To Profile or Not to Profile: A Multiinformant Study of the Robustness and Utility of Personality-Based Profiles on a Large Biobank Sample

Abstract

Person-centered personality profiles are widely used to examine latent covariation patterns in heterogeneous samples. However, their robustness across measurement and analytic choices and incremental utility beyond continuous traits remain controversial. We leveraged a well-powered ( N  = 73,563), multiinformant, multitrait data set to establish personality profiles based on self-regulation domains and individual items. Item-level latent-profile analyses yielded the best model fit and differentiated between five distinct profiles: high-functioning, well-adapted, anxious-perfectionistic, behaviorally dysregulated, and emotionally/behaviorally dysregulated. Profile structure was configurally robust, but individual profile memberships showed only moderate cross-informant agreement. Profiles significantly predicted life satisfaction and internalizing problems, although less in cross-informant comparisons, and continuous personality traits consistently out-predicted profiles. Together, these findings emphasize that self-regulation profiles are replicable and consistently tied to external validation variables yet have suboptimal predictive value compared with traits. Hence, profiles could primarily be used as aids for detecting and describing unique trait configurations instead.