59: Optimizing Engagement in Cancer Genomics

Crossnohere NL et al., Genetics in Medicine - Overview of how the PE-CGS Network defined, implemented, and evaluated strategies to engage participants and communities in cancer genomic sequencing research, and how engagement optimization using scientific methods informed study practices. Key terms: participant engagement, community engagement, engagement optimization, cancer genomics, return of results.

Study Highlights:
The PE-CGS Network conducted a document review and key informant interviews across five research centers to characterize engagement and optimization strategies during the first three years. Centers implemented tailored participant- and community-focused approaches spanning outreach, consent, data collection, return of results, and retention. Engagement optimization applied methods from behavioral science, implementation science, randomized experiments, surveys, and rapid-cycle research to iteratively refine practices. Harmonized definitions of engagement and optimization were developed to support evidence-based approaches across the network.

Conclusion:
PE-CGS established shared definitions and a range of participant and community engagement strategies and applied scientific methods to optimize them; these efforts informed changes to consent, return-of-results, recruitment, and retention and provide a foundation for developing evidence-based engagement practices in cancer genomics research.

Music:
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Article title:
Optimizing participant and community engagement in cancer genomic sequencing research

First author:
Crossnohere NL

Journal:
Genetics in Medicine

DOI:
10.1016/j.gim.2025.101483

Reference:
Crossnohere NL, Schuster ALR, Blair CK, Bland H, Carpten JD, Claus EB, Colditz GA, Diehl D, Ding L, Drake BF, Fields RC, George S, Janeway K, Kim H, Lenz HJ, Mack JW, Ricker C, Stern MC, Sussman A, Trent J, Van Allen E, Verhaak R, Willman C, Bridges JFP, Mishra SI, Kwan BM, For PE-CGS Network, Optimizing participant and community engagement in cancer genomic sequencing research, Genetics in Medicine (2025), doi: https://doi.org/10.1016/j.gim.2025.101483

License:
© 2025 Published by Elsevier Inc. on behalf of American College of Medical Genetics and Genomics.

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Episode link: https://basebybase.com/episodes/optimizing-engagement-cancer-genomics-59

QC:
This episode was checked against the original article PDF and publication metadata for the episode release published on 2025-06-29.

QC Scope:
- article metadata and core scientific claims from the narration
- excludes analogies, intro/outro, and music
- transcript coverage: Audited definitions of engagement and optimization, center-focused strategies, methods, and key tactical examples (consent visuals, language changes, bilingual webinars, educator training, decision support tools), plus discussion on outcomes and recommendations.
- transcript topics: Definitions of engagement and engagement optimization; Center populations and focus (JUNIPER, Count Me In, OPTIMUM, KOPEC, WU-PE-CGS); Indigenous consent materials and tribal advisory oversight; Language changes in return of results (shared learnings about your tumor); Multilingual outreach and community education (bilingual webinars); Community health educator training and evaluation

QC Summary:
- factual score: 10/10
- metadata score: 10/10
- supported core claims: 7
- claims flagged for review: 0
- metadata checks passed: 4
- metadata issues found: 0

Metadata Audited:
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