Dissertation Presentation: Understanding Women's Enrollment in AUD Treatment

School of Social Work PhD Candidate Bonnie Horgos presents her dissertation, "'A Lifeline for Millions:' Using Andersen’s Behavioral Model of Health Service Use to Understand Women’s Enrollment in Alcohol Use Disorder Treatment Through Medicaid."

Advisor: Marti DeLiema, PhD

Committee: Joseph Merighi, PhD, MSW, MA; Mimi Choy-Brown, PhD, MSW; Andrew Zieffler, PhD (Department of Educational Psychology)

When: Tuesday, May 20, 2025 at 2 pm  

Where: Peters Hall, Room 280 or via Zoom

Abstract: Alcohol use disorder (AUD) is a major concern for women, yet treatment utilization remains
low. Women face significant barriers to treatment, including stigma, lack of social support, and affordability challenges. Although there is limited empirical evidence explaining why some women overcome these barriers, research suggests that women on Medicaid may be more likely to access AUD treatment. However, the mechanisms behind this association are not well understood. Andersen’s Behavioral Model of Health Service Use proposes that treatment utilization is influenced by predisposing factors, enabling resources, and health needs. This study applied Andersen’s Model to examine the factors associated with treatment enrollment and settings for women with AUD, as well as the moderating effect of Medicaid.

Using pooled data from the 2015–2023 National Survey on Drug Use and Health (unweighted n = 28,739; weighted N = 14,382,241), the study first tested Andersen’s Model via confirmatory factor analysis (CFA), followed by exploratory factor analysis (EFA) to identify an improved factor structure. Structural equation modeling (SEM) assessed the relationship between empirically derived factors and past-year AUD treatment enrollment. Logistic and multinomial regression models tested the moderating role of Medicaid and differences in treatment settings.

CFA showed poor fit for Andersen’s Model (CFI = .73, RMSEA = .11), while EFA supported a two-factor structure: facilitators (income, education, higher self-rated physical health) and barriers (AUD severity, mental health status, disability, lower self-rated physical health). This model explained 70.4% of variance and had excellent fit (CFI = .995, RMSEA = .022). Facilitators were positively associated with treatment enrollment (β = 1.37, p < .001), but this effect weakened for Medicaid recipients (β = -0.84, p = .008). Barriers had a negative relationship with enrollment (β = -8.95, p < .001), which became positive when moderated by Medicaid (β = 1.45, p = .034). Medicaid recipients were more likely to receive inpatient/residential care and less likely to use outpatient or support services.

Medicaid appears to both buffer the impact of barriers and reduce the influence of facilitators. These findings point to the need for policies addressing structural barriers and supporting women with the highest treatment needs.