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Are citations from clinical trials evidence of higher impact research? An analysis of ClinicalTrials.gov

Author

Listed:
  • Mike Thelwall

    (University of Wolverhampton)

  • Kayvan Kousha

    (University of Wolverhampton)

Abstract

An important way in which medical research can translate into improved health outcomes is by motivating or influencing clinical trials that eventually lead to changes in clinical practice. Citations from clinical trials records to academic research may therefore serve as an early warning of the likely future influence of the cited articles. This paper partially assesses this hypothesis by testing whether prior articles referenced in ClinicalTrials.gov records are more highly cited than average for the publishing journal. The results from four high profile general medical journals support the hypothesis, although there may not be a cause-and effect relationship. Nevertheless, it is reasonable for researchers to use citations to their work from clinical trials records as evidence of the possible long-term impact of their research.

Suggested Citation

  • Mike Thelwall & Kayvan Kousha, 2016. "Are citations from clinical trials evidence of higher impact research? An analysis of ClinicalTrials.gov," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 1341-1351, November.
    • Handle: RePEc:spr:scient:v:109:y:2016:i:2:d:10.1007_s11192-016-2112-1
    DOI: 10.1007/s11192-016-2112-1
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    References listed on IDEAS

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    1. Mike Thelwall & Nabeil Maflahi, 2016. "Guideline references and academic citations as evidence of the clinical value of health research," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(4), pages 960-966, April.
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    7. Bárbara S. Lancho Barrantes & Vicente P. Guerrero Bote & Zaida Chinchilla Rodríguez & Félix de Moya Anegón, 2012. "Citation flows in the zones of influence of scientific collaborations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(3), pages 481-489, March.
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    11. Ehsan Mohammadi & Mike Thelwall, 2013. "Assessing non-standard article impact using F1000 labels," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(2), pages 383-395, November.
    12. Jing-Yuan Chiou & Laura Magazzini & Fabio Pammolli & Massimo Riccaboni, 2016. "Learning from successes and failures in pharmaceutical R&D," Journal of Evolutionary Economics, Springer, vol. 26(2), pages 271-290, May.
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    Citations

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    Cited by:

    1. Li, Xin & Tang, Xuli & Cheng, Qikai, 2022. "Predicting the clinical citation count of biomedical papers using multilayer perceptron neural network," Journal of Informetrics, Elsevier, vol. 16(4).
    2. Dongyu Zang & Chunli Liu, 2023. "Exploring the clinical translation intensity of papers published by the world’s top scientists in basic medicine," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2371-2416, April.
    3. Diana Hicks & Julia Melkers & Kimberley R. Isett, 2019. "A characterization of professional media and its links to research," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 827-843, May.
    4. Mike Thelwall & Kayvan Kousha & Mahshid Abdoli, 2017. "Is medical research informing professional practice more highly cited? Evidence from AHFS DI Essentials in drugs.com," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 509-527, July.
    5. Enrique Orduña-Malea & Adolfo Alonso-Arroyo & José-Antonio Ontalba-Ruipérez & Ferrán Catalá-López, 2023. "Evaluating the online impact of reporting guidelines for randomised trial reports and protocols: a cross-sectional web-based data analysis of CONSORT and SPIRIT initiatives," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 407-440, January.
    6. Kong, Ling & Wang, Dongbo, 2020. "Comparison of citations and attention of cover and non-cover papers," Journal of Informetrics, Elsevier, vol. 14(4).
    7. Christian Thiele & Gerrit Hirschfeld & Ruth Brachel, 2021. "Clinical trial registries as Scientometric data: A novel solution for linking and deduplicating clinical trials from multiple registries," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(12), pages 9733-9750, December.

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