6 General Psychopathology Factor as a Mediator Between Polysubstance Use and Lower-Order Psychopathology Constructs

OBJECTIVES/GOALS: We aim to develop an understanding of how polysubstance use (PSU) relates to the general psychopathology factor (p-factor), as well as to individual components of the Hierarchical Taxonomy of Psychopathology (HiTOP) model (e.g., fear, distress). This insight can help identify treat...

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Bibliographic Details
Published in:Journal of clinical and translational science 2024-04, Vol.8 (s1), p.2-2
Main Authors: Pavuluri, Asha, Carrasquillo, Kristiana, Zughaib, Laithe, Valença, Marina, Berry, Michelle, Nahabedian, Sophia, Chen, Yunzhi, Davis, Brittany, Bernat, Edward
Format: Article
Language:English
Subjects:
Antagonism
Biostatistics, Epidemiology, and Research Design
Check lists
Comorbidity
Drug use
Fear
Population studies
Psychopathology
Substance use
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Summary:OBJECTIVES/GOALS: We aim to develop an understanding of how polysubstance use (PSU) relates to the general psychopathology factor (p-factor), as well as to individual components of the Hierarchical Taxonomy of Psychopathology (HiTOP) model (e.g., fear, distress). This insight can help identify treatment targets related to substance use and psychopathology. METHODS/STUDY POPULATION: Psychopathology and substance use data, collected at a Baltimore treatment center over several years, will be analyzed. The center aids about 6000 underserved clients per year, and the population is primarily African American clients of all genders. Structural equation modeling (using Mplus software) will be used to develop the latent models and identify relationships between psychopathology and PSU (i.e., direct and indirect pathways). The current latent HiTOP model was developed from symptom checklists completed upon entry at the treatment center. The PSU latent factor will be developed from a biopsychosocial assessment where clients list their drug of choice. Due to the varying organizations of the datasets, smaller-scale preliminary models will be developed to ensure an accurate large-scale final model. RESULTS/ANTICIPATED RESULTS: Current models being tested are derived from January to September 2023 data (i.e., completed months' data), with an N of 1,564. From symptom checklist data collected at the treatment center, a preliminary HiTOP model was derived with reasonable fit (χ 2 = 4532.35 (df = 321, p
ISSN:2059-8661
2059-8661
DOI:10.1017/cts.2024.29