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

毒品预防联盟数据驱动技术援助系统的随机试验

• 批准号: 10231215
• 负责人: Louis Davis Brown
• 金额: $ 71.86万
• 依托单位: UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-30 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10231215
• 关键词: Address; Affect; Area; Communities; Community Health; Data; Data Reporting; Development; Drug Addiction; Drug Prevention Program; Effectiveness; Ensure; Evidence based program; Feedback; Goals; Interactive Systems Framework; Measures; Mediator of activation protein; Mission; Modeling; Monitor; National Institute of Drug Abuse; Outcome; Pathway interactions; Pharmaceutical Preparations; Policies; Prevention; Probability; Provider; Public Health; Randomized; Reporting; Research; Series; Strategic Planning; Structure; Support System; System; Team Process; Techniques; Testing; Work; Youth; adolescent drug use; adolescent substance use; base; checkup examination; cost; drug abuse prevention; evidence base; implementation science; improved; innovation; insight; intrinsic motivation; member; motivational enhancement therapy; operation; prevent; programs; randomized trial; research to practice; substance use prevention; therapy design

Project Summary/Abstract: 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.

项目总结/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 (CCU)支持社区联盟实施证据的技术援助（TA）系统- 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， 很多人缺乏能力。CCU TA支持联盟识别和解决其EBP中的差距 执行能力。拟议的研究通过应用Wandersman的 测试CCU对联盟EBP执行能力和青年的影响的交互式系统框架 结果。尽管毒品预防联盟作为EBP传播机制很受欢迎， 一直很少研究如何有效地支持联盟的最佳EBP实施。缺乏 足够的支持，联盟和EBP往往失败，和TA提供的证据为基础的联盟模型， 通常太昂贵而无法在现实世界中扩展。CCU提供了一种成本较低的TA系统， 适用于各种联盟模式。我们的主要目的是测试CCU的整体成效，包括 它如何有助于EBP的实施和预防青少年药物使用。建立在互动的基础上 系统框架，我们的中心假设是，CCU，作为执行支持系统的一部分， 增加了EBP实施的联盟能力，从而增加了EBP减少的可能性。 青少年吸毒我们将通过以下三个方面来检验这一中心假设和我们更大的概念模型： 明确的目标。第一个目标是估计CCU对联盟能力的影响。联盟将是 随机分配给CCU或“没有TA的数据报告”条件，以评估CCU是否改善 联盟能力，通过联盟成员对团队流程、网络组成和 协作结构。第二个目标是估计CCU对EBP执行的影响， 包括EBP覆盖范围、实施质量和可持续性。第三个目标是估计 青少年药物滥用问题CCU。CCU在强调主动监测和数据驱动方面具有创新性 TA，其使用动机访谈，以加强联盟驱动的行动规划，并检查 网络结构，以提高联盟的能力。这项研究的贡献非常重要，因为 该领域目前缺乏明确的证据来证明适用于异质混合的技术援助模式的有效性 毒品预防联盟在运作。该研究将提高社区联盟的能力， 预防毒品方案拟订中的研究与实践差距。预计结果将对以下方面产生积极影响： 通过为低成本、数据驱动、手动化的技术援助模型建立证据基础， 如何对社区联盟进行干预以支持循证药物持续实施 预防计划和政策，以促进社区健康。