Development and user testing of gene pilot: an electronic health decision support tool for Black cancer patients about tumor genomic profile testing

Sarah Bauerle Bass, Yana Chertock, Jesse Brajuha, Patrick J.A. Kelly, Alexandru Mircea Rotaru, Paul D’Avanzo, Ariel Hoadley, Caseem Luck, Katie Singley, Michael J. Hall

Research output: Contribution to journalArticlepeer-review

Abstract

Introduction: Tumor genomic profiling (TGP) is used to optimize cancer treatment but is underutilized by Black patients, despite having disproportionately higher cancer morbidity and mortality. No interventions using electronic health decision support tools (eHealth DSTs) have been developed to assist patients with understanding this test or address barriers to uptake and communicating preferences with a doctor. Methods: Using the Ottawa Decision Support Framework, we systematically developed the Gene Pilot eHealth DST with Black cancer patients. We conducted qualitative focus groups (five groups, N = 33) and surveys (N = 121), elicited community advisory board feedback (N = 10) to devise DST content and communication strategies, and then conducted user testing (N = 10). Content was informed by commercial marketing techniques - segmentation, perceptual mapping, vector message modeling – to elucidate how medical mistrust was an important construct to address in Gene Pilot. Results: User testing (1–7 scale) indicated Gene Pilot was highly accepted, including ease of use (M = 6.67, SD = 0.50), that it addressed important barriers such as medical mistrust and genetic literacy (6.63, SD = 0.52), and allowed patients to prepare for the decision (M = 6.44, SD = 0.73) and to communicate with their doctor (M = 6.33, SD = 0.73). Suggestions for improved navigability were addressed. Conclusion: Overall, Gene Pilot was found to be acceptable, suggesting its readiness for efficacy testing.

Original languageEnglish
Article number1505456
JournalFrontiers in Communication
Volume10
DOIs
StatePublished - 2025

Keywords

  • Black/African American patients
  • Cancer
  • decision support
  • eHealth
  • genetic testing

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