Randomized trial of a data-driven technical assistance system for drug prevention coalitions

项目摘要 家长奖总结/摘要：这项为期五年的R 01研究的总体目标是测试联盟检查- UP（CCU）技术援助（TA）系统，用于支持社区联盟实施证据- 毒品预防计划（EBP）。社区联盟是联邦毒品预防的基石 政策，但只有在实施EBP时才能证明在预防药物使用方面的有效性， 很多人缺乏。CCU TA支持联盟确定和解决其EBP实施能力的差距。 这项研究通过应用Wandersman的交互系统推进了实施科学 测试CCU对联盟EBP执行能力和青年成果的影响的框架。尽管 毒品预防联盟作为EBP传播机制的普及，很少有研究 如何有效地支持联盟，以实现最佳的EBP实施。缺乏足够的支持，联盟 EBP经常失败，基于证据的联盟模型提供的TA通常过于昂贵，无法扩展 真实世界的设置。CCU提供了一种成本较低的TA系统，广泛适用于各种联盟模式。 我们的主要目标是测试CCU的整体有效性，包括它对EBP的贡献 执行和预防青少年使用药物。建立在互动系统框架，我们的 中心假设是，作为实施支持系统的一部分，作战协调单元提高了联合作战能力 为EBP的实施，从而增加EBP将减少青年物质使用的可能性。我们将 通过追求三个具体目标来测试这个中心假设和我们更大的概念模型。第一个目标是 估计CCU对联盟能力的影响。联盟将被随机分配到CCU或“数据 报告没有TA的条件，以评估CCU是否提高了联盟的能力，如联盟所测量的 团队流程、网络组成和协作结构的成员报告。第二个目标是 评估CCU对EBP实施的影响，包括EBP覆盖范围、实施质量， 和可持续性。第三个目标是估计CCU对青少年药物使用的影响。CCU是 创新性地强调主动监测和数据驱动的技术评估，使用动机性访谈， 加强联盟驱动的行动规划，并加强对网络结构的审查，以提高联盟能力。 这项研究的贡献是非常重要的，因为该领域目前缺乏明确的证据， 一个适用于各种不同的预防毒品联盟的技术援助模式的有效性。的 研究将加强社区联盟的能力，以弥合药物预防研究与实践之间的差距 编程.预计这些成果将通过建立以下方面的证据基础，对实地产生积极影响： 一个低成本、数据驱动、手动化的TA模型，确定如何与社区联盟进行干预， 支持持续实施以证据为基础的毒品预防方案和政策， 社区健康。我们的主要目标是测试CCU的整体有效性，包括它如何做出贡献 EBP的实施和预防青少年药物使用。在交互式系统框架的基础上， 我们的中心假设是，CCU可以加强预防支持系统，从而增加联盟 EBP的实施能力和EBP将减少青少年药物使用的可能性。本研究 将为可扩展的TA模型建立证据基础，指出如何与社区联盟进行干预， 最大化EBP的保真度和可持续性。

PROJECT SUMMARY Summary/Abstract of Parent Award: The overall goal of this five-year R01 study is to test the Coalition Check- Up (CCU) technical assistance (TA) system for supporting community coalitions' implementation of evidence- based drug prevention programs (EBPs). Community coalitions are a cornerstone of federal drug prevention policy but have only demonstrated efficacy in preventing substance use when they implement EBPs, a capacity many lack. CCU TA supports coalitions in identifying and addressing gaps in their EBP implementation capacity. The proposed study advances implementation science by applying Wandersman's Interactive Systems Framework to test the effects of CCU on coalition EBP implementation capacity and youth outcomes. Despite the popularity of drug prevention coalitions as a mechanism for EBP dissemination, there has been little research on how to effectively support coalitions for optimal EBP implementation. Lacking adequate support, coalitions and EBPs often fail, and TA as provided in evidence-based coalition models is often too expensive to scale in real-world settings. The CCU provides a lower-cost TA system that is broadly applicable across coalition models. Our main objective is to test the overall effectiveness of the CCU, including how it contributes to EBP implementation and prevention of youth substance use. Building on the Interactive System Framework, our central hypothesis is that the CCU, as part of the implementation support system, increases coalition capacity for EBP implementation, thereby increasing the probability that EBPs will reduce youth substance use. We will test this central hypothesis and our larger conceptual model by pursuing three specific aims. The first aim is to estimate the impact of the CCU on coalition capacity. Coalitions will be randomly assigned to the CCU or a 'data report without TA' condition to evaluate whether the CCU improves coalition capacity as measured by coalition member reports of team processes, network composition, and collaborative structure. The second aim is to estimate the impact of the CCU on the implementation of EBPs, including EBP reach, implementation quality, and sustainability. The third aim is to estimate the impact of the CCU on youth substance use. The CCU is innovative in its emphasis on proactive monitoring and data-driven TA, its use of motivational interviewing to enhance coalition-driven action planning, and its examination of network structure to enhance coalition capacity. The proposed study's contribution is highly significant because the field currently lacks clear evidence of the effectiveness of a TA model applicable to the heterogeneous mix of drug prevention coalitions in operation. The research will enhance community coalition ability to bridge the research to practice gap in drug prevention programming. Results are expected to have a positive impact on the field by establishing the evidence-base for a low-cost, data-driven, manualized TA model that identifies how to intervene with community coalitions to support sustained implementation of evidence-based drug prevention programs and policies known to promote community health. Our main objective is to test the overall effectiveness of the CCU, including how it contributes to EBP implementation and prevention of youth substance use. Building on the Interactive System Framework, our central hypothesis is that the CCU can enhance the prevention support system, thereby increasing coalition capacity for EBP implementation and the probability that EBPs will reduce youth substance use. This research will build the evidence-base for a scalable TA model, indicating how to intervene with community coalitions to maximize EBP fidelity and sustainability.