Objectives/Goals: To explore how CTSA-supported research is cited and used in policy documents by applying Yu et al.’s (2023) coding framework. We aim to move beyond citation counts by examining how research engages with policy and identifying substantive examples of research informing policy decisions. Methods/Study Population: We will use Overton to identify CTSA-supported publications with the highest number of policy citations. For these highly cited publications, we will conduct a content analysis of the citing policy documents using Yu et al.’s (2023) motivation codes. These five codes classify how research is used in policy documents – from background context to supporting arguments or forming the policy evidence base – and help distinguish citations that reflect more versus less substantive research-to-policy engagement. We will then analyze coded data with Overton metadata (e.g., citing organization characteristics) to identify emerging patterns and assess whether substantive uses of research provide compelling examples of CTSA impact on policy. Results/Anticipated Results: We will report how CTSA-supported research is used in policy documents. This analysis will identify more meaningful examples of research engagement in policy – publications that inform or shape policy decisions versus those cited for background context. By linking these codes with Overton fields, such as citing organization characteristics, we will explore whether more meaningful uses of research are associated with specific organization types or sectors. Findings will offer preliminary insight into whether analyzing research use in policy documents can help evaluators identify strong examples of CTSA impact. Discussion/Significance of Impact: This study applies methods from scientometric policy citation analysis and builds on a growing focus within the CTSA program on research’s role in shaping policy. It moves beyond citation counts to identify meaningful cases of CTSA-supported research influencing policy and demonstrating impact.
Hawkins et al. (Wed,) studied this question.