Using Multiphase Optimization Strategy (MOST) to Optimize a Cost-effective, Sustainable and Scalable Smoking Cessation Package for Smokers in HIV Clinical Care

使用多阶段优化策略 (MOST) 为 HIV 临床护理中的吸烟者优化具有成本效益、可持续且可扩展的戒烟方案

基本信息

  • 批准号:
    10548592
  • 负责人:
  • 金额:
    $ 66.84万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-07-01 至 2027-06-30
  • 项目状态:
    未结题

项目摘要

Project Summary The adverse health impact of cigarette smoking on persons living with HIV is profound and effective treatments for long-term abstinence remain elusive. There is an acute need for interventions that address patient barriers to quitting and clinical barriers to effectively treating a broad heterogeneous population of smokers living with HIV (SLWH). This study’s long-term goal is to improve clinical outcomes among SLWH by providing optimized smoking cessation interventions in HIV clinical care. This proposal will use the Multiphase Optimization STrategy (MOST) to test four intervention components aimed at barriers to quitting among SLWH, with the objective of selecting the set that constitutes a cost-effective, sustainable, scalable smoking cessation package for HIV clinical care. Components include: Motivational Interviewing (Off/On); Peer Mentoring (Off/On); Text-messaging (Off/On); Varenicline or Combination Nicotine Replacement Therapy (Off/On). These components have shown promise in research but are under-utilized to help SLWH quit and have not been tested in an optimization trial. The proposed MOST factorial optimization trial is a highly efficient method for estimating the main effect contribution of each intervention component and all interactions between components. This approach addresses weaknesses in prior studies, which are not able to assess the contribution of individual components of multicomponent interventions. The proposal will also include a rigorous evaluation of the implementation process and theory-driven assessment of barriers to and facilitators of intervention implementation, sustainability and scalability in HIV clinical care. Aims include: (1) Assess the effectiveness of four smoking cessation intervention components on long-term abstinence among SLWH by conducting a highly efficient factorial optimization trial (i.e., MOST) with 500 SLWH in HIV clinical care. (2) Assess costs and the implementation process, including factors that affect the potential for sustainability and scalability of cessation treatment in HIV care settings serving SLWH. Guided by Proctor’s Implementation Outcomes Framework and the Consolidated Framework for Implementation Research, we will collect mixed methods data on reach, fidelity, acceptability and appropriateness among SLWH, stakeholders and study interventionists. (3) Identify the optimized intervention by conducting an innovative multi-criteria decision analysis to select the subset of the four components that achieves the highest level of cost-effectiveness and is both scalable and sustainable in HIV clinical care. Working in collaboration with New York City Health and Hospitals (H+H), the largest municipal public healthcare system in the U.S., and a team with unparalleled expertise in intervention optimization, smoking cessation and HIV/AIDS, the proposed study responds directly to the National Cancer Institute’s (NCI) call for smoking research that “optimizes intervention effectiveness, implementation and sustainability.” The optimized intervention will have a significant public health impact and add to scientific knowledge by providing a clear basis for further improvement of cessation interventions for SLWH in future research.
项目总结

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
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Jennifer Cantrell其他文献

Jennifer Cantrell的其他文献

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{{ truncateString('Jennifer Cantrell', 18)}}的其他基金

Using Multiphase Optimization Strategy (MOST) to Optimize a Cost-effective, Sustainable and Scalable Smoking Cessation Package for Smokers in HIV Clinical Care
使用多阶段优化策略 (MOST) 为 HIV 临床护理中的吸烟者优化具有成本效益、可持续且可扩展的戒烟方案
  • 批准号:
    10649607
  • 财政年份:
    2022
  • 资助金额:
    $ 66.84万
  • 项目类别:

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