UMMS Affiliation

Division of Cardiovascular Medicine, Department of Medicine; Department of Quantitative Health Sciences

Publication Date


Document Type



Cardiology | Cardiovascular Diseases | Diagnosis | Telemedicine


BACKGROUND: New models of scalable population-based data collection that integrate digital and mobile health (mHealth) data are necessary.

OBJECTIVE: 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).

METHODS: 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.

RESULTS: 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.

CONCLUSIONS: 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.


ambulatory, blood pressure monitoring, cohort studies, smartphone, tele-medicine

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© David D McManus, Ludovic Trinquart, Emelia J Benjamin, Emily S Manders, Kelsey Fusco, Lindsey S Jung, Nicole L Spartano, Vik Kheterpal, Christopher Nowak, Mayank Sardana, Joanne M Murabito. Originally published in the Journal of Medical Internet Research (, 01.03.2019. This is an open-access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on, as well as this copyright and license information must be included.

DOI of Published Version



J Med Internet Res. 2019 Mar 1;21(3):e12143. doi: 10.2196/12143. Link to article on publisher's site

Journal/Book/Conference Title

Journal of medical Internet research

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Link to Article in PubMed

PubMed ID


Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.