Pilot & Feasibility Program

P&F计划：计划摘要/摘要 佐治亚州糖尿病翻译研究中心的试点和可行性(P&F)计划 通过发展初级和代表性不足的少数族裔，在催化高回报投资方面发挥关键作用 调查人员，吸引过渡的调查人员，并显著增加了NIH的广度和深度- 资助美国东南部跨学科的糖尿病翻译合作研究。P&F计划 支持高影响研究，以促进不同人群的健康公平 糖尿病负担。P&F计划是一项中心范围的活动(位于核心A)，旨在支持 调查人员进行研究，解决GCDTR翻译研究的优先重点领域 核心：公平的设计和评估(核心B)、社会生态和行为科学的公平(核心 C)，并使用促进翻译和公平的技术(区域核心)，以将GCDTR的覆盖范围扩大到 佛罗里达州和田纳西州的邻近机构。GCDTR旨在通过减少 我们成员中的种族/民族、性别、年龄、社会经济、共同发病率和地理差异 我们的研究。P&F计划与GCDTR的岩心和浓缩计划的整合确保了 该试点研究的调查人员将在国家认可的核心专家的支持下进行创新 研究使用最先进的技术和参与方法、创新的设计和多种 纪律评估方法。在赠款年度1-4，P&F方案资助了18笔赠款，这些赠款导致 联邦政府资助的13项奖励，每发放1美元可获得23美元的回报。P&F计划的主要作用是 TO：作为资金催化剂(目标1)；通过将有抱负的人与 具有GCDTR核心专家的申请者(目标2)；并发展不同和多学科的社区 通过研究提高试点研究/调查人员的工作效率、可见性和影响力 职业和传播技能培训(目标3)。这些目标将通过创新实现，例如： GCDTR机构为共同支持试点作出的相应资源承诺(5年内总计857,500美元) 研究；小额赠款计划；一个多学科、多机构的审查小组，负责监督P&F奖 遴选；与有抱负的调查人员充实方案共同主办技能发展模块；新 在提交申请前将P&F申请者与核心专家联系起来的流程；创新的指导对象- 指导计划，包括引导试点获奖者过渡到指导其他人；以及高效 利用美国国立卫生研究院资助的其他项目。基于GCDTR广泛的研究基础、有影响力的科学和试点 迄今为止的成果，以及与社区、临床中心以及地方和联邦政府接触的丰富历史 在该地区的卫生机构，P&F调查人员可以接触到一些最好的糖尿病导师 翻译研究，对弱势群体的研究不足，以及未充分利用但健壮的数据集。

P&F PROGRAM: PROGRAM SUMMARY / ABSTRACT The Pilot and Feasibility (P&F) Program of the Georgia Center for Diabetes Translation Research (GCDTR) serves a pivotal role in catalyzing high-return investments by developing junior and underrepresented minority investigators, attracting transitioning investigators, and significantly adding to the breadth and depth of NIH- funded collaborative interdisciplinary diabetes translation research in the Southeastern U.S.. The P&F Program supports high impact studies to promote health equity for diverse populations with disproportionately high diabetes burdens. The P&F Program is a center-wide activity (situated in Core A) designed to support investigators in conducting studies that address the priority focal areas of GCDTR's Translation Research Cores: Design and Evaluation for Equity (Core B), Socio-ecological and Behavioral Science for Equity (Core C), and engage Technologies Advancing Translation and Equity (Regional Core) to extend GCDTR's reach to neighboring institutions in Florida and Tennessee. The GCDTR aims to promote equity by reducing race/ethnic, gender, age, socioeconomic, co-morbidity, and geographical disparities in our membership and our research. The integration of the P&F Program with GCDTR's Cores and Enrichment Program ensures that pilot study investigators will be supported by nationally-recognized Core Experts in conducting innovative studies using state-of-the-art technologies and engagement methodologies, innovative designs, and multi- disciplinary evaluation approaches. In grant years 1-4, the P&F Program funded 18 grants which have led to 13 federally-funded awards yielding a $23 return on every dollar granted. The P&F Program's main roles are to: serve as a funding catalyst (Aim 1); support high-quality health equity research through linking aspiring applicants with GCDTR's Core Experts (Aim 2); and grow the community of diverse and multidisciplinary investigators by enhancing the productivity, visibility, and impact of pilot studies/investigators through research career and dissemination skills training (Aim 3). These aims will be accomplished through innovations such as: matched resource commitments (totaling $857,500 over 5 years) from GCDTR institutions to co-support pilot studies; a Micro Grants program; a multi-disciplinary, multi-institutional review group to oversee P&F award selection; co-hosting skills development modules with the Enrichment Program for aspiring investigators; new processes to link P&F applicants with Core Experts prior to submitting their applications; an innovative mentee- to-mentor program that involves guiding pilot grant awardees to transition to mentoring others; and efficiently leveraging other NIH-funded programs. Based on GCDTR's broad research base, impactful science and pilot outcomes to date, and rich history of engagement with communities, clinical centers, and local and federal health agencies in the region, P&F investigators have access to some of the finest mentors in diabetes translation research, understudied vulnerable populations, and underused but robust datasets.