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Remote feedback in endovascular simulation training: a mixed-methods study

Authors :
Adam F. Roche
Daragh Moneley
Tim Lawler
Emily Boyle
Greg Gosi
Adrian O’Callaghan
Caitriona Cahir
Dara O’Keeffe
Claire M. Condron
Source :
Advances in Simulation, Vol 9, Iss 1, Pp 1-9 (2024)
Publication Year :
2024
Publisher :
BMC, 2024.

Abstract

Abstract Background There is an increasing need to increase simulation-based learning opportunities for vascular surgery residents in endovascular skills training. This study aims to explore the effectiveness of remote expert instructional feedback of endovascular simulation-based education, as a means of increasing training opportunities in this area for vascular surgery residents. Methods A mixed-methods study design was adopted. Twelve vascular surgery residents from Ireland were tasked with completing two endovascular renal artery procedures: one with in-person expert feedback and the other with remote instruction. Participants ranged in experience levels from second year to final year of residency. Following the training activities, interviews and a questionnaire were employed to gather information on the usefulness of remote feedback. Results There was no significant difference reported by participants using a post-event validated questionnaire between remote and in-person feedback. During the interviews, participants expressed mixed feelings about the presence of the educator while practicing, but they eventually saw no limiting factors to their practice when the trainer provided remote feedback. When receiving performance feedback remotely, clear communication and a shared knowledge of the task development are critical to success. Conclusions We believe these findings can inform the design and development of remote learning and assessment of endovascular skills training and ultimately provide increased opportunities for more skills practice for vascular surgical residents.

Details

Language :
English
ISSN :
20590628
Volume :
9
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Advances in Simulation
Publication Type :
Academic Journal
Accession number :
edsdoj.b3b5f7815cdc46fea7fa85eb7bc71c3d
Document Type :
article
Full Text :
https://doi.org/10.1186/s41077-024-00297-0