A Genomic Counseling Model for Population-Based Sequencing: A Pre-Post Intervention Study.

Digital tools Genome sequencing Genomic counseling Population screening Preferences

Journal

Genetics in medicine : official journal of the American College of Medical Genetics
ISSN: 1530-0366
Titre abrégé: Genet Med
Pays: United States
ID NLM: 9815831

Informations de publication

Date de publication:
17 Sep 2024
Historique:
received: 01 05 2024
revised: 10 09 2024
accepted: 11 09 2024
medline: 20 9 2024
pubmed: 20 9 2024
entrez: 20 9 2024
Statut: aheadofprint

Résumé

Novel uses of genome sequencing (GS) present an opportunity for return of results to healthy individuals, prompting the need for scalable genetic counseling strategies. We evaluate the effectiveness of a genomic counseling model (GCM) and explore preferences for GS findings in the general population. Participants (N=466) completed GS and our GCM (digital genomics platform and group-based webinar), and indicated results preferences. Surveys were administered pre- (T0) and post- (T1) GCM. Change in knowledge and decisional conflict (DC) were evaluated using paired-sample T and Wilcoxon tests. Factors influencing knowledge and results preferences were evaluated using linear and logistic regression models. Participants were 56% female, 58% white, and 53% ≥40 years of age. Mean knowledge scores increased (Limitations: 3.73 to 5.63; benefits: 3.73 to 5.48, p<0.0001) and DC decreased (-21.9, p<0.0001) at T1 versus T0. Eighty-six percent of participants wished to learn all GS findings at T1 vs 78% at T0 (p<0.0001). Older age, negative/mixed attitudes toward genetics, and greater DC were associated with change in preferences post-intervention. In a population-based cohort undergoing GS interested in learning GS findings, our GCM increased knowledge and reduced DC, illustrating the GCM's potential effectiveness for GS counseling in the general population.

Sections du résumé

BACKGROUND BACKGROUND
Novel uses of genome sequencing (GS) present an opportunity for return of results to healthy individuals, prompting the need for scalable genetic counseling strategies. We evaluate the effectiveness of a genomic counseling model (GCM) and explore preferences for GS findings in the general population.
METHODS METHODS
Participants (N=466) completed GS and our GCM (digital genomics platform and group-based webinar), and indicated results preferences. Surveys were administered pre- (T0) and post- (T1) GCM. Change in knowledge and decisional conflict (DC) were evaluated using paired-sample T and Wilcoxon tests. Factors influencing knowledge and results preferences were evaluated using linear and logistic regression models.
RESULTS RESULTS
Participants were 56% female, 58% white, and 53% ≥40 years of age. Mean knowledge scores increased (Limitations: 3.73 to 5.63; benefits: 3.73 to 5.48, p<0.0001) and DC decreased (-21.9, p<0.0001) at T1 versus T0. Eighty-six percent of participants wished to learn all GS findings at T1 vs 78% at T0 (p<0.0001). Older age, negative/mixed attitudes toward genetics, and greater DC were associated with change in preferences post-intervention.
CONCLUSION CONCLUSIONS
In a population-based cohort undergoing GS interested in learning GS findings, our GCM increased knowledge and reduced DC, illustrating the GCM's potential effectiveness for GS counseling in the general population.

Identifiants

pubmed: 39301805
pii: S1098-3600(24)00206-5
doi: 10.1016/j.gim.2024.101272
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

101272

Informations de copyright

Copyright © 2024. Published by Elsevier Inc.

Auteurs

Selina Casalino (S)

Mount Sinai Hospital, Sinai Health; Lunenfeld-Tanenbaum Research Institute, Sinai Health.

Chloe Mighton (C)

Mount Sinai Hospital, Sinai Health; Lunenfeld-Tanenbaum Research Institute, Sinai Health; University of Toronto; Unity Health Toronto.

Marc Clausen (M)

Unity Health Toronto.

Erika Frangione (E)

Mount Sinai Hospital, Sinai Health; Lunenfeld-Tanenbaum Research Institute, Sinai Health.

Navneet Aujla (N)

Mount Sinai Hospital, Sinai Health; Lunenfeld-Tanenbaum Research Institute, Sinai Health.

Georgia MacDonald (G)

Mount Sinai Hospital, Sinai Health; Lunenfeld-Tanenbaum Research Institute, Sinai Health.

Juliet Young (J)

Mount Sinai Hospital, Sinai Health; Lunenfeld-Tanenbaum Research Institute, Sinai Health.

Chun Yiu Jordan Fung (CY)

Mount Sinai Hospital, Sinai Health; Lunenfeld-Tanenbaum Research Institute, Sinai Health.

Gregory Morgan (G)

Mount Sinai Hospital, Sinai Health; Lunenfeld-Tanenbaum Research Institute, Sinai Health; University of Toronto.

Saranya Arnoldo (S)

University of Toronto; William Osler Health System.

Erin Bearss (E)

Mount Sinai Hospital, Sinai Health.

Alexandra Binnie (A)

University of Toronto; William Osler Health System.

Bjug Borgundvaag (B)

University of Toronto; Schwartz/Reisman Emergency Medicine Institute, Sinai Health.

Sunakshi Chowdhary (S)

University Health Network.

Marc Dagher (M)

Women's College Hospital.

Luke Devine (L)

Mount Sinai Hospital, Sinai Health; University of Toronto.

Steven Marc Friedman (SM)

Mount Sinai Hospital, Sinai Health; University Health Network.

Limin Hao (L)

Laboratory for Molecular Medicine, Partner Personalized Medicine.

Zeeshan Khan (Z)

Mackenzie Health.

William Lane (W)

Harvard Medical School & Brigham and Women's Hospital.

Elisa Lapadula (E)

Mount Sinai Hospital, Sinai Health; Lunenfeld-Tanenbaum Research Institute, Sinai Health.

Matthew Lebo (M)

Laboratory for Molecular Medicine, Partner Personalized Medicine; Harvard Medical School & Brigham and Women's Hospital.

David Richardson (D)

William Osler Health System.

Seth Stern (S)

Mackenzie Health.

Lisa Strug (L)

The Hospital for Sick Children.

Ahmed Taher (A)

University of Toronto; University Health Network; Mackenzie Health.

Elena Greenfeld (E)

Mount Sinai Hospital, Sinai Health; University of Toronto.

Abdul Noor (A)

Mount Sinai Hospital, Sinai Health; University of Toronto.

Hanna Faghfoury (H)

Mount Sinai Hospital, Sinai Health; University of Toronto; University Health Network.

Jennifer Taher (J)

Mount Sinai Hospital, Sinai Health; University of Toronto.

Yvonne Bombard (Y)

University of Toronto; Unity Health Toronto. Electronic address: Yvonne.bombard@utoronto.ca.

Jordan Lerner-Ellis (J)

Mount Sinai Hospital, Sinai Health; Lunenfeld-Tanenbaum Research Institute, Sinai Health; University of Toronto. Electronic address: Jordan.lerner-ellis@sinaihealth.ca.

Classifications MeSH