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35th AM (2025) - Poster Session
The Association between Substance Abuse and Mental ...
The Association between Substance Abuse and Mental Illness_Predictive Regression and Propensity Score Analysis
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Pdf Summary
This study investigates the relationship between substance use disorder (SUD) and mental illness (AMI) in the U.S., controlling for education, gender, income, and age using advanced Data Science methods. Utilizing data from the 2022 National Survey on Drug Use and Health (NSDUH), the final analytic sample included 47,100 civilian American adults after exclusions. Analyses incorporated bivariate assessments, logistic regression, and propensity score methods to predict SUD prevalence based on AMI and demographic variables.<br /><br />Key findings reveal that individuals with a mental illness are 3.6 times (263%) more likely to have a SUD compared to those without AMI. Males show a 40% higher likelihood of SUD diagnosis than females. Socioeconomic status plays a significant role: individuals earning under $20,000 annually have a 27.8% higher risk of SUD than those earning over $75,000. Younger adults aged 18 to 25 are at higher risk compared to older age groups. The predictive models demonstrated strong agreement (c = 0.70) between logistic regression and propensity score analyses, indicating robust prediction capacity.<br /><br />The research highlights the importance of addressing mental illness within substance abuse interventions and suggests prioritizing funding for programs targeting young people and low-income populations. It also underscores potential benefits of integrating mental health services into primary care and providing gender-tailored treatments. The study advocates for the adoption of Data Science techniques in psychological research to refine risk prediction and enhance understanding of addiction’s underlying factors. This aligns with recommendations from leading mental health and addiction research agencies emphasizing Big Data’s role in revealing complex mental health dynamics.<br /><br />Presented at AAAP 2025, this research contributes to improving public health strategies by informing targeted prevention and treatment efforts that address the intersecting challenges of SUD and mental illness in diverse demographic groups.
Keywords
Substance Use Disorder
Mental Illness
Data Science
National Survey on Drug Use and Health
Logistic Regression
Propensity Score Methods
Socioeconomic Status
Young Adults
Gender Differences
Addiction Risk Prediction
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