Date Approved

8-8-2024

Embargo Period

8-9-2024

Document Type

Thesis

Degree Name

Master of Arts (M.A.)

Department

Clinical Psychology

College

College of Science & Mathematics

Advisor

Tom Dinzeo, Ph.D.

Committee Member 1

Katherine Gotham, Ph.D.

Committee Member 2

Christina Simmons, Ph.D.

Keywords

Social determinants of health (SDOHs), social connectedness, childhood trauma, healthcare access

Subject(s)

Psychoses--Risk factors; Social ecology

Disciplines

Clinical Psychology | Psychology | Social and Behavioral Sciences

Abstract

Social determinants of health (SDOHs) significantly impact psychosis risk beyond heritability. However, there is a need for an organizing framework to observe how these diverse elements concurrently predict psychosis risk. This study examines SDOHs as psychosis risk factors using a four-level model, aligned with Bronfenbrenner's social ecology theory. The study aims to assess the proposed model’s ability to predict psychosis risk. Specifically, it is hypothesized that each socioecological level of the model would predict psychosis risk with more proximal SDOHs (e.g., individual level vs community) exhibiting stronger predictive power, aligning with Social Ecology theory. College students (N = 210) completed self-report measures of schizotypy, childhood trauma, minority group position, social connectedness, urbanicity, health care access, and SES via online surveys. The overall model accounted for a significant amount of psychosis risk variance (34.8%) with each level contributing significantly. However, contrary to expectations, SDOH proximity did not correspond with predictive ability. Rather, social connectedness, childhood trauma, and healthcare access emerged as salient predictors. The current study provides evidence that a Social Ecology Model, despite limitations, may provide an advantageous framework for future research, risk measurement, and interventions. Current findings reinforce that many of these SDOHs, particularly social connectedness, may be worthwhile targets for interventions.

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