1Faculty of Arts,Nursing and Theology,Avondale College of Higher Education,Wahroonga,New South Wales,Australia.
4National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Healthcare-Associated Infection and Antimicrobial Resistance, Imperial College London in partnership with Public Health England (PHE),London,United Kingdom.
Infect Control Hosp Epidemiol. 2017 Nov;38(11):1271-1276. doi: 10.1017/ice.2017.170. Epub 2017 Aug 22.
OBJECTIVE To examine tweeting activity, networks, and common topics mentioned on Twitter at 4 international infection control and infectious disease conferences. DESIGN A cross-sectional study. METHODS An independent company was commissioned to undertake a Twitter 'trawl' each month between July 1, 2016, and November 31, 2016. The trawl identified any tweets that contained the official hashtags of the conferences for (1) the UK Infection Prevention Society, (2) IDWeek 2016, (3) the Federation of Infectious Society/Hospital Infection Society, and (4) the Australasian College for Infection Prevention and Control. Topics from each tweet were identified, and an examination of the frequency and timing of tweets was performed. A social network analysis was performed to illustrate connections between users. A multivariate binary logistic regression model was developed to explore the predictors of 'retweets.' RESULTS In total, 23,718 tweets were identified as using 1 of the 2 hashtags of interest. The results demonstrated that the most tweets were posted during the conferences. Network analysis demonstrated a diversity of twitter networks. A link to a web address was a significant predictor of whether a tweet would be retweeted (odds ratio [OR], 2.0; 95% confidence interval [CI], 1.9-2.1). Other significant factors predicting a retweet included tweeting on topics such as Clostridium difficile (OR, 2.0; 95% CI, 1.7-2.4) and the media (OR, 1.8; 95% CI, 1.6-2.0). Tweets that contained a picture were significantly less likely to be retweeted (OR, 0.06; 95% CI, 0.05-0.08). CONCLUSION Twitter is a useful tool for information sharing and networking at infection control conferences. Infect Control Hosp Epidemiol 2017;38:1271-1276.
在 4 个国际感染控制和传染病会议上，检查 Twitter 上的发推活动、网络和常见话题。
横断面研究。
2016 年 7 月 1 日至 11 月 31 日，一家独立公司每月委托进行一次 Twitter“检索”。检索识别出任何包含会议官方标签的推文，这些会议是：（1）英国感染预防学会，（2）IDWeek 2016，（3）传染病学会/医院感染学会联合会，和（4）澳大利亚传染病预防和控制学院。从每条推文中识别出主题，并对推文的频率和时间进行了检查。进行社会网络分析以说明用户之间的联系。开发了多变量二项逻辑回归模型，以探讨“转发”的预测因子。
共确定了 23718 条使用 2 个感兴趣标签之一的推文。结果表明，会议期间发布的推文最多。网络分析表明 Twitter 网络具有多样性。链接到网站的链接是推文是否会被转发的重要预测因素（优势比[OR]，2.0；95%置信区间[CI]，1.9-2.1）。其他预测转发的重要因素包括在艰难梭菌（OR，2.0；95%CI，1.7-2.4）和媒体（OR，1.8；95%CI，1.6-2.0）等主题上发推。包含图片的推文被转发的可能性显著降低（OR，0.06；95%CI，0.05-0.08）。
Twitter 是感染控制会议上信息共享和网络联系的有用工具。感染控制与医院流行病学 2017；38：1271-1276。
