Linking personality traits to vocational interest profiles via the circumplex: Research synthesis and new applications

Vocational interests and personality traits are among the most important and widely studied individual differences constructs in vocational psychology. Although many studies have examined their bivariate associations, no study has approached this question from a profile-based perspective. In this study, we close this gap by linking personality traits to vocational interest profiles via the circumplex, an established model for structuring the interrelations between interest domains. We illustrate potential pitfalls of focusing solely on isolated bivariate associations and show how the circumplex makes it possible to summarize and visualize complex correlation patterns in a directly interpretable way. Study 1 presents a meta-analytic reanalysis of the relationships between FFM traits and RIASEC interests ( N = 18,291, k = 27). Study 2 uses a latent circumplex model to better understand how strong these associations truly are and to examine their consistency across different interest taxonomies. Specifically, we apply the latent circumplex model to the aggregated data from Study 1 and to two different datasets from Germany ( N = 1032) and Belgium ( N = 1317). Results were remarkably consistent, demonstrating that personality traits are more strongly associated with profile configurations compared to profile levels. Openness was almost as strongly related to individual differences in interest configurations as a typical interest scale. Similarly strong associations were found for Extraversion and Agreeableness, whereas those with Neuroticism and Conscientiousness were weaker. These results shed new light on how interests and traits can be integrated, with important implications for theory and practice. • We link FFM personality traits to interest profiles using the circumplex. • We present a meta-analysis of previous studies based on FFM and RIASEC. • We present a latent model to better judge the strength of the relationships. • Findings are very consistent across studies and interest taxonomies. • Our findings explain why some traits are more context dependent than others.