ArticleJournal of clinical and translational science2025
Operationalizing community engagement evaluation: A structured and scalable approach using the RE-AIM framework and net effects diagrams.
Article in Journal of clinical and translational science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Contextualizing Evaluation in Research Consortia: A Reflective Case Study from the Research Centers in Minority Institutions (RCMIs) Program.International journal of environmental research and public health · 2026Article
- Measuring what matters: Modern evaluation practices in clinical and translational science.Journal of clinical and translational science · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Introduction: Community engagement (CE) is essential in Clinical and Translational Science (CTS), yet its evaluation remains inconsistent and often lacks standardization. The RE-AIM framework (Reach, Effectiveness, Adoption, Implementation, Maintenance) offers a promising structure for evaluating CE efforts, but its application in dynamic, community-based contexts is often limited by data variability and implementation complexity. Methods: We developed and applied a seven-step, structured, and replicable approach to operationalizing RE-AIM for program evaluation. This method includes the use of tailored RE-AIM subdomains, standardized scoring systems, and visual analytics through Net Effects Diagrams. Results: We applied this framework to our community-based health education workshops delivered in English and Spanish across Los Angeles, using participant surveys and facilitator feedback data. The operationalized framework enabled consistent assessment and comparison between language groups. Spanish-language workshops outperformed English-language workshops (ELWs) in measures of attendance, participant satisfaction, and short-term effectiveness. Visualizations using Net Effects Diagrams facilitated collaboration among stakeholders to interpret program outputs and outcomes, supporting actionable insights for program adaptation. Differences between workshop groups will inform changes to recruitment and content delivery strategies in ELWs. Conclusions: This approach offers a transparent, scalable, and context-sensitive method for assessing CE programs. It supports data-driven decision-making, continuous program improvement, and stakeholder engagement. While developed for CE initiatives, the method is broadly adaptable to other community and public health programs. Future efforts will include expanded outcome tracking, integration into dashboards, and dissemination as a toolkit for broader adoption within and beyond the CTS Award network.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.