TY - JOUR
T1 - Bibliometric Analysis of Predictors of Altmetric Attention Scores in Orthopedic Research
T2 - Investigating Online Visibility
AU - Ibrahim, Muhammad Talal
AU - Imran, Hamza
AU - Shuja, Muhammad Hamza
AU - Sheraz, Haider
AU - Howard, Andrew
AU - Noordin, Shahryar
PY - 2024/11/1
Y1 - 2024/11/1
N2 - 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. 2024;47(6):e317-e321.].
AB - 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. 2024;47(6):e317-e321.].
UR - https://www.scopus.com/pages/publications/85210549066
U2 - 10.3928/01477447-20240809-03
DO - 10.3928/01477447-20240809-03
M3 - Article
C2 - 39163605
AN - SCOPUS:85210549066
SN - 0147-7447
VL - 47
SP - e317-e321
JO - Orthopedics
JF - Orthopedics
IS - 6
ER -