Cardiovascular (CV) disease affects more than a third of adults in the United States and is associated with significant morbidity and mortality. Improvements in symptom recognition, treatment, health behavior modification, and medication adherence could reduce the burden of CV disease. In the current digital age, needed is a better understanding of how information on social media sites may inform our approaches to improving CV health through novel methodologies. We propose to study the conversation on Twitter about several CV diseases (hypertension [HTN], diabetes [DM], congestive heart failure [CHF], myocardial infarction [MI], sudden cardiac arrest [SCA]) and their associated sequelae (e.g. symptoms, risk factors, health behaviors, medication adherence, outcomes). First, in Aim 1 we will characterize tweets related to CV diseases and associated sequelae by frequency, relevance, content, accuracy, source, temporal characteristics, geography, and demographics.
In Aim 2, we will then use these data to measure the extent to which CV diseases and health behaviors reported via Twitter correlate with the known epidemiology of these conditions.
Aim 3 will explore temporal trends and news shocks to reveal the evolution, diffusion, and transformation of CV health data with a goal of creating a forecasting model to determine when and how to optimally disseminate CV high impact health messages. Finally, in Aim 4 we will identify and validate a sample of tweeters with self-reported CV diseases. We will then use Twitter to deliver high impact CV disease-specific information to improve patient activation and disease management. The long term goal of this proposal is to better understand the uses and limitations of studying this social and digital form of communication as an approach to improving CV health and health behaviors.

Public Health Relevance

In the current networking era, social media sites offer a unique opportunity to explore health related communication generated by the public and for the public. Using Twitter data, this research will reveal much about tweet dynamics in public health-information that can be used strategically to promote effective communication about cardiovascular health. The downstream goal of this study is to better understand how this data can be used to: predict cardiovascular epidemiology, disseminate high impact heart-targeted health messages, and engage and communicate with patients with heart disease through digital social networks.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL122457-02
Application #
8969697
Study Section
Biomedical Computing and Health Informatics Study Section (BCHI)
Program Officer
Wells, Barbara L
Project Start
2014-12-01
Project End
2017-11-30
Budget Start
2015-12-01
Budget End
2016-11-30
Support Year
2
Fiscal Year
2016
Total Cost
$728,538
Indirect Cost
$273,202
Name
University of Pennsylvania
Department
Emergency Medicine
Type
Schools of Medicine
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
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