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FEM: Revista de la Fundación Educación Médica

versão On-line ISSN 2014-9840versão impressa ISSN 2014-9832

Resumo

DAVILA-QUINTANA, C. Delia; LOPEZ-VALCARCEL, Beatriz G.; BARBER, Patricia  e  ORTUN, Vicente. The academic grade in access to specialist medical training in Spain. FEM (Ed. impresa) [online]. 2015, vol.18, n.3, pp.219-224. ISSN 2014-9840.  https://dx.doi.org/10.4321/S2014-98322015000400011.

Introduction: The selection on specialized health training of doctors (MIR) is based on interpersonal fairness that rewards candidates by effort. Academic achievement, through the average grade, reflects the long-distance race, while the MIR test measures the sprint effort. This article discusses the pros and cons of maintaining the academic grade, that currently weighs 10%. On the one hand, it measures skills and abilities beyond the mere knowledge that provides the test, but on the other, it may have problems of validity, it could not change elections, given their low weight, and/or it could be not cost-effective. Materials and methods: Database of MIR 2012-2013 (Ministry of Health, Social Services and Equality ) and own survey of MIR-1 2012-2013. We used a multilevel model to estimate the effect of the university on the candidate's academic grade. Results: There are systematic differences in the grades of the candidates attributable to the university when all universities, Spanish and foreign are compared (intragroup correlation: 47%). There are no significant differences between Spanish universities (intragroup correlation: 7%). 62% of the candidates move less than a hundred places in the ranking if the academic grade would be suppressed, and at least 1 % of the candidates would change their chosen specialty. It represents a maximum cost of 576 euros per change. Conclusions: The academic grade is valid for the Spanish universities but not for foreign universities. Its suppression would marginally alter the order of choice and MIR assignments.

Palavras-chave : MIR tests; Multilevel models; Scales; University bias.

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