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Bibliometric Analysis of Predictors of Altmetric Attention Scores in Orthopedic Research: Investigating Online Visibility.
Orthopedics ; : 1-5, 2024 Aug 19.
Article em En | MEDLINE | ID: mdl-39163605
ABSTRACT

BACKGROUND:

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. MATERIALS AND

METHODS:

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.

RESULTS:

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.

CONCLUSION:

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.].

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Orthopedics Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Orthopedics Ano de publicação: 2024 Tipo de documento: Article
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