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Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
Published on: October 24, 2019
Using bibliometrics to evaluate translational science training: evidence for early career success of KL2 scholars
1School of Medicine, Clinical and Translational Science Collaborative, Case Western Reserve University, Cleveland, OH, USA.
Introduction:
Evaluating clinical and translational research (CTR) mentored training programs is challenging because no two programs are alike. Careful selection of appropriate metrics is required to make valid comparisons between individuals and between programs. The KL2 program provides mentored-training for early-stage CTR investigators. Clinical and Translational Awards across the country have unique KL2 programs. The evaluation of KL2 programs has begun to incorporate bibliometrics to measure KL2 scholar and program impact.
Methods:
This study investigated demographic differences in bibliometric performance and post-K award funding of KL2 scholars and compared the bibliometric performance and post-K award federal funding of KL2 scholars and other mentored-K awardees at the same institution. Data for this study included SciVal and iCite bibliometrics and National Institutions of Health RePORTER grant information for mentored-K awardees (K08, K23, and KL2) at Case Western Reserve University between 2005 and 2013.
Results:
Results showed no demographics differences within the KL2 program scholars. Bibliometric differences between KL2 and other mentored-K awardee indicated an initial KL2 advantage for the number of publications at 5 years' post-matriculation (i.e., the start of the K award). Regression analyses indicated the number of initial publications was a significant predictor of federal grant funding at the same time point. Analysis beyond the 5-year post-matriculation point did not result in a sustained, significant KL2 advantage.
Conclusions:
Factors that contributed to the grant funding advantage need to be determined. Additionally, differences between translational and clinical bibliometrics must be interpreted with caution, and appropriate metrics for translational science must be established.
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