Design and methodological considerations of an effectiveness trial of a computer-assisted intervention: an example from the NIDA Clinical Trials Network

计算机辅助干预有效性试验的设计和方法学考量:以美国国家药物滥用研究所临床试验网络为例

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Abstract

Computer-assisted interventions hold the promise of minimizing two problems that are ubiquitous in substance abuse treatment: the lack of ready access to treatment and the challenges to providing empirically-supported treatments. Reviews of research on computer-assisted treatments for mental health and substance abuse report promising findings, but study quality and methodological limitations remain an issue. In addition, relatively few computer-assisted treatments have been tested among illicit substance users. This manuscript describes the methodological considerations of a multi-site effectiveness trial conducted within the National Institute on Drug Abuse's (NIDA's) National Drug Abuse Treatment Clinical Trials Network (CTN). The study is evaluating a web-based version of the Community Reinforcement Approach, in addition to prize-based contingency management, among 500 participants enrolled in 10 outpatient substance abuse treatment programs. Several potential effectiveness trial designs were considered and the rationale for the choice of design in this study is described. The study uses a randomized controlled design (with independent treatment arm allocation), intention-to-treat primary outcome analysis, biological markers for the primary outcome of abstinence, long-term follow-up assessments, precise measurement of intervention dose, and a cost-effectiveness analysis. Input from community providers during protocol development highlighted potential concerns and helped to address issues of practicality and feasibility. Collaboration between providers and investigators supports the utility of infrastructures that enhance research partnerships to facilitate effectiveness trials and dissemination of promising, technologically innovative treatments. Outcomes from this study will further the empirical knowledge base on the effectiveness and cost-effectiveness of computer-assisted treatment in clinical treatment settings.

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