Leveraging Cattell's data types to understand creativity from different research traditions

Understanding creativity remains a challenge due to the variety of measurement approaches. This study applies Cattell’s framework of T-, L-, and Q-Data to investigate whether different data-types to measure creativity converge into a unified general factor. We used a sample of 320 adults that completed tests assessing originality (T-Data), self-reported ideations (Q-Data), and everyday creative activities as well as achievements (L-Data). Confirmatory factor analyses—including models accounting for zero-inflation in creative achievement data—was employed. Results revealed that the three data types were intercorrelated, but could not be modeled below an overarching general factor. Creative achievement were predicted by L-Data, somewhat weaker by T-Data, and were unrelated with Q-Data. The findings support the distinctiveness of measurement approaches to creativity. The results caution against overreliance on a singular assessment approach, most strongly so for Q-data for predicting real-world outcomes. We discuss persistent terminological and conceptual challenges in creativity measurement.