التفاصيل البيبلوغرافية
| العنوان: |
A SMART data analysis method for constructing adaptive treatment strategies for substance use disorders. |
| المؤلفون: |
Nahum‐Shani, Inbal, Ertefaie, Ashkan, Lu, Xi (Lucy), Lynch, Kevin G., McKay, James R., Oslin, David W., Almirall, Daniel |
| المصدر: |
Addiction; May2017, Vol. 112 Issue 5, p901-909, 9p, 1 Diagram, 4 Charts |
| مصطلحات موضوعية: |
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 |
| مستخلص: |
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. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
