Twitter & Cardiovascular Health
Phase: NA
Conditions: Cardiovascular Disease, Hypertension
Sponsor: University of Pennsylvania

 
 Cover Page  
Study Title: Twitter and Cardiovascular Health  
NCT: NCT02806700  
PI: Raina Merchant MD  
University of Pennsylvania  
Re: Statistical analysis plan  
Last update 10.24.2018  
 
 
 

Protocol (Twitter and Cardiovascular Health: Twitter and Hypertension)  
 
Background 
Cardiovascular (CV) disease remains the leading cause of morbidity and mortality in the US and 
is associated with significant economic burden. While there is effective medical treatment for 
hypertension (HTN) in the form of prescription medications, blood pressure management is 
likewise dependent on several lifestyle choices. A patient’s diet, exercise, monitoring of 
symptoms and adherence to medication (activities that occur outside of the physician’s office), 
have an effect on clinical outcomes. Social media channels like Twitter offer a new opportunity 
to explore health related communication generated by the public and for the public about areas 
such as HTN and its management. 
 
Objectives 
This project leverages Twitter, a public online platform, to study if  there is a potential benefit of 
tweeting regularly about health. We will ask patients with a diagnosis of HTN and elevated BP to 
regularly tweet about health content and evaluate if this intervention will improve their perceived 
disease management and their systolic blood pressure over a six-month timeframe.  
 
Methods 
We will identify patients greater than or equal to 21 years of age, with known HTN (ICD-9 code 
401.9) from a single health system. These patients will then be contacted via email. Eligibility 
questions include: greater than or equal to 21 years of age, not pregnant (self-report), a 
diagnosis of hypertension and a Twitter account or willingness to create an account for the 
study. 
 
Eligible patients who consent to participate would then complete a baseline survey and be 
randomized to the control or intervention group. Randomization will occur via a computerized 
randomization program in a 1:1 allocation ratio not accessible until after collection of baseline 
data. 
 
Survey compensation of a gift card worth $25 would be provided for completion of the final 
survey at 6 months. Baseline and follow-up surveys will include questions regarding patient 
activation (PAM-13), self-rated health (SF-1), ideal CV health (BRFSS), HTN self-care practices 
and demographics. To assess technology use, we will also ask questions from the Perceived 
usefulness, and Perceived ease of use surveys. Patients will also consent to having their 
electronic health records accessed to validate clinical data (e.g. blood pressure (BP), BMI). 
 
Control: The control group study participation would include completing a baseline survey and a 
survey 6 months later. 
 
Intervention: Participants randomized to the intervention group will be asked to follow the study 
Twitter account, tweet or retweet health content twice per week using #health and complete a 
survey at study initiation and 6 months later. Participants will be sent weekly reminders to tweet.  
 
Outcome measures:  The primary outcome measure will be change in systolic blood pressure 
(5mm). The secondary outcome will be patient activation measured by the PAM (a measure of 
behavior change that has been shown to be changeable over time). Baseline variables will 
include demographic variables (gender, age, race/ethnicity, and geographic region of 
residence).  
 

Sample size: Sample size estimates based on the ability to detect a 5mmHg difference in 
systolic blood pressure at 90% power and type I error of 0.05. We planned to enroll 
approximately 240 in each control and intervention group, for a total of 480 participants, 
accounting for a 35% lost to follow up for an online Twitter intervention (total up to 648). 
 
Data analysis: We will use summary statistics to compare demographics and survey responses 
(health status, ideal CV health status, self-practices perceived usefulness/ease of use) between 
groups. Categorical variables will be presented as frequencies and percentages and continuous 
baseline variables will be presented as means and standard deviations (if skewed these will be 
presented as medians and interquartile ranges). 
 
Our primary outcome will be a 5mmHg change in systolic blood pressure from baseline to study 
end at 6 months. We will conduct an intent-to-treat analysis. We will use paired t-tests to 
compare the mean difference in SBP between the intervention and control groups. We will also 
conduct a multiple linear regression analysis for change in SBP adjusting for covariates which 
may be imbalanced even after randomization to improve efficiency of our estimates. We will 
also adjust for baseline SBP. The distribution of change in SBP will be assessed and if it is non-
normal (skewed) we will use an appropriate transformation (such as natural log) or we will use a 
generalized linear model with appropriate family and link choices to model our outcome.  
For the secondary outcome measure, we will use paired t-test for pre-post differences of PAM 
scores. A multiple linear regression model will also be used to account for additional imbalances 
in  demographic and baseline health characteristics not evenly distributed by arm.  In all models, 
a binary indicator for control/intervention group will be included. Baseline PAM score will also be 
adjusted for in the model. Covariates with missing data will be assessed for patterns of 
missingness and non-ignorability and will be multiply imputed if deemed necessary and 
reasonable.