Understanding cultural stress and mental health among Latinos in the us: probabilistic omnidirectional inference model

Abstract

Recent evidence suggests that cultural stress might predict Latinos’ mental health outcomes. Yet, how two sources of cultural stress such as discrimination and negative context of reception are related to anxiety and depression is not well understood. This study aimed to investigate the impact of discrimination, negative context of reception, and demographic factors on anxiety and depression levels among 1426 Latino adults in the United States. Using two novel online simulators based on Bayesian Belief Networks, we explored how variations in these independent variables influence mental health outcomes. Our findings reveal that discrimination and negative context of reception significantly affect anxiety and depression, with discrimination being a stronger predictor. Generational status also played a key role, with second-generation Latinos experiencing worse mental health compared to the first generation. The item “To what extent do you feel that Americans have something against you?” was identified as the strongest predictor of mental health. Probabilistic machine learning approach allowed for the examination of complex interactions and non-linear relationships, providing deeper insights into the dynamics of cultural stressors and mental health. These findings suggest that addressing discrimination and negative context of reception could be vital for interventions aimed at improving the mental health of Latino populations. The use of online simulation tools in this research offers a novel method for subject-matter experts to explore and understand the intricate relationships between cultural stressors and mental health, potentially informing future prevention strategies.