Yoon Paula W, Scheuner Maren T, Jorgensen Cynthia, Khoury Muin J
Centers for Disease Control and Prevention, 4770 Buford Hwy, NE, Mailstop K47, Atlanta, GA 30341, USA.
Prev Chronic Dis. 2009 Jan;6(1):A33. Epub 2008 Dec 15.
Family health history reflects the effects of genetic, environmental, and behavioral factors and is an important risk factor for a variety of disorders including coronary heart disease, cancer, and diabetes. In 2004, the Centers for Disease Control and Prevention developed Family Healthware, a new interactive, Web-based tool that assesses familial risk for 6 diseases (coronary heart disease, stroke, diabetes, and colorectal, breast, and ovarian cancer) and provides a "prevention plan" with personalized recommendations for lifestyle changes and screening. The tool collects data on health behaviors, screening tests, and disease history of a person's first- and second-degree relatives. Algorithms in the software analyze the family history data and assess familial risk based on the number of relatives affected, their age at disease onset, their sex, how closely related the relatives are to each other and to the user, and the combinations of diseases in the family. A second set of algorithms uses the data on familial risk level, health behaviors, and screening to generate personalized prevention messages. Qualitative and quantitative formative research on lay understanding of family history and genetics helped shape the tool's content, labels, and messages. Lab-based usability testing helped refine messages and tool navigation. The tool is being evaluated by 3 academic centers by using a network of primary care practices to determine whether personalized prevention messages tailored to familial risk will motivate people at risk to change their lifestyles or screening behaviors.
家族健康史反映了遗传、环境和行为因素的影响,是包括冠心病、癌症和糖尿病在内的多种疾病的重要风险因素。2004年,疾病控制与预防中心开发了家庭健康软件,这是一种新型的基于网络的交互式工具,可评估6种疾病(冠心病、中风、糖尿病以及结直肠癌、乳腺癌和卵巢癌)的家族风险,并提供一份“预防计划”,其中包含针对生活方式改变和筛查的个性化建议。该工具收集有关一个人的一级和二级亲属的健康行为、筛查测试和疾病史的数据。软件中的算法分析家族史数据,并根据受影响亲属的数量、疾病发病年龄、性别、亲属之间以及与用户的亲缘关系程度以及家族中的疾病组合来评估家族风险。第二组算法利用家族风险水平、健康行为和筛查数据来生成个性化的预防信息。关于公众对家族史和遗传学理解的定性和定量形成性研究有助于塑造该工具的内容、标签和信息。基于实验室的可用性测试有助于完善信息和工具导航。3个学术中心正在通过一个初级保健机构网络对该工具进行评估,以确定针对家族风险量身定制的个性化预防信息是否会促使有风险的人改变他们的生活方式或筛查行为。