Abstract
Altmetric Attention Score (AAS) captures online attention received by a research article in addition to traditional bibliometrics. We present a comprehensive bibliometric analysis of high AAS articles and identify predictors of AAS in orthopedics. The top 30 articles with highest AAS were selected from orthopedic journals using the Dimensions App. Multilevel mixed-effects linear regression was used to address clustering in articles from the same journal, with journals as the leveling variable. A total of 750 articles from 25 journals were included. In the final multivariable model, the funding source (none, industry, government, foundation, university, or multiple), findings (positive, negative, neutral, or not applicable), and the journal's impact factor were significant at P<.05. Predictors of AAS are similar to predictors of traditional bibliometrics. Future studies need prospective dynamic data to further elucidate the AAS. [Orthopedics. 20XX;4X(X):XXX-XXX.].
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