Suppr超能文献

美国国立卫生研究院R01申请评审、影响及标准评分分析:首席研究员的性别有影响吗?

Analysis of National Institutes of Health R01 Application Critiques, Impact, and Criteria Scores: Does the Sex of the Principal Investigator Make a Difference?

作者信息

Kaatz Anna, Lee You-Geon, Potvien Aaron, Magua Wairimu, Filut Amarette, Bhattacharya Anupama, Leatherberry Renee, Zhu Xiaojin, Carnes Molly

机构信息

A. Kaatz is director of computational sciences, Center for Women's Health Research, University of Wisconsin-Madison, Madison, Wisconsin. Y.G. Lee is associate researcher, Wisconsin Center for Education Research, University of Wisconsin-Madison, Madison, Wisconsin. A. Potvien is a doctoral candidate, Department of Statistics, and researcher, Health Innovation Program, University of Wisconsin-Madison, Madison, Wisconsin. W. Magua is postdoctoral research associate, Center for Women's Health Research, University of Wisconsin-Madison, Madison, Wisconsin. A. Filut is research assistant, Center for Women's Health Research, University of Wisconsin-Madison, Madison, Wisconsin. A. Bhattacharya is an undergraduate student and data science scholar, Center for Women's Health Research, University of Wisconsin-Madison, Madison, Wisconsin. R. Leatherberry is staff researcher, Center for Women's Health Research, University of Wisconsin-Madison, Madison, Wisconsin. X. Zhu is associate professor, Department of Computer Science, University of Wisconsin-Madison, Madison, Wisconsin. M. Carnes is director, Center for Women's Health Research, professor in the Departments of Medicine, Psychiatry, and Industrial and Systems Engineering, University of Wisconsin-Madison, and part-time physician, William S. Middleton Veterans Hospital, Madison, Wisconsin.

出版信息

Acad Med. 2016 Aug;91(8):1080-8. doi: 10.1097/ACM.0000000000001272.

Abstract

PURPOSE

Prior text analysis of R01 critiques suggested that female applicants may be disadvantaged in National Institutes of Health (NIH) peer review, particularly for renewals. NIH altered its review format in 2009. The authors examined R01 critiques and scoring in the new format for differences due to principal investigator (PI) sex.

METHOD

The authors analyzed 739 critiques-268 from 88 unfunded and 471 from 153 funded applications for grants awarded to 125 PIs (76 males, 49 females) at the University of Wisconsin-Madison between 2010 and 2014. The authors used seven word categories for text analysis: ability, achievement, agentic, negative evaluation, positive evaluation, research, and standout adjectives. The authors used regression models to compare priority and criteria scores, and results from text analysis for differences due to PI sex and whether the application was for a new (Type 1) or renewal (Type 2) R01.

RESULTS

Approach scores predicted priority scores for all PIs' applications (P < .001), but scores and critiques differed significantly for male and female PIs' Type 2 applications. Reviewers assigned significantly worse priority, approach, and significance scores to female than male PIs' Type 2 applications, despite using standout adjectives (e.g., "outstanding," "excellent") and making references to ability in more critiques (P < .05 for all comparisons).

CONCLUSIONS

The authors' analyses suggest that subtle gender bias may continue to operate in the post-2009 NIH review format in ways that could lead reviewers to implicitly hold male and female applicants to different standards of evaluation, particularly for R01 renewals.

摘要

目的

先前对R01评审意见的文本分析表明,女性申请者在美国国立卫生研究院(NIH)的同行评审中可能处于劣势,尤其是在申请续期时。NIH在2009年改变了其评审形式。作者研究了新形式下R01评审意见及评分中因首席研究员(PI)性别而产生的差异。

方法

作者分析了739份评审意见——其中268份来自威斯康星大学麦迪逊分校2010年至2014年间授予125位PI(76名男性,49名女性)的88份未获资助申请,471份来自153份获资助申请。作者使用七个词类进行文本分析:能力、成就、能动性、负面评价、正面评价、研究和突出形容词。作者使用回归模型比较优先级和标准分数,以及文本分析结果中因PI性别以及申请是新的(1类)还是续期的(2类)R01而产生的差异。

结果

方法分数预测了所有PI申请的优先级分数(P <.001),但男性和女性PI的2类申请在分数和评审意见上存在显著差异。尽管在更多的评审意见中使用了突出形容词(如“杰出的”“优秀的”)并提及了能力,但评审人员给女性PI的2类申请分配的优先级、方法和重要性分数明显低于男性PI的申请(所有比较P <.05)。

结论

作者的分析表明,在2009年后的NIH评审形式中,可能仍存在细微的性别偏见,这可能导致评审人员以不同的评价标准来隐性地对待男性和女性申请者,尤其是在R01续期申请方面。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验