Rodrigo J Daly Guris 1,2 , Christina R Miller 3 , Adam Schiavi 3 , Serkan Toy 3 Show Affiliations »
Abstract
Introduction: Understanding performance differences between learners may provide useful context for optimising medical education. This pilot study aimed to explore a technique to contextualise performance differences through retrospective secondary analyses of two randomised controlled simulation studies. One study focused on speaking up (non-technical skill); the other focused on oxygen desaturation management (technical skill). Methods: We retrospectively analysed data from two independent simulation studies conducted in 2017 and 2018. We used multivariate hierarchical cluster analysis to explore whether participants in each study formed homogenous performance clusters. We then used mixed-design analyses of variance and χ2 analyses to examine whether reported task load differences or demographic variables were associated with cluster membership. Results: In both instances, a two-cluster solution emerged; one cluster represented trainees exhibiting higher performance relative to peers in the second cluster. Cluster membership was independent of experimental allocation in each of the original studies. There were no discernible demographic differences between cluster members. Performance differences between clusters persisted for at least 8 months for the non-technical skill but quickly disappeared following simulation training for the technical skill. High performers in speaking up initially reported lower task load than standard performers, a difference that disappeared over time. There was no association between performance and task load during desaturation management. Conclusion: This pilot study suggests that cluster analysis can be used to objectively identify high-performing trainees for both a technical and a non-technical skill as observed in a simulated clinical setting. Non-technical skills may be more difficult to teach and retain than purely technical ones, and there may be an association between task load and initial non-technical performance. Further study is needed to understand what factors may confer inherent performance advantages, whether these advantages translate to clinical performance and how curricula can best be designed to drive targeted improvement for individual trainees. © Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ.
Introduction: Understanding performance differences between learners may provide useful context for optimising medical education. This pilot study aimed to explore a technique to contextualise performance differences through retrospective secondary analyses of two randomised controlled simulation studies. One study focused on speaking up (non-technical skill); the other focused on oxygen desaturation management (technical skill). Methods: We retrospectively analysed data from two independent simulation studies conducted in 2017 and 2018. We used multivariate hierarchical cluster analysis to explore whether participants in each study formed homogenous performance clusters. We then used mixed-design analyses of variance and χ2 analyses to examine whether reported task load differences or demographic variables were associated with cluster membership. Results: In both instances, a two-cluster solution emerged; one cluster represented trainees exhibiting higher performance relative to peers in the second cluster. Cluster membership was independent of experimental allocation in each of the original studies. There were no discernible demographic differences between cluster members. Performance differences between clusters persisted for at least 8 months for the non-technical skill but quickly disappeared following simulation training for the technical skill. High performers in speaking up initially reported lower task load than standard performers, a difference that disappeared over time. There was no association between performance and task load during desaturation management. Conclusion: This pilot study suggests that cluster analysis can be used to objectively identify high-performing trainees for both a technical and a non-technical skill as observed in a simulated clinical setting. Non-technical skills may be more difficult to teach and retain than purely technical ones, and there may be an association between task load and initial non-technical performance. Further study is needed to understand what factors may confer inherent performance advantages, whether these advantages translate to clinical performance and how curricula can best be designed to drive targeted improvement for individual trainees. © Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ.
Entities: Chemical
Keywords:
cognitive load; communication skills; desaturation; non technical skills; simulation education
Year: 2021
PMID： 35520970 PMCID： PMC8936955 DOI： 10.1136/bmjstel-2020-000812
Source DB: PubMed Journal: BMJ Simul Technol Enhanc Learn ISSN： 2056-6697