Abstract
Personality and intelligence are defined as hierarchical constructs, ranging from broad g-factors to (domain-)specific constructs. The present study investigated whether different combinations of hierarchical levels lead to different personality-intelligence correlations. Based on the integrative data analysis approach, we combined a total of five data sets. The focus of the first study (N = 682) was an elaborated measurement of personality (NEO-PI-R), which was applied with a relatively short intelligence test (Intelligence Structure Test 2000 R). In the second study (N = 413), a comprehensive measurement of intelligence (Berlin Intelligence Structure test) was used with a shorter personality questionnaire (NEO-FFI). In line with the Brunswik symmetry principle, the findings emphasize that personality-intelligence correlations varied greatly across the hierarchical levels of constructs considered in the analysis. On average, Openness showed the largest relation with intelligence. We recommend for future studies to investigate personality-intelligence relations at more fine-grained levels based on elaborated measurements of both personality and intelligence.
Highlights
The relation between intelligence and personality is of high theoretical and practical importance as personality and intelligence tests are often both applied in selection contexts
The primary aim of the present study is to examine the utility of the Brunswik symmetry principle [23] for examining the relations between intelligence and personality
The correlations between scores for the different hierarchical levels of personality (i.e., General Factor of Personality (GFP), Big Two, Five Factor Model (FFM) dimensions, facets) and reasoning are presented in Table 2
Summary
The relation between intelligence and personality is of high theoretical and practical importance as personality and intelligence tests are often both applied in selection contexts. Knowing their relation gives a hint on the incremental and combined validity of both constructs when predicting important criteria such as job performance. One popular way of doing this is to derive and test trait taxonomies describing important areas of personality and ability. In the field of intelligence research, the majority of contemporary models (i.e., taxonomies) define intelligence as a hierarchical, multidimensional construct instead of a simple, unidimensional construct. Based on the comprehensive and integrative Berlin Intelligence
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
