Using SMART Design to Identify an Effective and Cost-Beneficial Approach to Preventing OUD in Justice-Involved Youth

项目摘要 阿片类药物使用和过量死亡一直在上升，特别是在COVID期间。参与法律的 系统（YILS）中阿片类药物使用障碍（OUD）的发病率最高;华盛顿州的当地发病率 青少年康复（WSJR）系统的方法是三分之一的青少年。在全国范围内，大多数YILS从事有问题的 非阿片类物质使用，OUD的关键风险因素。非阿片类物质使用障碍（SUD）和OUD， 反过来，这是两个最重要的预测因素，随后重新参与少年或刑事系统。在 为期5年的UG 3/UH 3赠款，西雅图儿童医院（SCH），华盛顿大学（UW）和WSJR是 合作评估基于青少年的不同强度的OUD预防干预措施 社区强化方法与断言持续护理（ACRA/ACC）。多项研究 已确定ACRA/ACC在减少SUD方面的有效性;但是，没有人将其评价为OUD预防。 我们正在使用SMART方法构建一个高质量的适应性干预（AI），包括ACRA/ACC- 基于两种不同强度的OUD预防策略。在为期2年的UG 3阶段，我们进行了一次试点 智能实验，31年。在我们为期3年的UH 3阶段，我们正在进行一项全面的SMART试验， 15-25比较我们在以下阶段的预防干预措施的效果：a）随着青年的过渡， （B）一旦他们返回社区（第2阶段）。我们管理自我报告 在基线、1个月、3个月和6个月进行电子调查，以收集主要结局数据（启动和升级 使用任何物质的天数和频率）和次要结果（数量 使用特定物质（包括阿片类药物）的天数/频率;我们将使用行政数据来衡量 累犯。我们也在进行全面的成本分析。目前，我们已经实现了招聘 和保留率，超过了我们的目标，写在家长补助金（72%和76%）。但由于 增加OUD率导致当前WSJR YILS中有资格纳入此 阿片类药物预防试验，平均刑期延长，人口普查中COVID减少，我们正在招募 是我们原先预计的周薪的一半按照目前的速度，187名青年将完成这项研究。这将 允许我们评估第1阶段干预对主要结局的影响，但可能限制我们评估第1阶段的能力 对一些次要结果或第2阶段影响的影响。在本行政补编中，我们力求 通过增加激励措施、增加食品奖励预算（ ACRA/ACC的标准部分），以及招聘人员/测量员和干预人员FTE的增加。我们寻求 将招聘率和保留率提高到85%，这将使我们能够招募和保留至少292人和248人 YILS，分别。这些增加的参与者将增加我们检测主效应的能力。 结果从80%到87，并将提供足够的把握度来评估对以下患者的小/中度1期影响： 次要结果和阶段2效应。

PROJECT SUMMARY Opiate use and overdose deaths have been rising, especially during COVID. Youth involved with the legal system (YILS) have some of the highest rates of opioid use disorder (OUD); local rates in the Washington State Juvenile Rehabilitation (WSJR) system approach 1 in 3 youth. Nationwide, most YILS engage in problematic non-opioid substance use, a critical risk factor for OUD. Non-opioid substance use disorders (SUDs) and OUDs, in turn, are two of the most important predictors of subsequent re-involvement in juvenile or criminal systems. In a 5-year UG3/UH3 grant, Seattle Children’s Hospital (SCH), University of Washington (UW), and WSJR are collaboratively evaluating OUD prevention interventions of varying intensities based on the Adolescent Community Reinforcement Approach with Assertive Continuing Care (ACRA/ACC). Multiple studies have established ACRA/ACC effectiveness in reducing SUD; however, none have evaluated it as OUD prevention. We are using SMART methods to construct ahigh-quality adaptive intervention (AI) containing ACRA/ACC- based OUD prevention strategies of two different intensities. In our 2-year UG3 phase, we conducted a pilot SMART experiment with 31 YILS. In our 3-year UH3 phase, we are conducting a full SMART trial with YILS aged 15-25 to compared effects of our prevention interventions during the following stages: a) as youth transition out of confinement (stage 1), and b) once they are back in the community (stage 2). We administer self-report electronic surveys at baseline, 1, 3, & 6 months to collect data on primary outcomes (initiation and escalation of use measured by number of days and frequency of use of any substances) and secondary outcomes (number of days/ frequency of use of specific substances including opioids); we will use administrative data to measure recidivism. We are also conducting comprehensive cost analyses. Currently, we have achieved recruitment and retention rates that exceeded our goals as written in the parent grant (72% and 76%). However, due to increasing OUD rates resulting in a smaller proportion of current WSJR YILS qualifying for inclusion in this opioid prevention trial, longer average sentence lengths, and COVID reductions in census, we are recruiting at ~half of the weekly rate we originally anticipated. At the current rates, 187 youth will finish the study. This will allow us to assess stage 1 intervention effects on primary outcomes but could limit our ability to assess stage 1 effects on some secondary outcomes or stage 2 effects. In the present administrative supplement, we seek to mitigate COVID effects on sample size via increased incentives, increased budget for food rewards (which are a standard part of ACRA/ACC), as well as increases in recruiter/surveyor and interventionist FTEs. We seek to boost both recruitment and retention rates to 85%, which will allow us to enroll and retain at least 292 and 248 YILS, respectively. These added participants will increase our power to detect main effects on primary outcomes from 80% to 87 and will provide sufficient power to assess small/moderate stage 1 effects on secondary outcomes and stage 2 effects.