233 Beyond bibliometrics: Altmetric analysis as an early signal of the impact of the National Center for Advancing Translational Sciences (NCATS) Clinical and Translational Science Awards (CTSA) Program

Abstract

Objectives/Goals: To identify and characterize future potentially high impact research generated by the Clinical and Translational Science Awards (CTSA) Program, we evaluated the Altmetric Attention Scores (AAS) of recent articles associated with the Program and conducted an initial assessment of the attributes associated with high AAS for Program articles. Methods/Study Population: We used the NIH Query, View, Report (QVR) tool to identify recently-published scientific papers that cited support from a CTSA Program grant. The unique publications identified by QVR were used to construct an Altmetric Explorer report. We examined the relationship between the AAS and other variables, including number of authors, number of grants supporting the publication, number of CTSA program institutions supporting the publication, and if the publication included group authorship. Results/Anticipated Results: Our analyses confirmed that the Program indeed supports potentially high impact research, as indicated by the highest scoring papers, across a wide range of diseases and conditions. Nearly all the highest scoring papers were focused on a specific disease or condition rather than broader methodological research, despite the disease-agnostic focus of the CTSA program. We also found that the Program significantly contributed to critical research on the once-in-a-century COVID-19 pandemic. We confirmed the entire CTSA consortium is contributing to potentially high impact research, with all institutions represented in the highest scoring publications. Discussion/Significance of Impact: Understanding the impact of the CTSA Program presents a unique challenge – the program supports biomedical research infrastructure and training programs whose outcomes and impact can be difficult to track or measure. These data offer early signals of impact and can assist evaluators with designing future evaluations.