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Cognitive load predicts point-of-care ultrasound simulator performance
INTRODUCTION: The ability to maintain good performance with low cognitive load is an important marker of expertise. Incorporating cognitive load measurements in the context of simulation training may help to inform judgements of competence. This exploratory study investigated relationships between d...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Bohn Stafleu van Loghum
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5807260/ https://www.ncbi.nlm.nih.gov/pubmed/29305817 http://dx.doi.org/10.1007/s40037-017-0392-7 |
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author | Aldekhyl, Sara Cavalcanti, Rodrigo B. Naismith, Laura M. |
author_facet | Aldekhyl, Sara Cavalcanti, Rodrigo B. Naismith, Laura M. |
author_sort | Aldekhyl, Sara |
collection | PubMed |
description | INTRODUCTION: The ability to maintain good performance with low cognitive load is an important marker of expertise. Incorporating cognitive load measurements in the context of simulation training may help to inform judgements of competence. This exploratory study investigated relationships between demographic markers of expertise, cognitive load measures, and simulator performance in the context of point-of-care ultrasonography. METHODS: Twenty-nine medical trainees and clinicians at the University of Toronto with a range of clinical ultrasound experience were recruited. Participants answered a demographic questionnaire then used an ultrasound simulator to perform targeted scanning tasks based on clinical vignettes. Participants were scored on their ability to both acquire and interpret ultrasound images. Cognitive load measures included participant self-report, eye-based physiological indices, and behavioural measures. Data were analyzed using a multilevel linear modelling approach, wherein observations were clustered by participants. RESULTS: Experienced participants outperformed novice participants on ultrasound image acquisition. Ultrasound image interpretation was comparable between the two groups. Ultrasound image acquisition performance was predicted by level of training, prior ultrasound training, and cognitive load. There was significant convergence between cognitive load measurement techniques. A marginal model of ultrasound image acquisition performance including prior ultrasound training and cognitive load as fixed effects provided the best overall fit for the observed data. DISCUSSION: In this proof-of-principle study, the combination of demographic and cognitive load measures provided more sensitive metrics to predict ultrasound simulator performance. Performance assessments which include cognitive load can help differentiate between levels of expertise in simulation environments, and may serve as better predictors of skill transfer to clinical practice. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s40037-017-0392-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5807260 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Bohn Stafleu van Loghum |
record_format | MEDLINE/PubMed |
spelling | pubmed-58072602018-02-15 Cognitive load predicts point-of-care ultrasound simulator performance Aldekhyl, Sara Cavalcanti, Rodrigo B. Naismith, Laura M. Perspect Med Educ Original Article INTRODUCTION: The ability to maintain good performance with low cognitive load is an important marker of expertise. Incorporating cognitive load measurements in the context of simulation training may help to inform judgements of competence. This exploratory study investigated relationships between demographic markers of expertise, cognitive load measures, and simulator performance in the context of point-of-care ultrasonography. METHODS: Twenty-nine medical trainees and clinicians at the University of Toronto with a range of clinical ultrasound experience were recruited. Participants answered a demographic questionnaire then used an ultrasound simulator to perform targeted scanning tasks based on clinical vignettes. Participants were scored on their ability to both acquire and interpret ultrasound images. Cognitive load measures included participant self-report, eye-based physiological indices, and behavioural measures. Data were analyzed using a multilevel linear modelling approach, wherein observations were clustered by participants. RESULTS: Experienced participants outperformed novice participants on ultrasound image acquisition. Ultrasound image interpretation was comparable between the two groups. Ultrasound image acquisition performance was predicted by level of training, prior ultrasound training, and cognitive load. There was significant convergence between cognitive load measurement techniques. A marginal model of ultrasound image acquisition performance including prior ultrasound training and cognitive load as fixed effects provided the best overall fit for the observed data. DISCUSSION: In this proof-of-principle study, the combination of demographic and cognitive load measures provided more sensitive metrics to predict ultrasound simulator performance. Performance assessments which include cognitive load can help differentiate between levels of expertise in simulation environments, and may serve as better predictors of skill transfer to clinical practice. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s40037-017-0392-7) contains supplementary material, which is available to authorized users. Bohn Stafleu van Loghum 2018-01-05 2018-02 /pmc/articles/PMC5807260/ /pubmed/29305817 http://dx.doi.org/10.1007/s40037-017-0392-7 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Article Aldekhyl, Sara Cavalcanti, Rodrigo B. Naismith, Laura M. Cognitive load predicts point-of-care ultrasound simulator performance |
title | Cognitive load predicts point-of-care ultrasound simulator performance |
title_full | Cognitive load predicts point-of-care ultrasound simulator performance |
title_fullStr | Cognitive load predicts point-of-care ultrasound simulator performance |
title_full_unstemmed | Cognitive load predicts point-of-care ultrasound simulator performance |
title_short | Cognitive load predicts point-of-care ultrasound simulator performance |
title_sort | cognitive load predicts point-of-care ultrasound simulator performance |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5807260/ https://www.ncbi.nlm.nih.gov/pubmed/29305817 http://dx.doi.org/10.1007/s40037-017-0392-7 |
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