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The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time

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Meta-evaluative practices of Clinical and Translational Research evaluators.

Sue Giancola¹, John F Stevenson², Ingrid Philibert³

¹Center for Research in Education and Social Policy (CRESP), College of Education and Human Development, University of Delaware, Newark, DE, USA.

Journal of Clinical and Translational Science

|September 22, 2025

Summary

Many National Institutes of Health (NIH) Institutional Development Award (IDeA) Clinical and Translational Research (CTR) evaluators use meta-evaluation. Key challenges include data management, impact metrics, and realistic expectations for translational research evaluation.

Keywords:

Clinical and Translational Research continuous improvement internal formative meta-evaluation translational research evaluation

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Area of Science:

Biomedical Research
Translational Science
Health Services Research

Background:

The National Institutes of Health (NIH) Institutional Development Award (IDeA) program supports research capacity in states with limited NIH funding.
IDeA Clinical and Translational Research (CTR) networks aim to enhance statewide and regional biomedical research capabilities.
Evaluation components within CTRs are crucial for data collection, continuous improvement, and impact assessment.

Purpose of the Study:

To assess the utilization of meta-evaluative practices among IDeA-CTR evaluators.
To understand how meta-evaluation informs the evaluation process within CTRs.
To identify challenges faced by evaluators in planning and implementing CTR evaluations.

Main Methods:

A survey was administered to evaluators within the IDeA-CTR network.
The survey examined the extent of meta-evaluative practices and their influence on evaluation.
Evaluators reported on challenges encountered during evaluation planning and implementation.

Main Results:

Approximately 50% of CTRs engaged in some form of meta-evaluation.
Significant challenges were identified in translational research evaluation, including data management systems.
Selection of program-wide impact metrics and setting realistic expectations for recipients were also prominent challenges.

Conclusions:

Adopting participatory and collaborative evaluation approaches is recommended.
Sharing insights and strategies within a learning community of evaluators can enhance practice.
This study underscores the value of meta-evaluation in CTR settings and offers best practices for addressing common challenges.