杂志文章@ JMIR出版公司基于互联网的健康风险评估能否突出心脏病风卡塔尔世界杯8强波胆分析险因素意识的问题?横断面分析%A Dickerson,Justin B %A McNeal,Catherine J %A Tsai,Ginger A Rivera, kathleen M %A Smith,Matthew Lee Ohsfeldt,Robert L %A Ory,Marcia G %+公共卫生学院，健康促进和社区健康科学系，德州A&M健康科学中心，1266 TAMU，大学城，德克萨斯州，77843，美国，1 979 777 8714，hsrhealthservices@gmail.com %K健康风险评估%K互联网%K风险因素%K健康疾病%K一致%D 2014 %7 18.04.2014 %9原始论文%J J医学互联网Res %G英文%X背景:健康风险评估作为一种工具越来越受欢迎，可以方便有效地接触到可能存在严重慢性疾病(如冠心病)风险的社区成年人。使用这些工具来提高成年人的风险因素意识，并与临床测量的风险因素值保持一致，可能是提高公共卫生知识和建立有效干预措施的一个机会。目的:本研究的目的是确定基于互联网的健康风险评估是否可以突出受访者自我报告和临床测量的可能有冠心病风险的社区成年人的冠心病风险因素之间的重要一致性。方法:分析来自127个临床地点社区居民的基于互联网的心血管健康风险评估(Heart Aware)的数据。受访者是通过各个医院的营销活动招募的，如在住院和门诊设施中发现的媒体广告和印刷媒体。研究了弗雷明汉心脏研究的冠心病危险因素。计算加权kappa统计量，以衡量受访者自我报告的冠心病危险因素与临床测量的冠心病危险因素之间的等级间一致性。然后按10年冠心病总风险分层计算每个样本的加权kappa统计值。 Three samples were drawn based on strategies for treating missing data: a listwise deleted sample, a pairwise deleted sample, and a multiple imputation (MI) sample. Results: The MI sample (n=16,879) was most appropriate for addressing missing data. No CHD risk factor had better than marginal interrater agreement (κ>.60). High-density lipoprotein cholesterol (HDL-C) exhibited suboptimal interrater agreement that deteriorated (eg, κ<.30) as overall CHD risk increased. Conversely, low-density lipoprotein cholesterol (LDL-C) interrater agreement improved (eg, up to κ=.25) as overall CHD risk increased. Overall CHD risk of the sample was lower than comparative population-based CHD risk (ie, no more than 15% risk of CHD for the sample vs up to a 30% chance of CHD for the population). Conclusions: Interventions are needed to improve knowledge of CHD risk factors. Specific interventions should address perceptions of HDL-C and LCL-C. Internet-based health risk assessments such as Heart Aware may contribute to public health surveillance, but they must address selection bias of Internet-based recruitment methods. %M 24760950 %R 10.2196/jmir.2369 %U //www.mybigtv.com/2014/4/e106/ %U https://doi.org/10.2196/jmir.2369 %U http://www.ncbi.nlm.nih.gov/pubmed/24760950