Factors Associated with Psychological Constructs: A Conditional Inference Tree Analysis

Psychological constructs such as anxiety, depression, fatalism subscales—fatalism, divine control, luck, helplessness, and internality—play an important role in shaping mental health outcomes in the United States (US). Although several studies have explored how specific variables correlate with these constructs, less is known about how sociodemographic and experiential factors interact to shape multidimensional fatalism, including the subscales of fatalism, divine control, luck, helplessness and internality. This study addresses the gap by using Conditional Inference Trees (CITs) to explore how interactions among variables are associated with these constructs. Using the Conditional Inference Tree (CIT) analyses, we examined how Adverse Childhood Experience (ACE), age, gender, race, education, and urbanicity are associated with depression, anxiety, and fatalism subscales. Our analyses revealed that ACE and age were the most significant variables associated with depression and anxiety, with higher ACE scores associated with higher levels of both depression and anxiety. For multidimensional fatalism, age, race, gender, and urbanicity were key variables, although their effects varied across subscales. Overall, these findings highlight the importance of considering interaction effects when examining mental health outcomes and fatalistic belief systems. CIT analysis provides a useful explanatory framework for identifying complex patterns of association between early life adversity, sociodemographic factors and psychological constructs.