A systematic review of stakeholder views of selection methods for medical schools admission-Reference-Cited by-同舟云学术

A systematic review of stakeholder views of selection methods for medical schools admission

Published:2018-06-15 Issue:1 Volume:18 Page:
ISSN:1472-6920
Container-title:BMC Medical Education
language:en
Short-container-title:BMC Med Educ

Author:

Kelly M. E.^ORCID,Patterson F.,O’Flynn S.,Mulligan J.,Murphy A. W.

Publisher

Springer Science and Business Media LLC

Subject

Education,General Medicine

Link

http://link.springer.com/content/pdf/10.1186/s12909-018-1235-x.pdf

Reference110 articles.

1. Brown CA, Lilford RJ. Selecting medical students. Br Med J. 2008;336:786.

2. British Medical Association. Equality and diversity in UK medical schools. London: British Medical Association; 2009.

3. Harden, R. Welcome Address. 16th Ottawa Conference - Transforming healthcare through excellence in assessment and evaluation. Ottawa, Canada: 2014 April 25th -29th.

4. Lakhan SE. Diversification of U.S. medical schools via affirmative action implementation. BMC Medical Education. 2003;3:6.

5. Patterson F, Ferguson E. Selection for medical education and training. In: Swanwick T, editor. Understanding medical education. Sussex: Wiley Online Library; 2010.

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