ABSTRACT
Laughter-related dispositions, including gelotophobia (fear of being laughed at), gelotophilia (enjoyment of being laughed with), and katagelasticism (enjoyment of laughing at others), may explain patterns of humor use beyond broad personality traits and social anxiety. However, their incremental predictive value across distinct humor domains remains insufficiently examined. A sample of 788 Canadian university students completed self-report measures of laughter-related dispositions, HEXACO personality traits, social anxiety, and six humor domains. Hierarchical regression models assessed incremental validity beyond personality and social anxiety. Gradient boosting machine learning models were conducted to examine nonlinear effects and relative predictor importance. Gelotophilia consistently predicted greater humor use across domains. Gelotophobia predicted lower everyday humor, reduced laughing at oneself, and diminished humor under stress, even after controlling for personality and social anxiety. Katagelasticism showed minimal associations with adaptive humor domains. Machine learning analyses converged with regression findings, underscoring the robustness of these effects. Laughter-related dispositions demonstrate distinct and incremental contributions to humor use beyond personality and social anxiety. Gelotophilia and gelotophobia, in particular, represent meaningful predictors of adaptive humor engagement.