The Ability of the Multiple Mini-Interview to Predict Preclerkship Performance in Medical School

Eva, Kevin W.; Reiter, Harold I.; Rosenfeld, Jack; Norman, Geoffrey R.

doi:10.1097/00001888-200410001-00012

Cited by 196 publications

(191 citation statements)

References 12 publications

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“…These can be grouped into ''paper and pencil'' assessments of personality traits (e.g., Adams et al 2012Adams et al , 2015Bore et al 2005a, b;Dowell et al 2011;Fukui et al 2014;James et al 2013;Lumsden et al 2005;Manuel et al 2005;Nedjat et al 2013), structured multiple interview approaches (Dore et al 2010;Eva et al, 2004aEva et al, , b, 2009Hofmeister et al 2008Hofmeister et al , 2009O'Brien et al 2011;Reiter et al 2007;Roberts et al 2008;Rosenfeld et al 2008), selection centres (Gafni et al 2012;ten Cate and Smal 2002;Ziv et al 2008;Gale et al 2010;Randall et al 2006a, b) and-the ''new kid on the block''-situational judgement tests (Christian et al 2010;Koczwara et al 2012;Lievens 2013;Lievens et al 2008;Patterson et al 2009). …”

Section: Introductionmentioning

confidence: 99%

Do personality traits assessed on medical school admission predict exit performance? A UK-wide longitudinal cohort study

MacKenzie

Dowell

Ayansina

et al. 2016

Adv in Health Sci Educ

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Traditional methods of assessing personality traits in medical school selection have been heavily criticised. To address this at the point of selection, ''non-cognitive'' tests were included in the UK Clinical Aptitude Test, the most widely-used aptitude test in UK medical education (UKCAT: http://www.ukcat.ac.uk/). We examined the predictive validity of these non-cognitive traits with performance during and on exit from medical school. We sampled all students graduating in 2013 from the 30 UKCAT consortium medical schools. Analysis included: candidate demographics, UKCAT non-cognitive scores, medical school performance data-the Educational Performance Measure (EPM) and national exit situational judgement test (SJT) outcomes. We examined the relationships between these variables and SJT and EPM scores. Multilevel modelling was used to assess the relationships adjusting for confounders. The 3343 students who had taken the UKCAT non-cognitive tests and had both EPM and SJT data were entered into the analysis. There were four types of non-cognitive test: (1) libertariancommunitarian, (2) NACE-narcissism, aloofness, confidence and empathy, (3) MEARS-self-esteem, optimism, control, self-discipline, emotional-nondefensiveness (END) and faking, (4) an abridged version of 1 and 2 combined. Multilevel regression showed that, after correcting for demographic factors, END predicted SJT and EPM decile. Aloofness and empathy in NACE were predictive of SJT score. This is the first large-scale study examining the relationship between performance on non-cognitive selection tests and medical school exit assessments. The predictive validity of these tests was limited, and the relationships revealed do not fit neatly with theoretical expectations. This study does not support their use in selection.

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Section: Introductionmentioning

confidence: 99%

Do personality traits assessed on medical school admission predict exit performance? A UK-wide longitudinal cohort study

MacKenzie

Dowell

Ayansina

et al. 2016

Adv in Health Sci Educ

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“…Este método de admisión ha sido validado e implementado por primera vez tanto en el Canadá de habla inglesa como en el Canadá de habla francesa (Eva, Reiter, Rosenfeld et al, 2004;St-Onge, Côté&Brailovsky, 2009). Actualmente es utilizado por todas las facultades de medicina del país.…”

Section: Tendencias En Admisión De Estudiantesunclassified

Algunas Tendencias Actuales en Educación Médica

Brailovsky

Centeno

2012

REDU

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ResumenDesde la revolución "flexneriana" de hace 100 años hubo muchos intentos de cambios en la enseñanza de la medicina y surgieron nuevas tendencias generales en educación médica.Principalmente surge la necesidad de superar el modelo biomédico clásico hacia uno más centrado en la persona (y en la sociedad). El curriculum tiende a ser más competo e integral, con la incorporación de aspectos comunitarios, de integración de dimensiones clínicas y de habilidades interpersonales. La planificación curricular se adapta mejor a las necesidades del estudiante y de la sociedad.La admisión de los estudiantes y su selección, busca hacerse más inclusiva, equitativa, y basada en la ciencia de la evaluación.Aparecen modelos de universidades virtuales que seguramente en el futuro serán exitosas, a partir del rápido desarrollo de simuladores, de nuevas tecnologías de la información y del uso de redes sociales. Hay muchos ejemplos de modelos mixtos de aprendizaje a distancia y actividades presenciales (blendede-learning).Se incorpora la concepción de entrenamiento y formación multiprofesional e interprofesional, e incluso la integración de la formación de pregrado y de posgrado en algunas escuelas de acuerdo a la orientación elegida.La evaluación de los saberes y las competencias profesionales tienden a hacerse cada vez más descriptivas, con énfasis en la reflexión y en las habilidades metacognitivas, y utilizan tests sofisticados (OSCE, miniCEX, Script Concordance Tests).La formación docente tiende a ser más longitudinal, reflexiva, interactiva y favoreciendo el compromiso personal y profesional como elemento de aprendizaje.

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“…The selection interview has been implicated with issues surrounding reliability, validity and fairness [15]. Modifications of the traditional interview, where multiple interview panels conduct structured interviews, have produced encouraging results [16]. A method borrowed from the industrial world, called the 'assessment centre', which assesses the applicant more comprehensively over a longer period of time using a battery of tests have produced good predictive validity especially in postgraduate selection [17].…”

Section: Predictors Of Success During the Medical Careermentioning

confidence: 99%

Selection criteria towards competent and caring doctors

Mendis¹,

Ponnamperuma

2011

Ceylon Med. J.

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The Ability of the Multiple Mini-Interview to Predict Preclerkship Performance in Medical School

Abstract: While further validity testing is required, the MMI appears better able to predict preclerkship performance relative to traditional tools designed to assess the noncognitive qualities of applicants.

Cited by 196 publications

References 12 publications

Do personality traits assessed on medical school admission predict exit performance? A UK-wide longitudinal cohort study

Do personality traits assessed on medical school admission predict exit performance? A UK-wide longitudinal cohort study

Algunas Tendencias Actuales en Educación Médica

Selection criteria towards competent and caring doctors

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