ClinicalTrials.gov
public full text
Public Domain
Choices About Genetic Testing And Learning Your Risk With Smart Technology
breast-cancercolorectal-cancerendometrial-cancergenetic-testingovarian-cancerpancreas-cancerprostate-cancer
This study seeks to enhance genetic education and increase the uptake of genetic testing for hereditary cancer risk among cancer survivors. The study will focus on the feasibility and acceptability of a digital intervention designed to improve cancer genomic care. The study objectives are to: 1. Finalize the development and optimize the usability of the CATALYST digital intervention (also known as the relational assistant \[RA\]). 2. Evaluate the feasibility and acceptability of a streamlined cancer genomic care delivery model for cancer survivors. Participants will be randomized to one of two study arms: the RA intervention arm or the enhanced usual care (EUC) arm. 3. Assess the uptake of genetic counseling (GC) and genetic testing (GT) and conduct a process evaluation to identify barriers and facilitators to GC, GT, and engagement with the CATALYST intervention and the RA.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Applying Population Management Best Practices to Preventative Genomic Medicine Trial#1308498
- Effects of web-based interventions on cancer caregivers' burden and quality of life: A systematic review and meta-analysis.#182227
- Real-world Clinical Effectiveness of Whole Genome and Transcriptome Analysis to Guide Advanced Cancer Care#825007
- Patient-reported outcomes in cancer survivorship: insights from two decades of population-based PROFILES registry research.#159927
- Sarah Cannon Outcomes Registry#1243701
Record · ID 1338985
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive