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Feasibility of common bibliometrics in evaluating translational science

INTRODUCTION: A pilot study by 6 Clinical and Translational Science Awards (CTSAs) explored how bibliometrics can be used to assess research influence. METHODS: Evaluators from 6 institutions shared data on publications (4202 total) they supported, and conducted a combined analysis with state-of-the...

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Autores principales: Schneider, M., Kane, C. M., Rainwater, J., Guerrero, L., Tong, G., Desai, S. R., Trochim, W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408837/
https://www.ncbi.nlm.nih.gov/pubmed/28480055
http://dx.doi.org/10.1017/cts.2016.8
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author Schneider, M.
Kane, C. M.
Rainwater, J.
Guerrero, L.
Tong, G.
Desai, S. R.
Trochim, W.
author_facet Schneider, M.
Kane, C. M.
Rainwater, J.
Guerrero, L.
Tong, G.
Desai, S. R.
Trochim, W.
author_sort Schneider, M.
collection PubMed
description INTRODUCTION: A pilot study by 6 Clinical and Translational Science Awards (CTSAs) explored how bibliometrics can be used to assess research influence. METHODS: Evaluators from 6 institutions shared data on publications (4202 total) they supported, and conducted a combined analysis with state-of-the-art tools. This paper presents selected results based on the tools from 2 widely used vendors for bibliometrics: Thomson Reuters and Elsevier. RESULTS: Both vendors located a high percentage of publications within their proprietary databases (>90%) and provided similar but not equivalent bibliometrics for estimating productivity (number of publications) and influence (citation rates, percentage of papers in the top 10% of citations, observed citations relative to expected citations). A recently available bibliometric from the National Institutes of Health Office of Portfolio Analysis, examined after the initial analysis, showed tremendous potential for use in the CTSA context. CONCLUSION: Despite challenges in making cross-CTSA comparisons, bibliometrics can enhance our understanding of the value of CTSA-supported clinical and translational research.
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spelling pubmed-54088372017-05-04 Feasibility of common bibliometrics in evaluating translational science Schneider, M. Kane, C. M. Rainwater, J. Guerrero, L. Tong, G. Desai, S. R. Trochim, W. J Clin Transl Sci Research Methods and Technology INTRODUCTION: A pilot study by 6 Clinical and Translational Science Awards (CTSAs) explored how bibliometrics can be used to assess research influence. METHODS: Evaluators from 6 institutions shared data on publications (4202 total) they supported, and conducted a combined analysis with state-of-the-art tools. This paper presents selected results based on the tools from 2 widely used vendors for bibliometrics: Thomson Reuters and Elsevier. RESULTS: Both vendors located a high percentage of publications within their proprietary databases (>90%) and provided similar but not equivalent bibliometrics for estimating productivity (number of publications) and influence (citation rates, percentage of papers in the top 10% of citations, observed citations relative to expected citations). A recently available bibliometric from the National Institutes of Health Office of Portfolio Analysis, examined after the initial analysis, showed tremendous potential for use in the CTSA context. CONCLUSION: Despite challenges in making cross-CTSA comparisons, bibliometrics can enhance our understanding of the value of CTSA-supported clinical and translational research. Cambridge University Press 2017-01-31 /pmc/articles/PMC5408837/ /pubmed/28480055 http://dx.doi.org/10.1017/cts.2016.8 Text en © The Association for Clinical and Translational Science 2017 http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Pressmust be obtained for commercial re-use or in order to create a derivative work.
spellingShingle Research Methods and Technology
Schneider, M.
Kane, C. M.
Rainwater, J.
Guerrero, L.
Tong, G.
Desai, S. R.
Trochim, W.
Feasibility of common bibliometrics in evaluating translational science
title Feasibility of common bibliometrics in evaluating translational science
title_full Feasibility of common bibliometrics in evaluating translational science
title_fullStr Feasibility of common bibliometrics in evaluating translational science
title_full_unstemmed Feasibility of common bibliometrics in evaluating translational science
title_short Feasibility of common bibliometrics in evaluating translational science
title_sort feasibility of common bibliometrics in evaluating translational science
topic Research Methods and Technology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408837/
https://www.ncbi.nlm.nih.gov/pubmed/28480055
http://dx.doi.org/10.1017/cts.2016.8
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