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- Title
A SMART data analysis method for constructing adaptive treatment strategies for substance use disorders.
- Authors
Nahum‐Shani, Inbal; Ertefaie, Ashkan; Lu, Xi (Lucy); Lynch, Kevin G.; McKay, James R.; Oslin, David W.; Almirall, Daniel
- Abstract
Aims To demonstrate how Q-learning, a novel data analysis method, can be used with data from a sequential, multiple assignment, randomized trial (SMART) to construct empirically an adaptive treatment strategy (ATS) that is more tailored than the ATSs already embedded in a SMART. Method We use Q-learning with data from the Extending Treatment Effectiveness of Naltrexone (ExTENd) SMART ( N = 250) to construct empirically an ATS employing naltrexone, behavioral intervention, and telephone disease management to reduce alcohol consumption over 24 weeks in alcohol dependent individuals. Results Q-learning helped to identify a subset of individuals who, despite showing early signs of response to naltrexone, require additional treatment to maintain progress. Conclusions Q-learning can inform the development of more cost-effective, adaptive treatment strategies for treating substance use disorders.
- Subjects
ALCOHOLISM treatment; SUBSTANCE abuse treatment; ALCOHOLISM; BEHAVIOR therapy; CONFIDENCE intervals; COST effectiveness; EXPERIMENTAL design; NALTREXONE; QUESTIONNAIRES; REGRESSION analysis; RESEARCH funding; SUBSTANCE abuse; TELEMEDICINE; DISEASE management; DATA analysis; TREATMENT effectiveness; DATA analysis software; DESCRIPTIVE statistics
- Publication
Addiction, 2017, Vol 112, Issue 5, p901
- ISSN
0965-2140
- Publication type
Article
- DOI
10.1111/add.13743