Short Courses on the Conduct of Reproducible Aging Research with Big Data

利用大数据进行可重复衰老研究的短期课程

• 批准号: 10681414
• 负责人: JUNE ML CHAN
• 金额: $ 15.01万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-15 至 2027-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10681414
• 关键词: Acceleration; Active Learning; Address; Administrator; Aging; Applications Grants; Attitude; Behavioral; Behavioral Research; Benchmarking; Big Data; Biometry; California; Code; Cognition; Communities; Complex; Critiques; Data; Data Analyses; Data Collection; Data Set; Data Sources; Discipline; Documentation; Ecosystem; Educational Curriculum; Elderly; Elements; Epidemiology; Evaluation; Face; Fostering; Foundations; Health; Hybrids; Hygiene; Interdisciplinary Study; Learning; Learning Module; Measures; Mental Depression; Methodology; Nature; Participant; Persons; Physicians; Postdoctoral Fellow; Preparation; Professional Role; Proliferating; Protocols documentation; Publications; Publishing; Quality Control; Reporting; Reproducibility; Research; Research Design; Research Personnel; Research Training; San Francisco; Science; Scientific Advances and Accomplishments; Scientist; Sea; Series; Social Sciences; Technical Expertise; Techniques; Trainers Training; Training; Training Activity; Training Programs; Universities; Work; aging population; behavioral and social science; career; complex data; computing resources; course module; data quality; disability; dissemination strategy; hands-on learning; health disparity; healthy aging; journal article; learning strategy; population health; programs; racism; response; satisfaction; self-directed learning; skills; social; social epidemiology; social integration; social science research; symposium; tool

ABSTRACT A sea-change in attitudes towards reproducible research in social science and epidemiology has occurred over the past 30 years. Reproducibility has moved from a footnote to center-stage and is now recognized as an essential component of scientific rigor. The concepts of reproducible science relate not only to the capacity to reproduce the work of a specific study when using the same data, but to the larger ecosystem in which research is planned, fielded, critiqued, and interpreted. Systemic biases and error-prone research pipelines both compromise reproducibility and are now recognized to hinder scientific progress. The nature of research has also evolved, with increasing emphasis on data analysis, growing access to extensive computational power, and large, complex data sets. Behavioral and social science research on healthy aging faces special concerns for reproducibility and these concepts should be integral to training on aging research. The University of California, San Francisco Training in Reproducible Research on Aging for Social Science and Epidemiology (UCSF-TRASE) program will develop (AIM 1) intensive short courses on reproducible research perspectives and skills. We propose four brief (3-day), intensive training modules. Each module combines didactics and experiential learning, with a substantive focus on health disparities and aging, and methodologic focus on causal inference. Module 1 introduces concepts of reproducibility for research on population health and aging. This module is appropriate for researchers and consumers of scientific research and will provide critical evaluation skills relevant for reviewing journal articles and grant applications, interpreting published findings, and leading research Module 1 assumes a basic scientific research background but will be accessible to, for example, practicing physicians, science journalists, administrators, as well as graduate and post-doctoral trainees. Module 2 provides skills for implementing reproducible analyses, such as pre-registration; statistical coding hygiene and evaluation; transparent reporting; and documentation, including for collaborative projects. Module 3 addresses fielding primary data collection to foster reproducibility, considering study design, statistical power, protocol documentation, data quality control. Module 4 provides training on integrating evidence to enhance reproducibility of scientific advances, e.g., meta-research, evidence triangulation approaches. Each training module can stand alone or be combined for a more comprehensive skill set. We emphasize hands-on skills building to learn best practices in the context of contemporary problems. The modules build on the outstanding foundation in the existing UCSF training programs, using many activities already demonstrated to succeed in our other training programs, and curating for the intensive short-course format to provide participants, across career stages, with both conceptual and technical skills to enhance reproducibility. We propose (AIM 2) to roll out the modules with ongoing evaluation and refinement and (AIM 3) use multiple dissemination strategies to maximize the impact of the curriculum.

摘要 在社会科学和流行病学中，人们对可重复研究的态度发生了翻天覆地的变化 在过去的30年里。可再生性已经从脚注走到了舞台的中心，现在被公认为 科学严谨性的基本组成部分。可再生科学的概念不仅涉及到 当使用相同的数据时，复制特定研究的工作，但在更大的生态系统中 研究是计划的、现场的、批评的和解释的。系统性偏差和容易出错的研究管道 两者都损害了重复性，现在被认为是阻碍科学进步的因素。研究的性质 也发生了变化，越来越重视数据分析，越来越多地获得广泛的计算 电力，以及庞大、复杂的数据集。健康老龄化面临特殊的行为和社会科学研究 对可再生性和这些概念的关注应成为老龄研究培训的组成部分。 加州大学旧金山分校关于社会老龄化的可重复研究培训 科学和流行病学(加州大学旧金山分校-TRASE)计划将开发(目标1)关于 可重复使用的研究观点和技能。我们提出了四个简短(3天)的强化培训模块。每个人 模块结合了教学和体验式学习，重点放在健康差距和老龄化问题上， 方法论上注重因果推理。模块1介绍了可再生性的概念，用于研究 人口健康与老龄化。本模块适用于科研人员和科研消费者 并将提供与审查期刊文章和拨款申请相关的关键评估技能， 解释已发表的发现，和领先的研究模块1假设有基本的科学研究背景 例如，执业医生、科学记者、管理人员以及 研究生和博士后实习生。模块2提供了实施可重复分析的技能，例如 登记前；统计编码卫生和评价；透明报告；以及文件，包括 用于协作项目。模块3处理现场主要数据收集以促进再现性， 考虑研究设计、统计能力、方案文件、数据质量控制。模块4提供 关于综合证据以提高科学进步的再现性的培训，例如，元研究， 证据三角测量即将到来。每个培训模块可以是独立的，也可以组合成更多 全面的技能组合。我们强调实践技能培养，以学习在以下背景下的最佳实践 当代问题。这些模块建立在加州大学旧金山分校现有培训的杰出基础上 计划，使用在我们的其他培训计划中已经证明成功的许多活动，并策划 对于密集的短期课程形式，为参与者提供跨职业阶段的概念性和 提高重现性的技术技能。我们建议(目标2)推出正在进行评估的模块 和细化(AIM 3)使用多种传播策略，以最大限度地发挥课程的影响。