Personality Across the Lifespan

Abstract

Abstract. Personality is a relevant predictor for important life outcomes across the entire lifespan. Although previous studies have suggested the comparability of the measurement of the Big Five personality traits across adulthood, the generalizability to childhood is largely unknown. The present study investigated the structure of the Big Five personality traits assessed with the Big Five Inventory-SOEP Version (BFI-S; SOEP = Socio-Economic Panel) across a broad age range spanning 11–84 years. We used two samples of N = 1,090 children (52% female, Mage = 11.87) and N = 18,789 adults (53% female, Mage = 51.09), estimating a multigroup CFA analysis across four age groups (late childhood: 11–14 years; early adulthood: 17–30 years; middle adulthood: 31–60 years; late adulthood: 61–84 years). Our results indicated the comparability of the personality trait metric in terms of general factor structure, loading patterns, and the majority of intercepts across all age groups. Therefore, the findings suggest both a reliable assessment of the Big Five personality traits with the BFI-S even in late childhood and a vastly comparable metric across age groups.

Personality‐achievement associations in adolescence—examining associations across grade levels and learning environments

“…We aimed to examine whether these results are replicable using two large and fully representative cross-sectional samples of 6th and 9th graders in Berlin, Germany. Targeting 6th graders offered an advantage in that this grade constitutes the last year of primary school education in Berlin and previous research has provided evidence for the replicability of personality self-ratings in 12 year olds (Allik et al, 2004;Brandt et al, 2018). Targeting 9th graders offered the advantage that students had already spent three years in Berlin's secondary education system, so potential effects of secondary school environments should be more pronounced than in lower grades.…”

“…The most prominent and frequently applied conceptualization of personality is the fivefactor model (or Big Five), which distinguishes five broad domains of individual differences: Extraversion, Neuroticism, Openness, Agreeableness, and Conscientiousness (McCrae & Costa, 1997). Research has provided evidence for their replicability across different ages, even in childhood and adolescence (Allik, Laidra, Realo, & Pullmann, 2004;Brandt et al, 2018).…”

Ant Colony Optimization and Local Weighted Structural Equation Modeling. A Tutorial on Novel Item and Person Sampling Procedures for Personality Research

“…'I keep my workplace tidy') will only be relevant for participants that are part of the work force. The importance of measurement invariance across age in personality development research has received more attention in recent years (Allemand et al, 2008(Allemand et al, , 2007Brandt et al, 2018;Nye et al, 2016;Olaru et al, 2018;Small, Hertzog, Hultsch, & Dixon, 2003). Because the number of observations per year of age is often too small to estimate MGCFA for singular age points, participants are often grouped to larger units (e.g.…”

“…gender and age) is referred to as measurement invariance and can be examined with different statistical methods (Mellenbergh, 1989;Meredith, 1993;Millsap, 2012). Cross-sectional personality development studies that test for measurement invariance across age (Allemand, Zimprich, & Hendriks, 2008;Allemand, Zimprich, & Hertzog, 2007;Brandt et al, 2018;Nye, Allemand, Gosling, Potter, & Roberts, 2016;Olaru et al, 2018) usually examine measurement invariance across age groups by artificially categorizing age in an arbitrary number of groups after separating them based on equally arbitrary thresholds, even though age is continuous in nature. This approach and the associated decisions concerning number of groups, for example, will inevitably influence the results and can therefore provide us with a distorted picture of personality development (Hildebrandt, Lüdtke, Robitzsch, Sommer, & Wilhelm, 2016;Hildebrandt, Wilhelm, & Robitzsch, 2009;MacCallum, Zhang, Preacher, & Rucker, 2002).…”

The HEX-ACO-18: Developing an age-invariant HEXACO short scale using Ant Colony Optimization

“…MI refers to the equivalence of factor loadings, item intercepts, and item residuals across groups of people: in the case of ageing research, across the age of participants. This constraint ensures that the extracted factors and factor parameters are comparable across age, which is essential when studying ageassociated differences in the latent traits (Allemand et al, 2007;Brandt et al, 2018;Nye et al, 2016). A lack of MI can severely bias the findings on developmental trends (e.g., Chen, 2007).…”