Personality profiles in SAPA data: An exploratory study

Abstract

In the last two decades, individual differences have been examined from a person-oriented approach which tends to classify individuals into personality types based on their unique configurations of personality traits. Previous typological studies explored the consistency of personality profiles by varying different methodological factors (e.g., sample characteristics, personality theoretical frameworks, personality assessment methods, and data analysis methods). The aim of the study was to explore the replicability of personality profiles based on three major personality models (Big Five, HEXACO, and Tellegen's model) across two large SAPA (Synthetic Aperture Personality Assessment) datasets. Data analysis included the following steps: model-based clustering, profile similarity assessment, evaluation of class replicability, and comparison of merged classes' profiles in both samples. Four robust personality types re-emerged within the Big Five domain closely corresponding with four types identified in recent studies. Three types were extracted from Tellegen's and the HEXACO models. Despite the challenges of interpreting types from Tellegen's model, results demonstrated congruence with previous findings, whereas results for the HEXACO model showed little evidence of class/profile robustness. This exploratory study highlights the importance of personality profiles in personality assessment which could be further investigated with new data sources such as SAPA and advanced statistical tools.