Twitter and Cardiovascular Health

描述（由申请人提供）：心血管（CV）疾病影响美国超过三分之一的成年人，并与显著的发病率和死亡率相关。症状识别、治疗、健康行为改变和药物依从性的改善可以减轻CV疾病的负担。在当前的数字时代，我们需要更好地了解社交媒体网站上的信息如何通过新方法为我们改善CV健康提供信息。我们建议研究Twitter上关于几种CV疾病（高血压[HTN]、糖尿病[DM]、充血性心力衰竭[CHF]、心肌梗死[MI]、心脏骤停[SCA]）及其相关后遗症（例如症状、风险因素、健康行为、药物依从性、结局）的对话。首先，在目标1中，我们将通过频率、相关性、内容、准确性、来源、时间特征、地理和人口统计学来描述与CV疾病和相关后遗症相关的推文。在目标2中，我们将使用这些数据来衡量通过Twitter报告的CV疾病和健康行为与这些疾病的已知流行病学相关的程度。目标3将探索时间趋势和新闻冲击，以揭示CV健康数据的演变、扩散和转化，目标是创建预测模型，以确定何时以及如何最佳地传播CV高影响力健康信息。最后，在目标4中，我们将识别和验证一个自我报告CV疾病的高音扬声器样本。然后，我们将使用Twitter提供高影响力的CV疾病特定信息，以改善患者激活和疾病管理。该提案的长期目标是更好地了解研究这种社交和数字形式的沟通作为改善CV健康和健康行为的方法的用途和局限性。

DESCRIPTION (provided by applicant): 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.