Identifying barriers to optimizing data sharing and accelerate discovery in Alzheimer’s disease and related dementia research

识别优化数据共享和加速阿尔茨海默病及相关痴呆症研究发现的障碍

• 批准号: 10568214
• 负责人: Jalayne J Arias
• 金额: $ 62.23万
• 依托单位: GEORGIA STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-15 至 2027-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10568214
• 关键词: Acceleration; Achievement; Address; Adherence; Affect; Alzheimer' s disease related dementia; Behavior; Biological Markers; Biological Sciences; Clinical; Clinical Trials; Data; Data Analyses; Disadvantaged; Disease; Empirical Research; Ethical Review; Exclusion; Generations; Genetic; Genetic Research; Goals; Guidelines; Health Sciences; Image; Incentives; Individual; Inequity; Institution; Institutional Policy; Intervention; Interview; Journals; K-Series Research Career Programs; Knowledge; Laws; Lead; Literature; Methods; Neurology; Neurosciences; Outcome; Ownership; Perception; Policies; Population; Predictive Factor; Prevalence; Professional Organizations; Qualifying; Recommendation; Reporting; Research; Research Personnel; Resource-limited setting; Resources; Risk; Sampling; Scientist; Structure; Surveys; Technology; Therapeutic; Therapeutic Research; Thinking; Time; Training; Underrepresented Minority; United States National Institutes of Health; Work; career; data management; data repository; data sharing; design; effective intervention; equity, diversity, and inclusion; experience; improved; innovation; large datasets; minority investigator; multidisciplinary; prevent; repository; system-level barriers; therapy development; tool

It is a pivotal time for Alzheimer’s disease and related dementias (ADRD) research to harness data sharing and accelerate therapeutic discovery. Data sharing is important to advance research because it supports large data sets that are more representative of the population, increasing the ability to detect generalizable contributors to disease. Sharing data increases efficiency by allowing investigators to build upon each other’s work and prevents redundant data generation. For of these reasons, the National Institutes of Health has committed to promoting data sharing to accelerate research in the biosciences since 1997. Nevertheless, our preliminary data indicate that in ADRD individual, institutional, and system-level barriers are impeding optimal data sharing. Furthermore, the policies of institutions, publishers, and funders may be incompatible with one another, preventing or discouraging investigators from sharing data. Efforts to exponentially expand ADRD research achievement through data repositories and research consortia will fail to meet therapeutic discovery goals if investigators cannot or will not share data. To address this risk and identify effective interventions to improve the prevalence and quality of data sharing, current gaps in knowledge regarding ADRD investigators’ sharing practices, perceptions of policies, and navigation of barriers must be closed. We propose to further explore these provocative preliminary findings, collecting generalizable data to better understand ADRD investigators’ practices and perceptions of data sharing responsibilities. Such data would support development of interventions that mitigate barriers considering unique challenges associated with conducting ADRD research and the distinctive subculture of the field. Our goal is to provide ADRD investigators with tools that promote data sharing and facilitate adherence to data sharing policies, including the NIH Data Management and Sharing Policy (effective 2023). We will conduct surveys with ADRD investigators to better understand the prevalence of data sharing and withholding practices and gain clarity about barriers to data sharing. Following surveys, we will conduct in-depth interviews with a subset of subjects to collect and analyze their narrative descriptions of barriers to data sharing and how they navigate such barriers. This will provide rich understanding of investigators’ unique experiences. Finally, we will compare investigators’ reported experiences with various policies that guide ADRD scientific practices. This will include policies from journals, academic/research centers, repositories, consortia, and others. We will make recommendations of interventions which might mitigate barriers to data sharing. This study is critical to promoting optimal data sharing behaviors that are needed to advance therapeutic research in ADRD.

现在是阿尔茨海默病和相关痴呆症 (ADRD) 研究利用数据共享和 加速治疗发现对于推进研究非常重要，因为它支持大数据。 更能代表总体的集合，提高了检测可概括的贡献者的能力 共享数据使研究人员能够在彼此的工作基础上进行研究，从而提高效率并预防疾病。 由于这些原因，美国国立卫生研究院致力于促进冗余数据的生成。 自 1997 年以来，数据共享加速了生物科学研究。尽管如此，我们的初步数据表明 在 ADRD 中，个人、机构和系统层面的障碍正在阻碍最佳的数据共享。 机构、出版商和资助者的政策可能彼此不一致，从而阻碍或阻碍 阻碍研究人员共享数据的努力。 如果研究人员通过数据存储库和研究联盟将无法实现治疗发现目标 不能或不会共享数据来应对这一风险并确定有效的干预措施以提高患病率。 数据共享的质量、当前关于 ADRD 调查人员共享实践的知识差距、 我们建议进一步探讨这些问题。 具有争议性的初步结果，收集可概括的数据以更好地了解 ADRD 研究人员的 数据共享责任的实践和看法。此类数据将支持干预措施的制定。 考虑到与进行 ADRD 研究相关的独特挑战，减少障碍 我们的目标是为 ADRD 研究人员提供促进数据共享的工具。 促进遵守数据共享政策，包括 NIH 数据管理和共享政策 （2023 年生效）我们将与 ADRD 调查人员一起进行调查，以更好地了解数据的普遍性。 通过调查，我们将了解共享和保留做法，并明确数据共享的障碍。 对一部分受试者进行深入访谈，收集并分析他们对障碍的叙述性描述 数据共享以及他们如何克服这些障碍，这将为研究人员的独特之处提供丰富的理解。 最后，我们将调查人员报告的经验与指导 ADRD 的各种政策进行比较。 这将包括来自期刊、学术/研究中心、知识库、联盟的政策。 我们将提出可能减轻数据共享障碍的干预措施建议。 研究对于促进最佳数据共享行为至关重要，而这些行为是推进治疗研究所需的 ADRD。