title: Trial Promoter: A Web-Based Tool for Boosting the Promotion of Clinical Research Through Social Media.
abstract: Scarce information about clinical research, in particular clinical trials, is among the top reasons why potential participants do not take part in clinical studies. Without volunteers, on the other hand, clinical research and the development of novel approaches to preventing, diagnosing, and treating disease are impossible. Promising digital options such as social media have the potential to work alongside traditional methods to boost the promotion of clinical research. However, investigators and research institutions are challenged to leverage these innovations while saving time and resources.
  
  
  
  To develop and test the efficiency of a Web-based tool that automates the generation and distribution of user-friendly social media messages about clinical trials.
  
  
  
  Trial Promoter is developed in Ruby on Rails, HTML, cascading style sheet (CSS), and JavaScript. In order to test the tool and the correctness of the generated messages, clinical trials (n=46) were randomized into social media messages and distributed via the microblogging social media platform Twitter and the social network Facebook. The percent correct was calculated to determine the probability with which Trial Promoter generates accurate messages.
  
  
  
  During a 10-week testing phase, Trial Promoter automatically generated and published 525 user-friendly social media messages on Twitter and Facebook. On average, Trial Promoter correctly used the message templates and substituted the message parameters (text, URLs, and disease hashtags) 97.7% of the time (1563/1600).
  
  
  
  Trial Promoter may serve as a promising tool to render clinical trial promotion more efficient while requiring limited resources. It supports the distribution of any research or other types of content. The Trial Promoter code and installation instructions are freely available online.
authors.affiliation: Southern California Clinical and Translational Science Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States. Katja.Reuter@usc.edu.
authors.forename: Katja
authors.identifier: 0000-0002-1559-9058
authors.initials: K
authors.lastname: Reuter
authors.forename: Francis
authors.identifier: 0000-0002-7040-5914
authors.initials: F
authors.lastname: Ukpolo
authors.forename: Edward
authors.identifier: 0000-0002-3910-7994
authors.initials: E
authors.lastname: Ward
authors.forename: Melissa L
authors.identifier: 0000-0001-7785-4221
authors.initials: ML
authors.lastname: Wilson
authors.forename: Praveen
authors.identifier: 0000-0001-7022-7049
authors.initials: P
authors.lastname: Angyan
mesh_terms: D035843:Biomedical Research; D006801:Humans; D020407:Internet; D008389:Marketing of Health Services; D018579:Patient Selection; D061108:Social Media
keywords: Facebook; Internet; Twitter; algorithm; automation; clinical trial; communication; online; patient; recruitment; social media; social network