The surge in the number of authors per article in the biomedical field makes it difficult to quantify the contribution of individual authors. Conventional citation metrics are typically based on the number of publications and the number of citations generated by a scientist, thereby disregarding the contribution of co-authors. Previously we developed the p-index that estimates the dependency of a scientist on co-authors during their career. In this study we aimed to evaluate the ability of the p-index to identify researchers with a relatively high degree of scientific dependence on co-authors. For this purpose, we retrieved articles, which were rejected for publication in Journal of Thrombosis and Haemostasis and subsequently published elsewhere. Assuming that authors who were added to a later version of these articles would not fulfill the full authorship criteria, we tested whether these authors showed a larger dependency on co-authors during their scientific career as would be evident from a higher p-index. In accordance with this hypothesis, authors who were added on later versions of articles showed a higher p-index than their peers, indicating an enduring pattern of dependency on other co-authors for publishing their work. This study underscores that questionable authorship practices are endemic to the biomedical research, which calls for alternative methods to evaluate a scientist’s qualities.
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The authors would like to thank Professor Lex Bouter, VUmc, for fruitful discussions relating to this manuscript. The authors are also extremely grateful for the indispensable help and assistance by Ms Fee Johnstone and Ms Sofija Gugina (Managing Editors of the Journal of Thrombosis and Hemostasis). NAA was supported by a VENI-grant (#91615080) from the Netherlands Organization of Scientific Research and a Marie Sklodowska-Curie Individual Fellowship grant from the European Union (Horizon 2020, #701130).
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The authors report no conflicts of interest.
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Rozing, M.P., van Leeuwen, T.N., Reitsma, P.H. et al. Freeloading in biomedical research. Scientometrics 122, 47–55 (2020). https://doi.org/10.1007/s11192-018-2984-3
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