The effect of observing novice and expert performance on acquisition of surgical skills on a robotic platform
dc.contributor.author | Harris, DJ | |
dc.contributor.author | Vine, SJ | |
dc.contributor.author | Wilson, MR | |
dc.contributor.author | McGrath, JS | |
dc.contributor.author | LeBel, ME | |
dc.contributor.author | Buckingham, G | |
dc.date.accessioned | 2019-03-04T15:06:07Z | |
dc.date.issued | 2017-11-15 | |
dc.description.abstract | Background: Observational learning plays an important role in surgical skills training, following the traditional model of learning from expertise. Recent findings have, however, highlighted the benefit of observing not only expert performance but also error-strewn performance. The aim of this study was to determine which model (novice vs. expert) would lead to the greatest benefits when learning robotically assisted surgical skills. Methods: 120 medical students with no prior experience of robotically-assisted surgery completed a ring-carrying training task on three occasions; baseline, post-intervention and at one-week follow-up. The observation intervention consisted of a video model performing the ring-carrying task, with participants randomly assigned to view an expert model, a novice model, a mixed expert/novice model or no observation (control group). Participants were assessed for task performance and surgical instrument control. Results: There were significant group differences post-intervention, with expert and novice observation groups outperforming the control group, but there were no clear group differences at a retention test one week later. There was no difference in performance between the expert-observing and error-observing groups. Conclusions: Similar benefits were found when observing the traditional expert model or the error-strewn model, suggesting that viewing poor performance may be as beneficial as viewing expertise in the early acquisition of robotic surgical skills. Further work is required to understand, then inform, the optimal curriculum design when utilising observational learning in surgical training. | en_GB |
dc.description.sponsorship | Intuitive Surgical Inc | en_GB |
dc.description.sponsorship | Intuitive Surgical grant | en_GB |
dc.identifier.citation | Vol. 12 (11), e0188233 | en_GB |
dc.identifier.doi | 10.1371/journal.pone.0188233 | |
dc.identifier.uri | http://hdl.handle.net/10871/36250 | |
dc.language.iso | en | en_GB |
dc.publisher | Public Library of Science | en_GB |
dc.relation.source | The full dataset is available for download at: https://osf.io/5z89v/?view_only=145ae36726f146b5bbb5ea6762a0d4f6. | en_GB |
dc.rights | © 2017 Harris et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | en_GB |
dc.subject | Human learning | en_GB |
dc.subject | entropy | en_GB |
dc.subject | learning | en_GB |
dc.subject | robotics | en_GB |
dc.subject | hands | en_GB |
dc.subject | laparoscopy | en_GB |
dc.subject | Surgical and invasive medical procedures | en_GB |
dc.subject | minimally invasive surgery | en_GB |
dc.title | The effect of observing novice and expert performance on acquisition of surgical skills on a robotic platform | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2019-03-04T15:06:07Z | |
dc.description | This is the final version. Available from Public Library of Science via the DOI in this record. | en_GB |
dc.identifier.eissn | 1932-6203 | |
dc.identifier.journal | PLoS ONE | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2017-11-02 | |
exeter.funder | ::Intuitive Surgical Inc | en_GB |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2017-11-02 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2019-03-04T15:02:29Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2019-03-04T15:06:11Z | |
refterms.panel | C | en_GB |
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Except where otherwise noted, this item's licence is described as © 2017 Harris et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.