Video Experimental Relacionado
Updated: Feb 12, 2026
08:42
Design and Implementation of an fMRI Study Examining Thought Suppression in Young Women with, and At-risk, for Depression
Published on: May 19, 2015
11.3K
Reexaminar las afirmaciones sobre el éxito de la implementación de la competencia por diseño (CBD) en la educación
Jonathan Chainey1,2, Ayelet Kuper2,3,4, Ryan Brydges2,3,5
1Division of Neurosurgery, Department of Surgery, University of Montreal, Montreal, Canada.
Medical teacher
|February 11, 2026
Resumen
Al evaluar críticamente la Competencia por Diseño (CBD), este estudio encontró evidencia empírica limitada que respalda su éxito en la educación médica de posgrado canadiense. Los aprendices informaron de un aumento del estrés y la carga administrativa, contrariamente a la narrativa promovida.
Área de la Ciencia:
- Educación Médica Investigación Educación Médica.
- Desarrollo Curricular y Evaluación.
Sus antecedentes:
- La Educación Médica Basada en Competencias (CBME, por sus siglas en inglés) es una tendencia global en la formación de postgrado.
- El modelo de Competencia por Diseño (CBD) de Canadá, adoptado en 2017, se promueve como una reforma exitosa.
- Las críticas emergentes destacan la falta de evidencia empírica y las posibles consecuencias no deseadas del CBD.
Objetivo del estudio:
- Examinar críticamente un artículo reciente que promueve el éxito del CBD utilizando análisis de citas y evaluación de la evidencia.
- Para sintetizar estudios empíricos sobre las actividades profesionales confiables (EPA) dentro de los programas canadienses de CDB.
- Para contextualizar los hallazgos con el Plan de Adaptaciones al CBD 2024 del Colegio Real de Médicos y Cirujanos de Canadá (RCPSC).
Principales métodos:
- Análisis de 169 referencias del artículo revisado, categorizadas por tipo y relevancia empírica.
- Síntesis de estudios empíricos canadienses centrados en los EPA y la retroalimentación en el CBD.
- Consulta del Plan de Adaptaciones de la CDB de 2024 de la RCPSC para los desarrollos recientes.
Principales resultados:
- Los estudios empíricos comprendieron el 49,2% de las citas, con el 59,4% directamente relevante para CBME.
- Una parte significativa de las citas (25,3%) fueron autocitaciones, lo que indica una diversidad de perspectivas limitada.
- Los estudios sintetizados mostraron resultados mixtos: las EPAs tenían como objetivo mejorar la retroalimentación, pero los aprendices informaron un aumento del estrés, la carga administrativa y la calidad de la retroalimentación inconsistente.
Conclusiones:
- Los hallazgos desafían la narrativa del éxito incondicional del CBD en Canadá.
- Se observaron consecuencias no deseadas, como el estrés de los aprendices y la carga administrativa.
- La investigación empírica sensible al contexto es crucial para guiar futuras reformas de la educación médica.
Palabras clave:
La educación médica basada en competencias (CBME, por sus siglas en inglés)Educación basada en competencias.las actividades profesionales confiables (EPAs).La implementación de la implementación de la implementación de la implementación de la implementación.Más Videos Relacionados
Videos de Conceptos Relacionados
02:17Ecological Succession
21.6K
Ecological succession is influenced by the processes of facilitation, inhibition, and toleration. Facilitation occurs when early successional species create more favorable ecological conditions for subsequent species, such as enhanced nutrient, water, or light availability. In contrast, inhibition happens when early successional species create unfavorable ecological conditions for potential successive species, such as limiting resource availability. In some cases, later successional species...
21.6K
01:11Testing a Claim about Mean: Known Population SD
3.3K
A complete procedure of testing the hypothesis about a population mean is explained here.
Estimating a population mean requires the samples to be distributed normally. The data should be collected from the randomly selected samples having no sampling bias. The sample size needed to be higher than 30, and most importantly, the population standard deviation should be already known.
In most realistic situations, the population standard deviation is often unknown, but in rare circumstances, when it...
Estimating a population mean requires the samples to be distributed normally. The data should be collected from the randomly selected samples having no sampling bias. The sample size needed to be higher than 30, and most importantly, the population standard deviation should be already known.
In most realistic situations, the population standard deviation is often unknown, but in rare circumstances, when it...
3.3K
01:24Testing a Claim about Population Proportion
4.0K
A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
4.0K
01:19Testing a Claim about Standard Deviation
3.0K
A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
3.0K
01:21Testing a Claim about Mean: Unknown Population SD
6.3K
A complete procedure of testing a hypothesis about a population mean when the population standard deviation is unknown is explained here.
Estimating a population mean requires the samples to be approximately normally distributed. The data should be collected from the randomly selected samples having no sampling bias. There is no specific requirement for sample size. But if the sample size is less than 30, and we don't know the population standard deviation, a different approach is used;...
Estimating a population mean requires the samples to be approximately normally distributed. The data should be collected from the randomly selected samples having no sampling bias. There is no specific requirement for sample size. But if the sample size is less than 30, and we don't know the population standard deviation, a different approach is used;...
6.3K
01:15Nursing Implementation
6.2K
Implementation is the execution of the nursing care plan developed during the planning phase.
The five steps to implementing effective nursing care include reassessing the patient, reviewing and revising the existing nursing care plan, organizing the resources and care delivery, anticipating and preventing complications, and implementing nursing interventions.
The five steps to implementing effective nursing care include reassessing the patient, reviewing and revising the existing nursing care plan, organizing the resources and care delivery, anticipating and preventing complications, and implementing nursing interventions.
6.2K