Refining a Multifaceted Model of Perceived Utility of Genomic Sequencing Results

Public Health Genomics. 2023;26(1):135-144. doi: 10.1159/000531782. Epub 2023 Aug 22.

Abstract

Introduction: Research on the perceived utility of genomic sequencing has focused primarily on pediatric populations and on individuals and families with rare genetic diseases. Here, we evaluate how well a multifaceted perceived utility model developed with these populations applies to a diverse, adult population aged 18-49 at risk for hereditary cancer and propose new considerations for the model.

Methods: Participants received clinical genomic sequencing in the Cancer Health Assessments Reaching Many (CHARM) study. Semi-structured qualitative interviews were conducted with a subset of participants at 1 and 6 months after results disclosure. We used an approach influenced by grounded theory to examine perceptions of the utility of genomic sequencing and analyzed how utility in CHARM mapped to the published multifaceted perceived utility model, noting which domains were represented or absent and which were most salient to our population.

Results: Participants' discussions of utility often involved multiple domains and revealed the variety of ways in which receiving sequencing results can impact one's life. Results demonstrated that an individual's perception of utility can change over the life course when sequenced at a relatively young age and may be influenced by the resources available to them to act on the results.

Conclusion: Our findings demonstrate the relevance of a multifaceted perceived utility model for a diverse adult population at risk for hereditary cancer. We identified refinements that could make the model more robust, including emphasizing the overlapping nature of the domains and the importance of life stage and personal resources to the perception of utility.

Keywords: Clinical utility; Genomic sequencing; Hereditary cancer risk; Perceived utility; Personal utility.

MeSH terms

  • Adult
  • Child
  • Disclosure*
  • Genetic Predisposition to Disease*
  • Genomics
  • Humans