%0期刊文章@ 1438- 8871% I JMIR出版公司%V 17卡塔尔世界杯8强波胆分析% N 7% P 165% T为什么乳腺癌风险的数字是不够的:多民族、低数字妇女决策辅助的评估% a Kukafka,Rita % a Yi,Haeseung % a Xiao,Tong % a Thomas,Parijatham % a Aguirre,Alejandra % a Smalletz,Cindy % a David,Raven % a Crew,Katherine %+哥伦比亚大学内科和外科学院，生物医学信息学，Mailman公共卫生学院，社会医学科学，622西168街，ph20, 314室，纽约，美国，1212580 5560，rk326@cumc.columbia.edu %K乳腺癌%K决策%K风险沟通%K消费者健康信息%K基因检测%K决策辅助%K风险分层筛查%D 2015 %7 14.07.2015 %9原始论文%J J医学互联网Res %G英文%X背景:包括基因检测在内的乳腺癌风险评估可用于将人们划分为不同的风险群体，并根据每个群体的需要进行筛选和预防干预，但在初级保健环境中实施风险分层的乳腺癌预防是复杂的。目的:为了解决初级保健环境中乳腺癌风险评估、风险沟通和预防策略的障碍，我们开发了一个基于web的决策辅助工具，RealRisks，旨在改善乳腺癌预防的基于偏好的决策，特别是在低数量女性中。方法:RealRisks结合了基于经验的动态接口来传达风险，旨在减少不准确的风险认知，并提供了量身定制的乳腺癌风险、基因检测和化学预防模块。首先，参与者通过与两个基于经验的风险界面游戏互动来了解风险，展示平均5年和终生乳腺癌风险。我们在讲英语的女性(年龄≥18岁)中进行了四个焦点小组，在与决策辅助工具互动之前和之后完成了问卷调查，并进行了半结构化小组讨论。我们采用混合方法评估感知乳腺癌风险的准确性和真实风险的可接受性。对半结构化讨论的定性分析评估了对风险、风险模型和风险适当预防策略的理解。 Results: Among 34 participants, mean age was 53.4 years, 62% (21/34) were Hispanic, and 41% (14/34) demonstrated low numeracy. According to the Gail breast cancer risk assessment tool (BCRAT), the mean 5-year and lifetime breast cancer risk were 1.11% (SD 0.77) and 7.46% (SD 2.87), respectively. After interacting with RealRisks, the difference in perceived and estimated breast cancer risk according to BCRAT improved for 5-year risk (P=.008). In the qualitative analysis, we identified potential barriers to adopting risk-appropriate breast cancer prevention strategies, including uncertainty about breast cancer risk and risk models, distrust toward the health care system, and perception that risk assessment to pre-screen women for eligibility for genetic testing may be viewed as rationing access to care. Conclusions: In a multi-ethnic population, we demonstrated a significant improvement in accuracy of perceived breast cancer risk after exposure to RealRisks. However, we identified potential barriers that suggest that accurate risk perceptions will not suffice as the sole basis to support informed decision making and the acceptance of risk-appropriate prevention strategies. Findings will inform the iterative design of the RealRisks decision aid. %M 26175193 %R 10.2196/jmir.4028 %U //www.mybigtv.com/2015/7/e165/ %U https://doi.org/10.2196/jmir.4028 %U http://www.ncbi.nlm.nih.gov/pubmed/26175193