Background Blogs are the major contributors to the large increase of new websites created each year. Most blogs allow readers to leave comments and, in this way, generate both conversation and encourage collaboration. Despite their popularity, however, little is known about blogs or their creators.Objectives To contribute to a better understanding of the medical blogosphere by investigating the characteristics of medical bloggers and their blogs, including bloggers’ Internet and blogging habits, their motivations for blogging, and whether or not they follow practices associated with journalism.Methods We approached 197 medical bloggers of English-language medical blogs which provided direct contact information, with posts published within the past month. The survey included 37 items designed to evaluate data about Internet and blogging habits, blog characteristics, blogging motivations, and, finally, the demographic data of bloggers.Pearson’s Chi-Square test was used to assess the significance of an association between 2 categorical variables. Spearman’s rank correlation coefficient was utilized to reveal the relationship between participants’ ages, as well as the number of maintained blogs, and their motivation for blogging. The Mann-Whitney U test was employed to reveal relationships between practices associated with journalism and participants’ characteristics like gender and pseudonym use.Results A total of 80 (42%) of 197 eligible participants responded. The majority of responding bloggers were white (75%), highly educated (71% with a Masters degree or doctorate), male (59%), residents of the United States (72%), between the ages of 30 and 49 (58%), and working in the healthcare industry (67%). Most of them were experienced bloggers, with 23% (18/80) blogging for 4 or more years, 38% (30/80) for 2 or 3 years, 32% (26/80) for about a year, and only 7% (6/80) for 6 months or less. Those who received attention from the news media numbered 66% (53/80). When it comes to best practices associated with journalism, the participants most frequently reported including links to original source of material and spending extra time verifying facts, while rarely seeking permission to post copyrighted material. Bloggers who have published a scientific paper were more likely to quote other people or media than those who have never published such a paper (U= 506.5, n1= 41, n2= 35, P= .016). Those blogging under their real name more often included links to original sources than those writing under a pseudonym (U= 446.5, n1= 58, n2= 19, P= .01). Major motivations for blogging were sharing practical knowledge or skills with others, influencing the way others think, and expressing oneself creatively.Conclusions Medical bloggers are highly educated and devoted blog writers, faithful to their sources and readers. Sharing practical knowledge and skills, as well as influencing the way other people think, were major motivations for blogging among our medical bloggers. Medical blogs are frequently picked up by mainstream media; thus, b...

Use of Lifesaver by school children, compared to F2F training alone, can lead to comparable learning outcomes for several key elements of successful CPR. Its use can be considered where resources or time do not permit formal F2F training sessions. The true benefits of Lifesaver can be realised if paired with F2F training.

Only a small proportion of registered emergency physicians use Twitter. Among them exists a smaller inner network of emergency physicians with strong social bonds that is using Twitter's full potentials for professional development.

IntroductionTwitter has recently gained popularity in emergency medicine (EM). Opinion leaders on Twitter have significant influence on the conversation and content, yet little is known about these opinion leaders. We aimed to describe a methodology to identify the most influential emergency physicians (EP) on Twitter and present a current list.MethodsWe analyzed 2,234 English-language EPs on Twitter from a previously published list of Twitter accounts generated by a snowball sampling technique. Using NodeXL software, we performed a network analysis of these EPs and ranked them on three measures of influence: in-degree centrality, eigenvector centrality, and betweenness centrality. We analyzed the top 100 users in each of these three measures of influence and compiled a list of users found in the top 100 in all three measures.ResultsOf the 300 total users identified by one of the measures of influence, there were 142 unique users. Of the 142 unique users, 61 users were in the top 100 on all three measures of influence. We identify these 61 users as the most influential EM Twitter users.ConclusionWe both describe a method for identifying the most influential users and provide a list of the 61 most influential EPs on Twitter as of January 1, 2016. This application of network science to the EM Twitter community can guide future research to better understand the networked global community of EM.

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