LAUSR

Abstract Research investigating performance-related outcomes has established that the predictive validity of Big Five models can be doubled, simply by contextualizing scale items. We herein test whether this contextualization effect can be leveraged to universally improve the predictive validity of Big Five models by considering the breadth, depth, and nature of contextualization effects. Study 1 (N = 320) compared the predictive validity of an uncontextualized measure of Conscientiousness (C), with three measures of C contextualized to organizational, academic, and romantic settings, respectively. Nine outcome variables served as indices of validity (three per context). We hypothesized that contextualized scales would be superior in predicting all context-congruent outcomes. Study 2 (N = 680) and Study 3 (N = 378) extended the results to consider alternative trait and outcome measures (e.g., Implicit Association Task). Across all three studies, predictive validity was enhanced for contextualized vs. uncontextualized measures only when outcomes were context-congruent. However, this enhancement varied greatly, with contextualized scales improving the prediction of some outcomes by as much as 32% (GPA), and as little as 1% (income). Our findings suggest that scale contextualization can be adopted by psychometricians to easily improve the predictive validity of personality models. Guidelines for contextualization are discussed.