Mapping the Creative Personality: A Psychometric Network Analysis of Highly Creative Artists and Scientists

Qunlin Chen, Alexander P. Christensen, Yoed N. Kenett, Zhiting Ren, David M. Condon, Robert M. Bilder, Jiang Qiu, Roger E. Beaty

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Existing research has consistently supported a relationship between creative achievement and specific personality traits (e.g. openness to experience). However, such work has largely focused on univariate associations, potentially obscuring complex interactions among multiple personality factors, rendering an incomplete picture of the creative personality. We applied a psychometric network approach to characterize the multidimensional personality structure of highly creative individuals in the arts (“artists”) and sciences (“scientists”), using data from three samples (N = 4,015): college students, a representative adult sample, and the Big-C project of eminent creative professionals. Replicating past work, we found that artists showed reliably higher levels of openness to experience compared to scientists and a control group of less creative people. Psychometric network analysis revealed that artists were characterized by higher connectivity (i.e. co-occurrence) with other personality traits for openness, indicating that openness may be more heterogeneous in how it co-occurs with other personality traits in highly creative people. Across all three samples, we found that the scientists’ personality network structure was more cohesive than the personality network of artists and the control group, indicating greater homogeneity in the personality characteristics of scientists. Our findings uncover a constellation of traits that give rise to creative achievement in the arts and sciences.

Original languageEnglish
Pages (from-to)455-470
Number of pages16
JournalCreativity Research Journal
Volume35
Issue number3
DOIs
StatePublished - 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2023 Taylor & Francis Group, LLC.

Funding

The work was supported by the US National Science Foundation (NSF) Division of Research on Learning in Formal and Informal Settings [DRL-1920653]; NSF Division of Undergraduate Education [DUE- 2155070]; National Natural Science Foundation of China [NSFC32071070]; National Natural Science Foundation of China [NSFC31800919]; Chongqing Humanities and Social Sciences [2018PY80]; Natural Science Foundation of Chongqing [cstc2021jcyj-msxmX1080]

FundersFunder number
Chongqing Humanities and Social Sciences2018PY80
National Science FoundationDRL-1920653
Division of Undergraduate EducationDUE- 2155070
National Natural Science Foundation of ChinaNSFC31800919, NSFC32071070
Natural Science Foundation of Chongqing Municipalitycstc2021jcyj-msxmX1080

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