McManus David D, Trinquart Ludovic, Benjamin Emelia J, Manders Emily S, Fusco Kelsey, Jung Lindsey S, Spartano Nicole L, Kheterpal Vik, Nowak Christopher, Sardana Mayank, Murabito Joanne M
Cardiology Division, Department of Medicine, University of Massachusetts Medical School, Worcester, MA, United States.
Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, United States.
J Med Internet Res. 2019 Mar 1;21(3):e12143. doi: 10.2196/12143.
New models of scalable population-based data collection that integrate digital and mobile health (mHealth) data are necessary.
The aim of this study was to describe a cardiovascular digital and mHealth electronic cohort (e-cohort) embedded in a traditional longitudinal cohort study, the Framingham Heart Study (FHS).
We invited eligible and consenting FHS Generation 3 and Omni participants to download the electronic Framingham Heart Study (eFHS) app onto their mobile phones and co-deployed a digital blood pressure (BP) cuff. Thereafter, participants were also offered a smartwatch (Apple Watch). Participants are invited to complete surveys through the eFHS app, to perform weekly BP measurements, and to wear the smartwatch daily.
Up to July 2017, we enrolled 790 eFHS participants, representing 76% (790/1044) of potentially eligible FHS participants. eFHS participants were, on average, 53±8 years of age and 57% were women. A total of 85% (675/790) of eFHS participants completed all of the baseline survey and 59% (470/790) completed the 3-month survey. A total of 42% (241/573) and 76% (306/405) of eFHS participants adhered to weekly digital BP and heart rate (HR) uploads, respectively, over 12 weeks.
We have designed an e-cohort focused on identifying novel cardiovascular disease risk factors using a new smartphone app, a digital BP cuff, and a smartwatch. Despite minimal training and support, preliminary findings over a 3-month follow-up period show that uptake is high and adherence to periodic app-based surveys, weekly digital BP assessments, and smartwatch HR measures is acceptable.
需要新的基于人群的可扩展数据收集模型，该模型要整合数字和移动健康（mHealth）数据。
本研究旨在描述一个嵌入传统纵向队列研究——弗雷明汉心脏研究（FHS）中的心血管数字和mHealth电子队列（e队列）。
我们邀请符合条件并同意参与的FHS第三代和Omni参与者将电子弗雷明汉心脏研究（eFHS）应用程序下载到他们的手机上，并共同部署了一个数字血压（BP）袖带。此后，还为参与者提供了一块智能手表（苹果手表）。邀请参与者通过eFHS应用程序完成调查问卷，每周进行血压测量，并每天佩戴智能手表。
截至2017年7月，我们招募了790名eFHS参与者，占潜在符合条件的FHS参与者的76%（790/1044）。eFHS参与者的平均年龄为53±8岁，57%为女性。共有85%（675/790）的eFHS参与者完成了所有基线调查，59%（470/790）完成了3个月的调查。在12周内，分别有42%（241/573）和76%（306/405）的eFHS参与者坚持每周上传数字血压和心率（HR）数据。
我们设计了一个e队列，通过一款新的智能手机应用程序、一个数字BP袖带和一块智能手表来识别新的心血管疾病风险因素。尽管培训和支持很少，但3个月随访期的初步结果表明，接受度很高，对基于应用程序的定期调查、每周数字血压评估和智能手表心率测量的依从性是可以接受的。
