themselves
may gradually change
over time (i.e., develop). In the given example, this means that
the time-relative
probabilities of the other children should also be estimated
based on 20 h of
observation across a time span of 2 weeks. These children
should also be of similar
age in order to disentangle differences between individuals from
differences between
age groups. Furthermore, the situational contexts in which
different individuals are
studied should be comparable between them because the average
time-relative
probabilities of particular groups of individuals may generally
shift across different
situations (Uher, An integrative meta-theoretical framework for
research on individ-
ual behaviour in context—situations, populations, species,
unpublished.) Analyses of
differentiality therefore require statistical standardisation of
time-relative probabilities
within the time periods and within the situational contexts in
which they are deter-
mined (Uher 2011a). Statistical standardisation removes the
information on absolute
time-relative probability scores, however, because the data are

converted into relative,
but still ratio-scaled data. Yet, the absolute scores can always
be traced when needed
for interpretation and for later comparisons with other samples
or with future inves-
tigations of the same sample.
Temporal Patterns Differential patterns in time-relative
probabilities that change
rapidly cannot characterise an individual’s uniqueness. To
reflect individual-
specificity, they must be stable across time periods that are
longer than those in
which the probabilities were first ascertained. As with the
analyses of differential
patterns, the analyses of temporal patterns presuppose that
probability estimations are
based on numbers of occasions and periods of time that are
comparable between the
individuals being studied and between the time periods being
contrasted. In the above
example, this means that the differential patterns in the
children’s time-relative
probabilities for self-play should be similar when estimated
again some time later
in a second period of 2 weeks. Temporal stability is an essential
prerequisite for
justifying interpretations of the obtained standardised aggregate
scores as reflecting
individual-specific patterns (Uher 2011a).
Temporal stability can be analysed for differential patterns in
the individuals’
averages, ranges, and variabilities. For example, it is quite
possible that individuals
with similar differential scores in their average probabilities

will differ from one
another in stable ways with regard to their ranges and patterns
of within-individual
variability. The magnitude of temporal stability considered
meaningful to construct
individual-specificity is necessarily a matter of convention that
can and must be
explicitly defined. It depends on the ontogenetic stages of the
individuals under study
as well as on their species-specific life expectancy (Uher 2009).
It also depends on the
phenomena being studied and the meta-theory used. For
example, in biology, weak
test-retest correlations of individual differences in behaviour
across just a few days or
weeks of r=.20 are considered ecologically and evolutionarily
meaningful (Sih and
Bell 2008), whereas in human psychology, such weak
correlations are considered
indicators of unreliable measurements of individual-specific
patterns (Uher 2011a).
In conclusion, for fluctuating and dynamic phenomena such as
those of the psyche
and behaviour, individual-specificity refers to differential
patterns in time-relative
probabilities that are stable in ways that are considered to be
meaningful. This
concept fits well into Brunswik’s (1955) probabilistic theory for
functional psychol-
ogy. Brunswik ascertained that although the environment may

be lawful in terms of
physical principles, to the individual, “it presents itself as semi-
erratic … therefore all
functional psychology is inherently probabilistic” (Brunswik
1955, p. 193). An
empirical application of this meta-theoretical concept of
individual-specificity to
behaviour was demonstrated in a study on capuchin monkeys
based on 141 con-
textualised behavioural variables (Uher et al., Contextualised
behavioural measure-
ments of personality differences obtained in behavioural tests
and social observations
in adult capuchin monkeys (Cebus apella), unpublished).
Individual-specific patterns that have been identified in these
ways can be subse-
quently studied across longer periods of time to explore patterns
in their gradual
change and ontogenetic development (Uher 2011a). This
presupposes again that the
occasions and time spans as well as the historical times that are
studied should be
specified and should be comparable between the individuals
under study.
The concept of time-relative probabilities allows for the close
examination of individ-
ual cases in specified situations. By studying many individuals
in this way, it also allows
for the study of lawful patterns at the sample level. The former
type of study is commonly
referred to as ideographic; the latter one as nomothetic. But
ideographic approaches in
terms of single case studies in and of themselves need not be
informative about particular

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