Predictors of Residential Treatment Retention among Individuals with Co-Occurring Substance Abuse and Mental Health Disorders

• Published in: Journal of psychoactive drugs 2013-04, Vol.45 (2), p.122-131
• Main Authors: Choi, Sam, Adams, Susie M., MacMaster, Samuel A., Seiters, John
• Format: Article
• Language: English
• Subjects: Adult; Age Factors; co-occurring substance abuse and mental disorders; Comorbidity; Drug abuse; Female; Health Behavior; Health Knowledge, Attitudes, Practice; Humans; Length of Stay; Logistic Models; Male; Mental disorders; Mental Disorders - diagnosis; Mental Disorders - epidemiology; Mental Disorders - psychology; Middle Aged; Multivariate Analysis; Odds Ratio; Patient Acceptance of Health Care - statistics & numerical data; Patient Dropouts - psychology; Patient Dropouts - statistics & numerical data; predictors; Private Practice; Residential Facilities - statistics & numerical data; residential treatment; Retention; Risk Assessment; Risk Factors; Severity of Illness Index; Sex Factors; Socioeconomic Factors; Substance abuse treatment; Substance Abuse Treatment Centers - statistics & numerical data; Substance-Related Disorders - diagnosis; Substance-Related Disorders - epidemiology; Substance-Related Disorders - psychology; Substance-Related Disorders - rehabilitation; Time Factors; Treatment Outcome; United States; Young Adult
• ISSN: 0279-1072; 2159-9777
• DOI: 10.1080/02791072.2013.785817

A significant number of individuals with co-occurring substance abuse and mental health disorders do not engage, stay, and/or complete residential treatment. The purpose of this study is to identify factors during the initial phase of treatment which predict retention in private residential treatment for individuals with co-occurring substance use and mental health disorders. The participants were 1,317 individuals with co-occurring substance abuse and mental health disorders receiving treatment at three residential treatment centers located in Memphis, TN, Malibu, CA, and Palm Springs, CA. Bivariate analysis and logistic regression were utilized to identify factors that predict treatment retention at 30 days. The findings indicate a variety of factors including age, gender, types of drug, Addiction Severity Index Medical and Psychiatric scores, and readiness to change. These identified factors could be incorporated into pretreatment assessments, so that programs can initiate preventive measures to decrease attrition and improve treatment outcomes.