Department of Psychiatry and Behavioral Sciences, College of Medicine, Medical University of South Carolina, Charleston, SC, United States.
Department of Health Policy & Behavioral Sciences, School of Public Health, Georgia State University, Atlanta, GA, United States.
J Subst Use Addict Treat. 2024 Jun;161:209335. doi: 10.1016/j.josat.2024.209335. Epub 2024 Mar 14.
Prior systematic and meta-analytic reviews observed mixed evidence for the efficacy of cannabis brief interventions (BIs). Inconsistent support for cannabis BIs may be the result of intersecting methodological factors, including intervention structure and content, participant eligibility criteria, and outcome assessment measures. The current systematic review of cannabis BI studies narratively synthesizes these data to guide intervention development decision-making in future cannabis BI studies (PROSPERO CRD42022285990).
We searched PubMed/MEDLINE, PsycINFO, and CINAHL databases in January 2022 and again in June 2023 to capture newly published studies. Studies were included if they were a randomized trial, enrolled adolescents (13-17) and/or young adults (18-30), specified cannabis use and/or problems inclusion criteria, and evaluated a cannabis BI (defined as ≤4 sessions). We extracted and synthesized data on intervention characteristics (e.g., components, length/duration, modality), cannabis inclusion criteria and recruitment setting, baseline cannabis use descriptives and treatment-seeking status, and outcome assessment measures to discern if/how they may intersect to determine intervention efficacy. The Cochrane Risk of Bias Tool 2 assessed study quality.
Our search resulted in a final sample of 25 study records including 4094 participants. Recruitment setting seemed to provide an influential backdrop for how well inclusion criteria determined baseline cannabis use level, as well as for the type/length of the BI evaluated. Motivational interviewing (MI) and personalized feedback (PF) were the most frequently used BI components overall; however, some differences were observed in the proportion of BIs with reported intervention effects using MI vs. PF. Frequency of use days was the most commonly used outcome measure, although this may not be the most sensitive measure for assessing cannabis BI efficacy.
Our systematic review indicates that cannabis BI studies require greater precision in their design, giving special attention to matching the content and structure of the BI to the needs of the target population and selecting outcomes commensurate to the goals of the BI and the target population to more accurately reflect the efficacy of the BI. However, consistent with prior reviews, all included studies demonstrated at least some concerns for risk of bias, and most were at high risk.
先前的系统评价和荟萃分析观察到大麻简短干预(BI)的疗效存在混合证据。大麻 BI 的不一致支持可能是由于相交的方法因素的结果,包括干预结构和内容、参与者资格标准和结果评估措施。目前对大麻 BI 研究的系统综述以叙述的方式综合了这些数据,以指导未来大麻 BI 研究中的干预发展决策(PROSPERO CRD42022285990)。
我们于 2022 年 1 月和 2023 年 6 月再次在 PubMed/MEDLINE、PsycINFO 和 CINAHL 数据库中进行了搜索,以捕获新发表的研究。如果研究是一项随机试验,招募青少年(13-17 岁)和/或年轻人(18-30 岁),规定了大麻使用和/或问题纳入标准,并评估了大麻 BI(定义为≤4 节),则将其纳入研究。我们提取并综合了干预特征的数据(例如,成分、长度/持续时间、模式)、大麻纳入标准和招募设置、基线大麻使用描述和治疗寻求状态,以及评估措施,以确定它们如何交叉以确定干预效果。Cochrane 风险偏倚工具 2 评估了研究质量。
我们的搜索结果最终得到了 25 份研究记录,包括 4094 名参与者。招募设置似乎为纳入标准确定基线大麻使用水平以及评估的 BI 的类型/长度提供了一个有影响力的背景。动机访谈(MI)和个性化反馈(PF)总体上是最常用的 BI 成分;然而,在使用 MI 与 PF 报告干预效果的 BI 比例方面观察到了一些差异。使用天数的频率是最常用的结果测量指标,尽管这可能不是评估大麻 BI 疗效的最敏感指标。
我们的系统评价表明,大麻 BI 研究需要在设计上更加精确,特别注意将 BI 的内容和结构与目标人群的需求相匹配,并选择与 BI 和目标人群的目标相匹配的结果,以更准确地反映 BI 的疗效。然而,与先前的综述一致,所有纳入的研究都至少存在一些偏倚风险的关注,并且大多数研究的偏倚风险较高。