Utility of selection methods for specialist medical training: A BEME (best evidence medical education) systematic review: BEME guide no. 45
- Publication Type:
- Journal Article
- Medical Teacher, 2018, 40 (1), pp. 3 - 19
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© 2017 AMEE. Background: Selection into specialty training is a high-stakes and resource-intensive process. While substantial literature exists on selection into medical schools, and there are individual studies in postgraduate settings, there seems to be paucity of evidence concerning selection systems and the utility of selection tools in postgraduate training environments. Aim: To explore, analyze and synthesize the evidence related to selection into postgraduate medical specialty training. Method: Core bibliographic databases including PubMed; Ovid Medline; Embase, CINAHL; ERIC and PsycINFO were searched, and a total of 2640 abstracts were retrieved. After removing duplicates and screening against the inclusion criteria, 202 full papers were coded, of which 116 were included. Results: Gaps in underlying selection frameworks were illuminated. Frameworks defined by locally derived selection criteria, and heavily weighed on academic parameters seem to be giving way to the evidencing of competency-based selection approaches in some settings. Regarding selection tools, we found favorable psychometric evidence for multiple mini-interviews, situational judgment tests and clinical problem-solving tests, although the bulk of evidence was mostly limited to the United Kingdom. The evidence around the robustness of curriculum vitae, letters of recommendation and personal statements was equivocal. The findings on the predictors of past performance were limited to academic criteria with paucity of long-term evaluations. The evidence around nonacademic criteria was inadequate to make an informed judgment. Conclusions: While much has been gained in understanding the utility of individual selection methods, though the evidence around many of them is equivocal, the underlying theoretical and conceptual frameworks for designing holistic and equitable selection systems are yet to be developed.
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