Twitter and Cardiovascular Health

推特和心血管健康

• 批准号: 8969697
• 负责人: Raina Merchant
• 金额: $ 73.96万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-12-01 至 2017-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8969697
• 关键词: Address; Adult; Affect; Age; Behavior Therapy; Belief; Body Weight decreased; Cardiovascular Diseases; Cardiovascular system; Characteristics; Chronic Disease; Clinical; Collection; Communication; Communications Media; Congestive Heart Failure; Data; Diabetes Mellitus; Diffusion; Disease; Disease Management; Epidemiology; Ethics; Evolution; Frequencies; Friends; Geography; Goals; Health; Health Status; Health behavior; Health behavior change; Hearing; Heart; Heart Arrest; Heart Diseases; Hour; Hypertension; Individual; Influentials; Intercept; Life; Logistics; Measures; Media Intervention; Methodology; Mining; Modeling; Morbidity - disease rate; Myocardial Infarction; Outcome; Patient Self-Report; Patients; Personal Behavior; Persons; Pharmaceutical Preparations; Physical activity; Physicians; Population; Provider; Public Health; Reporting; Research; Risk Factors; Sampling; Shock; Site; Social Network; Source; Symptoms; Time; United States; Variant; Work; cardiovascular disorder epidemiology; cardiovascular health; demographics; digital; health data; improved; medication compliance; mortality; news; novel; patient population; social; social media; social networking website; social norm; trend

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.

描述（由申请人提供）：心血管疾病（CV）疾病影响了美国的三分之一以上，并且与显着的发病率和死亡率有关。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简历疾病的负担。在当前的数字时代，需要更好地理解社交媒体网站上的信息如何通过新颖的方法来告知我们改善简历健康的方法。我们建议在Twitter上研究有关几种CV疾病（高血压[HTN]，糖尿病[DM]，充血性心力衰竭[CHF]，心肌梗死[MI]，突然心脏骤停[SCA]）及其相关的后遗症（例如，症状，风险因素，健康性因素，健康行为，医学上的辅助，超级效果））。首先，在AIM 1中，我们将按频率，相关性，内容，准确性，源，时间特征，地理和人口统计学来表征与简历疾病和相关后遗症相关的推文。在AIM 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。 AIM 3将探索时间趋势和新闻冲击，以揭示简历健康数据的演变，扩散和转换，目的是创建一个预测模型，以确定何时以及如何最佳地传播CV高影响力健康消息。最后，在AIM 4中，我们将识别并验证具有自我报告的简历疾病的高音扬声器样本。然后，我们将使用Twitter提供高影响CV特定疾病的信息，以改善患者的激活和疾病管理。该提案的长期目标是更好地理解研究这种社会和数字形式的交流的用途和局限性，以改善简历健康和健康行为的方法。