BACKGROUND: Twitter in anesthesiology conferences promotes rapid science dissemination, global audience participation, and real-time updates of simultaneous sessions. We designed this study to determine if an association exists between conference attendance/registration and 4 defined Twitter metrics. METHODS: Using publicly available data through the Symplur Healthcare Hashtags Project and the Symplur Signals, we collected data on total tweets, impressions, retweets, and replies as 4 primary outcome metrics for all registered anesthesiology conferences occurring from May 1, 2016 to April 30, 2017. The number of Twitter participants, defined as users who contributed a tweet, retweet, or reply 3 days before through 3 days after the conference, was collected. We also collected influencer data as determined by mentions (number of times a user is referenced). Two authors independently verified the categories for influencers assigned by Symplur. Conference demographic data were obtained by e-mail inquiries. Associations between meeting attendees/registrants and Twitter metrics, between Twitter participants and the metrics, and between physician influencers and Twitter participants were tested using Spearman rho. RESULTS: Fourteen conferences with 63,180 tweets were included. With the American Society of Anesthesiologists annual meeting included, the correlations between meeting attendance/registration and total tweets (rs = 0.588; P = .074), impressions (rs = 0.527; P = .117), and retweets (rs = 0.539; P = .108) were not statistically significant; for replies, it was moderately positive (rs = 0.648; P = .043). Without the American Society of Anesthesiologists annual meeting, total tweets (rs = 0.433; P = .244), impressions (rs = 0.350; P = .356), retweets (rs = 0.367; P = .332), and replies (rs = 0.517; P = .154) were not statistically significant. Secondary outcomes include a highly positive correlation between Twitter participation and total tweets (rs = 0.855; P< .001),very highly positive correlations between Twitter participation and impressions (rs = 0.938; P < .001), retweets (rs = 0.925; P < .001), and a moderately positive correlation between Twitter participation and replies (rs = 0.652; P = .044). Doctors were top influencers in 8 of 14 conferences, and the number of physician influencers in the top 10 influencers list at each conference had a moderately positive correlation with Twitter participation (rs = 0.602; P = .023). CONCLUSIONS: We observed that the number of Twitter participants for a conference is positively associated with Twitter activity metrics. No relationship between conference size and Twitter metrics was observed. Physician influencers may be an important driver of participants.
Schwenk, E. S., Jaremko, K. M., Park, B. H., Stiegler, M. A., Gamble, J. G., Chu, L. F., … Mariano, E. R. (2020). I tweet, therefore I learn: An analysis of twitter use across anesthesiology conferences. Anesthesia and Analgesia, 333–340. https://doi.org/10.1213/ANE.0000000000004036