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      Social media in cardiovascular medicine: a contemporary review

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          Abstract

          Social media increasingly impact both the private and professional lives of the majority of the population, including individuals engaged in cardiovascular healthcare and research. Healthcare providers across the world use social media platforms such as Twitter or Facebook to find medical and scientific information, to follow scientific meetings, to discuss individual clinical cases with colleagues, and to engage with patients. While social media provide a means for fast, interactive and accessible communication without geographic boundaries, their use to obtain and disseminate information has limitations and the potential threats are not always clearly understood. Governance concerns include a lack of rigorous quality control, bias due to the pre-selection of presented content by filter algorithms, and the risk of inadvertent breach of patient confidentiality. This article provides information and guidance regarding the role and use of social media platforms in cardiovascular medicine, with an emphasis on the new opportunities for the dissemination of scientific information and continuing education that arise from their responsible use.

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          Most cited references39

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          Social Networking Sites and Addiction: Ten Lessons Learned

          Online social networking sites (SNSs) have gained increasing popularity in the last decade, with individuals engaging in SNSs to connect with others who share similar interests. The perceived need to be online may result in compulsive use of SNSs, which in extreme cases may result in symptoms and consequences traditionally associated with substance-related addictions. In order to present new insights into online social networking and addiction, in this paper, 10 lessons learned concerning online social networking sites and addiction based on the insights derived from recent empirical research will be presented. These are: (i) social networking and social media use are not the same; (ii) social networking is eclectic; (iii) social networking is a way of being; (iv) individuals can become addicted to using social networking sites; (v) Facebook addiction is only one example of SNS addiction; (vi) fear of missing out (FOMO) may be part of SNS addiction; (vii) smartphone addiction may be part of SNS addiction; (viii) nomophobia may be part of SNS addiction; (ix) there are sociodemographic differences in SNS addiction; and (x) there are methodological problems with research to date. These are discussed in turn. Recommendations for research and clinical applications are provided.
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            The Use of Facebook in Recruiting Participants for Health Research Purposes: A Systematic Review

            Background Social media is a popular online tool that allows users to communicate and exchange information. It allows digital content such as pictures, videos and websites to be shared, discussed, republished and endorsed by its users, their friends and businesses. Adverts can be posted and promoted to specific target audiences by demographics such as region, age or gender. Recruiting for health research is complex with strict requirement criteria imposed on the participants. Traditional research recruitment relies on flyers, newspaper adverts, radio and television broadcasts, letters, emails, website listings, and word of mouth. These methods are potentially poor at recruiting hard to reach demographics, can be slow and expensive. Recruitment via social media, in particular Facebook, may be faster and cheaper. Objective The aim of this study was to systematically review the literature regarding the current use and success of Facebook to recruit participants for health research purposes. Methods A literature review was completed in March 2017 in the English language using MEDLINE, EMBASE, Web of Science, PubMed, PsycInfo, Google Scholar, and a hand search of article references. Papers from the past 12 years were included and number of participants, recruitment period, number of impressions, cost per click or participant, and conversion rate extracted. Results A total of 35 studies were identified from the United States (n=22), Australia (n=9), Canada (n=2), Japan (n=1), and Germany (n=1) and appraised using the Critical Appraisal Skills Programme (CASP) checklist. All focused on the feasibility of recruitment via Facebook, with some (n=10) also testing interventions, such as smoking cessation and depression reduction. Most recruited young age groups (16-24 years), with the remaining targeting specific demographics, for example, military veterans. Information from the 35 studies was analyzed with median values being 264 recruited participants, a 3-month recruitment period, 3.3 million impressions, cost per click of US $0.51, conversion rate of 4% (range 0.06-29.50), eligibility of 61% (range 17-100), and cost per participant of US $14.41. The studies showed success in penetrating hard to reach populations, finding the results representative of their control or comparison demographic, except for an over representation of young white women. Conclusions There is growing evidence to suggest that Facebook is a useful recruitment tool and its use, therefore, should be considered when implementing future health research. When compared with traditional recruitment methods (print, radio, television, and email), benefits include reduced costs, shorter recruitment periods, better representation, and improved participant selection in young and hard to reach demographics. It however, remains limited by Internet access and the over representation of young white women. Future studies should recruit across all ages and explore recruitment via other forms of social media.
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              Tracking Social Media Discourse About the COVID-19 Pandemic: Development of a Public Coronavirus Twitter Data Set

              Background At the time of this writing, the coronavirus disease (COVID-19) pandemic outbreak has already put tremendous strain on many countries' citizens, resources, and economies around the world. Social distancing measures, travel bans, self-quarantines, and business closures are changing the very fabric of societies worldwide. With people forced out of public spaces, much of the conversation about these phenomena now occurs online on social media platforms like Twitter. Objective In this paper, we describe a multilingual COVID-19 Twitter data set that we are making available to the research community via our COVID-19-TweetIDs GitHub repository. Methods We started this ongoing data collection on January 28, 2020, leveraging Twitter’s streaming application programming interface (API) and Tweepy to follow certain keywords and accounts that were trending at the time data collection began. We used Twitter’s search API to query for past tweets, resulting in the earliest tweets in our collection dating back to January 21, 2020. Results Since the inception of our collection, we have actively maintained and updated our GitHub repository on a weekly basis. We have published over 123 million tweets, with over 60% of the tweets in English. This paper also presents basic statistics that show that Twitter activity responds and reacts to COVID-19-related events. Conclusions It is our hope that our contribution will enable the study of online conversation dynamics in the context of a planetary-scale epidemic outbreak of unprecedented proportions and implications. This data set could also help track COVID-19-related misinformation and unverified rumors or enable the understanding of fear and panic—and undoubtedly more.
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                Author and article information

                Journal
                European Heart Journal - Digital Health
                Oxford University Press (OUP)
                2634-3916
                November 2020
                November 01 2020
                November 30 2020
                November 2020
                November 01 2020
                November 30 2020
                : 1
                : 1
                : 10-19
                Affiliations
                [1 ]Cardiology Department, Gaia Hospital Centre, Vila Nova de Gaia, Portugal
                [2 ]Cardiovascular Research Centre, Faculty of Medicine, University of Porto, Porto, Portugal
                [3 ]European Society of Cardiology
                [4 ]Barts Heart Centre, London, UK
                [5 ]Barking, Havering and Redbridge University Hospitals, London, UK
                [6 ]Department of Cardiology, Hospital Universitario Lucus Augusti, Lugo, Spain
                [7 ]Department of Acute Cardiology, National Institute of Cardiovascular Diseases, Bratislava, Slovakia
                [8 ]Academy - Research Organization, Bratislava, Slovakia
                [9 ]Department of Cardiology, Oulu University Hospital, Oulu, Finland
                [10 ]Heart Centre Leipzig, Leipzig, Germany
                [11 ]University Hospital of Basel, Basel, Switzerland
                [12 ]Department of Cardiology, Policlinico Universitario “Tor Vergata”, Rome, Italy
                [13 ]Lewis Katz School of Medicine, Temple University, Cardiovascular Research Center, Philadelphia, PA, USA
                [14 ]Division of Cardiology, Medical University of Graz, Graz, Austria
                [15 ]Cardiology Department, Scientific and Research Institute of Cardiology and Internal Diseases, Almaty, Kazakhstan
                [16 ]Semmelweiss University Heart and Vascular Centre, Budapest, Hungary
                [17 ]Digital Health Committee of the European Society of Cardiology, Imperial College London (Royal Brompton Hospital), London, UK
                [18 ]Media Committee of the European Society of Cardiology, Royal Papworth Hospital, Cambridge, UK
                [19 ]Department of Cardiology, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany
                Article
                10.1093/ehjdh/ztaa004
                36713964
                dd42e020-a74f-4c24-8064-3ccde7f5a447
                © 2020

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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