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Insights for knowledge brokers: Factors predicting relationships with federal staffers

Background: In theory and practice, it is understood personal relationships play a role in the effectiveness of translational models that bridge research and policy. These models can be made more efficient by understanding factors impacting relationships between policymaking players and third-party knowledge brokers.

Aims and Objectives: This study investigates a range of personal and office-level characteristics in predicting initial meetings and sustained relationships between federal staffers and knowledge brokers.

Methods: A public affairs database, Quorum, was used to pull data on staffers who were contacted between September 2021-August 2022 during an optimization phase of the Research-to-Policy Collaboration (RPC). Logistic regression models were used to understand the impact of the characteristics on outcomes such as attending initial meetings and attending meetings facilitated by the RPC.

Findings: Mid-level staffers and democratic staffers were more likely to meet with RPC staff. Staffers who had high motivation ratings were more likely to prompt an actionable request from the RPC. Office tenure was predictive of lower odds of meeting with RPC staff. For significant associations, the sample was stratified by political party to determine if the results differed by party.

Discussion and Conclusions: Together, these results suggest there are both personal and office-level characteristics affecting the federal staffers’ engagement with knowledge brokers. This work further informs efforts to bridge the gap between science and policy by informing knowledge brokers which offices and staffers they may want to approach.

This is a post-peer-review, pre-copy edited version of an article published in Evidence & Policy. The definitive publisher-authenticated version [Insight for knowledge brokers: factors predicting relationships with federal staffers. Evidence & Policy p1-16 (2024)] is available online at: https://doi.org/10.1332/17442648Y2024D000000032

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Metadata

Work Title Insights for knowledge brokers: Factors predicting relationships with federal staffers
Access
Open Access
Creators
  1. Patrick O'Neill
  2. Jessica Pugel
  3. Elizabeth C. Long
  4. D. Max Crowley
  5. Taylor Scott
Keyword
  1. Science communication
  2. Use of research evidence
  3. Research-policy relationship
  4. Research engagement
License In Copyright (Rights Reserved)
Work Type Article
Publisher
  1. Policy Press
Publication Date September 4, 2024
Publisher Identifier (DOI)
  1. https://doi.org/10.1332/17442648Y2024D000000032
Deposited February 18, 2025

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Version 1
published

  • Created

    February 18, 2025 08:17 by Researcher Metadata Database

  • Added Manuscript_TrackedChanges_accepted.docx

    February 18, 2025 08:17 by Researcher Metadata Database

  • Added Figure_1.docx

    February 18, 2025 08:17 by Researcher Metadata Database

  • Added Table_1.docx

    February 18, 2025 08:17 by Researcher Metadata Database

  • Added Table_2.docx

    February 18, 2025 08:17 by Researcher Metadata Database

  • Added Table_3.docx

    February 18, 2025 08:17 by Researcher Metadata Database

  • Added Creator Daniel M. Crowley

    February 18, 2025 08:17 by Researcher Metadata Database

  • Added Creator Patrick O'Neill

    February 18, 2025 08:17 by Researcher Metadata Database

  • Added Creator Jessica Pugel

    February 18, 2025 08:17 by Researcher Metadata Database

  • Added Creator E Long

    February 18, 2025 08:17 by Researcher Metadata Database

  • Added Creator T Scott

    February 18, 2025 08:17 by Researcher Metadata Database

  • Published

    February 18, 2025 08:17 by Researcher Metadata Database

  • Updated

    February 18, 2025 21:05 by [unknown user]

  • Updated Keyword, Description Show Changes

    April 14, 2025 10:29 by avs5190

    Keyword
    • Science communication, Use of research evidence, Research-policy relationship, Research engagement
    Description
    • Background: In theory and practice, it is understood personal relationships play a role in the effectiveness of translational models that bridge research and policy. These models can be made more efficient by understanding factors impacting relationships between policymaking players and third-party knowledge brokers.
    • Aims and Objectives: This study investigates a range of personal and office-level characteristics in predicting initial meetings and sustained relationships between federal staffers and knowledge brokers.
    • Methods: A public affairs database, Quorum, was used to pull data on staffers who were contacted between September 2021-August 2022 during an optimization phase of the Research-to-Policy Collaboration (RPC). Logistic regression models were used to understand the impact of the characteristics on outcomes such as attending initial meetings and attending meetings facilitated by the RPC.
    • Findings: Mid-level staffers and democratic staffers were more likely to meet with RPC staff. Staffers who had high motivation ratings were more likely to prompt an actionable request from the RPC. Office tenure was predictive of lower odds of meeting with RPC staff. For significant associations, the sample was stratified by political party to determine if the results differed by party.
    • Discussion and Conclusions: Together, these results suggest there are both personal and office-level characteristics affecting the federal staffers’ engagement with knowledge brokers. This work further informs efforts to bridge the gap between science and policy by informing knowledge brokers which offices and staffers they may want to approach.
  • Renamed Creator D. Max Crowley Show Changes

    April 14, 2025 10:30 by avs5190

    • Daniel M. Crowley
    • D. Max Crowley
  • Updated Creator Patrick O'Neill

    April 14, 2025 10:30 by avs5190

  • Updated Creator Jessica Pugel

    April 14, 2025 10:30 by avs5190

  • Renamed Creator Elizabeth C. Long Show Changes

    April 14, 2025 10:30 by avs5190

    • E Long
    • Elizabeth C. Long
  • Renamed Creator Taylor Scott Show Changes

    April 14, 2025 10:30 by avs5190

    • T Scott
    • Taylor Scott

Version 2
published

  • Created

    July 31, 2025 12:21 by avs5190

  • Updated Creator Patrick O'Neill

    July 31, 2025 12:22 by avs5190

  • Updated Creator Jessica Pugel

    July 31, 2025 12:22 by avs5190

  • Updated Creator Elizabeth C. Long

    July 31, 2025 12:22 by avs5190

  • Updated Creator Taylor Scott

    July 31, 2025 12:22 by avs5190

  • Deleted Figure_1.docx

    July 31, 2025 12:22 by avs5190

  • Deleted Manuscript_TrackedChanges_accepted.docx

    July 31, 2025 12:22 by avs5190

  • Deleted Table_1.docx

    July 31, 2025 12:22 by avs5190

  • Deleted Table_2.docx

    July 31, 2025 12:22 by avs5190

  • Deleted Table_3.docx

    July 31, 2025 12:22 by avs5190

  • Added AccessibleCopy_4-14_Table_3_Insights_for_Knowledge_Brokers.docx

    July 31, 2025 12:22 by avs5190

  • Added AccessibleCopy_4-14_Table_2_Insights_for_Knowledge_Brokers.docx

    July 31, 2025 12:22 by avs5190

  • Added AccessibleCopy_4-14_Insights_for_knowledge_brokers.docx

    July 31, 2025 12:22 by avs5190

  • Added AccessibleCopy_4-14_Table_1_Insights_for_Knowledge_Brokers.docx

    July 31, 2025 12:22 by avs5190

  • Added AccessibleCopy_4-14_Figure_1_Insights_for_Knowledge_Brokers.docx

    July 31, 2025 12:22 by avs5190

  • Published

    July 31, 2025 12:22 by avs5190