Bergman Margo W, Goodson Patricia, Goltz Heather Honoré
Milgard School of Business, University of Washington - Tacoma, Tacoma, WA, United States.
Department of Health and Kinesiology, Texas A&M University, College Station, TX, United States.
Front Public Health. 2017 Aug 29;5:229. doi: 10.3389/fpubh.2017.00229. eCollection 2017.
Misconceptions concerning numerical genetic risk exist even within educated populations. To more fully characterize and understand the extent of these risk misunderstandings, which have large potential impact on clinical care, we analyzed the responses from 2,576 students enrolled at 2 Southwestern universities using the PGRID tool, a 138-item web-based survey comprising measures of understanding of genetics, genetic disease, and genetic risk. The primary purpose of this study was to characterize the intersection of risk perception and knowledge, termed genetic numeracy (GN). Additionally, we identify sociodemographic factors that might shape varying levels of GN skills within the study sample and explore the impact of GN on genetic testing intentions using both the Marascuilo procedure and logistic regression analysis. Despite having some college coursework or at least one college degree, most respondents lacked high-level aptitude in understanding genetic inheritance risk, especially with respect to recessive disorders. Prior education about genetics and biology, as well as exposure to biomedical models of genetics, was associated with higher GN levels; exposure to popular media models of genetics was inversely associated with higher GN levels. Differing GN levels affects genetic testing intentions. GN will become more relevant as genetic testing is increasingly incorporated into general clinical care.
即使在受过教育的人群中，关于数字遗传风险的误解也依然存在。为了更全面地描述和理解这些风险误解的程度（这些误解对临床护理有很大的潜在影响），我们使用PGRID工具分析了来自西南地区两所大学的2576名学生的回答。PGRID工具是一项基于网络的138项调查，包括对遗传学、遗传疾病和遗传风险的理解测量。本研究的主要目的是描述风险认知与知识的交叉点，即遗传数字能力（GN）。此外，我们确定了可能影响研究样本中不同水平GN技能的社会人口因素，并使用马腊斯奎洛程序和逻辑回归分析探讨了GN对基因检测意愿的影响。尽管大多数受访者有一些大学课程作业或至少拥有一个大学学位，但他们在理解遗传遗传风险方面缺乏高水平的能力，尤其是在隐性疾病方面。先前接受的遗传学和生物学教育，以及接触遗传学的生物医学模型，与较高的GN水平相关；接触遗传学的大众媒体模型与较高的GN水平呈负相关。不同的GN水平会影响基因检测意愿。随着基因检测越来越多地纳入普通临床护理，GN将变得更加重要。
