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Creativity is the tendency to generate or recognize ideas, alternatives, or possibilities. Following a study on the genetic contribution to working in a creative profession, based on polygenic score analysis, we report the total heritability of this trait in a large sample of adult twins and their siblings registered with the Netherlands Twin Register. Data from 6755 twins and 1817 siblings were analyzed using genetic structural equation modeling. Working in a creative profession is relatively rare in our sample (2.6% of twins and 3.2% of siblings). Twin correlations (identical 0.68 and fraternal 0.40) commended a model with additive genetic factors (full model estimate 0.56), shared (full model estimate 0.12), and unique environmental factors (full model estimate 0.32). Genetic model fitting resulted in a best-fitting model existing of additive genetic factors and unique environmental factors, resulting in a heritability of 0.70.
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Heritability of Working in a Creative Profession
Mark Patrick Roeling
Gonneke Willemsen
Dorret I. Boomsma
Received: 6 June 2016 / Accepted: 18 November 2016 / Published online: 15 December 2016
ÓThe Author(s) 2016. This article is published with open access at
Abstract Creativity is the tendency to generate or recog-
nize ideas, alternatives, or possibilities. Following a study
on the genetic contribution to working in a creative pro-
fession, based on polygenic score analysis, we report the
total heritability of this trait in a large sample of adult twins
and their siblings registered with the Netherlands Twin
Register. Data from 6755 twins and 1817 siblings were
analyzed using genetic structural equation modeling.
Working in a creative profession is relatively rare in our
sample (2.6% of twins and 3.2% of siblings). Twin corre-
lations (identical 0.68 and fraternal 0.40) commended a
model with additive genetic factors (full model estimate
0.56), shared (full model estimate 0.12), and unique envi-
ronmental factors (full model estimate 0.32). Genetic
model fitting resulted in a best-fitting model existing of
additive genetic factors and unique environmental factors,
resulting in a heritability of 0.70.
Keywords Creativity Twin study Talent Working
Profession Heritability
Creativity is the tendency to generate or recognize ideas,
alternatives, or possibilities that may be useful in solving
problems, communicating with others, and entertaining
ourselves and others (Franken 2006). This broad array of
discrete abilities has a strong cognitive component (Weis-
berg 1992) and creativity correlates with intelligence and
cognitive performance (Guilford 1967; Penke 2006).
There is ample evidence for the influence of genetic
factors but heritability estimates are diverse. Ten early twin
studies were summarized in a review presenting average
correlations of 0.61 for MZ twins and 0.50 for DZ twins
(Nichols 1978), resulting in a rough heritability estimate of
25% (and 38% shared environmental factors; Penke 2006).
A subsequent study into perceptual and esthetic abilities
(Barron and Parisi 1976) also argued in favor of hereditary
influences in creativity. Generally, studies in adolescents
provide lower heritability estimates of creativity-related
traits. One twin study in adolescents (13–19 years) exam-
ined 11 creative ability measures (e.g. recognizing obscure
figures or create story plot titles) and observed only three
scales with significant MZ-DZ differences (Reznikoff et al.
1973). A Russian twin study estimated a heritability of 0.44
in creative thinking (Grigorenko et al. 1992). Compared to
the aforementioned studies in adolescents, heritability
estimates are slightly higher in adults for traits as creative
personality (50–54%; Bouchard et al. 1993; Velazquez
et al. 2015), drawing (38–47%; Velazquez et al. 2015), arts
(60%; Vinkhuyzen et al. 2009), creative writing (83%;
Vinkhuyzen et al. 2009), creative achievement (61%; Piffer
and Hur 2014), perceived (62%) and figural (26%) cre-
ativity (Kandler et al. 2016). Variability in creativity over
age has been interpreted as indicative for cognitive matu-
rity, with children first becoming proficient learners while
Edited by Yoon-Mi Hur.
&Mark Patrick Roeling
Department of Computer Science, University of Oxford,
Robert Hooke Building, Parks Road, Oxford OX1 3QD, UK
Department of Biological Psychology, Vrije Universiteit
Amsterdam, Amsterdam, The Netherlands
Behav Genet (2017) 47:298–304
DOI 10.1007/s10519-016-9832-0
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
the ability to think creatively evolves throughout devel-
opment (Fogarty et al. 2015).
Another aspect of creativity is the phenotypic and
genotypic overlap with traits such as openness, extraver-
sion, and intelligence (Canter 1973; Kandler et al. 2016;
Penke 2006), which extends to extreme expressions of
behavior (Carson 2011) illustrated by the co-occurrence of
creativity with attention problems (Mayseless et al. 2013),
schizophrenia and bipolar disorder (Power et al. 2015). The
latter study linked genetic variants underlying schizophre-
nia and bipolar disorder to creativity, explaining 0.24 and
0.26% of the variance of creativity, respectively. Power
et al. (2015) analyzed creativity as working in a creative
profession, but did not report the overall heritability of this
trait. Therefore, we now use data from 6755 twins and
1817 siblings aged C21 years registered with the NTR
(Willemsen et al. 2013), to estimate the total heritability of
working in a creative profession. Extending the classical
twin design of mono- and dizygotic twins with their sib-
lings gives larger statistical power to estimate both shared
environmental and non-additive genetic effects (Posthuma
and Boomsma 2000).
This study is part of an ongoing study on health, lifestyle
and personality in twins and their family members regis-
tered in the NTR. Every two to three years, registered
families receive surveys on health and lifestyle and the
present study uses from the seventh and eight surveys
respectively collecting data in 2004–2008 and 2009–2012
(described in Willemsen et al. 2013). Informed consent was
obtained from all individual participants included in the
study. Zygosity was determined either through genotyping
or from self- and parental report answers to survey ques-
tions on physical resemblance or confusion of the twins by
other family members and peers. DNA and survey zygosity
agreement reached more than 96%.
Data were available from 8802 participants
=6942, N
=1860). We removed indi-
viduals with age unknown (N =6) or age below 20 years
(N =3) and families including only one twin (N =95),
multiple twins from a different pair (N =31), or twins
with missing zygosity (N =27). A maximum of two
brothers and two sisters were included in the analyses,
remaining siblings were excluded (N =68). In families
with triplets, we selected two random twins, and if dizy-
gotic, the remaining twin was used as a sibling. In families
with multiple twin pairs, we selected the first twin pair and
used the other twin pairs to extract one random twin as
sibling. This resulted in a total sample of 6755 twins and
1817 siblings from 4734 families, including 999 monozy-
gotic males (MZM), 541 dizygotic males (DZM), 2585
monozygotic females (MZF), 1249 dizygotic females
(DZF), 1381 DZ opposite-sex pairs, with 679 brothers and
1138 sisters. Table 1shows the complete family configu-
ration of the sample. There were 2427 families in which
both members of a twin pair completed the questionnaire,
1901 families in which only one member of the twin pair
completed the questionnaire and 406 families in which
only non-twin siblings completed the questionnaire (added
to DZMales). The mean age of the twins was 38.42 years
[standard deviation (SD) 11.98, range 20–90 years] and the
mean age for their siblings was 41.26 years (SD 12.18,
range 20–90 years).
Following an earlier study (Power et al. 2015), creativity
(being in a creative profession) scoring relied on surveys
including detailed questions about the participants’ occu-
pations. Using a detailed description, individuals were
asked to report their profession. We then classified these
professions on being creative or not. Creative professionals
were defined as those having positions in the fields of
dance, film, music, theatre, visual arts, or writing. We did
not differentiate whether, within these categories, persons
were more or less creative. When persons were not work-
ing or reported to be a housewife at the moment of data
completion, they were asked for their past occupation and
this was used to assess whether they had a creative pro-
fession. When a person indicated to be a housewife and had
not had another profession in the past, this was coded as not
involved in a creative profession. In the case of full-time or
part-time education, creative profession was regarded
Statistical analyses
Descriptive analyses were performed in SPSS v.20.
Genetic structural equation model analyses were conducted
in Mx (Mx: statistical modeling; Neale 2006). Given the
categorical nature of the data (yes/no) we fitted a ‘liability’
model (Falconer 1965), in which the categorical variable
was assumed to reflect an imprecise measurement of an
underlying normal distribution of liability. Being a theo-
retical construct, the liability’s scale needs to be defined. In
general, the liability is assumed to be standard normally
distributed with zero mean and unit variance. The threshold
acts as a reference of incidence of the different categories
in the population (Falconer and Mackay 2005).
We fitted different sets of models to the raw ordinal data
using maximum likelihood estimation. In the fully
Behav Genet (2017) 47:298–304 299
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saturated model, thresholds were allowed to vary as a
function of sex (0 for male and 1 for female) and twin/sib
status. Specifying separate thresholds for twins and siblings
allows to investigate sibling effects (a specific kind of
genotype-environment autocorrelation), which can occur
because the genotype of one sibling or twin is genetically
correlated with the phenotype of the other sibling which is
providing part of the environment, potentially resulting in
different thresholds between siblings (Neale and Maes
2002). Age (standardized and sex specific coefficients) was
modelled as a covariate on the threshold to account for any
remaining variability in incidence of creativity as a func-
tion of age, expecting similar effects of the age bcoeffi-
cient between zygosity groups. Tetrachoric correlations
were estimated for the continuous liability distribution,
with a total of eight correlations for MZMales, DZMales,
MZFemales, DZFemales, DZ opposite-sex pairs, brother–
brother, sister–sister, and brother–sister) to be estimated. In
total, the saturated model comprised of 16 free parameters:
one threshold for male twins and one threshold for female
twins, one threshold for brothers and one for sisters, two
fixed effects, i.e., covariates coefficients (age and sex) for
males and two coefficients for females, and eight correla-
tions estimating the familial resemblance. In a series of
nested models we tested constraints to test the significance
of different parameters and derive the most parsimonious
model. The fit of submodels was evaluated with Log-
likelihood ratio testing, which involves subtracting the
negative log-likelihood (-2LL) for the more general model
from the -2LL of the more restricted model. This gives a
test with the degrees of freedom (df) equal to the dif-
ference in the number of estimated parameters in the two
models. A significant v
(p\0.05) indicates that the
constrained model fits significantly worse than the previous
model. As a result, the previous model is kept as the most
parsimonious model, to which a new model can be com-
pared. Thus, those models that are the most parsimonious
and efficient representations of the data are selected.
Genetic analyses
From the difference in genetic relatedness in MZ and DZ
twins, who share respectively 100 and 50% (on average) of
their segregating genes, the amount of variance can be
estimated and ascribed to genetic and environmental fac-
tors (Boomsma et al. 2002). A higher MZ correlation
compared to the DZ correlation is indicative of genetic
influences. If MZ and DZ correlations are similar, genetic
effects are not suggested.
Quantitative genetic modeling is based on the fact that the
phenotypic variance is a function of genetic, shared, and
unique environmental variance. The expectation for the phe-
notypic variance may be written as: V
. Genetic variance can be additive (A),
indicating that the effects of multiple alleles are additive, or
nonadditive (dominance, D) meaning that alleles at a
Table 1 Family structures in
dataset Families yielding
No siblings 1 sibling 2 siblings 3 siblings 4 siblings Total
Families yielding a twin pair 258 81 14 10 1 364
Families yielding a single twin 233 26 11 0 1 271
Families yielding a twin pair 108 44 831164
Families yielding a single twin 165 36 10 2 0 213
Families yielding a twin pair 777 220 53 9 5 1064
Families yielding a single twin 400 46 10 1 0 457
Families yielding a twin pair 300 95 39 8 0 442
Families yielding a single twin 314 43 620365
Families yielding a twin pair 260 101 24 6 2 393
Families yielding a single twin 498 75 16 6 0 595
Families yielding no twins 335 62 8 1 406
Total 3315 1102 253 55 11 4734
Family structures in dataset
MZM monozygotic males, DZM dizygotic males, MZF monozygotic females, DZF dizygotic females, DOS
DZ opposite-sex
300 Behav Genet (2017) 47:298–304
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particularlocus interact. When the DZ correlation is morethan
half the MZ correlation, there is evidence for environmental
effects shared by twins from the same family (C) and when the
DZ correlation is less than half the MZ correlation, there is
evidence for non-additive genetic effects. Broad-sense heri-
tability (h
) is the proportion of phenotypic variance that is
attributable to genotypic variance (h
narrow-sense heritability is the proportion of variation
explained by additive genetic factors (h
). A
classical twin design only provides information to model
either an ACE model or an ADE model, but adding data from
siblings of twins provides more information and statistical
power to distinguish between additive and dominant genetic
factors. The additive genetic variance is perfectly correlated in
MZ twins, whereas for DZ twins and siblings the cross-twin/
cross-sib correlation between the A factors is 0.5. Again, the
significance of genetic parameters was tested by comparing
submodels against a more general model, using log-likelihood
ratio testing.
We observed a low frequency of working in a creative
profession with 175 (2.6%) of 6755 twins and 58 (3.2%) of
1817 siblings reporting positive (see Table 2). For each
family, we indicated the number of individuals within the
family, restricted to twins, siblings and parents. From the
8572 individuals (twins with B4 siblings) included in the
statistical analyses, no data on additional family members
were available in 1331 persons. In the remaining 7241
individuals with data from family members: 4.5% had 1 or
more family members in a creative profession. We then
split the data according to creative profession of the person
itself. Of the persons who were, themselves, not in a cre-
ative profession (N =7042), 3.9% had family members in
a creative profession. In the persons who were in a creative
profession (N =199), 26.1% had family members in a
creative profession.
Table 2 Reported creative
professions N (%) for first profession N (%) for second profession
Architecture 18 (7.6)
Art teacher 15 (6.4) 7 (21.9)
Art therapy 1 (0.4)
Artisan 16 (3.8) 6 (18.8)
Cinematography 20 (8.5) 3 (9.4)
Creative director 13 (5.5) 2 (6.3)
Creative writer 5 (2.1)
Curator 2 (0.8)
Dance teacher 4 (1.7) 1 (3.1)
Fashion design 2 (0.8)
Flower design 15 (6.4)
Game design 1 (0.4)
Graphical design 41 (17.4)
Illustrator 2 (0.8)
Interior design 18 (7.6)
Landscape architect 3 (1.3)
Music teacher 9 (3.8)
Musician 3 (1.3)
Photography 2 (0.8) 1 (3.1)
Reporter 19 (8.1)
Set decoration 3 (1.3)
Singer 1 (0.4)
Theatre artist 7 (3.0) 1 (3.1)
Theatre teacher 5 (2.1) 1 (3.1)
Web design 7 (3.0)
Writer 4 (1.7) 9 (28.1)
Costume maker 1 (3.1)
Total 236 (100) 32 (100)
The Artisan category includes individuals working as a fine artist (painter, art drawing, and ceramics artist).
Three individuals reported two creative professions as first profession
Behav Genet (2017) 47:298–304 301
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Between twins, there was no evidence for birth-order
effects (v2
ð1Þ=0.010, p=0.920). Of the 4734 families,
4523 (95.5%) had no family members who are who are
working, or worked, in a creative profession. Table 3
presents the results of the tests in the saturated model.
Creativity scores, measured as thresholds, were not sig-
nificantly different for male twins and brothers nor for
female twins and sisters (v2
ð1Þ=1.759, p=0.415) sug-
gesting the absence of sibling effects. Thresholds could
also be constrained across gender (v2
p=0.857). In females, there was a significant positive age
effect (v2
ð1Þ=12.309, pB0.001) indicating that older
females more frequently report to work, or to have worked,
in a creative profession. Phenotypic correlations between
twins were 0.54 in MZMales and 0.69 in MZFemales
versus 0.47 in DZMales, 0.25 in DZFemales and 0.31 in
DZ-opposite sex pairs. Sibling correlations were 0.54
between brothers, 0.31 between sisters, and 0.51 between
sisters and brothers. Constraining the phenotypic correla-
tions between twins and siblings (e.g., brother–brother
correlation to DZMales) and between males and females
did not result in a significant deterioration of the model fit,
commending a model where the heritability is equal for
both gender groups. After constraining the correlations, the
constrained MZ (MZMales and MZFemales) correlation
was 0.68 and the constrained DZ (DZ twins and siblings)
correlation was 0.40, suggesting the influence of shared
environmental factors (C) and providing evidence for an
ACE model.
The full model estimated A to be 0.56 (95% CI 0.11–
0.80), C to be 0.12 (95% CI 0–0.45) and E to be 0.32 (95%
CI 0.19–0.50). Dropping the shared environmental factor
from the ACE model did not significantly worsen the
model fit (v2
ð1Þ=0.478, p=0.489), whereas removal of
the additive genetic component did (v2
p=0.014). Therefore, the best fitting model is an AE
model with a heritability estimate of 0.70.
This study estimated the heritability of working in a cre-
ative profession in a large sample of Dutch adult twins and
their siblings. The best fitting model yielded a heritability
Table 3 Model fit results for the saturated model
Model Test Versus -2LL df v
Ddf p
0 Full model 2115.081 8572
1 Thresholds male twins =brothers
Threshold female twins =sisters
0 2116.840 8574 1.759 2 0.415
2 Thresholds males =females 1 2116.872 8575 0.032 1 0.857
3 Age effects males =females 2 2122.821 8576 5.949 1 0.015
3a Age effects males =0 2 2116.962 8576 0.090 1 0.764
3b Age effects females =0 2 2129.181 8576 12.309 1 \0.001
4 Sex effects males =females 3a 2117.011 8577 0.049 1 0.825
4a Sex effects males and females =0 4 2117.107 8578 0.096 1 0.757
5 DZ twin correlations =sibling correlations 4a 2117.860 8581 0.753 3 0.861
6 Male correlations =female correlations 5 2118.288 8583 0.428 2 0.807
7Same sex DZ/sibling correlations =opposite sex DZ/sibling correlations 6 2119.074 8584 0.786 1 0.375
Model fit results for the saturated model. The best fitting model had four free parameters (one threshold, MZ correlation, DZ correlation, and age
coefficient females). The best fitting model is printed in bold
-2LL -2 log likelihood, df degrees of freedom, ppvalue, DZ dizygotic
Illustration 1 MZ twins are more often concordant for creativity, as
illustrated by these portraits where Dutch MZ twins David and Pieter
Oyens (successful nineteenth century painters) painted each other
302 Behav Genet (2017) 47:298–304
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estimate of 70% with the remaining variance explained by
unique environmental factors. Our finding confirms earlier
smaller studies in adults (Bouchard et al. 1993; Kandler
et al. 2016; Penke 2006; Piffer and Hur 2014; Vinkhuyzen
et al. 2009) presenting evidence for significant genetic
influences underlying creativity. Outcomes of this study are
also in line with twin studies investigating personality traits
where the majority of studies show a heritability of
0.49–0.57 and low to zero shared environmental influences
(Bouchard and McGue 2003). The insignificant prevalence
differences and similar heritability estimates between sexes
conforms to earlier work (Penke 2006; Piffer and Hur
2014) and adds evidence to a field where studies that report
higher creativity scores in females are counterbalanced (in
number) by studies where males score higher (Baer and
Kaufman 2006).
This study is limited in using only self-report data on
profession that is categorized by us as creative or not cre-
ative, and in the low prevalence of working in a creative
profession. Possibly, the focus on working in a creative
profession provides an underestimate of creativity in gen-
eral, as participants can still be creative in their own time
(e.g., during leisure) which is not captured by this study. The
combination of subtle influences of C (ACE model esti-
mate =0.12) and the use of a threshold model in an
unbalanced dataset reduces the power of our method. The
inclusion of (at least one) additional sibling(s) is a proven
strategy to increase the power to accurately estimate vari-
ance components, especially common environmental factors
(Posthuma and Boomsma 2000). From Neale et al. (1994)we
deduce that with our prevalence (between 0.01 and 0.05) a
sample size at least 100,000 twins would be needed to detect
the AE model under a true C of 0.12. Despite this being one
of the largest twin studies focusing on creativity to date,
there may be much to learn about shared environmental
effects that contribute to the decision to pursue a creative
carreer with more powerful samples or methods. From our
work and others, the substantial heritability estimate for the
phenotype indicates that multiple DNA variants, in addition
to those overlapping with schizophrenia and bipolar disorder
are likely to be found in the future (Illustration 1).
Acknowledgements The Netherlands Twin Register thanks all par-
ticipants. The research leading to these results has received support
from the Netherlands Organization for Scientific Research (NWO)
and MagW/ZonMW, BBMRI-NL (184.021.007), the VU University
Institute for Health and Care Research (EMGO ?) and Neuroscience
Campus Amsterdam, the European Science Council (ERC) Genetics
of Mental Illness (230374), the Avera Institute for Human Genetics,
and the Engineering and Physical Sciences Research Council.
Compliance with ethical standards
Conflict of interest Mark Patrick Roeling, Gonneke Willemsen, and
Dorret I. Boomsma declare no conflict of interest.
Human and animal rights The study protocols were approved by
the Central Ethics Committee on Research Involving Human Subjects
of the VU University Medical Centre, Amsterdam, an Institutional
Review Board certified by the US Office of Human Research Pro-
tections (IRB number IRB-2991 under Federalwide Assurance-3703;
IRB/institute codes, NTR 03-180).
Informed consent Twin families are voluntarily registered with the
NTR and the data collection protocol was approved by the Medical
Research Ethics Committee of the VU University Medical Center.
Open Access This article is distributed under the terms of the
Creative Commons Attribution 4.0 International License (http://crea, which permits unrestricted use,
distribution, and reproduction in any medium, provided you give
appropriate credit to the original author(s) and the source, provide a
link to the Creative Commons license, and indicate if changes were
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... On the other hand, recent studies have convincingly demonstrated the heritability of non-STEM occupations, with Nicolaou and Shane's [15] twin-based research revealing high heritability in professions such as teaching, management, sales, and self-employment. The findings of Roeling et al. [18] estimated the heritability of creative professions to be approximately 0.70, and more recently, Song et al. [19] discovered nine genetic loci that were significantly linked to leadership roles using a largescale genome-wide association study. Despite these compelling results, it is noteworthy that no specific genetic variants have yet been empirically linked to occupational choices in STEM fields, to the best of our knowledge. ...
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Background Science, technology, engineering, and mathematics (STEM) professionals are regarded as the highly skilled labor force that fosters economic productivity, enterprise innovation, and international competitiveness of a country. This study aims to understand the genetic predisposition to STEM occupations and investigate its associations with regional economic performance. We conducted a genome-wide association study on the occupational choice of STEM jobs based on a sample of 178,976 participants from the UK Biobank database. Results We identified two genetic loci significantly associated with participants’ STEM job choices: rs10048736 on chromosome 2 and rs12903858 on chromosome 15. The SNP heritability of STEM occupations was estimated to be 4.2%. We also found phenotypic and genetic evidence of assortative mating in STEM occupations. At the local authority level, we found that the average polygenic score of STEM is significantly and robustly associated with several metrics of regional economic performance. Conclusions The current study expands our knowledge of the genetic basis of occupational choice and potential regional disparities in socioeconomic developments.
... For example, using data on twins, Nicolaou and Shane (2010) found that the choice to become a teacher, manager, salesperson, or selfemployed was highly heritable. Roeling et al. (2017) estimated that the heritability of working in a creative profession was approximately 0.70. More recently, Song et al. (2022) identi ed nine genetic loci signi cantly associated with leadership positions based on a large-scale genome-wide association study. ...
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Science, technology, engineering, and mathematics (STEM) professionals are regarded as the highly skilled labor force that fosters economic productivity, enterprise innovation, and international competitiveness of a country. We conducted a genome-wide association study on the occupational choice of STEM jobs based on a sample of 178,976 participants from the UK Biobank database. We identified two genetic loci significantly associated with participants’ STEM job choices: rs10048736 on chromosome 2 and rs12903858 on chromosome 15. The SNP heritability of STEM occupations was estimated to be 4.2%. We also found phenotypic and genetic evidence of assortative mating in STEM occupations. At the local authority level, we found that the average polygenic score of STEM is significantly and robustly associated with several metrics of regional economic performance. The current study expands our knowledge of the genetic basis of occupational choice and potential regional disparities in socioeconomic developments.
... A twin study of working in a creative profession is also relevant to this discussion (Roeling et al., 2017). Twins working in various design fields were among the many artistic areas included. ...
The unique sources of artistic inspiration and talent of twin artists are examined. The professional literature is rich with twin studies of creativity, but lacking when it comes to specific artistic domains — for example, painting and sculpting. The section that follows provides reviews of current research on ethnic and racial factors affecting type of twin delivery, pregnancy outcomes when twins are conceived naturally or with reproductive assistance, the effects of intrauterine growth discordance on the timing of twin delivery, and three-dimensional (3D) assessment of twins’ facial resemblance. The final section summarizes information about twins in the media. The stories include twins distinguished for both baseball playing and physical injuries, twins who reached the National College Athletic Association’s Elite 8, a twin pair’s grave and epitaph, a mother who conceived twins three times in 2 years, twins in the Hockey Hall of Fame, and a set of superfetated twins.
... A polygenic risk score analysis showed that the genetic risk for schizophrenia and bipolar disorder could predict a creative occupation regardless of familial relations, implicating that these disorders share a genetic background with creative employment [23]. The heritability of working in a creative profession, such as architecture, art teaching, design, curating, writing, reporting or performing, has been calculated at 70%, pointing to a strong genetic influence [25]. The preservation of genetic polymorphisms related to mental disorders in the gene pool could signify they also carry positive effects, namely creativity and altruism [26,27]. ...
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Creativity, art and artistic creation in music, dance and visual arts are brain activities specific to humans. Their genetic background remained unexplored for years, but many recent studies have uncovered significant associations with cognition-related genes and loci. These studies are summarized in the present article. Creativity is a trait with heavy genetic influences, which are also associated with mental disorders and altruism. Associated genes include dopaminergic, serotoninergic and other genes (a1-antitrypsin, neuregulin, Brain-derived neurotrophic factor). Music is another complex phenotype with important genetic background. Studies in musicians and their families have highlighted the contribution of loci (e.g., 4q22) and specific genes (vasopressin receptor 1α and serotonin transporter). The latter two are also associated with dancing. Although few studies have investigated visual arts, they appear to be influenced by genetic differences, which could explain the increased prevalence of synesthesia in artists and individuals with autism. Lastly, although genes play an important role in creativity and art, epigenetics and the environment should not be overlooked. The genetic exploration of artistic creativity may provide useful knowledge on cognition, behavior and brain function. It may also enable targeted and personalized art therapy in health and disease.
... Although relevant, the sociocultural factors likely do not fully explain the pattern of present results. That is because in some instances there was no correlation between intrinsic and extrinsic measures, and there are indeed important biological components to artistic talent including strong intrinsic motivation, referred to as "rage to master" (Winner and Drake, 2018), including multigenerational continuity (Perrone et al., 2010), and medium to high heritability in the choice of creative professions (Roeling et al., 2017). A twin-based study even showed that as musical ability, a musical practice also is substantially heritable (40-70%), and the association between both practice and ability was predominantly genetic so that identical twins differing in the amount of practice did not differ in their ability (Mosing et al., 2014). ...
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Darwin explored the evolutionary processes underlying artistic propensities in humans. He stressed the universality of the human mind by pointing to the shared pleasure which all populations take in dancing, engaging in music, acting, painting, tattooing, and self-decorating. Artistic motivation drives/reinforces individuals to engage in aesthetically oriented activities. As curiosity/play, artistic behavior is hypothesized as a functionally autonomous activity motivated intrinsically through an evolved, specific, and stable aesthetic motivational system. The author tested whether artistic motivation is rather intrinsically sourced, domain-specific, and temporally stable using a large decades-long real-life public Brazilian database of university applications. In Study I, the author analyzed reasons for career-choice responded to by 403,832 late-adolescent applicants (48.84% women), between 1987 and 1998. In Study II, the author analyzed another career-choice reason question responded to by 1,703,916 late-adolescent applicants (51.02% women), between 1987 and 2020. Music, Dance, Scenic Arts, Visual Arts, and Literary Studies, in combination, presented a higher percentage of individuals reporting intrinsic factors (e.g., personal taste/aptitude/fulfillment) and the lower proportion reporting extrinsic motives (e.g., the influence of media/teacher/family, salary, social contribution/prestige) than other career groups. If artistic motivation were a recent by-product of general curiosity or status-seeking, artistic and non-artistic careers would not differ. Overall, intrinsic motives were 2.60–6.35 times higher than extrinsic factors; among artistic applicants’ were 10.81–28.38 times higher, suggesting domain-specificity. Intrinsic motivation did not differ among artistic careers and remained stable throughout the periods. Converging results corroborated a specific, stable, and intrinsically sourced artistic motivation consistent with its possible evolutionary origins.
... To explore all these hypotheses, we used Generalized Additive Models (GAM) to test for non-linear associations between the predictors and musical creative achievement, using web survey data from two samples-one large twin cohort and one sample of professional musicians. Given the generally skewed distribution of creative achievement (Carson, Peterson, & Higgins, 2005), the sample of professionals was crucial in order to pad the number of participants with high achievement since previous work indicates that only about 2-10% of individuals in a random sample of the general population actually have a high (professional) level of creative achievement (de Manzano & Ullén, 2018;Roeling, Willemsen, & Boomsma, 2017). Since the web surveys included the Swedish version of the creative achievement questionnaire (CAQ) (de Manzano & Ullén, 2018), which asks participants to report engagement/attainment in seven creative domains (5 artistic and 2 scientific), there was an additional opportunity to address the question of "multipotentiality", i.e. the potential of succeeding in multiple domains, which has traditionally been attributed to high general ability. ...
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Previous research shows that individuals choose careers based on the relative strengths of various traits. More debated however, is how specific combinations of traits predict individual differences in professional achievements. General intelligence is often proposed to be the best predictor of eminence, but some studies suggest that more specific traits can be relatively important when performance depends on specific skills and expertise. Here we identified a comprehensive set of variables relevant for music achievement (intelligence, auditory ability, absolute pitch, Big-five personality traits, psychosis proneness, music flow proneness, childhood environment and music practice), and tested how they predicted level of musicianship (non-musicians vs. amateur musicians vs. professional musicians) and number of achievements among professional musicians. We used web survey data from a total of 2150 individuals, and generalized additive models that can also reveal non-linear relationships. The results largely confirmed our three main hypotheses: (i) non-musicians, amateur musicians, and professional musicians are best differentiated by domain specific abilities, personality traits, and childhood factors; (ii) largely the same significant predictors are also associated with the number of creative achievements within professional musicians; (iii) individuals who reach a professional level in two domains (here science and music) possess the union of the relevant traits of both domains. In addition, many of the associations between predictors and achievement were non-linear. This study confirms that in music, and potentially in other occupational fields where performance relies on specific competences, domain relevant characteristics may be better predictors of engagement and creative achievement than broad traits.
... The most straightforward interpretation of these results is that variation in eminence, much like the extremes of more conventionally measured dimensions of individual differences (such as IQ), is mostly influenced by additive genetic variation, which in turn is consistent with existing knowledge of the basis of normal-range phenotypic variance in many traits believed to contribute in part to eminence (again, such as IQ; Shakesharf et al., 2015). Congruent with this, Roeling et al. (2016) estimated that the additive heritability of working in a creative profession (a potentially more normalrange manifestation of the sorts of phenotypes that contribute to 'eminence') is .70. Further, and interestingly, they found that the best-fitting model in their dataset was one estimating only A and E variances. ...
By merging analytical approaches from the fields of historiometrics and behavior genetics, a social pedigree-based estimate of the heritability of eminence is generated. Eminent individuals are identified using the Pantheon dataset. A single super-pedigree, comprised of four prominent and interrelated families (including the Wedgwood–Darwin, Arnold–Huxley, Keynes-Baha’u’lláh, and Benn-Rutherford pedigrees) is assembled, containing 30 eminent individuals out of 301 in total. Each eminent individual in the super-pedigree is assigned a relative measure of historical eminence (scaled from 1 to 100) with noneminent individuals assigned a score of 0. Utilizing a Bayesian pedigree-based heritability estimation procedure employing an informed prior, an additive heritability of eminence of .507 (95% CI [.434, .578]) was found. The finding that eminence is additively heritable is consistent with expectations from behavior-genetic studies of factors that are thought to underlie extraordinary accomplishment, which indicate that they are substantially additively heritable. Owing to the limited types of intermarriage present in the data, it was not possible to estimate the impact of nonadditive genetic contributions to heritability. Gene-by-environment interactions could not be estimated in the present analysis either; therefore, the finding that eminence is simply a function of additive genetic and nonshared environmental variance should be interpreted cautiously.
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Cultural innovations, such as tools and other technical articles useful for survival, imply that creativity is an outcome of evolution. However, the existence of purely ornamental items obfuscates the functional value of creativity. What is the functional or adaptive value of aesthetic and intellectual ornaments? Recent evidence shows a connection between ornamental creativity, an individual’s attractiveness, and their reproductive success. However, this association is not sufficient for establishing that creativity in humans evolved by sexual selection. In this critical review, we synthesize findings from many disciplines about the mechanisms, ontogeny, phylogeny, and the function of creativity in sexual selection. Existing research indicates that creativity has the characteristics expected of a trait evolved by sexual selection: genetic basis, sexual dimorphism, wider variety in males, influence of sex hormones, dysfunctional expressions, an advantage in mating in humans and other animals, and psychological modules adapted to mating contexts. Future studies should investigate mixed findings in the existing literature, such as creativity not being found particularly attractive in a non-WEIRD society. Moreover, we identified remaining knowledge gaps and recommend that further research should be undertaken in the following areas: sexual and reproductive correlates of creativity in non-WEIRD societies, relationship between androgens, development, and creative expression, as well as the impact of ornamental, technical and everyday creativity on attractiveness. Evolutionary research should analyze whether being an evolved signal of genetic quality is the only way in which creativity becomes sexually selected and therefore passed on from generation to generation. This review has gone a long way toward integrating and enhancing our understanding of ornamental creativity as a possible sexual selected psychological trait.
In this chapter, we address the question whether individuals born from a multiple pregnancy differ from singletons. The answer to this question is important for health-care professionals and researchers, as well as multiples themselves and their family members. First, we review findings from the literature with respect to twin – non-twin differences in early life and conclude that a multiple pregnancy increases the risk of congenital problems and mortality for the unborn and newborn children. Next, we provide an overview of the outcomes of comparing adult twins to their singleton siblings across a wide range of traits assessed in the Netherlands Twin Register (NTR). In a within-family design, comparing twins to siblings from the same family, we correct for familial confounding. Overall, hardly any evidence was found for the presence of twin-sibling differences for the five domains explored, which included body composition and physical development, personality and psychopathology, behavioral and sociodemographic traits, physiological parameters and physical disease, and cognitive function. With the exception of minor differences in body composition, twins do not seem to differ from singletons, when taking family factors into account. In conclusion, while being a twin can be seen as special, adult twins are similar to ordinary siblings across most domains of life.
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This multitrait multimethod twin study examined the structure and sources of individual differences in creativity. According to different theoretical and metrological perspectives, as well as suggestions based on previous research, we expected 2 aspects of individual differences, which can be described as perceived creativity and creative test performance. We hypothesized that perceived creativity, reflecting typical creative thinking and behavior, should be linked to specific personality traits, whereas test creativity, reflecting maximum task-related creative performance, should show specific associations with cognitive abilities. Moreover, we tested whether genetic variance in intelligence and personality traits account for the genetic component of creativity. Multiple-rater and multimethod data (self- and peer reports, observer ratings, and test scores) from 2 German twin studies-the Bielefeld Longitudinal Study of Adult Twins and the German Observational Study of Adult Twins-were analyzed. Confirmatory factor analyses yielded the expected 2 correlated aspects of creativity. Perceived creativity showed links to openness to experience and extraversion, whereas tested figural creativity was associated with intelligence and also with openness. Multivariate behavioral genetic analyses indicated that the heritability of tested figural creativity could be accounted for by the genetic component of intelligence and openness, whereas a substantial genetic component in perceived creativity could not be explained. A primary source of individual differences in creativity was due to environmental influences, even after controlling for random error and method variance. The findings are discussed in terms of the multifaceted nature and construct validity of creativity as an individual characteristic. (PsycINFO Database Record
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We tested whether polygenic risk scores for schizophrenia and bipolar disorder would predict creativity. Higher scores were associated with artistic society membership or creative profession in both Icelandic (P = 5.2 × 10−6 and 3.8 × 10−6 for schizophrenia and bipolar disorder scores, respectively) and replication cohorts (P = 0.0021 and 0.00086). This could not be accounted for by increased relatedness between creative individuals and those with psychoses, indicating that creativity and psychosis share genetic roots.
Creativity is considered a positive personal trait. However, highly creative people have demonstrated elevated risk for certain forms of psychopathology, including mood disorders, schizophrenia spectrum disorders, and alcoholism. A model of shared vulnerability explains the relation between creativity and psychopathology. This model, supported by recent findings from neuroscience and molecular genetics, suggests that the biological determinants conferring risk for psychopathology interact with protective cognitive factors to enhance creative ideation. Elements of shared vulnerability include cognitive disinhibition (which allows more stimuli into conscious awareness), an attentional style driven by novelty salience, and neural hyperconnectivity that may increase associations among disparate stimuli. These vulnerabilities interact with superior meta-cognitive protective factors, such as high IQ, increased working memory capacity, and enhanced cognitive flexibility, to enlarge the range and depth of stimuli available in conscious awareness to be manipulated and combined to form novel and original ideas.
Preface. List of Figures. List of Tables. 1. The Scope of Genetic Analyses. 2. Data Summary. 3. Biometrical Genetics. 4. Matrix Algebra. 5. Path Analysis and Structural Equations. 6. LISREL Models and Methods. 7. Model Fitting Functions and Optimization. 8. Univariate Analysis. 9. Power and Sample Size. 10. Social Interaction. 11. Sex Limitation and GE Interaction. 12. Multivariate Analysis. 13. Direction of Causation. 14. Repeated Measures. 15. Longitudinal Mean Trends. 16. Observer Ratings. 17. Assortment and Cultural Transmission. 18. Future Directions. Appendices: A. List of Participants. B. The Greek Alphabet. C. LISREL Scripts for Univariate Models. D. LISREL Script for Power Calculation. E. LISREL Scripts for Multivariate Models. F. LISREL Script for Sibling Interaction Model. G. LISREL Scripts for Sex and GE Interaction. H. LISREL Script for Rater Bias Model. I. LISREL Scripts for Direction of Causation. J. LISREL Script and Data for Simplex Model. K. LISREL Scripts for Assortment Models. Bibliography. Index.
Cultural traits originate through creative or innovative processes, which might be crucial to understanding how culture evolves and accumulates. However, because of its complexity and apparent subjectivity, creativity has remained largely unexplored as the dynamic underpinning of cultural evolution. Here, we explore the approach to innovation commonly taken in theoretical studies of cultural evolution and discuss its limitations. Drawing insights from cognitive science, psychology, archeology, and even animal behavior, it is possible to generate a formal description of creativity and to incorporate a dynamic theory of creativity into models of cultural evolution. We discuss the implications of such models for our understanding of the archaeological record and the history of hominid culture.