PURPOSE: We evaluated the concurrent and predictive validity of a novel robotic surgery simulator in a prospective, randomized study. MATERIALS AND METHODS: A total of 24 robotic surgery trainees performed virtual reality exercises on the da Vinci® Skills Simulator using the da Vinci Si™ surgeon console. Baseline simulator performance was captured. Baseline live robotic performance on ex vivo animal tissue exercises was evaluated by 3 expert robotic surgeons using validated laparoscopic assessment metrics. Trainees were then randomized to group 1-simulator training and group 2-no training while matched for baseline tissue scores. Group 1 trainees underwent a 10-week simulator curriculum. Repeat tissue exercises were done at study conclusion to assess performance improvement. Spearman's analysis was used to correlate baseline simulator performance with baseline ex vivo tissue performance (concurrent validity) and final tissue performance (predictive validity). The Kruskal-Wallis test was used to compare group performance. RESULTS: Groups 1 and 2 were comparable in pre-study surgical experience and had similar baseline scores on simulator and tissue exercises (p >0.05). Overall baseline simulator performance significantly correlated with baseline and final tissue performance (concurrent and predictive validity each r = 0.7, p <0.0001). Simulator training significantly improved tissue performance on key metrics for group 1 subjects with lower baseline tissue scores (below the 50th percentile) than their group 2 counterparts (p <0.05). Group 1 tended to outperform group 2 on final tissue performance, although the difference was not significant (p >0.05). CONCLUSIONS: Our study documents the concurrent and predictive validity of the Skills Simulator. The benefit of simulator training appears to be most substantial for trainees with low baseline robotic skills.
RCT Entities:
PURPOSE: We evaluated the concurrent and predictive validity of a novel robotic surgery simulator in a prospective, randomized study. MATERIALS AND METHODS: A total of 24 robotic surgery trainees performed virtual reality exercises on the da Vinci® Skills Simulator using the da Vinci Si™ surgeon console. Baseline simulator performance was captured. Baseline live robotic performance on ex vivo animal tissue exercises was evaluated by 3 expert robotic surgeons using validated laparoscopic assessment metrics. Trainees were then randomized to group 1-simulator training and group 2-no training while matched for baseline tissue scores. Group 1 trainees underwent a 10-week simulator curriculum. Repeat tissue exercises were done at study conclusion to assess performance improvement. Spearman's analysis was used to correlate baseline simulator performance with baseline ex vivo tissue performance (concurrent validity) and final tissue performance (predictive validity). The Kruskal-Wallis test was used to compare group performance. RESULTS: Groups 1 and 2 were comparable in pre-study surgical experience and had similar baseline scores on simulator and tissue exercises (p >0.05). Overall baseline simulator performance significantly correlated with baseline and final tissue performance (concurrent and predictive validity each r = 0.7, p <0.0001). Simulator training significantly improved tissue performance on key metrics for group 1 subjects with lower baseline tissue scores (below the 50th percentile) than their group 2 counterparts (p <0.05). Group 1 tended to outperform group 2 on final tissue performance, although the difference was not significant (p >0.05). CONCLUSIONS: Our study documents the concurrent and predictive validity of the Skills Simulator. The benefit of simulator training appears to be most substantial for trainees with low baseline robotic skills.
Authors: Daniel J Kiely; Walter H Gotlieb; Susie Lau; Xing Zeng; Vanessa Samouelian; Agnihotram V Ramanakumar; Helena Zakrzewski; Sonya Brin; Shannon A Fraser; Pira Korsieporn; Laura Drudi; Joshua Z Press Journal: J Robot Surg Date: 2015-05-16
Authors: Ankit Patel; Meghna Patel; Nathaniel Lytle; Juan P Toro; Rachel L Medbery; Sheryl Bluestein; Sebastian D Perez; John F Sweeney; S Scott Davis; Edward Lin Journal: Surg Endosc Date: 2014-03 Impact factor: 4.584
Authors: Beiqun Zhao; Hannah M Hollandsworth; Arielle M Lee; Jenny Lam; Nicole E Lopez; Benjamin Abbadessa; Samuel Eisenstein; Bard C Cosman; Sonia L Ramamoorthy; Lisa A Parry Journal: J Surg Educ Date: 2019-09-23 Impact factor: 2.891
Authors: Michael I Hanzly; Tareq Al-Tartir; Syed Johar Raza; Atif Khan; Mohammad Manan Durrani; Thomas Fiorica; Phillip Ginsberg; James L Mohler; Boris Kuvshinoff; Khurshid A Guru Journal: Curr Urol Rep Date: 2015-06 Impact factor: 3.092