Does the quality of orthodontic studies influence their Altmetric Attention Score?
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
Objective: The aim of this study was to determine whether an association between study quality, other study characteristics, and Altmetric Attention Scores (AASs) existed in orthodontic studies. Methods: The Scopus database was searched to identify orthodontic studies published between January 1, 2017, and December 31, 2019. Articles that satisfied the eligibility criteria were included in this study. Study characteristics, including study quality were extracted and entered into a pre-pilot data collection sheet. Descriptive statistics were calculated. On an exploratory basis, random forest and gradient boosting machine learning algorithms were used to examine the influence of article characteristics on AAS. Results: In total, 586 studies with an AAS were analyzed. Overall, the mean AAS of the samples was 5. Twitter was the most popular social media platform for publicizing studies, accounting for 53.7%. In terms of study quality, only 19.1% of the studies were rated as having a high level of quality, with 41.8% of the studies deemed moderate quality. The type of social media platform, number of citations, impact factor, and study type were among the most influential characteristics of AAS in both models. In contrast, study quality was one of the least influential characteristics on the AAS. Conclusions: Social media platforms contributed the most to the AAS for orthodontic studies, whereas study quality had little impact on the AAS.
Abstract
Objective: The aim of this study was to determine whether an association between study quality, other study characteristics, and Altmetric Attention Scores (AASs) existed in orthodontic studies. Methods: The Scopus database was searched to identify orthodontic studies published between January 1, 2017, and December 31, 2019. Articles that satisfied the eligibility criteria were included in this study. Study characteristics, including study quality were extracted and entered into a pre-pilot data collection sheet. Descriptive statistics were calculated. On an exploratory basis, random forest and gradient boosting machine learning algorithms were used to examine the influence of article characteristics on AAS. Results: In total, 586 studies with an AAS were analyzed. Overall, the mean AAS of the samples was 5. Twitter was the most popular social media platform for publicizing studies, accounting for 53.7%. In terms of study quality, only 19.1% of the studies were rated as having a high level of quality, with 41.8% of the studies deemed moderate quality. The type of social media platform, number of citations, impact factor, and study type were among the most influential characteristics of AAS in both models. In contrast, study quality was one of the least influential characteristics on the AAS. Conclusions: Social media platforms contributed the most to the AAS for orthodontic studies, whereas study quality had little impact on the AAS.
참고문헌 (27)
- Pardeep Sud, "Evaluating altmetrics", Scientometrics, 98(2), pp.1131~1143 (2013), Springer Science and Business Media LLC[DOI]
- Wenya Huang, "A correlation comparison between Altmetric Attention Scores and citations for six PLOS journals", PLOS ONE, 13(4), pp.e0194962~ (2018), Public Library of Science (PLoS)[DOI]
- Robert K. Merton, "The Matthew Effect in Science", Science, 159(3810), pp.56~63 (1968), American Association for the Advancement of Science (AAAS)[DOI]
- Daniele Garcovich, "Measuring the social impact of research in Paediatric Dentistry: An Altmetric study", International Journal of Paediatric Dentistry, 30(1), pp.66~74 (2019), Wiley[DOI]
- Zeina Asyyed, "The Use of Twitter by Plastic Surgery Journals", Plastic & Reconstructive Surgery, 143(5), pp.1092e~1098e (2019), Ovid Technologies (Wolters Kluwer Health)[DOI]
- Tara J. Brigham, "An Introduction to Altmetrics", Medical Reference Services Quarterly, 33(4), pp.438~447 (2014), Informa UK Limited[DOI]
- Susan A. Elmore, "The Altmetric Attention Score: What Does It Mean and Why Should I Care?", Toxicologic Pathology, 46(3), pp.252~255 (2018), SAGE Publications[DOI]
- Christos Livas, "Looking Beyond Traditional Metrics in Orthodontics: An Altmetric Study on the Most Discussed Articles on the Web", European Journal of Orthodontics, 40(2), pp.193~199 (2017), Oxford University Press (OUP)[DOI]
- Simon R. Knight, "Social Media and Online Attention as an Early Measure of the Impact of Research in Solid Organ Transplantation", Transplantation, 98(5), pp.490~496 (2014), Ovid Technologies (Wolters Kluwer Health)[DOI]
- Remedios Melero, "Altmetrics – a complement to conventional metrics", Biochemia Medica, 25(2), pp.152~160 (2015), Croatian Society for Medical Biochemistry and Laboratory Medicine[DOI]
- Robin Champieux, "PlumX", Journal of the Medical Library Association : JMLA, 103(1), pp.63~64 (2015), University Library System, University of Pittsburgh[DOI]
- Hannah Hughes, "The use of twitter by the trauma and orthopaedic surgery journals:twitter activity, impact factor, and alternative metrics", Cureus, pp.c13~ (2018), Springer Science and Business Media LLC[DOI]
- Aysah Amath, "Comparing alternative and traditional dissemination metrics in medical education", Medical Education, 51(9), pp.935~941 (2017), Wiley[DOI]
- K. Delli, "Measuring the social impact of dental research: An insight into the most influential articles on the Web", Oral Diseases, 23(8), pp.1155~1161 (2017), Wiley[DOI]
- Dafang Zhang, "Correlation Between Social Media Posts and Academic Citations of Orthopaedic Research", JAAOS: Global Research and Reviews, 4(9), pp.e20.00151~ (2020), Ovid Technologies (Wolters Kluwer Health)[DOI]
- Asha Madhavji, "Attitudes, awareness, and barriers toward evidence-based practice in orthodontics", American Journal of Orthodontics and Dentofacial Orthopedics, 140(3), pp.309~316.e2 (2011), Elsevier BV[DOI]
- Amanda Costa Araujo, "What are the variables associated with Altmetric scores?", Systematic Reviews, 10(1), pp.193~ (2021), Springer Science and Business Media LLC[DOI]
- Kyle N. Kunze, "Altmetrics Attention Scores for Randomized Controlled Trials in Total Joint Arthroplasty Are Reflective of High Scientific Quality: An Altmetrics-Based Methodological Quality and Bias Analysis", JAAOS: Global Research and Reviews, 4(12), pp.e20.00187~ (2020), Ovid Technologies (Wolters Kluwer Health)[DOI]
- L. Bondemark, "Long-term Stability of Orthodontic Treatment and Patient Satisfaction", The Angle Orthodontist, 77(1), pp.181~191 (2007), The Angle Orthodontist (EH Angle Education & Research Foundation)[DOI]
- Leo Breiman, "Random forests", Machine Learning, 45(1), pp.5~32 (2001), Springer Science and Business Media LLC[DOI]
- Jerome H. Friedman, "Greedy function approximation: A gradient boosting machine.", The Annals of Statistics, 29(5), pp.1189~1232 (2001), Institute of Mathematical Statistics[DOI]
- Jafar Kolahi, "Analysis of highly tweeted dental journals and articles: a science mapping approach", British Dental Journal, 226(9), pp.673~678 (2019), Springer Science and Business Media LLC[DOI]
- Yazan Hassona, "The online attention to oral cancer research: An Altmetric analysis", Oral Diseases, 25(6), pp.1502~1510 (2019), Wiley[DOI]
- Brent Thoma, "The impact of social media promotion with infographics and podcasts on research dissemination and readership", CJEM, 20(2), pp.300~306 (2017), Springer Science and Business Media LLC[DOI]
- Daniele Garcovich, "The online attention to orthodontic research: an Altmetric analysis of the orthodontic journals indexed in the journal citation reports from 2014 to 2018", Progress in Orthodontics, 21(1), pp.31~ (2020), Springer Science and Business Media LLC[DOI]
- StacyR Konkiel, "What can altmetrics tell us about interest in dental clinical trials?", Dental Hypotheses, 8(2), pp.31~33 (2017), Medknow[DOI]
- Maria A. Rodrigues, "Journal Impact Factor versus the Evidence Level of Articles Published in Plastic Surgery Journals", Plastic & Reconstructive Surgery, 133(6), pp.1502~1507 (2014), Ovid Technologies (Wolters Kluwer Health)[DOI]