Intersectional multilevel modeling as a method for intersectional analysis of inequity in mental health distress among college student-parents - Joachin, Vanessa S., author; Conner, Brad, advisor; Chavez, Ernesto, committee member; Lucas-Thompson, Rachel, committee member; Graham, Daniel, committee member (Colorado State University. Libraries, 2025)
This study applied the Intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (I-MAIHDA) to explore the intersectional effects of social positioning on mental health among college student-parents. Using data from the American College Health Association-National College Health Assessment (ACHA-NCHA), the study examined relationships between social context variables—campus climate, social support, and loneliness—and psychological distress, while also assessing the utility of I-MAIHDA as a quantitative intersectional method. The student-parent population is a growing yet understudied subgroup in higher education, facing unique challenges that influence their well-being. The study applied multilevel linear regression models to understand the variance in psychological distress across intersectional social strata defined by race, gender, sexual orientation, and food security status. Results indicated that student-parents in more privileged social strata experienced lower levels of psychological distress, more favorable campus climate perceptions, lower loneliness, and higher social support, whereas those from marginalized identities, particularly those with low food security, faced increased distress and more adverse social contexts. I-MAIHDA was demonstrated to be a promising approach for capturing the nuances of intersectionality, effectively addressing issues related to sample size, and revealing significant variability across strata. Findings underscore the importance of inclusive campus policies that better support student-parents, with a specific focus on addressing disparities stemming from intersecting social identities.