Five-Factor Model Personality Domains and Facets Associated With Markers of Cognitive Health

Using a diverse, age-stratified sample (N = 3,478; age range: 18-90), this study examines the cross-sectional association between five-factor model personality traits - domains and facets - and three measures of cognitive health - processing speed, visuospatial ability, subjective memory - and whether these associations vary by age, race, and ethnicity. Consistent with the literature on personality and cognitive health, higher openness and conscientiousness were associated with better cognitive performance and subjective memory, whereas higher neuroticism was associated with slower processing speed and worse subjective memory but was unrelated to visuospatial ability. Moderation analyses suggested some associations were stronger in midlife compared to younger and older adulthood but were generally similar across race and ethnicity. The facet-level analyses indicated the components of each domain most strongly associated with cognitive function (e.g., the responsibility facet of conscientiousness) and suggested some differences across facets within the same domain (e.g., depression was associated with worse performance, whereas anxiety was unrelated to performance: sociability was the only facet of extraversion associated with worse performance). The present research is consistent with the larger literature on personality and cognition and extends it by documenting similarities and differences across facets and demographic groups.

Automated summary

Using a diverse, age-stratified sample, this study explores the association between personality traits and cognitive health measures, and the potential moderating effects of age, race, and ethnicity. The findings reveal that higher levels of openness and conscientiousness are linked to better cognitive performance and subjective memory, while higher neuroticism is associated with slower processing speed and worse subjective memory. These associations are generally consistent across different demographic groups. The facet-level analyses further identify specific facets within each domain that are most strongly associated with cognitive function.