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Background: Twitter is a social media platform popularly used by health practitioners, a trend that has been followed by medical journals. The impact of Twitter in bibliometrics of stroke-related literature is yet to be determined.
Aims: We aimed to qualitatively assess the usage of Twitter by stroke journals and study the relationship between Twitter activity and citation rates of stroke articles.
Methods: We used Journal Citation Reports to identify stroke journals. We collected the 2021 Impact Factor (IF) and the top 50 articles contributing to each journal IF. Relevant metrics were collected through Twitonomy, Altmetric, and Web of Science. The association between Twitter activity and citation rates was tested by a negative binomial regression model adjusted to journal's IF. A bivariate correlation and a log-linear regression model adjusted to journal's IF tested the relationship between number of tweets, tweeters, and the number of citations.
Results: We collected 450 articles across nine stroke-dedicated journals, five of which had a Twitter account. Only 95 (21%) articles had no Twitter mentions. The median number of citations in articles with versus without Twitter activity was 19 (10-39) versus 11(7-17) ( < 0.001). Twitter activity was associated with higher citation rates controlling for the IF (odds ratio (OR): 2.7, 95% confidence interval (CI) 2.12-3.38, < 0.001). We found number of tweets to be predicted by the number of citations controlling for the IF (B = 0.33, 95% CI 0.29-0.40, β = 0.54, < 0.001).
Conclusions: Tweeted stroke articles tend to have higher citation rates which can be predicted by the number of tweets.
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http://dx.doi.org/10.1177/17474930221136704 | DOI Listing |
J Sci Med Sport
August 2025
Sports Research Centre (Department of Sport Sciences), Miguel Hernandez University of Elche, Spain; Translational Research Centre of Physiotherapy, Department of Pathology and Surgery, Faculty of Medicine, Miguel Hernandez University, Spain.
Objectives: This study aimed to analyse the mechanisms, injury patterns, biomechanics and neurocognitive factors of anterior cruciate ligament tears in professional female Spanish football players during training and competitive matches.
Design: Systematic video-analysis observational study.
Methods: Four hundred and sixty-one players from 16 teams of the Spanish top division (Liga F) were tracked over three consecutive seasons (2021/2022 to 2023/2024).
Surgery
September 2025
Department of Surgery, University of Chicago, Chicago, IL. Electronic address: https://twitter.com/selwyn_rogers.
Public policy and health care are demonstrably interconnected. Medical and surgical outcomes are inseparableable from the political processes and laws that govern our nation. Health care delivery and public health are shaped by public discourse in city councils, county commissions, and state/national legislatures and agencies.
View Article and Find Full Text PDFJTCVS Open
August 2025
Department of Cardiothoracic Surgery, Wake Forest University School of Medicine, Winston-Salem, North Carolina.
Background: Social media use among cardiothoracic surgeons has yet to be analyzed. This study aimed to explore how online media utilization by cardiothoracic surgeons differs by subspecialty, sex, geographic region, practice type, level of experience, and training pathway.
Methods: A list of 223 cardiothoracic surgeons was generated by querying the 1066 members of the American Association for Thoracic Surgery and randomly selecting 223 actively practicing surgeons.
Rheumatol Int
September 2025
Department of Rheumatology, Immunology and Internal Medicine, University Hospital in Kraków, Kraków, Poland.
Introduction: Social media (SoMe) platforms provide ample opportunities for disseminating research results and journal updates. The presence of indexed rheumatology journals on SoMe has been scarcely explored.
Objectives: The purpose of this study is to assess the presence of mainstream rheumatology journals on key SoMe platforms and to analyze the relationship between bibliometric indicators and alternative metrics.
PLoS One
August 2025
Biocomputing and Developmental Systems (BDS) Research Group, University of Limerick, Limerick, Ireland.
The analysis of Arabic Twitter data sets is a highly active research topic, particularly since the outbreak of COVID-19 and subsequent attempts to understand public sentiment related to the pandemic. This activity is partially driven by the high number of Arabic Twitter users, around 164 million. Word embedding models are a vital tool for analysing Twitter data sets, as they are considered one of the essential methods of transforming words into numbers that can be processed using machine learning (ML) algorithms.
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