Federal Funding and Citation Metrics of US Biomedical Researchers, 1996 to 2022

Abstract

ImportanceBoth citation and funding metrics converge in shaping current perceptions of academic success.ObjectiveTo evaluate what proportion of the most-cited US-based scientists are funded by biomedical federal agencies and whether funded scientists are more cited than nonfunded ones.Design, Setting, and ParticipantsThis survey study used linkage of a Scopus-based database on top-cited US researchers (according to a composite citation metric) and the National Institutes of Health RePORTER database of federal funding (33 biomedical federal agencies). Matching was based on name and institution. US-based top-cited scientists who were allocated to any of 69 scientific subfields highly related to biomedicine were considered in the main analysis. Data were downloaded on June 11, 2022.Main Outcomes and MeasuresProportion of US-based top-cited biomedical scientists who had any (1996-2022), recent (2015-2022), and current (2021-2022) funding. Comparisons of funded and nonfunded scientists assessed total citations and a composite citation index.ResultsThere were 204 603 records in RePORTER (1996-2022) and 75 316 US-based top-cited scientists in the career-long citation database; 40 887 scientists were included in the main analysis. The proportion of US-based top-cited biomedical scientists (according to career-long citation impact) who had received any federal funding from biomedical research agencies was 62.7% (25 650 of 40 887) for any funding (1996-2022), 23.1% (9427 of 40 887) for recent funding (2015-2022), and 14.1% (5778 of 40 887) for current funding (2021-2022). Respective proportions were 64.8%, 31.4%, and 20.9%, for top-cited scientists according to recent single-year citation impact. There was large variability across scientific subfields (eg, current funding: 31% of career-long impact top-cited scientists in geriatrics, 30% in bioinformatics and 29% in developmental biology, but 0% in legal and forensic medicine, general psychology and cognitive sciences, and gender studies). Funded top-cited researchers were overall more cited than nonfunded top-cited scientists (median [IQR], 9594 [5650-1703] vs 5352 [3057-9890] citations; P < .001) and substantial difference remained after adjusting for subfield and years since first publication. Differences were more prominent in some specific biomedical subfields.Conclusions and RelevanceIn this survey study, biomedical federal funding had offered support to approximately two-thirds of the top-cited biomedical scientists at some point during the last quarter century, but only a small minority of top-cited scientists had current federal biomedical funding. The large unevenness across subfields needs to be addressed with ways that improve equity, efficiency, excellence, and translational potential.

The landscape of biomedical research funding in Brazil: a current overview

“…In addition, securing funding may be important for career advancement. Success in grant applications is often perceived as an important quality and an indicator of potential for academic success in future ( 21 ). It not only proves the researcher's capacity to obtain financial resources, but also the ability to conceive and plan robust scientific investigations.…”

Impact of medical technologies may be predicted using constructed graph bibliometrics

“…In some instances, researchers may engage in self-citation, which artificially inflates their citation counts, or they may publish multiple papers on the same topic to boost their h-index. Thus, relying solely on conventional citation metrics may introduce biases that impede our progress in identifying and pursuing impactful research areas 7 , 23 , 24 . In fact, the use of time-rescaled measures of node centrality is an important consideration in knowledge graph analysis for objective decision-making.…”

Impact of Medical Technologies may be Predicted Using Constructed Graph Bibliometrics

“…In some instances, researchers may engage in self-citation, which artificially inflates their citation counts, or they may publish multiple papers on the same topic to boost their h-index. Thus, relying solely on conventional citation metrics may introduce biases that impede our progress in identifying and pursuing impactful research areas [23][24][25]. In fact, the use of time-rescaled measures of node centrality is an important consideration in knowledge graph analysis for objective decision-making.…”

“…Standardized citation metrics of research articles in a scientific field and scientist profiles may be used in part to inform the decision-making to fund new scientific projects [6,7,8]. Using the number of citations alone as the sole quality indicator of research is limited due to its narrow scope that only measures the uptake of the work by other researchers [9,10].…”