Bio


I work on omics and digital health related projects at Stanford

Projects


All Publications


  • The effect of digital physical activity interventions on daily step count: a randomised controlled crossover substudy of the MyHeart Counts Cardiovascular Health Study LANCET DIGITAL HEALTH Shcherbina, A., Hershman, S. G., Lazzeroni, L., King, A. C., O'Sullivan, J. W., Hekler, E., Moayedi, Y., Pavlovic, A., Waggott, D., Sharma, A., Yeung, A., Christle, J. W., Wheeler, M. T., McConnell, M. V., Harrington, R. A., Ashley, E. A. 2019; 1 (7): E344–E352
  • Physical activity, sleep and cardiovascular health data for 50,000 individuals from the MyHeart Counts Study. Scientific data Hershman, S. G., Bot, B. M., Shcherbina, A., Doerr, M., Moayedi, Y., Pavlovic, A., Waggott, D., Cho, M. K., Rosenberger, M. E., Haskell, W. L., Myers, J., Champagne, M. A., Mignot, E., Salvi, D., Landray, M., Tarassenko, L., Harrington, R. A., Yeung, A. C., McConnell, M. V., Ashley, E. A. 2019; 6 (1): 24

    Abstract

    Studies have established the importance of physical activity and fitness for long-term cardiovascular health, yet limited data exist on the association between objective, real-world large-scale physical activity patterns, fitness, sleep, and cardiovascular health primarily due to difficulties in collecting such datasets. We present data from the MyHeart Counts Cardiovascular Health Study, wherein participants contributed data via an iPhone application built using Apple's ResearchKit framework and consented to make this data available freely for further research applications. In this smartphone-based study of cardiovascular health, participants recorded daily physical activity, completed health questionnaires, and performed a 6-minute walk fitness test. Data from English-speaking participants aged 18 years or older with a US-registered iPhone who agreed to share their data broadly and who enrolled between the study's launch and the time of the data freeze for this data release (March 10 2015-October 28 2015) are now available for further research. It is anticipated that releasing this large-scale collection of real-world physical activity, fitness, sleep, and cardiovascular health data will enable the research community to work collaboratively towards improving our understanding of the relationship between cardiovascular indicators, lifestyle, and overall health, as well as inform mobile health research best practices.

    View details for PubMedID 30975992

  • Physical activity, sleep and cardiovascular health data for 50,000 individuals from the MyHeart Counts Study SCIENTIFIC DATA Hershman, S. G., Bot, B. M., Shcherbina, A., Doerr, M., Moayedi, Y., Pavlovic, A., Waggott, D., Cho, M. K., Rosenberger, M. E., Haskell, W. L., Myers, J., Champagne, M., Mignot, E., Salvi, D., Landray, M., Tarassenko, L., Harrington, R. A., Yeung, A. C., McConnell, M. V., Ashley, E. A. 2019; 6
  • Perceived Generational, Geographic, and Sex-Based Differences in Choosing a Career in Advanced Heart Failure. Circulation. Heart failure Moayedi, Y., Hershman, S. G., Ross, H. J., Khush, K. K., Teuteberg, J. J. 2019; 12 (7): e005754
  • The Myheart Counts Cardiovascular Health Study: A Randomized Controlled Trial of Digital Health Coaching for Physical Activity Promotion Shcherbina, A., Hershman, S., King, A. C., Hekler, E., Pavlovic, A., Waggott, D., McConnell, M. V., Ashley, E. A., Harrington, R. A. LIPPINCOTT WILLIAMS & WILKINS. 2018: E767
  • Data Descriptor: The asthma mobile health study, smartphone data collected using ResearchKit SCIENTIFIC DATA Chan, Y., Bot, B. M., Zweig, M., Tignor, N., Ma, W., Suver, C., Cedeno, R., Scott, E. R., Hershman, S., Schadt, E. E., Wang, P. 2018; 5: 180096

    Abstract

    Widespread adoption of smart mobile platforms coupled with a growing ecosystem of sensors including passive location tracking and the ability to leverage external data sources create an opportunity to generate an unprecedented depth of data on individuals. Mobile health technologies could be utilized for chronic disease management as well as research to advance our understanding of common diseases, such as asthma. We conducted a prospective observational asthma study to assess the feasibility of this type of approach, clinical characteristics of cohorts recruited via a mobile platform, the validity of data collected, user retention patterns, and user data sharing preferences. We describe data and descriptive statistics from the Asthma Mobile Health Study, whereby participants engaged with an iPhone application built using Apple's ResearchKit framework. Data from 6346 U.S. participants, who agreed to share their data broadly, have been made available for further research. These resources have the potential to enable the research community to work collaboratively towards improving our understanding of asthma as well as mobile health research best practices.

    View details for PubMedID 29786695

  • Big data, artificial intelligence, and cardiovascular precision medicine EXPERT REVIEW OF PRECISION MEDICINE AND DRUG DEVELOPMENT Krittanawong, C., Johnson, K. W., Hershman, S. G., Tang, W. 2018; 3 (5): 305–17