Creating a social media strategy for an international cardiothoracic research network: a scoping review.

Autor: Fredericks, Suzanne, Bae, Tammy, Sochaniwskyj, Mark, Sanders, Julie, Martorella, Geraldine, Wynne, Rochelle
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Zdroj: European Journal of Cardiovascular Nursing; Nov2023, Vol. 22 Issue 8, p751-757, 7p
Abstrakt: Aims: A cardiac surgery international nursing and allied professional research network titled CONNECT was created to strengthen collaborative cardiac surgery research through shared initiatives including supervision, mentorship, workplace exchange programs, and multi-site clinical research. As with any new initiative, there is a need to build brand awareness to enhance user familiarity, grow membership, and promote various opportunities offered. Social media has been used across various surgical disciplines; however, their effectiveness in promoting scholarly and academic-based initiatives has not been examined. The aim of this scoping review was to examine the different types of social media platforms and strategies used to promote cardiac research initiatives for CONNECT. Methods and results: A scoping review was undertaken in which a comprehensive and thorough review of the literature was performed. Fifteen articles were included in the review. Twitter appeared to be the most common form of social media used to promote cardiac initiatives, with daily posts being the most frequent type of engagement. Frequency of views, number of impressions and engagement, link clicks, and content analysis were the most common types of evaluation metrics that were identified. Conclusion: Findings from this review will inform the design and evaluation of a targeted Twitter campaign aimed at increasing brand awareness of CONNECT, which will include the use of @CONNECTcardiac Twitter handle, hashtags, and CONNECT-driven journal clubs. In addition, the use of Twitter to disseminate information and brand initiatives related to CONNECT will be evaluated using the Twitter Analytics function. Registration: Open Science Framework: osf.io/q54es Graphical Abstract [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index