Modelers and Storytellers: Transdisciplinary Training to Advance Community Health Intervention Research

建模者和故事讲述者：跨学科培训以推进社区健康干预研究

• 批准号: 10663806
• 负责人: MICHAEL Lee PRELIP
• 金额: $ 18.72万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10663806
• 关键词: Acceleration; Address; Advisory Committees; Affect; Behavioral Sciences; Big Data; Biometry; Canada; Cluster randomized trial; Collaborations; Communities; Community Health; Complex; Computer Models; Computer software; Computing Methodologies; Data Science; Development; Discipline; Disparate; Eating; Educational Curriculum; Educational process of instructing; Environment; Epidemiology; Equity; Evaluation; Familiarity; Family; Foundations; Funding; Generations; Goals; Health; Health Policy; Health Sciences; Health behavior; Intervention; Intervention Studies; Knowledge; Mathematics; Methods; Modeling; Physical activity; Play; Policies; Policy Maker; Postdoctoral Fellow; Public Health; Reduce health disparities; Research; Research Personnel; Risk; Role; Saskatchewan; Schools; Science; Scientist; Social Sciences; System; Time; Training; Training Programs; Training Support; Translational Research; United States National Institutes of Health; Universities; Work; behavioral and social science; cohort; computational reasoning; computer science; design; early childhood; education research; educational atmosphere; experience; health disparity; innovation; insight; interest; knowledge integration; large datasets; learning strategy; lens; member; multidisciplinary; obesity in children; pre-doctoral; professor; programs; recruit; research to practice; scale up; skills; social health determinants; summer research; theories; therapy development; trial design; virtual

PROJECT ABSTRACT The accumulation of epidemiologic evidence on the roles that policies, systems and environments (PSE) play in influencing health behaviors such as eating and physical activity has led to increased interest in applying the socio-ecological framework and community-engaged approaches to the development of “multi- level interventions” targeting at-risk communities. Evaluation of such innovative interventions, often to address social determinants of health and reduce health disparities, is often challenged as it may be impractical to use the `gold-standard' cluster randomized trial design. Further, the social and behavioral science theories that provide the foundation for the development of interventions may be overlooked when efforts are made to scale- up an intervention. Systems science methods, which have been used to investigate complex causal mechanisms, have been proposed as an alternative for evaluating such interventions. However, their application, which typically involves computational modeling, requires researchers from disparate disciplines to integrate their knowledge and skills at a level that can be difficult to attain. The proposed summer research education program aims to create a learning environment that will support the training of researchers from diverse disciplines to collaborate effectively with each other and with community stakeholders, with the goal of accelerating the translation of research into practice. Specifically, over three summers, it will (i) provide 75 researchers (pre-docs, postdocs, investigators) interested in addressing social determinants of health, with the basic knowledge and skills necessary for applying systems science and data science methods, while also (ii) providing more advanced knowledge and skills to apply either of these methods as well as foundational knowledge of social and behavioral science theories and approaches, to researchers in quantitative methods-focused disciplines (such as math, computer science, biostatistics). In addition, this program will also (iii) provide a three-week practicum to 30 of the 75 trainees who are interested in gaining hands-on experience in working with large datasets. The proposed program will consist of two components: (i) a 3-week curriculum consisting of virtual didactic sessions with learning activities; and (ii) a 3-week practicum for a subset of trainees who will work closely with each other to build and refine agent-based models and interpret results for policy-makers with the engagement of stakeholders. The recruitment and selection plan will be developed with an equity lens, and with an Advisory Committee providing guidance and oversight. To create the learning environment for this training program, we will select applicants to create a cohort that is also diverse in academic background and lived experiences.

项目摘要 关于政策、系统和环境 (PSE) 作用的流行病学证据的积累 影响健康行为（例如饮食和身体活动）的游戏引起了人们对 应用社会生态框架和​​社区参与的方法来发展“多 针对高危社区的此类创新干预措施的评估，通常是为了解决问题。 健康的社会决定因素并减少健康差距，经常受到挑战，因为使用起来可能不切实际 此外，“黄金标准”的整群随机试验设计还包括社会和行为科学理论。 当努力扩大规模时，为制定干预措施提供基础可能会被忽视。 系统科学方法已被用于研究复杂的因果关系。 机制，已被提议作为评估此类干预措施的替代方案。 应用程序通常涉及计算建模，需要来自不同学科的研究人员 将他们的知识和技能整合到难以达到的水平。 拟议的夏季研究教育计划旨在创造一个学习环境，以支持 培训来自不同学科的研究人员，使其能够有效地相互合作以及与 社区利益相关者的目标是加速研究成果转化为实践。 在三个夏天，它将 (i) 提供 75 名感兴趣的研究人员（博士前、博士后、研究人员） 解决健康的社会决定因素，具备应用系统所需的基本知识和技能 科学和数据科学方法，同时还（ii）提供更先进的知识和技能来应用 这些方法以及社会和行为科学理论的基础知识和 方法，面向以定量方法为重点的学科（例如数学、计算机科学、 此外，该计划还将 (iii) 为 75 名学员中的 30 名提供为期三周的实习机会。 有兴趣获得处理大型数据集的实践经验。 拟议的计划将由两个部分组成：(i) 为期 3 周的课程，包括虚拟教学 包含学习活动的课程；以及 (ii) 为一部分学员提供为期 3 周的实习，他们将与他们密切合作 彼此建立和完善基于代理的模型，并通过参与为政策制定者解释结果 招聘和选拔计划将通过公平视角和咨询来制定。 委员会提供指导和监督，为该培训计划创造学习环境。 将选择申请人来创建一个学术背景和生活经历也多样化的群体。