BackgroundPoor dissemination of research findings may hamper the reach and impact of scientific discoveries. One key emerging platform for research dissemination is social media, including Twitter. While Twitter and other social media are increasingly being used to disseminate research content presented during scientific conferences, few studies have investigated the extent to which these tools are used throughout conferences and how they are being used. The aim for this study was to better understand the use of Twitter during the 2016 Annual Conference on the Science of Dissemination and Implementation in Health (D&I conference).MethodsWe performed an analysis of Twitter use before, during, and after the 2016 D&I conference, which took place from December 14 to 15. All tweets (posted between December 1 and 31) that included the conference-specific hashtag (#DIScience16) were assessed. We identified 2639 tweets using the data analytics platform NUVI. We used NUVI software to generate statistics about reach, influence, mentions, and origin of the tweets. Individual tweet content was also assessed using DiscoverText and coded for disease category, implementation outcomes discussed, category of tweet, and conference track.ResultsA total of 2639 tweets were analyzed; 89.1% of the tweets were posted during the conference. A total of 389 unique users participated on Twitter, representing 31 states and 22 locations outside of the USA. Most (56.8%) tweets were re-tweets and were used for scientific promotion (50.6%). Key conference speakers and implementation outcomes (de-implementation, adaptation, and fidelity) were commonly discussed.ConclusionsOur findings reveal that Twitter was used as a platform during the D&I conference, both to facilitate conference discussion and to promote scientific ideas. This work contributes to the existing data analytics and implementation science literature in two major ways: (1) by advancing knowledge of how social media is used during annual academic conferences and (2) by providing a deeper understanding of themes and emerging areas of interest in the dissemination and implementation sciences. Knowing specific topics of interest can help planners and scientists better understand the landscape of current and future implementation research and encourage new research dissemination strategies.

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To better understand user conversations revolving around antibiotics and antimicrobial resistance (AMR) on Twitter, we used an online data collection and analysis toolkit with full firehose access to collect corpuses of tweets with "antibiotic" and "antimicrobial resistance" keyword tracks. The date range included tweets from November 28, 2015, to November 25, 2016, for both datasets. This yearlong date range provides insight into how users have discussed antibiotics and AMR and identifies any spikes in activity during a particular time frame. Overall, we found that discussions about antibiotics and AMR predominantly occur in the United States and the United Kingdom, with roughly equal gender participation. These conversations are influenced by news sources, health professionals, and governmental health organizations. Users will often defer to retweet and recirculate content posted from these official sources and link to external articles instead of posting their own musings on the subjects. Our findings are important benchmarks in understanding the prevalence and reach of potential misinformation about antibiotics and AMR on Twitter.

Background: The growing availability of genomic information to the public may spur discussion about genetics and genomics on social media. Sites, including Twitter, provide a unique space for the public to access and discuss health information. The objective of this study was to better understand how social media users are sharing information about genetics and genomics in health and healthcare and what information is most commonly discussed among Twitter users. Methods: We obtained tweets with specific genetics- and genomics-related keywords from Crimson Hexagon. We used Boolean logic to collect tweets containing chosen keywords within the timeframe of October 1, 2016, to October 1, 2017. Features of the software were used to identify salient themes in conversation, conduct an emergent content analysis, and gather key demographic information. Results: We obtained 347,196 tweets from our search. There was a monthly average volume of 28,432 tweets. The five categories of tweets included: genetic disorders/disease (45.3%), health (15.6%), genomics (8%), and genetic testing (7.3%). Top influencers in the conversation included news outlets and universities. Conclusions: This content analysis provides insight about the types of conversation related to genomics and health. Conversations about genomics are occurring on Twitter, and they frequently emphasize rare genetic diseases and genetic disorders. These discussions tend to be driven by key influencers who primarily include news media outlets. Further understanding of the discussions related to genomics and health in social media may offer insight about topics of importance to the public.

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