Profiles of online racism exposure and mental health among Asian, Black, and Latinx emerging adults in the United States.

Online racism is a digital social determinant to health inequity and an acute and widespread public health problem. To explore the heterogeneity of online racism exposure within and across race, we latent class modelled this construct among Asian ( = 310), Black ( = 306), and Latinx ( = 163) emerging adults in the United States and analysed key demographic and psychosocial health correlates. We observed and classes across all racial groups, whereas classes appeared among Asian and Black people and the classes emerged uniquely in Asian and Latinx people. Generally, the classes reported the greatest psychological distress and unjust views of society compared to all other classes. The and classes reported greater mental health costs than the classes. Asian women were more likely to be in the class compared to the class, whereas Black women were more likely to be in the class compared to both and classes. About a third of each racial group belonged to the classes. Our findings highlight the multidimensionality of online racism exposure and identify hidden yet divergently risky subgroups. Research implications include examination of class membership chronicity and change over time, online exposure to intersecting oppressions, and additional antecedents and health consequences of diverse forms of online racism exposure.