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An analysis of bibliometric indicators, National Institutes of Health funding, and faculty size at Association of American Medical Colleges medical schools, 1997-2007.

机译:1997-2007年,对文献计量指标,美国国立卫生研究院(National Institutes of Health)经费以及美国医学院协会医学学校教员规模的分析。

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OBJECTIVE: The objective of this study was to analyze bibliometric data from ISI, National Institutes of Health (NIH)-funding data, and faculty size information for Association of American Medical Colleges (AAMC) member schools during 1997 to 2007 to assess research productivity and impact. METHODS: This study gathered and synthesized 10 metrics for almost all AAMC medical schools(n=123): (1) total number of published articles per medical school, (2) total number of citations to published articles per medical school, (3) average number of citations per article, (4) institutional impact indices, (5) institutional percentages of articles with zero citations, (6) annual average number of faculty per medical school, (7) total amount of NIH funding per medical school, (8) average amount of NIH grant money awarded per faculty member, (9) average number of articles per faculty member, and (10)average number of citations per faculty member. Using principal components analysis, the author calculated the relationships between measures, if they existed. RESULTS: Principal components analysis revealed 3 major clusters of variables that accounted for 91% of the total variance: (1) institutional research productivity, (2) research influence or impact, and (3)individual faculty research productivity. Depending on the variables in each cluster, medical school research may be appropriately evaluated in a more nuanced way. Significant correlations exist between extracted factors, indicating an interrelatedness of all variables. Total NIH funding may relate more strongly to the quality of the research than the quantity of the research. The elimination of medical schools with outliers in 1 or more indicators (n=20)altered the analysis considerably. CONCLUSIONS: Though popular, ordinal rankings cannot adequately describe the multidimensional nature of a medical school's research productivity and impact. This study provides statistics that can be used in conjunction with other sound methodologies to provide a more authentic view of a medical school's research. The large variance of the collected data suggests that refining bibliometric data by discipline, peer groups, or journal information may provide a more precise assessment.
机译:目的:本研究的目的是分析ISI的文献计量数据,美国国立卫生研究院(NIH)资助的数据以及美国医学院协会(AAMC)成员学校在1997年至2007年期间的教职人数信息,以评估研究效率和影响。方法:本研究收集并综合了几乎所有AAMC医学院(n = 123)的10个指标:(1)每所医学院的已发表文章总数,(2)每所医学院的对已发表文章的引用总数,(3)每篇文章的平均被引用次数;(4)机构影响指数;(5)被零引用的文章的机构百分比;(6)每所医学院的年度平均教师人数;(7)每所医学院的NIH资助总额,( 8)每位教职员工授予的NIH补助金的平均金额;(9)每位教职员工的平均文章数;以及(10)每位教职员工的平均引文数。使用主成分分析,作者计算了度量之间的关系(如果存在)。结果:主成分分析显示,变量的3个主要类别占总方差的91%:( 1)机构研究生产率,(2)研究影响或影响,以及(3)个人教师研究生产率。根据每个集群中的变量,可以以更细微的方式对医学院的研究进行适当的评估。提取的因子之间存在显着的相关性,表明所有变量之间存在相互关系。美国国立卫生研究院的总资助可能与研究质量的关系比与研究数量的关系更为密切。排除了具有1个或多个指标(n = 20)的异常值的医学院校,大大改变了该分析。结论:尽管受欢迎,但序数排名不能充分描述医学院的研究生产力和影响的多维性质。这项研究提供的统计数据可以与其他合理的方法结合使用,以提供对医学院研究的更真实的看法。所收集数据的巨大差异表明,按学科,同龄人群体或期刊信息细化文献计量数据可能会提供更精确的评估。

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