title: Imbalance of opinions expressed on Twitter relating to CT radiation risk: an opportunity for increased radiologist representation.
abstract: OBJECTIVE
  The purpose of this study was to assess perspectives and information relating to CT radiation risk on Twitter, a popular microblogging social network.
  
  
  METHODS
  Publicly available posts on Twitter ("tweets") containing both the words "CT" and "radiation" were identified from the 1st week of each month in 2013. Type of user posting and source of linked articles were recorded. Two reviewers assessed the content of tweets and links regarding CT's benefit-to-risk ratio (favorable, unfavorable, etc.).
  
  
  RESULTS
  Six hundred twenty-one relevant tweets were tweeted by 557 unique users, of whom 90 (16%) were physicians (17 of these were radiologists), 30 (5%) were medical practices or hospitals, 34 (6%) were patients, 8 (1%) were physicists or technologists, and 395 (71%) were other types of users. Two hundred twenty-seven tweets included user commentary regarding CT's benefit-to-risk ratio, of which 134 (59%) were unfavorable or concerned, 65 (29%) were neutral, 22 (10%) were informative regarding CT dose reduction strategies, and only 6 (3%) were favorable. Four hundred seventy-two tweets (76%) included links to a total of 99 unique articles, of which 25 (25%) were unfavorable or concerned, 10 (10%) were favorable, 25 (25%) were neutral, and 39 (39%) were informative regarding CT dose reduction. Article types were non-peer-reviewed medical sources (n = 50), lay press (n = 15), peer-reviewed medical journals (n = 13), blogs (n = 12), advertisements (n = 5), and informational websites (n = 4).
  
  
  CONCLUSIONS
  The large majority of content on Twitter was either unfavorable or concerned regarding CT radiation risk. Most articles were not peer-reviewed and were posted by nonphysicians; posts by physicians were largely by nonradiologists. More active engagement on Twitter by radiologists and physicists and increased dissemination of peer-reviewed articles may achieve a more balanced representation and alleviate concerns regarding CT radiation risk on social networks.
authors.affiliation: 1 Department of Radiology, NYU Langone Medical Center, 660 First Ave, New York, NY 10016.
authors.forename: Vinay
authors.initials: V
authors.lastname: Prabhu
authors.forename: Andrew B
authors.initials: AB
authors.lastname: Rosenkrantz
mesh_terms: D001294:Attitude to Health; D006801:Humans; D008402:Mass Media / Q000706:statistics & numerical data; D011639:Public Opinion; D011832:Radiation Injuries; D011871:Radiology; D018570:Risk Assessment / Q000706:statistics & numerical data*; D061108:Social Media / Q000706:statistics & numerical data*; D014057:Tomography, X-Ray Computed / Q000706:statistics & numerical data*
keywords: CT; Twitter; radiation risk; radiologists; social media