(PS7-D88) Exploring Race, Ethnic, and Gender Differences in Cognitive and Mood Reactivity Using Latent Difference Score Modeling

Numerous studies have demonstrated that a distinction between cognitive reactivity (changes in attitudes) and mood reactivity (changes in affect) using mood-induction paradigms is necessary to understand the impact of these processes on pathology (e.g., van Rijsbergen et al., 2013). In addition, gender identity has also been shown to impact the outcome of a mood induction (Joseph et al., 2020). Given that disparities exist in the rate of psychopathology among various racial/ethnic minorities and gender categories, the current study aimed to expand upon the literature by exploring race, ethnic, and gender differences in cognitive (i.e., pessimistic attributional style) and affective reactivity (i.e., sadness) pre- and post- a dysphoric mood intervention in a sample of undergraduate students (n = 497). The relationship between cognitive and mood reactivity and participant race, ethnicity, and gender were analyzed using latent difference score modeling, a technique that more accurately depicts change over time compared to traditional change scores (e.g., McArdle, 2009). Results showed that, compared to cognitive reactivity, increases in self-reported mood reactivity was significantly stronger, corresponding to a small effect, for Asian (standardized estimate = 0.15, p < 0.001), and female participants, although his latter effect was non-significant (stand. est. = 0.15, p = 0.08). No significant associations were demonstrated for other demographic predictors and cognitive reactivity. Taken together, these findings distinguish cognitive and mood reactivity and suggest that female and Asian populations may be more reactive to dysphoric moods after a mild stressor.