Back to Search
Start Over
Common genetic basis of the Five Factor Model facets and intelligence: A twin study
- Publication Year :
- 2022
- Publisher :
- Open Science Framework, 2022.
-
Abstract
- The main aim of this study was to explore the etiology of relations between general cognitive ability (g) and different hierarchical phenotypic levels of the Five Factor Model (FFM), including the General Factor of Personality (GFP), the Big Two, the five domains of the FFM, and their 30 facets. The second aim was to detect personality facets that contribute to the prediction of general intelligence. The sample consisted of 424 young adult twins (134 pairs of monozygotic twins) on whom the NEO-PI-R and Advanced Progressive Matrices were administered. The results did not support hierarchical solutions above the FFM. Thus, five-domain and facet level of personality were analyzed, showing that only Openness and Neuroticism had significant genetic or environmental correlations with intelligence. The several facets from all domains had significant associations, among which Ideas and Positive Emotions showed the highest positive correlations, while Order and Modesty showed the highest negative genetic correlations with intelligence. Furthermore, seven facets significantly predicted g factor (35%), with higher genetic (0.52) than environmental (0.13) correlations with intelligence. The results reveal the common genetic basis of narrow traits and intelligence, highlighting the importance of specific traits in the explanation of general cognitive abilities.
- Subjects :
- media_common.quotation_subject
g factor
05 social sciences
050109 social psychology
Hierarchical structure of the Big Five
Neuroticism
Twin study
050105 experimental psychology
Developmental psychology
Facet (psychology)
Openness to experience
Personality
0501 psychology and cognitive sciences
Big Five personality traits
Psychology
General Psychology
media_common
Subjects
Details
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....9a00d8522303a28e94077a07cc86f70d
- Full Text :
- https://doi.org/10.17605/osf.io/v528t