Issenberg's features of high-fidelity medical simulations that lead to effective learning¶

Design · All designs
Evidence · 2 claims (2 for) · 1 study (1 quant-synthesis), q2 · 1 of 1 report an effect size · 2 claims rest on one study

Description¶

The article invokes Issenberg and co-workers' account of the features needed for simulation to transform a principle into a lesson learned. The listed features include "provision of feedback, repetitive practice, curriculum integration, appropriate range of difficulty level, multiple learning strategies, simulation that captures clinical variation, a controlled environment, individualized learning, defined outcomes and simulator validity". The review uses this framework to interpret why simulation improved coronary anastomosis performance and to discuss curriculum design across the included trials.

Design Implications¶

Context¶

Requirements¶

Simulation programmes should incorporate the listed features such as feedback, repetitive practice and curriculum integration to be effective

Constraints¶

Target Learners¶

healthcare trainees learning coronary anastomosis
surgical residents and medical students

Learning Goals¶

technical skill in coronary anastomosis
time efficiency in task completion

Claims¶

Examples¶

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Key Sources¶

O'Dwyer M, Fleming CA, Ahern S, Barrett S, Raftery NB, Ní Dhonnchú T, Doddakula K. (2022). Objective improvement with coronary anastomosis simulation training: meta-analysis. BJS Open. https://doi.org/10.1093/bjsopen/zrab147

Page metadata

Field	Value
`type`	`design`
`id`	`issenberg-features-effective-simulation`
`title`	`Issenberg's features of high-fidelity medical simulations that lead to effective learning`
`description`	`The article invokes Issenberg and co-workers' account of the features needed for simulation to transform a principle into a lesson learned.`
`status`	`review`
`generated`	by `process:settle-candidates` on `2026-11-01`
`trust`	unverified — no one has confirmed this page's content
`sources`	1 — `odwyer-m-2022`

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