In a paper recently published in Science Advances, we delved into the underlying factors associated with the funding gap between white and black researchers. We identified three decision points where disparate outcomes arose between white and black researchers: 1) the decision to bring applications to discussion during peer review study section meetings; 2) impact score assignments for those applications brought to discussion; and (3) a previously unstudied factor, topic choice – that is what topic the investigators chose to study. Continue reading
In March 2018, we showed data suggesting that, despite still being in a state of hyper-competition (as described in this post), the severity may be lessening. The number of unique applicants for NIH research project grants (RPGs) appeared to stabilize after many years of uninterrupted growth. Furthermore, a person-based metric, called the cumulative investigator rate, started to rise in fiscal year (FY) 2015 for RPGs after declines in previous years. Continue reading
For the New Year, we resolve to make NIH data, reports, and analyses more accessible, interactive, and easy to use. For over a decade, the NIH Data Book has served as a helpful resource for describing funding trends on grants and contract awards, success rates, small business programs, peer review, as well as the scientific workforce. These data, presented as graphics and tables, have allowed you to get a better understanding of decisions made here at NIH. We are proud to announce a new edition is available for your 2019 reading list. Continue reading
At NIH, we are heavily invested in our workforce and in understanding the barriers they face. What characteristics do they share? How do they compete in the current hypercompetitive environment? When do they stop applying to NIH (drop out), even after receiving their first award? Staff from the National Institute of Allergy and Infectious Diseases (NIAID) delve into these questions in a paper published recently in PLOS ONE , whose findings I’d like to highlight today. Here, Drs. Patricia Haggerty and Matthew Fenton looked at factors that may contribute to the success of early-career investigators and if these factors affect all junior researchers equally. Continue reading
For nearly 10 years, more women than men received PhDs in the biomedical sciences, yet women are still underrepresented at every subsequent stage of academic advancement. In 2015, for example, women earned 53% of PhDs, but they comprised only 48% of post-doctoral fellows, 44% of assistant professors, and 35% of professors. To better understand what might be contributing to women’s underrepresentation in later stages of academia, Dr. Lisa Hechtman and her colleagues at the National Institute of General Medical Sciences (NIGMS) analyzed “funding longevity by gender” among funded NIH investigators. Their analysis, recently published in the Proceedings of the National Academy of Sciences, yielded a number of interesting findings which I’d like to share with you.
In May 2016, we posted a blog on “How Many Researchers” NIH supports. We cited the findings of a University of Wisconsin workshop, which concluded that the biomedical research enterprise suffers from two core problems: too many scientists vying for too few dollars and too many post-docs seeking too few faculty positions. We also noted that NIH leadership and others were increasingly interested in describing the agency’s portfolio not only in terms of the numbers of awards and dollars (as we do each year in our “By the Numbers” reports), but also in terms of the numbers of researchers those awards support. Today we show updated figures on how many researchers are vying for NIH support and how many are successful. Continue reading
We recently released our annual web reports, success rates and NIH Data Book with updated numbers for fiscal year 2017. Looking at data across both competing and non-competing awards, NIH supports approximately 2,500 organizations. In 2017 about 640 of these organizations received funding for competing Research Project Grants (RPGs) which involved over 11,000 principal investigators. Continue reading
We previously referenced Ioannidis’ and Khoury’s “PQRST” mnemonic for describing research impact: “P” is productivity, “Q” is quality, “R” is reproducibility, “S” is sharing, and “T” is translation. We wrote several blogs about “P,” productivity, focusing on publications, citations, and more recently the relative citation ratio. Now we’ll focus on a different kind of “P” for productivity, namely patents (which arguably are also related to “T” for translation). …. Do NIH-supported papers that are cited by patents have a higher Relative Citation Ratio than those that are not cited by patents? As a refresher, the Relative Citation Ratio uses citation rates to measure the influence of a publication at the article level…. We identified 119,674 unique NIH grants that were funded between 1995 and 2007 and that generated at least one publication…. Continue reading
By the 21st Century Cures Act, the Next Generation Researchers’ Initiative calls on the NIH to develop policies to increase funding opportunities for new researchers seeking to secure early independence. To put the Initiative in perspective and to extend on previous blogs we’ve posted on changing demographics in NIH-funded researchers, we thought it would be useful to explore trends according to career stage.
First, some definitions. We define “Early Stage Investigators” (ESI) as those who are within 10 years of completing their terminal degree or post-graduate clinical training and who have not yet secured independence as a PI of a substantial NIH research award. …. Continue reading
Measuring the impact of NIH grants is an important input in our stewardship of research funding. One metric we can use to look at impact, discussed previously on this blog, is the relative citation ratio (or RCR). This measure – which NIH has made freely available through the iCite tool – aims to go further than just raw numbers of published research findings or citations, by quantifying the impact and influence of a research article both within the context of its research field and benchmarked against publications resulting from NIH R01 awards.
In light of our more recent posts on applications and resubmissions, we’d like to go a step further by looking at long-term bibliometric outcomes as a function of submission number. In other words, are there any observable trends in the impact of publications resulting from an NIH grant funded as an A0, versus those funded as an A1 or A2? And does that answer change when we take into account how much funding each grant received? …. Continue reading