Austin D Chen, Qing Zhao Ruan, Alexandra Bucknor, Anmol S Chattha, Patrick P Bletsis, Heather J Furnas, Bernard T Lee, Samuel J Lin
BACKGROUND: The aim of this study was to assess readability of articles shared on Twitter and analyze differences between them to determine whether messages and written posts are at reading levels comprehended by the general public. METHODS: Top-rated #PlasticSurgery tweets (per Twitter algorithm) in January of 2017 were reviewed retrospectively. Text from tweeted links to full, open-access, and society/institutional patient information articles were extracted. Readability was analyzed using the following established tests: Coleman-Liau, Flesch-Kincaid, FORCAST Readability Formula, Fry Graph, Gunning Fog Index, New Dale-Chall Formula, New Fog Count, Raygor Readability Estimate, and Simple Measure of Gobbledygook Readability Formula...
September 2019: Plastic and Reconstructive Surgery