Personality and Thinking Style in Different Creative Domains

Chiara Simone HallerUniversity of Bern, Switzerland

Delphine Sophie CourvoisierUniversity of Geneva and Geneva University Hospitals,

Switzerland

The crucial aspect of creativity in both personality and thinking style may be the ability or tendency tochange within personality traits, such as, for example, moving between extraversion and introversion, andwithin thinking styles, such as moving between heuristic and algorithmic thinking. Such mobility ischaracteristic of the “complex” personality. On personality and thinking style tests, complexity would beexpected to manifest itself in greater variability of responses to items measuring the same overall trait.This issue was investigated with 158 visual art, 136 music, and 309 psychology students. Art students(visual art and music students) showed greater complexity in conscientiousness than psychology andmusic students, respectively. Visual art students further showed a greater overall complexity (meancomplexities across personality and thinking style) than psychology students did. A more traditionalanalysis revealed that visual art students were more neurotic, more open to experience and more inclinedto heuristic thinking than psychology students do, whereas music students were more extraverted andmore agreeable than visual art students were, and more inclined to heuristic thinking than psychologystudents were. Thus, it was possible to distinguish visual art students from music and psychology studentsby their personality and thinking style.

Keywords: creativity, personality, thinking style, complexity

Since the 1950s, many studies have examined the link betweencreativity and personality (e.g., Barron & Harrington, 1981; Csik-szentmihalyi, 1996; Dellas & Gaier, 1970; Drevdahl & Cattell,1958; Eysenck, 1992, 1993; Farisha, 1978; Feist, 1998). As aresult, the list of traits found to occur commonly in creativeindividuals has become more exact, precise, and encompassing.Traits that have been identified are, among others, tolerance ofambiguity, autonomy, intrinsic motivation, and openness to expe-rience.

A large number of personality characteristics have also beenconnected with aesthetic preferences, such as the Big Three(Eysenck, 1988, 1992), and the Big Five (Costa & McCrae, 1992).Although creativity has the strongest relationship with openness toexperience, research has connected all of the NEO-FFI dimensionsto creativity: Neuroticism (e.g., Kemp, 1981b; Marchant-Haycox& Wilson, 1992), conscientiousness or rather a lack of it (e.g.,Getzels & Csikszentmihalyi, 1976; Kemp, 1981b; Shelton & Har-ris, 1979; Walker, Koestner, & Hum, 1995), introversion (e.g.,Busse & Mansfield, 1984; MacKinnon, 1978; Roco, 1993), as well

as a lack of agreeableness (e.g., Dudek, Berneche, Berube, &Royer, 1991; Eysenck, 1995; Getzels & Csikszentmihalyi, 1976).

One area in which there has been longstanding interest is thepersonality of artists (e.g., Burt, 1933); most studies involving artstudents (e.g., Munsterberg & Mussen, 1953; Shelton & Harris,1979). Many of the studies were concerned with paintings (e.g.,Tobycyck, Myers, & Bailey, 1981; Zaleski, 1984), and differentstyles of painting (e.g., Furnham & Avison, 1997; Rawlings,Barrantes-Vidal, & Furnham, 2000). Other studies focused onmusic (e.g., Glasgow, Cartier, & Wilson, 1985; Little & Zucker-man, 1986), and investigated the creative potential of musicians(e.g., Charyton & Snelbecker, 2007); musicians have also beencompared with nonmusicians (e.g., Kemp, 1981b; Marchant-Haycox & Wilson, 1992; Pavitra, Chandrashekar, & Choudhurry,2007), or scientists (e.g., Charyton & Senelbecker, 2007), whereasmale musicians have been compared with woman musicians (e.g.,Buttsworth & Smith, 1995; Kemp, 1982).

Investigations have also involved differences among musiciansplaying different instruments (e.g., Davies, 1976; Kemp, 1981a;Wilson, 1994) and among different groups of instrumentalists(e.g., Kemp, 1981b; Langendorfer, 2008; Motte-Haber, 2005).Kemp (1996) found differences between string players and othermusicians in an orchestra on the personality trait of reluctance, ascale of Cattell’s 16PF instrument. Bell and Cresswell (1984)found that string players are more often worried, are less antago-nistic, more conscientious, and control themselves more often.Woodwind instrumentalists, on the other hand, are more extra-verted according to Kemp, and control themselves less. Kemp alsofound that keyboard players seem to be more introverted, whereassingers are more extraverted, independent, and sensitive. However,all of the named studies compared instrumentalists in their studentyears. Therefore, Langendorfer (2008) compared instrumentalists

Chiara Simone Haller, University of Bern, Switzerland; DelphineSophie Courvoisier, University of Geneva and Geneva University Hospi-tals, Switzerland.

We thank all participants who volunteered in this study; R. Brotbeck, M.Eidenbenz, and C. Swanepoel who agreed to distribute the link of thehomepage to all of their students; R. Groner, who supported our investi-gation; D. Stricker who installed the homepage and all the others we havenot mentioned by name. Profound thanks to Arthur Cropley for his supportand his valuable advice.

Correspondence concerning this article should be addressed to ChiaraSimone Haller, Falkenweg 15, 3012 Bern, Switzerland. E-mail: chiarahaller@gmail.com

Psychology of Aesthetics, Creativity, and the Arts © 2010 American Psychological Association2010, Vol. 4, No. 3, 149–160 1931-3896/10/$12.00 DOI: 10.1037/a0017084

149

of six professional orchestras. She found that string players hadsignificantly higher scores on conscientiousness than woodwindand brass players, the woodwind being the least conscientious. Thebrass players scored higher on socially prescribed perfectionismthan the woodwind players. For other personality traits, no signif-icant differences were found.

Despite the existence of such findings, some authors who at-tempted to connect the NEO-FFI dimensions to creativity found norelationship (e.g., Dollinger & Clancy, 1993; McCrae, 1987).Indeed, Helson (1996) concluded that there is no single homoge-neous set of personality characteristics that is typical of all creativeindividuals and differentiates them as a group from less creativepeople. However, one phenomenon that some researchers havenoted among creative individuals is the aggregation of conflictingattributes in the same person. This was referred to by McMullan(1978, p. 265) as involving a “paradox.” According to him, thecreative personality is characterized by seven “polarities”:

• Openness versus drive to complete incomplete gestalts• High level of fantasy versus strong sense of reality• Destructive versus constructive attitudes• Cool neutrality versus passionate engagement• Self-centeredness versus altruism• Self-doubt versus self-confidence• Tension versus relaxedness

Cropley (1997, p. 8) expanded McMullan’s list and referred tothe creative personality as “a bundle of paradoxes.” Csikszentmi-halyi (1996) made a similar point, when he emphasized the im-portance in creativity of a “complex” personality combining, forinstance, toughness and sensitivity. As Csikszentmihalyi (1996, p.47) wrote it:

. . . they show tendencies of thought and action that in most people aresegregated. They contain contradictory extremes—instead of being“an individual,” each of them is a “multitude”. Like the color whitethat includes all the hues in the spectrum, they tend to bring togetherthe entire range of human possibilities within themselves.

Thus, the special quality of creative people as a group may notbe a specific profile of personality, but greater “complexity” inpersonality: The creative individual may be able to fluctuate be-tween apparently contradictory poles such as selfishness versusaltruism or acceptance of fantasy versus rigid realism.

Csikszentmihalyi (1996) argued that complexity is presentwithin all of us, but that people often develop a strong preferencefor one pole of the continuum—usually the one that is regarded as“good” in the particular setting in which they live—whereas the“bad” pole is inhibited. Thus, most people tend consistently towardone end of each personality continuum, according to the prefer-ences of the environment in which they live, whereas creativity “[. . .] involves the ability to move from one extreme to the other asthe occasion requires” (Csikszentmihalyi, 1996, p. 57). Sticking toa particular set of traits that are highly approved in one’s socialmilieu not only wins the approval of most other people but alsomakes the surrounding world more easily understandable andpredictable, that is, it makes getting along easy, although the priceis conformity.

Most of the studies described in previous paragraphs supposedthat artists differed from others in that they were “more” of

something: more extraverted, for instance, or more open. In otherwords, the studies examined mean differences on various dimen-sions between groups of artists and contrasting groups. Fleeson(2001), however, postulated that there must be variability withinevery person for the different NEO-FFI dimensions, and thisvariability must be measurable, and stable. Some people may bemore variable in their reactions to personality tests, and some traitsmay show greater variability. Looking at the big five personalitytraits, Fleeson found that long-term variability is greatest forextraversion, less for neuroticism, openness to experience, andconscientiousness, and smallest for agreeableness. Thus, he turnedattention to the issue not of differences in means of scale scores orindividual items, but of variability in the way, people answer testitems that all measure the same trait.

This approach is easily reconcilable with the idea of complexity.By virtue of being more “complex,” creative people would beinconsistent in responding to test items, sometimes tending towardone pole of the trait being measured, but in the case of other itemschoosing the opposite pole. Thus, the indicator of complexity andtherefore creativity in personality tests would not be mean scoresbut a measure of the variability of responses.

Although creativity has often been linked with personality,many psychologists have been more interested in cognitiveprocesses and have compared creativity with problem solving(Flavell & Draguns, 1957; Guilford, 1967; Kaufmann, 1988;Klahr, 2000; Klahr & Simon, 1999). However, creative indi-viduals often work in domains where problems have not yetbeen specified, which make their success dependent on theformulation of a new problem (Beittel & Burkhart, 1963; Csik-szentmihalyi, 1965; Getzels, 1964; Mackworth, 1965). In otherwords, from a cognitive point of view, creativity may be moredependent on problem finding than on problem solving (Saw-yer, 2006; Sternberg, 1985; Weisberg, 2006). Problem solvingcan be approached with algorithms (Bowden & Beeman, 1998;Schooler, Ohlsson, & Brooks, 1993). Algorithms are well-defined sequences of operations that guarantee a solution. Theysuppose a systematic progression from the actual condition tothe target state for a specific class of problem (e.g., algebra).Heuristics, on the other hand, are rules for finding solutions;they do not guarantee a solution but they help to find it (Newell& Simon, 1972). According to Amabile (1983, 1996), to becreative, a task cannot be algorithmic. An algorithmic task isone for which “the solution is clear and straightforward”whereas a creative task is one “not having a clear and readilyidentifiable path to the solution” (Amabile, 1996, p. 35). Thus,a new algorithm has to be created before the task can beterminated.

As Runco (2008) argued, assessing creativity with divergentthinking tests (e.g., McCrae, 1987) is unfairly limited since there ismuch more to creativity than the cognitive process of creativity.Problem-finding or heuristic thinking may be one important ingre-dient to become or be creative, rather than define creativity itself.Furthermore, different domains probably ask for different thinkingstyles to become creative in this specific domain. Although prob-lem finding may be more consistently related to creativity (e.g.,Amabile, 1996), different creative domains should be investigatedin accordance to the differences in the proportion of algorithmicversus heuristic thinking between domains.

150 HALLER AND COURVOISIER

Differences Among Groups

One approach to investigating creativity and personality hasfocused on what Cropley (2001, p. 53) called “occupational cre-ativity”: Certain occupations are regarded as inherently creative,such as musician, artist, novelist, or actor. Cropley listed severalexamples of research on occupational creativity, starting with Roe(1953) and Cattell and Drevdahl (1955). One question that hasbeen asked in this type of research is whether there are psycho-logical differences between people in different “creative” occupa-tions: for example, whether visual artists are psychologically dif-ferent from musicians, despite the fact that both groups areengaged in inherently creative occupations. Following this ap-proach, the purpose of the research described in this article was todetermine if and how visual art, music, and psychology studentsdiffer from each other with respect to personality and thinkingstyle.

Earlier studies often compared artists with nonartists, the term“artist” usually referring to a mixture of visual artists and musi-cians. This aggregation of two very different types of artists maybe inappropriate. Thus, we examined the differences betweenmusicians, visual art students and nonartists, namely psychologystudents. We also investigated the differences between visual artand music students. Two kinds of differences were examined:differences in level of various personality and thinking style vari-ables (mean differences) and differences in the complexity ofanswers. Furthermore, mean and complexity differences betweenmusic students playing different instruments were also investi-gated.

Method

Participants. Participants were recruited in 2008 at the Uni-versities of the Arts in Zurich and Bern, Switzerland, and at theUniversity of Psychology in Bern, Switzerland. They were in-formed of the link to the homepage that hosted the questionnaires.A total of 633 students responded (158 visual art students and 136music students from the Zurich and Bern University of the Artsand 324 psychology students from the University of Bern). A totalof 24 psychology students were excluded because of missing data.The mean age of the visual art students was 26.25 (SD: 5.28) yearsand 72.8% were women. The mean age of the music students was23.93 years (SD: 4.77) with 61.8% women, and the mean age ofthe psychology students was 25.52 (SD: 8.60) and 76.2% werewomen. The music students belonged to four different instrumen-tal categories: 29 Chant (82.8% women), 23 keyboard or percus-sion instrument (56.5% women), 45 string or plucked instrument(46.4% women), and 39 wind instrument (46.2% women).

Materials. Participants completed the German computer ver-sion of the 60-item NEO-FFI of Costa and McCrae (1992) byBorkenau and Ostendorf (1993) as well as the short computerversion of the Heuristic Questionnaire (Groner & Groner, 1990).The NEO-FFI is a 60-item inventory assessing 30 specific facetsthat define five personality factors or domains. Items are answeredon a 5-point Likert scale ranging from strongly disagree (coded 0)to strongly agree (coded 4). This questionnaire has high internalconsistency for all dimensions: neuroticism (� � .85), extraver-sion (� � .80), openness to experience (� � .71), agreeableness(� � .71), and conscientiousness (� � .85). The Heuristic Ques-

tionnaire is a 30-item inventory assessing algorithmic and heuristicthinking styles. Items are answered on a 4-point Likert scaleranging from not at all (coded 0) to exactly (coded 3). Theheuristic questionnaire was originally published by Groner andGroner, 1990 (see the Appendix). Groner and Groner did notprovide information on the internal consistency in the originalmanuscript. However, they conducted a factor analysis thatshowed that 67% of the variance was explained by 17 items,loading on one factor. The two poles (algorithmic vs. heuristicthinking) were based on factor scores. Instruments were adminis-tered and scored according to the standard directions given in themanuals (Borkenau & Ostendorf, 1993; Groner & Groner, 1990).Demographic data (age, sex, university, and section) were alsocollected.

Analysis. We first verified the reliability of all scales usingCronbach’s alpha. Analyses were carried out using SPSS 16.0. Wethen computed means and complexities (see below for an expla-nation of how complexity was calculated) for each of the fivedimensions of the NEO-FFI and on the heuristic questionnaire,yielding 12 variables.

Complexity was operationalized by investigating the variabilityin the way each individual person answered each personality andthinking style items. A person displaying a high level of complex-ity would give answers scattered across the complete range ofalternatives for responding to the items of a particular personalityor thinking style dimension, possibly agreeing strongly with someitems but disagreeing strongly with others referring to the samepersonality dimension. A person displaying a low level of com-plexity would tend to answer homogeneously, for instance possi-bly agreeing (or disagreeing) strongly with nearly all items. Thesecond person could therefore obtain a higher mean for the scale inquestion, but obtain a much lower standard deviation for the scale.Such a person would be said to have a less “complex” personality.It could also be that people might obtain similar means, but oneperson might answer homogenously whereas the other might agreewith some items and disagrees with others. Again, the secondperson would display greater complexity. Thus, the individualrespondent’s variability in responding to items on a scale that referto the same construct would be an indicator of complexity. Be-cause there are more easy, and more difficult items on a dimension(because there are no right or wrong answers on a personality test,the terms “easy” and “difficult” are used here in the psychometricsense to refer to responses across participants clustering at one endof the range of possible answers), relative item difficulty has to betaken into account. Thus, for a given dimension, complexity re-flects both the variability within individuals and the difficulty ofeach item:

��i�1

n�xij � �x� .j � �x� i. � x� ..���

2

n � 1

where xij refers to the individual value of a person j on an item i.x� .j refers to the mean of a person j over all items of a dimension.x� i. refers to the mean of all the people for a specific item i of adimension, x� .. refers to the global mean of all individuals over allitems of a dimension, and n refers to the number of items of adimension. A person with high complexity will have a largedifference between his or her answer to a specific item and his or

151COMPLEXITY AS AN INDICATOR

her mean on the dimension (xij � x� .j). However, this does not takeinto account easier or more difficult items. Therefore, relative itemdifficulty was taken into account by adding the relative difficultyof the items ( x� i. � x� ..) to the mean of the person j over the items.

Mean differences were examined using MANOVA with the sixmeans as dependent variables and type of study (art, music, orpsychology) as independent variable. Analyses were adjusted forgender because the gender distributions in the groups of studentswere different (�2 � 8.57, p � .01). However, they were notadjusted for age, since there was very little age variation amongstudents. Subsequent analyses considered each dependent variableseparately using ANOVAs. The differences between participantswithin each area of studies (visual arts, music, psychology) wereanalyzed using multiple comparisons (post hoc analysis) withScheffe’s correction for multiple tests. Finally, within music stu-dents, the relationships between type of instrument and personalityand thinking style were examined using multiple comparisons.

Complexity differences were investigated similarly to mean-level differences. MANOVA was run with the six mean complex-ities as dependent variables and type of study (art, music, orpsychology) as independent variable. Again, scores were adjustedfor sex, subsequent analyses for every dependent variable usedANOVAs, and differences between type of study were tested withmultiple comparisons using Scheffe’s correction for multiple tests.To verify the significant results, further analyses were conducted atthe item level. We first calculated mean differences for the inde-pendent variable “type of study” over all items to verify whetherstudents of one group scored lower on some items, higher onothers. Second, we calculated differences in variance over all ofthe items to find out whether students within groups differedgreatly within each item. Furthermore, correlations among thecomplexity scores for the six dependent variables were calculated.This was done to find out whether there is a general new trait ofcomplexity, which could be added as another dependent variable

with six different facets (complexity on all of the NEO-FFI di-mensions, and the thinking style questionnaire). Because the cor-relations were highly significant, we carried out a factor analysisfor verification. We then computed the mean of all complexitiesand compared the different groups according to the new dependentvariable “overall complexity.”

Results

Reliability

Reliabilities for all the NEO-FFI dimensions were consistentwith those in the manual (see Borkenau & Ostendorf, 1993).Cronbach’s alpha for Neuroticism was .82, for Extraversion .78,for Openness to experience .69, for Agreeableness .70, for Con-scientiousness .83. For thinking style, Cronbach’s alpha was .76(.74 for visual arts, .78 for music, .75 for psychology students),item-total correlations were good and comparable to the ones inthe manual. Finally, for complexity, Cronbach’s alpha across allsix complexity scores (personality and thinking style) was .82 forvisual art, .74 for music, and .84 for psychology students.

Mean-Level Differences

When all personality and thinking style were considered to-gether (MANOVA), they differed significantly across type ofstudies ( p � .001). Subsequent ANOVAs showed that visual artstudents, as compared to psychology students, had significantlyhigher mean neuroticism and mean openness to experience, andsignificantly lower mean extraversion, agreeableness, and consci-entiousness than psychology students (see Table 1). Visual artstudents also differed significantly from music students: they wereless extraverted (mean difference: �0.21, p � .01) and less agree-able (mean difference: �0.19, p � .01) than music students.

Table 1Mean-Level Differences on Personality and Thinking Style by Type of Studies, Adjusted for Sex

Dependent variable Type of studies Mean Mean difference p-value Adjusted R2

CI95%

Low High

Neuroticism Psychology 1.70 �0.001 0.05Visual arts 1.95� 0.25 0.10 0.40Music 1.78 0.08 �0.08 0.24

Extraversion Psychology 2.50 �0.001 0.06Visual arts 2.31� �0.18 �0.30 �0.06Music 2.52 0.02 �0.10 0.15

Openness Psychology 2.78 �0.001 0.03Visual arts 2.95� 0.17 0.06 0.28Music 2.85 0.08 �0.05 0.20

Agreeableness Psychology 2.72 �0.001 0.04Visual arts 2.55� �0.18 �0.28 �0.07Music 2.74 0.01 �0.10 0.13

Conscientiousness Psychology 2.64 �0.001 0.04Visual arts 2.39� �0.24 �0.38 �0.10Music 2.56 �0.08 �0.23 0.07

Thinking style Psychology 0.35 �0.001 0.04Visual arts 0.51� 0.16 0.08 0.24Music 0.44� 0.09 0.01 0.17

� p � .01.

152 HALLER AND COURVOISIER

Finally, music students did not differ from psychology students onany dimension of personality. In terms of thinking style, visual artstudents, and music students were significantly more heuristicoriented than psychology students, respectively, but the differencewas numerically greater for visual art, than for music students(nonsignificant).

Complexity Differences

When all personality and thinking style were considered to-gether (MANOVA), they did differ significantly across type ofstudies only on conscientiousness ( p � .001). SubsequentANOVAs showed that Complexity of personality and thinkingstyle differed significantly across type of studies on conscientious-ness ( p � .01), in that visual art students showed greater com-plexity than psychology students (see Table 2), as well as greatercomplexity than music students (mean difference: 0.08, p � .05).Figure 1 shows the means and variance of scores across studentsby item and by type of study. The top panel shows that means donot seem to differ so greatly between items, and visual art studentsare almost consistently lower than both music and psychologystudents. The bottom panel of Figure 1 shows the between-subjectsvariance for each item. The variance is higher for visual artstudents, than for psychology students on 10 items, and than musicstudents on nine items. Thus, visual art students are not only morecomplex (intraindividual variability), they are also more variableamong other students (interindividual variability).

Correlations among all the complexities were all significant (seeTable 3). Factor analysis indicated unidimensionality, in that allthe complexities loaded on one factor (explained variance � 53%).Principal component analysis showed the following factor load-ings for the different complexities: Neuroticism � 0.79, extraver-sion � 0.74, openness to experience � 0.68, Agreeableness �0.78, Conscientiousness � 0.73, and thinking style � 0.62. There-fore, we calculated ANOVA with the mean of the different Com-

plexities (as a measure of overall complexity) as dependent vari-able, and sex as covariate. Differences between people in each areaof study were analyzed using multiple comparisons with Scheffe’scorrection for multiple tests. Results indicated that visual art stu-dents showed significantly greater complexity than psychologystudents overall (mean difference: 0.04, p � .05).

Mean and Complexity Differences AcrossInstrumental Families

Mean and complexity of personality and thinking style did notdiffer significantly across instrumental family for either all depen-dent variables considered together ( p � .18 for mean-level differ-ences; p � .22 for complexity differences), or for each dependentvariable considered separately (data not shown).

Discussion

Mean-Level Differences

The mean differences on neuroticism showed that art studentsdescribe themselves as being more often distressed and sad, andalso as having more unrealistic ideas, whereas psychology studentsdescribe themselves as being rather calm, carefree, and balanced.Because in the present study, personality was not actually relatedto a creativity measurement instrument, we can only assume that inthe profession of visual art, but not music or psychology, peopleare more likely to be emotionally unstable. However, Gotz andGotz (1979) found that neuroticism was positively related tocreativity in the arts but negatively related to creativity in thesciences.

In a more recent study, Feist and Barron (2003) found artists tobe less emotionally stable, cold, and rejecting of group normscompared with scientists. Pavitra, Chandrashekar, and Choudhury(2007), who investigated the NEO-FFI among writers, musicians,

Table 2Complexity Differences on Personality and Thinking Style by Type of Studies, Adjusted for Sex

Dependent variable Type of studies Mean Mean difference p-value Adjusted R2

CI95%

Low High

Neuroticism Psychology 0.99 0.00Visual arts 1.04 0.05 0.13 �0.11 0.01Music 1.00 0.01 0.96 �0.08 0.06

Extraversion Psychology 1.18 0.00Visual arts 1.17 �0.01 0.89 �0.05 0.08Music 1.19 0.00 0.99 �0.07 0.06

Openness Psychology 1.05 0.00Visual arts 1.05 0.00 1.00 �0.07 0.07Music 1.07 0.01 0.93 �0.08 0.06

Agreeableness Psychology 1.13 0.01Visual arts 1.17 0.04 0.36 �0.11 0.03Music 1.17 0.04 0.44 �0.11 0.03

Conscientiousness Psychology 1.05 0.05Visual arts 1.19� 0.14 0.00 �0.21 �0.08Music 0.11 0.06 0.10 �0.13 0.01

Thinking style Psychology 2.82 0.02Visual arts 2.84 0.02 0.72 �0.08 0.04Music 2.79 �0.03 0.43 �0.03 0.08

� p � .01.

153COMPLEXITY AS AN INDICATOR

and controls, found significant differences between the first twogroups and the control group. Musicians and writers scored higheron neuroticism than did controls, whereas no significant differencewas found between musicians and writers. One explanation for theresult of the present study could be that visual art students needtheir unrealistic ideas to create new products during their studies,whereas psychology, as well as music, students seem to mostlyaccrue knowledge (psychology) or technical ability (music), atleast during student years. Indeed, Universities of the Arts focusmore on the creative process, rather than on functional creativity,whereas Universities of Music focus on technical ability (at leastfor instrumentalists), as well as performance, and Universities ofScience focus on gaining knowledge. Therefore, people who show

less emotional stability might choose to be visual artists rather thanmusicians or psychologists.

The mean differences on extraversion show that psychology andmusic students defined themselves as more companionable, active,communicative, energetic, cheerful, and optimistic than visual artstudents. Thus, visual art students seem to be more introverted(e.g., Bachtold & Werner, 1973; Busse & Mansfield, 1984). Feist(1998) found that creative scientists and artists were less extra-verted than their noncreative counterparts were. Pavitra, Chan-drashekar, and Choudhury (2007) found musicians to be moreextraverted than a noncreative control group. It must be noted,however, that they did not investigate creativity with a test, butmainly assumed that musicians are more creative than controls. Bycontrast, in the present sample, musicians and psychologists aremore extraverted than visual art students do. Thus, the threedomains seem to require different personality profiles, and musicand visual art students should not be lumped together under thelabel “artist.” It can be further assumed that people choose adomain that fits their personality profile, because personality hasbeen found to be stable (e.g., Caspi & Roberts, 2001; Caspi,Roberts, & Shiner, 2005; Lehnart & Neyer, 2006). People whoprefer external or highly varied stimuli (known to characterizehigh scorers on extraversion) are possibly more attracted by pro-fessions such as music and psychology, whereas introverted peoplemight chose a profession such as visual art, where they can usetheir capacity to focus inward.

On the dimension of agreeableness, similar to the dimension ofextraversion, psychology and music students both showed signif-icantly higher scores than visual art students. This means that

Figure 1. Mean and variance of conscientiousness items.

Table 3Pearson Correlation Matrix for Complexities on All of theDependent Variables

N E O A CThinking

style

N 0.22�� 0.27�� 0.33�� 0.20�� 0.11��

E 0.17�� 0.24�� 0.21�� 0.09�

O 0.28�� 0.16�� 0.20��

A 0.30�� 0.30��

C 0.15��

Thinkingstyle

� p � .05 (two-tailed). �� p � .01 (two-tailed).

154 HALLER AND COURVOISIER

psychology and music students described themselves as facingothers with appreciation, benevolence, and compassion more oftenthan visual art students, and as liking harmony in relationships.Visual art students, on the other hand, described themselves asbeing more antagonistic, egocentric, and as behaving less cooper-atively. Agreeableness is the dimension with the most unclearrelationship to creativity. This may be because of the fact thatvisual art students often want to work alone, and thus do not needto interact with others as much (Guncer & Oral, 1993), or do notwant to interact with others (Gridley, 2007; McKinnon, 1975).Indeed, Guncer, and Oral (1993) argued that creative people havea less agreeable but more independent perspective and do not placemuch importance on social conformity. King, McKee, Walker, andBroyles (1996) on the other hand, failed to find any significantcorrelation between agreeableness and creativity, and Walker,Koestner, and Hum (1995) found creative achievers to be moreagreeable than noncreative achievers. Pavitra, Chandrashekar, andChoudhury (2007), for example, found musicians to be moreagreeable than members of a control group.

Visual art students scored significantly higher on openness toexperience than psychology students, which is consistent with theresults of Feist (1998), Chamorro-Premuzic (2006), and Costa andMcCrae (1997). They described themselves as being visionary,keen to experiment, and behaving unconventionally. Openness toexperience is the dimension most closely related to ego develop-ment (Einstein & Lanning, 1998; McCrae & Costa, 1980), identityexploration (Clancy & Dollinger, 1993; Tesch & Cameron, 1987)and creativity (e.g., McCrae, 1987). Soldz and Vaillant (1999), forexample, found that openness to experience is the best predictor oflife course creativity, 45 years after the original investigation. Feist(1998) found that creative scientists and artists are more open toexperience than their noncreative counterparts were. Costa andMcCrae (1997) postulate that high openness is a characteristic ofartists: “As neurotics can be used as exemplars of high scores onthe dimension of Neuroticism, so artists can be considered primeexamples of individuals high in Openness to experience” (p. 825).However, their postulate is only partly confirmed, because musicstudents did not show significantly higher scores on openness toexperience than psychology students, and the term “artist” refers tomusic students as well as visual art students.

Gridley (2007) found that artists, compared to engineers, pre-ferred to work alone, to follow their own muse, and “input fromothers during the creation of an artwork is felt to accompany lossof integrity” (p. 179). This could be related to visual art students’lower levels of extraversion and agreeableness, as well as higherlevels of neuroticism. Engineers, on the other hand, like interactingwith others, since they have to create what is required by thepotential customer. This could be related to the higher scores foragreeableness of music and psychology students, as well as to theirhigher levels of extraversion.

Conscientiousness is a facet that plays an elusive role in cre-ativity. In the present sample, visual art students scored signifi-cantly lower than psychology students scored on conscientious-ness, meaning that psychology students described themselves asbeing determined, ambitious, busy, persistent, systematic, strong-minded, neat, and exact at times. McCrae (1987), who found astrong positive correlation between conscientiousness and creativ-ity, reasoned that conscientiousness helps individuals followthrough their creative undertakings. King, McKee, Walker, and

Broyles (1996) on the other hand, found a negative correlationbetween conscientiousness and creativity, which was underlinedby the findings of Gelade (1997, 2002). However, in the presentsample, visual art students differed significantly from psychologystudents, whereas there was no significant difference betweeneither music and psychology, or music and visual art students.Feist (1998) found creative scientists to be more conscientiousthan their noncreative counterparts, whereas he found artists to beless conscientious than their noncreative counterparts. He furtherfound that creative scientists are more likely to be conscientiousthan creative artists. This is consistent with the results ofChamorro-Premuzic (2006), who found that scientists who aremore conscientious will perform better later in their career,whereas conscientiousness is the best predictor of student perfor-mance in science (for an overview see Chamorro-Premuzic &Furnham, 2005). This could mean that, in the present sample, thereare creative scientists and creative visual art students too. Turningto differences between different groups of artists (music and visualart), the present results do not show significant differences.Pavitra, Chandrashekar, and Choudhury (2007) found musicians tobe more conscientious than noncreative controls. In the presentsample, however, music students’ mean levels seem to lie some-where between psychology, and visual art students. Thus, studyingpsychology at university seems to require people to be very con-scientious, whereas visual art students may need to be less strong-minded at times so that they can let their ideas flow, and musicstudents have a tendency to be more conscientious than visual artstudents, but less than psychology students do.

In terms of thinking style, visual art and music students, respec-tively, were significantly more heuristically oriented than psychol-ogy students. Music students, while more heuristically orientedthan psychology students, were slightly less so than visual artstudents (not statistically significant). As mentioned in the intro-duction, creativity should not only be defined or measured bydivergent thinking (e.g., Runco, 2008). The present thinking stylequestionnaire does not actually test divergent thinking, but asksindividuals whether they describe themselves as being prone tounconventional ideas, and risk taking (heuristic thinking) orwhether they like following well-defined steps (algorithmic think-ing). Visual art students may need to use a more heuristic orproblem-finding thinking style because they must create a newproduct every semester, whereas psychology students often need tounderstand and store new knowledge, using mostly pre-establishedalgorithms. Gridley (2007) compared visual artists to engineers onthe Intellectual Styles Questionnaire (ISQ; Sternberg & Wagner,1991), a self-administered questionnaire that is composed of self-descriptive sentences (as is the present thinking style question-naire). He found that visual artists are more likely to create theirown rules than are engineers, which “makes sense, because orig-inality is prized in art, and a preference for generating one’s ownplans is consistent with this value” (p. 179).

This result may be because of the expectations of each type ofprogram of studies. Jancke (2008) argued that musicians are morelikely to have well developed cognitive abilities, such as intelli-gence. Universities of the Arts nowadays, focus mostly on theheuristic, or problem-finding, style of thinking, which Sawyer(2006) cynically stated by saying that if you are a problem-solvingartists you have been born 200 years too late. Psychology studies,on the other hand, favor algorithmic thinking, following conven-

155COMPLEXITY AS AN INDICATOR

tions, and using exact rules that guarantee a solution. This meansthat people who see themselves as algorithmic thinkers mightfavor a scientific field rather than an artistic one.

Complexity Differences

Complexity differed significantly between visual art studentsand psychology and music students, respectively, only on consci-entiousness. There could be two interpretations of the high com-plexity of visual art students on conscientiousness. The first is thatstudents differ between items, that is, all visual art students wouldscore low on some items and high on others. This would implythat, for visual art students, the items of this subscale are notmeasuring a single construct (i.e., conscientiousness), and, withinsimilar items, they would have low complexity. The other possibleinterpretation is that visual artists differ greatly within each item.This would mean that visual art students are more “unique,” in thatthey answer the same question differently from student to student,whereas all psychology, and music students answer the samequestion in the same way. If the first interpretation is correct, weshould find low means on some items for the visual art studentsand high means for other items. On the other hand, if the secondinterpretation is correct, and visual art students differ more thanpsychology and music students within items do, we should seegreater variance on each item. We found results congruent with thesecond interpretation. The means of each item did not vary morefor visual art students than for other students but the variance washigher for visual art students than for other students on most items,and especially high for four items overall (Items 2, 5, 9, and 11).Indeed, visual art students differ more between each other on theirability to divide their time to finish their work (Item 2), have clearobjectives and work on them (Item 5), and being reliable (Items 9and 11) than psychology, and music students, respectively. Thismay be because of the fact that the domains of music, and psy-chology ask for people who are able to work on a topic andpractice to achieve a particular goal. The domain of visual art onthe other hand, might be more open to people who either are ableto divide their time to finish their work for example, but as well tothose who are not. This may be because of the fact that Univer-sities of the Arts focus the process of creativity, meaning differentaspects of the creative process are meant to be supported. Thus, itseems that there is more variability among visual art students (butwithin their area of study) than among psychology and musicstudents.

The remaining question is whether the conscientiousness scaleis still relevant for visual art students. In other words, is theconscientiousness scale really measuring one construct for thesestudents? Cronbach’s alpha showed that while reliability is lowerfor visual arts and music students than for psychology students, itis still good. Thus, the conscientiousness scale still measuresconscientiousness for visual art students but these students, whileeach answering the questionnaire in a coherent manner, differmore than psychology, and music students (a) among visual artstudents on each item, and (b) among items within the same visualart student. Thus, we could say that visual art students are more“unique” in their conscientiousness than psychology and musicstudents are. They switch more often between being very consci-entious on one hand and rather lazy on the other. These results areconsistent with Csikszentmihalyi’s (1996) hypothesis that:

. . . when necessary, they [creative people] can focus it[their energy]like a laser beam; when it is not, they immediately start rechargingtheir batteries. (p. 58)

Sternberg (1995) found a positive correlation between toleranceof ambiguity (that can be related to complexity) and scores on theMyers-Briggs Type Indicator Creativity Index (MBTI-CI; Ten-gano, 1990). He summarized the situation by saying “. . . one mustbe willing and able to tolerate at least some ambiguity in orderfully to manifest one’s creativity” (p. 143). Tolerance of ambiguitymeans people tolerate their ambiguous personality, or the ambi-guity of life. They recognize and manage the uncertainty in life(e.g., Mickler & Staudinger, 2008). In doing so, they may acceptthat they are for example conscientious, as well as lazy, switchingever so often. Thus, they actually tolerate their complexity. Moon(2001) postulates two faces of Conscientiousness, namely duty andachievement striving. Duty is associated with other-centered ori-entation, whereas achievement striving is associated with a self-centered orientation. This would be consistent with one ofMcMullan’s (1978) seven “polarities” mentioned in the introduc-tion, namely Self-centeredness versus Altruism.

Hough (1992) demonstrated that achievement striving was im-portant for job performance of managers but not for health carepeople. On the other hand, duty (or dependability) was importantfor the performance of health care workers but unimportant formanagers. According to those two facets, one would probablyexpect psychologists to score higher on duty, whereas visual artstudents would score higher on achievement striving. Becausecomplexity means being variable within a dimension, it is possiblethat visual art students are more likely than psychology or musicstudents to switch between the two facets postulated by Moon(2001; see also Dudley, Orvis, Lebiecki, & Cortina, 2006). Furtherresearch should investigate this possibility by examining differentfacets of conscientiousness among artists and nonartists.

One unexpected result of this study is the discovery of a singlecomplexity dimension. Factor loadings were sufficiently high tojustify the conclusion that there is a single, hitherto neglecteddimension called “complexity.” All the different complexitieswere then facets of this new dimension. Visual art students showedgreater overall complexity (mean complexity) than psychologystudents (but not music students). This result should be furtherinvestigated by measuring creativity and examining whether cre-ativity is related to general complexity.

Conclusion

The present study shows that the three domains investigated(psychology, visual art, and music) can be differentiated by per-sonality, thinking style, and complexity. Visual art student aremore neurotic, introverted, open to experience, less agreeable andmore prone to heuristic thinking than psychology students are.Music students are more extraverted and more agreeable thanvisual art students are, and more prone to heuristic thinking thanpsychology students are. This shows not only that social scientists(nonartists) can be differentiated from artists but also that differentgroups of artists (visual art and music) differ. Furthermore, “art-ists” should not be looked at as a whole, but separated into thedifferent groups of art, because there are differences.

Psychology, visual art, and music students do not only differ onmean personality and thinking style, but also present complexity

156 HALLER AND COURVOISIER

differences. Visual art students show greater complexity in con-scientiousness than both music and psychology students. More-over, visual art students show greater overall complexity thanpsychology students do. The present investigation is a first attemptto investigate complexity in an empirical way. Therefore, thepresent results have to be looked at with caution. However, it canbe assumed that there is one overall complexity that can be a newdimension of personality with different facets of complexity.

Limitations and Suggestions for Further Research

First, this study is based on self-report questionnaires. Thisposes the problem of social desirability and other response-styletendencies that may limit validity of self-report personality scales(Paulhus, 1991; see also Piedmont, McCrae, Riemann, & Angle-itner, 2000). Second, the present sample contains only students.We cannot be sure that visual art and music students will becomehighly creative. Third, the three groups most likely contain moreand less creative people. Therefore, all the three groups should besplit into more or less creative people and compared according tocomplexity.

Finally, the main limitation of this study is that it does not allowus to decide who is creative and who is not. Although the presentfindings underline some of the relationships previously foundbetween creative and noncreative people within and between do-mains, the present differences can only be related to creativitywhen further investigating a creativity measurement instrument.Results from this study are coherent with an interpretation thatcreative individuals have a different personality and thinking style.However, they are also coherent with the interpretation that indi-viduals with different personality and thinking style might choosedifferent type of studies (self-selection). Indeed, research on thelong-term stability of personality suggests that personality profilesare stable (e.g., Caspi, Roberts, & Shiner, 2005; Lehnart & Neyer,2006; Roberts, Walton, & Viechtbauer, 2006), which would un-derline that individuals do not actually change during studies, butchoose a domain according to their profiles. Despite these limita-tions, the present study can be seen as a first investigation of a newtrait, namely complexity. Further research asking experts to eval-uate art or music students independently according to their cre-ativity would certainly provide more insights into the relationshipbetween creativity and personality and thinking style. Fourth,Adjusted R2, and mean differences are not large. Given the largesample size, even small differences are likely to become signifi-cant. The present results have therefore to be further investigated.

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(Appendix follows)

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Appendix

Heuristic Problem-Solving Questionnaire Adapted After Groner & Groner(1990, p. 320/321)

In the following 30 questions, we would like to get your opinion on some themes. Please answer asspontaneously as possible!

Thinking style Not at all Somewhat Mostly Completely

1. To work on something I already know is boring for me. ❑ ❑ ❑ ❑2. I hate mathematical problems. ❑ ❑ ❑ ❑3. If my radio or another apparatus does not work, I first try to fix it

myself before I ask an expert to do it. ❑ ❑ ❑ ❑4. I like to book my holiday as a package in a tourist agency. ❑ ❑ ❑ ❑5. Sometimes inventions or solutions enter my mind without me needing

the thing, and without a specific problem to solve. ❑ ❑ ❑ ❑6. Ruminating too much is pointless, there is nothing we can do against

the grievances in the world. ❑ ❑ ❑ ❑7. I try to do minor repairs by myself, including if I have not done this

before. ❑ ❑ ❑ ❑8. Well-tried means more to me, so I do not risk something new instead. ❑ ❑ ❑ ❑9. I would rather play chess or another game against a more experienced

player than against a less experienced one, who can easily be beaten. ❑ ❑ ❑ ❑10. When I do handicrafts, I do not like to do it according to instructions. ❑ ❑ ❑ ❑11. When I do routine work, I think about what I am actually doing, and

if it could be done differently. ❑ ❑ ❑ ❑12. When I try to solve a riddle, I give up immediately if I notice that it

is too difficult for me. ❑ ❑ ❑ ❑13. I rearrange the furniture every once in a while in my flat. ❑ ❑ ❑ ❑14. I like to do things according to a plan so that I do not have to worry

about routine details again and again. ❑ ❑ ❑ ❑15. Although it is possible to get lost in the forest, I rarely follow the

signposts. ❑ ❑ ❑ ❑16. I do not have the patience to stay with a problem for a long time. ❑ ❑ ❑ ❑17. I can ruminate on a solution to a problem for such a long time that

other things are forgotten. ❑ ❑ ❑ ❑18. When I have to do something technical, I get the correct instruments

first, and get information about how to do the task professionally. ❑ ❑ ❑ ❑19. If there was no corkscrew to hand, I would get the cork out of the

bottle in another way. ❑ ❑ ❑ ❑20. I get more out of a visit to a museum when I go on a guided tour. ❑ ❑ ❑ ❑21. I am always interested to learn a new game that gives me something

to think about. ❑ ❑ ❑ ❑22. If I am confronted with a task to solve, I try to find out how others

solved the problem before me. ❑ ❑ ❑ ❑23. I try to solve problems in new ways. ❑ ❑ ❑ ❑24. If I was a teacher, I would only teach using established methods, to

be sure that I use the material correctly. ❑ ❑ ❑ ❑25. I would rather find a solution for a previously unsolved problem than

do something according to a formula or an approved method. ❑ ❑ ❑ ❑26. I like routine tasks. In such cases, I know what to do, and what I

need to reach my goal. ❑ ❑ ❑ ❑27. If I ever get a dog, I won’t buy one that is already trained. ❑ ❑ ❑ ❑28. I do not like furniture that I have to build myself because I do not

have any mechanical experience. ❑ ❑ ❑ ❑29. To solve problems you do not have to be a professor. ❑ ❑ ❑ ❑30. People who think too much only get wrinkles and who wants to look

old? ❑ ❑ ❑ ❑

Received April 16, 2009Revision received September 14, 2009

Accepted September 14, 2009 �

160 HALLER AND COURVOISIER