Evaluating the Big Five as an Organizing Framework for Commonly Used Psychological Trait Scales

The Big Five is often represented as an effective taxonomy of psychological traits, yet little research has empirically examined whether stand-alone assessments of psychological traits can be located within the Big Five framework. Meanwhile, construct proliferation has created difficulty navigating the resulting landscape. In the present research, we developed criteria for assessing whether the Big Five provides a comprehensive organizing framework for psychological trait scales and evaluated this question across three samples (Total N = 1,039). Study 1 revealed that 83% of an author-identified collection of scales (e.g., Self-Esteem, Grit, etc.) were as related to the Big Five as at least four of 30 Big Five facets, and Study 2 found that 71% of scales selected based on citation counts passed the same criterion. Several scales had strikingly large links at the Big Five facet level, registering correlations with individual Big Five facets exceeding .9. We conclude that the Big Five can indeed serve as an organizing framework for a sizable majority of stand-alone psychological trait scales and that many of these scales could reasonably be labeled as facets of the Big Five. We suggest an integrative pluralism approach, where reliable, valid scales are located within the Big Five and pertinent Big Five research is considered in all research using trait scales readily located within the Big Five. By adopting such an approach, construct proliferation may be abated and it would become easier to integrate findings from disparate fields.

Automated summary

This study empirically examined whether the Big Five can serve as an organizing framework for psychological trait scales and found that a majority of stand-alone psychological trait scales can be closely related to the Big Five framework, with some scales reasonably labeled as facets of the Big Five. By adopting an integrative pluralism approach, construct proliferation can be reduced and findings from disparate fields can be more easily integrated.