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美沙酮治疗项目留存率的预测因素:信号检测分析

Predictors of retention in methadone programs: a signal detection analysis.

作者信息

Villafranca Steven W, McKellar John D, Trafton Jodie A, Humphreys Keith

机构信息

Center for Health Care Evaluation, Veterans Affairs Palo Alto Health Care System & Stanford University School of Medicine, CA, USA.

出版信息

Drug Alcohol Depend. 2006 Jul 27;83(3):218-24. doi: 10.1016/j.drugalcdep.2005.11.020. Epub 2005 Dec 27.

Abstract

Retention in Opioid Agonist Therapy (OAT) is associated with reductions in substance use, HIV risk behavior, and criminal activities in opioid dependent patients. To improve the effectiveness of treatment for opioid dependence, it is important to identify predisposing characteristics and provider-related variables that predict retention in OAT. Participants include 258 veterans enrolled in 8 outpatient methadone/l-alpha-acetylmethadol (LAAM) treatment programs. Signal detection analysis was utilized to identify variables predictive of 1-year retention and to identify the optimal cut-offs for significant predictors. Provider-related variables play a vital role in predicting retention in OAT programs, as higher methadone dose (> or =59 mg/day) and greater treatment satisfaction were among the strongest predictors of retention at 1-year follow-up.

摘要

接受阿片类激动剂治疗(OAT)的留存率与阿片类药物依赖患者的物质使用减少、HIV风险行为降低以及犯罪活动减少相关。为提高阿片类药物依赖治疗的有效性,识别预测OAT留存率的易感特征和与提供者相关的变量非常重要。研究参与者包括258名参加8个门诊美沙酮/左旋-α-乙酰美沙醇(LAAM)治疗项目的退伍军人。采用信号检测分析来识别预测1年留存率的变量,并确定显著预测因素的最佳临界值。与提供者相关的变量在预测OAT项目的留存率方面起着至关重要的作用,因为较高的美沙酮剂量(≥59毫克/天)和更高的治疗满意度是1年随访时留存率最强的预测因素之一。

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