AIM OF THE STUDY: Twitter has over 500 million subscribers but little is known about how it is used to communicate health information. We sought to characterize how Twitter users seek and share information related to cardiac arrest, a time-sensitive cardiovascular condition where initial treatment often relies on public knowledge and response. METHODS: Tweets published April-May 2011 with keywords cardiac arrest, CPR, AED, resuscitation, heart arrest, sudden death and defib were identified. Tweets were characterized by content, dissemination, and temporal trends. Tweet authors were further characterized by: self-identified background, tweet volume, and followers. RESULTS: Of 62,163 tweets (15,324, 25%) included resuscitation/cardiac arrest-specific information. These tweets referenced specific cardiac arrest events (1130, 7%), CPR performance or AED use (6896, 44%), resuscitation-related education, research, or news media (7449, 48%), or specific questions about cardiac arrest/resuscitation (270, 2%). Regarding dissemination (1980, 13%) of messages were retweeted. Resuscitation specific tweets primarily occurred on weekdays. Most users (10,282, 93%) contributed three or fewer tweets during the study time frame. Users with more than 15 resuscitation-specific tweets in the study time frame had a mean 1787 followers and most self-identified as having a healthcare affiliation. CONCLUSION: Despite a large volume of tweets, Twitter can be filtered to identify public knowledge and information seeking and sharing about cardiac arrest. To better engage via social media, healthcare providers can distil tweets by user, content, temporal trends, and message dissemination. Further understanding of information shared by the public in this forum could suggest new approaches for improving resuscitation related education.
AIM OF THE STUDY: Twitter has over 500 million subscribers but little is known about how it is used to communicate health information. We sought to characterize how Twitter users seek and share information related to cardiac arrest, a time-sensitive cardiovascular condition where initial treatment often relies on public knowledge and response. METHODS:Tweets published April-May 2011 with keywords cardiac arrest, CPR, AED, resuscitation, heart arrest, sudden death and defib were identified. Tweets were characterized by content, dissemination, and temporal trends. Tweet authors were further characterized by: self-identified background, tweet volume, and followers. RESULTS: Of 62,163 tweets (15,324, 25%) included resuscitation/cardiac arrest-specific information. These tweets referenced specific cardiac arrest events (1130, 7%), CPR performance or AED use (6896, 44%), resuscitation-related education, research, or news media (7449, 48%), or specific questions about cardiac arrest/resuscitation (270, 2%). Regarding dissemination (1980, 13%) of messages were retweeted. Resuscitation specific tweets primarily occurred on weekdays. Most users (10,282, 93%) contributed three or fewer tweets during the study time frame. Users with more than 15 resuscitation-specific tweets in the study time frame had a mean 1787 followers and most self-identified as having a healthcare affiliation. CONCLUSION: Despite a large volume of tweets, Twitter can be filtered to identify public knowledge and information seeking and sharing about cardiac arrest. To better engage via social media, healthcare providers can distil tweets by user, content, temporal trends, and message dissemination. Further understanding of information shared by the public in this forum could suggest new approaches for improving resuscitation related education.
Authors: Bentley J Bobrow; Daniel W Spaite; Robert A Berg; Uwe Stolz; Arthur B Sanders; Karl B Kern; Tyler F Vadeboncoeur; Lani L Clark; John V Gallagher; J Stephan Stapczynski; Frank LoVecchio; Terry J Mullins; Will O Humble; Gordon A Ewy Journal: JAMA Date: 2010-10-06 Impact factor: 56.272
Authors: Véronique L Roger; Alan S Go; Donald M Lloyd-Jones; Emelia J Benjamin; Jarett D Berry; William B Borden; Dawn M Bravata; Shifan Dai; Earl S Ford; Caroline S Fox; Heather J Fullerton; Cathleen Gillespie; Susan M Hailpern; John A Heit; Virginia J Howard; Brett M Kissela; Steven J Kittner; Daniel T Lackland; Judith H Lichtman; Lynda D Lisabeth; Diane M Makuc; Gregory M Marcus; Ariane Marelli; David B Matchar; Claudia S Moy; Dariush Mozaffarian; Michael E Mussolino; Graham Nichol; Nina P Paynter; Elsayed Z Soliman; Paul D Sorlie; Nona Sotoodehnia; Tanya N Turan; Salim S Virani; Nathan D Wong; Daniel Woo; Melanie B Turner Journal: Circulation Date: 2011-12-15 Impact factor: 29.690
Authors: Megan L Ranney; Brian Chang; Joshua R Freeman; Brian Norris; Mark Silverberg; Esther K Choo Journal: Acad Emerg Med Date: 2016-06-20 Impact factor: 3.451