= 164). We illustrated how valence categories are essentially arbitrary and largely influenced by sample size. In addition, valence ratings were continuously distributed, further questioning the validity of imposing categorical distinctions. In Study 2, we used an archival dataset to demonstrate how the different categorization schemes resulted in conflicting conclusions about the association between item valence and RMET performance. However, when we examined the association between item valence and performance in a continuous manner, a clear U-shaped pattern emerged: Items that had more extreme valence ratings (negative or positive) were associated with better performance than items with more neutral ratings. We conclude that using the item valence ratings we report, and treating item valence as a continuous rather than categorical predictor, will help bring consistency to the study of the association between item valence and performance in the RMET. (PsycInfo Database Record (c) 2020 APA, all rights reserved).