Social media dissemination of a novel digital health approach: a social network analysis of the TeleCheckAF project

Abstract

Abstract Funding Acknowledgements Type of funding sources: None. Background TeleCheck-AF is a novel remote on-demand mobile health (mHealth) infrastructure supporting teleconsultations. During the COVID-19 pandemic, social media (SoMe) communication on Twitter contributed to the rapid dissemination and implementation of this health care innovation into 41 European hospitals by using the hashtag #TeleCheckAF. Purpose To (1) analyze the SoMe Twitter network behind #TeleCheckAF, (2) describe the communities and behavioral groups within the network and (3) to determine the opinion leaders and influencers. Methods Publicly available data on actors and interactions within the #TeleCheckAF SoMe network was collected by web-scraping from the platform Twitter. This included all public tweets that used the hashtag #TeleCheckAF including their meta-data. Based on this, a node list (Twitter accounts) and an edge list (ties between accounts) as well as a social network were created. The position of an actor in the network and an actor’s opinion leadership was analyzed with the help of centrality measures (i.e. degree centrality, closeness centrality, betweenness centrality). Communities, or groups of nodes that were highly connected to each other, were further assessed by a modularity algorithm. Behavioral groups were analyzed based on participation in the healthcare innovation TeleCheck-AF (active participation) and dissemination of #TeleCheckAF on Twitter. Three behavioral groups were defined: Diffusers (dissemination but no active participation), adopters (no dissemination but active participation) and communicative adopters (dissemination and active participation). Results The network consisted of 413 086 nodes and 636 502 edges. 287 actors within the SoMe Twitter network behind #TeleCheckAF, who were either diffusers, adopters or communicative adopters, were further analyzed. Twenty-two different communities and 20 opinion leaders were identified. Peaks in Twitter activity could be temporally related to (inter-,)national virtual conferences, where results on TeleCheck-AF were presented. Two official European Society of Cardiology (ESC) Twitter handles and two Twitter handles of ESC SoMe supervisors and ESC Journal SoMe editors were among the group of opinion leaders reflecting the effect of the ESC SoMe promotion strategy. Overall, not only professionals directly involved in the TeleCheck-AF project, but also different other stakeholders such as allied health professionals or health technology companies were represented within the network. Conclusion The SoMe network behind #TeleCheckAF showed a wide dissemination involving a broad spectrum of healthcare professionals and was accelerated by the official ESC Twitter handles. Social network analysis created a helpful insight into the mechanisms behind innovation dissemination within social media. Future research could further analyze the difssemination process using e.g. hazard modeling and investigate the evolution of the network and behaviors over time.