Date Approved

6-8-2021

Embargo Period

6-9-2021

Document Type

Thesis

Degree Name

M.A. Clinical Psychology

Department

Psychology

College

College of Science & Mathematics

Advisor

Dustin A. Fife, PhD and Thomas Dinzeo, PhD

Committee Member 1

Steven Brunwasser, PhD

Committee Member 2

Chelsie Young, PhD

Keywords

Psychosis, Quantitative, Schizophrenia, Schizotypy

Subject(s)

Schizotypal personality disorder

Disciplines

Clinical Psychology

Abstract

There are currently many different conceptualizations of schizophrenia risk, which we argue is detrimental to any efforts to build a cumulative science in this area. This paper sought to evaluate various conceptualizations of schizophrenia risk and the extent to which they overlap. This paper attempts to identify overlap by utilizing meta-analytic methods in conjunction with data collected from a sample of undergraduate college students (n = 80). To do so, we first collected estimates of various schizophrenia risk measures and risk correlates from the literature. These estimates were subsequently combined with collected data. This paper attempted to analyze review data and collected data using meta-analytic structural equation modeling (MASEM) in a novel way. Analysis of our collected data provided support for a hybrid model where risk subscales loaded onto symptom clusters and two risk measures (SPQ-BR and O-LIFE) captured unique variance. Overall, our results appear to support a movement towards consolidating the fragmented risk literature and identified specific risk measures which may be candidates for consolidation. Future research in this area may expand data collection efforts and examine risk measures at an item level with the ultimate goal of developing a novel risk measure which incorporates pre-existing measures.

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