Impact of a Physician-Led Social Media Sharing Program on a Medical Journal's Web Traffic

J Am Coll Radiol. 2018 Jan;15(1 Pt B):184-189. doi: 10.1016/j.jacr.2017.09.035. Epub 2017 Nov 6.


Purpose: The use of social media by health professionals and medical journals is increasing. The aim of this study was to compare online views of articles in press (AIPs) released by Annals of Emergency Medicine before and after a nine-person social media team started actively posting links to AIPs using their personal Twitter accounts.

Methods: An observational before-and-after study was conducted. Web traffic data for Annals were obtained from the publisher (Elsevier), detailing the number of page views to by referring websites during the study period. The preintervention time period was defined as January 1, 2013, to June 30, 2014, and the postintervention period as July 1, 2014, to July 31, 2015. The primary outcome was page views from Twitter per AIP released each month to account for the number of articles published each month. Secondary outcomes included page views from Facebook (on which there was no article-sharing intervention) and total article views per month.

Results: The median page views from Twitter per individual AIP released each month increased from 33 in the preintervention period to 130, for an effect size of 97 (95% confidence interval, 56-111; P < .001). There was a smaller increase in median page views from Facebook per individual AIP of 21 (95% confidence interval, 10-32). There was no significant increase in these median values for total page views per AIP.

Conclusions: Twitter sharing of AIPs increased the number of page views that came from Twitter but did not increase the overall number of page views.

Keywords: Social media; education; peer-reviewed literature.

Publication types

  • Observational Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bibliometrics*
  • Emergency Medicine*
  • Humans
  • Medical Writing*
  • Periodicals as Topic*
  • Social Media / statistics & numerical data*