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The ASIBS Short Course: A unique strategy for increasing statistical competency of junior investigators in academic medicine

  • Emma K. T. Benn (a1), Chengcheng Tu (a1), Ann-Gel S. Palermo (a2), Luisa N. Borrell (a3), Michaela Kiernan (a4), Mary Sandre (a1) and Emilia Bagiella (a1)...
Abstract

As clinical researchers at academic medical institutions across the United States increasingly manage complex clinical databases and registries, they often lack the statistical expertise to utilize the data for research purposes. This statistical inadequacy prevents junior investigators from disseminating clinical findings in peer-reviewed journals and from obtaining research funding, thereby hindering their potential for promotion. Underrepresented minorities, in particular, confront unique challenges as clinical investigators stemming from a lack of methodologically rigorous research training in their graduate medical education. This creates a ripple effect for them with respect to acquiring full-time appointments, obtaining federal research grants, and promotion to leadership positions in academic medicine. To fill this major gap in the statistical training of junior faculty and fellows, the authors developed the Applied Statistical Independence in Biological Systems (ASIBS) Short Course. The overall goal of ASIBS is to provide formal applied statistical training, via a hybrid distance and in-person learning format, to junior faculty and fellows actively involved in research at US academic medical institutions, with a special emphasis on underrepresented minorities. The authors present an overview of the design and implementation of ASIBS, along with a short-term evaluation of its impact for the first cohort of ASIBS participants.

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Copyright
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Corresponding author
*Address for correspondence: E. K. T. Benn, DrPH., M.P.H., Center for Biostatistics and Department of Population Health Science & Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA. (Email: emma.benn@mountsinai.org)
References
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1. Jeffe, DB, Yan, Y, Andriole, DA. Do research activities during college, medical school, and residency mediate racial/ethnic disparities in full-time faculty appointments at U.S. Medical schools? Academic Medicine: Journal of the Association of American Medical Colleges 2012; 87: 15821593.
2. Ginther, DK, et al. Race, ethnicity, and NIH research awards. Science 2011; 333: 10151019.
3. Fang, D, et al. Racial and ethnic disparities in faculty promotion in academic medicine. JAMA 2000; 284: 10851092.
4. Harris, PA, et al. Research electronic data capture (REDCap) – a metadata-driven methodology and workflow process for providing translational research informatics support. Journal of Biomedical Informatics 2009; 42: 377381.
5. National Institute of General Medical Sciences. Clearinghouse for training modules to enhance data reproducibility [Internet], n.d. [cited Nov 16, 2016]. (https://www.nigms.nih.gov/training/pages/clearinghouse-for-training-modules-to-enhance-data-reproducibility.aspx)
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Journal of Clinical and Translational Science
  • ISSN: -
  • EISSN: 2059-8661
  • URL: /core/journals/journal-of-clinical-and-translational-science
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