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The purpose of this study is to identify the relative strengths of association of medication and health and social services in comprehensive substance use disorder (SUD) treatment. The study uses a novel variance decomposition method to assess the relative strength of association of six active ingredients of comprehensive SUD treatment: methadone medication, access services, SUD counseling, matched service ratio, client-provider relationship, and treatment duration. The study uses data from the National Treatment Improvement Evaluation Study (1992-1997), a dataset with an unusual number of services and service strategies measured. The data include 3012 clients from 45 SUD treatment programs. Linear mixed models are used to assess the relation of service variables to the outcome of posttreatment substance use. Variance decomposition methods are used to assess the relative importance of the ingredients in the treatment model. Along with a random intercept and background variables, receipt of methadone accounted for the greatest relative strength of association at 35.4%, compared with 23.8% for treatment duration, 15.4% for client-provider relationship, and 11.2% for matched service ratio. Access and SUD counseling accounted for modest strengths of association at 1% and 3% each. Findings indicate somewhat greater strength of association of methadone compared with other services and service strategies and overall, reinforce the importance of both medication and services and service strategies in the design and development of effective models of service delivery. This study, among the first to evaluate the relative importance of specific services and service strategies of comprehensive SUD treatment, provides insights relevant to the development of effective models of service delivery. Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.


Hee-Choon Shin, Jeanne C Marsh. Identifying relative strength of methadone versus health and social services in comprehensive substance use disorder treatment using a variance decomposition approach. Evaluation and program planning. 2022 Jun;92:102060

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PMID: 35247677

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