Selina Casalino , Chloe Mighton , Marc Clausen , Erika Frangione , Navneet Aujla , Georgia MacDonald , Juliet Young , Chun Yiu Jordan Fung , Gregory Morgan , Saranya Arnoldo , Erin Bearss , Alexandra Binnie , Bjug Borgundvaag , Sunakshi Chowdhary , Marc Dagher , Luke Devine , Steven Marc Friedman , Limin Hao , Zeeshan Khan , William Lane , Jared Simpson
{"title":"基于人口的测序基因组咨询模式:事后干预研究","authors":"Selina Casalino , Chloe Mighton , Marc Clausen , Erika Frangione , Navneet Aujla , Georgia MacDonald , Juliet Young , Chun Yiu Jordan Fung , Gregory Morgan , Saranya Arnoldo , Erin Bearss , Alexandra Binnie , Bjug Borgundvaag , Sunakshi Chowdhary , Marc Dagher , Luke Devine , Steven Marc Friedman , Limin Hao , Zeeshan Khan , William Lane , Jared Simpson","doi":"10.1016/j.gim.2024.101272","DOIUrl":null,"url":null,"abstract":"<div><h3>Purpose</h3><div>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.</div></div><div><h3>Methods</h3><div>Participants (<em>N</em> = 466) completed GS and our GCM (digital genomics platform and group-based webinar) and indicated results preferences. Surveys were administered before (T0) and after (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.</div></div><div><h3>Results</h3><div>Participants were 56% female, 58% white, and 53% ≥40 years of age. Mean knowledge scores increased (Limitations: 3.73 to 5.63; Benefits: 4.34 to 5.48, <em>P</em> < .0001), and DC decreased (−21.9, <em>P</em> < .0001) at T1 versus T0. Eighty-six percent of participants wished to learn all GS findings at T1 vs 78% at T0 (<em>P</em> < .0001). Older age, negative/mixed attitudes toward genetics and greater DC were associated with change in preferences after intervention.</div></div><div><h3>Conclusion</h3><div>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.</div></div>","PeriodicalId":12717,"journal":{"name":"Genetics in Medicine","volume":"26 12","pages":"Article 101272"},"PeriodicalIF":6.6000,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Genomic Counseling Model for Population-Based Sequencing: A Pre-Post Intervention Study\",\"authors\":\"Selina Casalino , Chloe Mighton , Marc Clausen , Erika Frangione , Navneet Aujla , Georgia MacDonald , Juliet Young , Chun Yiu Jordan Fung , Gregory Morgan , Saranya Arnoldo , Erin Bearss , Alexandra Binnie , Bjug Borgundvaag , Sunakshi Chowdhary , Marc Dagher , Luke Devine , Steven Marc Friedman , Limin Hao , Zeeshan Khan , William Lane , Jared Simpson\",\"doi\":\"10.1016/j.gim.2024.101272\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Purpose</h3><div>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.</div></div><div><h3>Methods</h3><div>Participants (<em>N</em> = 466) completed GS and our GCM (digital genomics platform and group-based webinar) and indicated results preferences. Surveys were administered before (T0) and after (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.</div></div><div><h3>Results</h3><div>Participants were 56% female, 58% white, and 53% ≥40 years of age. Mean knowledge scores increased (Limitations: 3.73 to 5.63; Benefits: 4.34 to 5.48, <em>P</em> < .0001), and DC decreased (−21.9, <em>P</em> < .0001) at T1 versus T0. Eighty-six percent of participants wished to learn all GS findings at T1 vs 78% at T0 (<em>P</em> < .0001). Older age, negative/mixed attitudes toward genetics and greater DC were associated with change in preferences after intervention.</div></div><div><h3>Conclusion</h3><div>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.</div></div>\",\"PeriodicalId\":12717,\"journal\":{\"name\":\"Genetics in Medicine\",\"volume\":\"26 12\",\"pages\":\"Article 101272\"},\"PeriodicalIF\":6.6000,\"publicationDate\":\"2024-09-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Genetics in Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1098360024002065\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genetics in Medicine","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1098360024002065","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
A Genomic Counseling Model for Population-Based Sequencing: A Pre-Post Intervention Study
Purpose
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
Participants (N = 466) completed GS and our GCM (digital genomics platform and group-based webinar) and indicated results preferences. Surveys were administered before (T0) and after (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
Participants were 56% female, 58% white, and 53% ≥40 years of age. Mean knowledge scores increased (Limitations: 3.73 to 5.63; Benefits: 4.34 to 5.48, P < .0001), and DC decreased (−21.9, P < .0001) at T1 versus T0. Eighty-six percent of participants wished to learn all GS findings at T1 vs 78% at T0 (P < .0001). Older age, negative/mixed attitudes toward genetics and greater DC were associated with change in preferences after intervention.
Conclusion
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.
期刊介绍:
Genetics in Medicine (GIM) is the official journal of the American College of Medical Genetics and Genomics. The journal''s mission is to enhance the knowledge, understanding, and practice of medical genetics and genomics through publications in clinical and laboratory genetics and genomics, including ethical, legal, and social issues as well as public health.
GIM encourages research that combats racism, includes diverse populations and is written by authors from diverse and underrepresented backgrounds.