PDF(Pubmed)
Abstract：
BACKGROUND: 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).
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.
摘要：
背景：先前的系统和荟萃分析综述观察到大麻简短干预（BIs）有效性的混合证据。对大麻BI的不一致支持可能是方法学因素交叉的结果，包括干预结构和内容，参与者资格标准，和结果评估措施。当前对大麻BI研究的系统评价叙述地综合了这些数据，以指导未来大麻BI研究中的干预发展决策（PROSPEROCRD42022285990）。
方法：我们搜索了PubMed/MEDLINE，PsycINFO,和CINAHL数据库在2022年1月和2023年6月再次捕获新发表的研究。如果研究是一项随机试验，注册青少年（13-17）和/或年轻人（18-30），指定的大麻使用和/或问题纳入标准，并评估了大麻BI（定义为≤4个疗程）。我们提取并合成了有关干预特征的数据(例如，组件,长度/持续时间，模态)，大麻纳入标准和招聘设置，基线大麻使用描述和寻求治疗状态，和结果评估措施，以辨别它们是否/如何相交，以确定干预效果。Cochrane偏差风险工具2评估研究质量。
结果：我们的搜索结果最终得到了25个研究记录的样本，包括4094名参与者。招聘设置似乎为纳入标准确定基线大麻使用水平提供了有影响力的背景，以及评估的BI的类型/长度。激励式访谈(MI)和个性化反馈(PF)是总体上最常用的BI组件；然而，使用MI与已报告干预效果的BI的比例观察到一些差异。PF.使用天数是最常用的结果衡量标准，尽管这可能不是评估大麻BI疗效的最敏感指标。
结论：我们的系统评价表明，大麻BI研究需要更高的设计精度，特别注意使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称的结果，以更准确地反映BI的功效。然而,与以前的评论一致，所有纳入的研究至少表明了一些对偏见风险的担忧，大多数人都处于高风险之中。
方法：我们搜索了PubMed/MEDLINE，PsycINFO,和CINAHL数据库在2022年1月和2023年6月再次捕获新发表的研究。如果研究是一项随机试验，注册青少年（13-17）和/或年轻人（18-30），指定的大麻使用和/或问题纳入标准，并评估了大麻BI（定义为≤4个疗程）。我们提取并合成了有关干预特征的数据(例如，组件,长度/持续时间，模态)，大麻纳入标准和招聘设置，基线大麻使用描述和寻求治疗状态，和结果评估措施，以辨别它们是否/如何相交，以确定干预效果。Cochrane偏差风险工具2评估研究质量。
结果：我们的搜索结果最终得到了25个研究记录的样本，包括4094名参与者。招聘设置似乎为纳入标准确定基线大麻使用水平提供了有影响力的背景，以及评估的BI的类型/长度。激励式访谈(MI)和个性化反馈(PF)是总体上最常用的BI组件；然而，使用MI与已报告干预效果的BI的比例观察到一些差异。PF.使用天数是最常用的结果衡量标准，尽管这可能不是评估大麻BI疗效的最敏感指标。
结论：我们的系统评价表明，大麻BI研究需要更高的设计精度，特别注意使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称的结果，以更准确地反映BI的功效。然而,与以前的评论一致，所有纳入的研究至少表明了一些对偏见风险的担忧，大多数人都处于高风险之中。
