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A study of psychological pain in substance use disorder and its relationship to treatment outcome
S. Mee, B. G. Bunney, K. Fujimoto, J. Penner, G. Seward, W. E. Bunney, C. Reist
Abstract
Substance Use Disorder (SUD) is a major public health concern affecting an estimated 22.5 million individuals in the United States. The primary aim of this study was to characterize psychological pain in a cohort of patients participating in outpatient substance abuse treatment. A secondary aim was to determine the relationships between pre-treatment assessments of psychological pain, depression, anxiety and hopelessness with treatment retention time and completion rates. Data was analyzed from 289 patients enrolled in an outpatient community drug treatment clinic that provides mental healthcare to the underserved. A previously determined threshold score on the Mee-Bunney Psychological Pain Assessment Scale (MBP) was utilized to group patients into high and low-moderate scoring subgroups. The higher pain group reported increased levels of anxiety, hopelessness and depression compared to those in the low-moderate pain group. Additionally, patients scoring in the higher psychological pain group exhibited reduced retention times in treatment and more than two-fold increased odds of dropout relative to patients with lower pre-treatment levels of psychological pain. Among all assessments, the correlation between psychological pain and treatment retention time was strongest. To our knowledge, this is the first study to demonstrate that psychological pain is an important construct that correlates with relevant clinical outcomes in substance abuse treatment. Further, pre-treatment screening for psychological pain may be of benefit in identifying higher-risk patients in need of targeted additional clinical resources to improve treatment retention and completion rates.
- organism: human
- assay: clinical cohort / trial
- research focus: host-pathogen & immune response
- research focus: cell type annotation
- research focus: differential expression
- approach: statistical model
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