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

点击翻译按钮获取中文摘要

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.