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Brain Morphology of Cannabis Users With or Without Psychosis: A Pilot MRI Study
Published on: August 18, 2020
An Analysis of 16-Year Trends in Cannabis Use Disorder Treatment: Predictors, Barriers, and Utilization Patterns
Brian D Graves1, Orion Mowbray2, Lydia Aletraris2
1Phyllis & Harvey Sandler School of Social Work, Florida Atlantic University, Boca Raton, Florida, USA.
None:
Background: Recent changes in cannabis potency, prevalence, and recreational policies have notable implications for those with cannabis use disorder (CUD) needing treatment. However, many individuals with CUD do not receive treatment and little is known about consistent correlates of CUD treatment and reasons for not receiving treatment. Objectives: This study used national data to examine predictors of receiving CUD treatment and reasons for not receiving treatment at three time points across sixteen years. Data came from 2003, 2011, and 2019 National Survey on Drug Use and Health datasets on individuals who met diagnostic criteria for CUD. Multivariate logistic regression models examined predictors of receiving CUD treatment compared to those who did not receive treatment. Results: Across timepoints, CUD treatment utilization decreased and most individuals with CUD did not receive treatment. Reasons for not receiving treatment varied, but results suggest people increasingly do not know where to access treatment or are not ready to stop use, could not afford treatment, and perceive stigma or occupational impact. Consistent predictors include receiving past-year mental health treatment and community supervision involvement. Hispanic individuals had significantly lower odds of CUD treatment compared to non-Hispanic White individuals in 2003, but not later years. Prior arrest was not significant in 2003 but was associated with 2-3 times higher odds of receiving CUD treatment in later years. Conclusions: CUD treatment is often overlooked compared to other substance use disorders. Dynamic treatment barriers and predictors of CUD treatment may highlight areas for targeted improvement of CUD treatment utilization.
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