BACKGROUND: Previous randomized studies have compared high- versus low-fidelity laparoscopic simulators; however, no proficiency criteria were defined and results have been mixed. The purpose of this research was to determine whether there were any differences in the learning outcomes of participants who had trained to proficiency on low- or high-fidelity laparoscopic surgical simulators. METHODS: We conducted a randomized, prospective crossover trial with participants recruited from New South Wales, Western Australia, and South Australia. Participants were randomized to high-fidelity (LapSim, Surgical Science) or low-fidelity (FLS, SAGES) laparoscopic simulators and trained to proficiency in a defined number of tasks. They then crossed over to the other fidelity simulator and were tested. The outcomes of interest were the crossover mean scores, the proportion of tasks passed, and percentage passes for the crossover simulator tasks. RESULTS: Of the 228 participants recruited, 100 were randomized to LapSim and 128 to FLS. Mean crossover score increased from baseline for both simulators, but there was no significant difference between them (11.0 % vs. 11.9 %). FLS-trained participants passed a significantly higher proportion of crossover tasks compared with LapSim-trained participants (0.26 vs. 0.20, p = 0.016). A significantly higher percentage of FLS-trained participants passed intracorporeal knot tying than LapSim-trained participants (35 % vs. 8 %, p < 0.001). CONCLUSION: Similar increases in participant score from baseline illustrate that training on either simulator type is beneficial. However, FLS-trained participants demonstrated a greater ability to translate their skills to successfully complete LapSim tasks. The ability of FLS-trained participants to transfer their skills to new settings suggests the benefit of this simulator type compared with the LapSim.
RCT Entities:
BACKGROUND: Previous randomized studies have compared high- versus low-fidelity laparoscopic simulators; however, no proficiency criteria were defined and results have been mixed. The purpose of this research was to determine whether there were any differences in the learning outcomes of participants who had trained to proficiency on low- or high-fidelity laparoscopic surgical simulators. METHODS: We conducted a randomized, prospective crossover trial with participants recruited from New South Wales, Western Australia, and South Australia. Participants were randomized to high-fidelity (LapSim, Surgical Science) or low-fidelity (FLS, SAGES) laparoscopic simulators and trained to proficiency in a defined number of tasks. They then crossed over to the other fidelity simulator and were tested. The outcomes of interest were the crossover mean scores, the proportion of tasks passed, and percentage passes for the crossover simulator tasks. RESULTS: Of the 228 participants recruited, 100 were randomized to LapSim and 128 to FLS. Mean crossover score increased from baseline for both simulators, but there was no significant difference between them (11.0 % vs. 11.9 %). FLS-trained participants passed a significantly higher proportion of crossover tasks compared with LapSim-trained participants (0.26 vs. 0.20, p = 0.016). A significantly higher percentage of FLS-trained participants passed intracorporeal knot tying than LapSim-trained participants (35 % vs. 8 %, p < 0.001). CONCLUSION: Similar increases in participant score from baseline illustrate that training on either simulator type is beneficial. However, FLS-trained participants demonstrated a greater ability to translate their skills to successfully complete LapSim tasks. The ability of FLS-trained participants to transfer their skills to new settings suggests the benefit of this simulator type compared with the LapSim.
Authors: Shanu N Kothari; Brian J Kaplan; Eric J DeMaria; Timothy J Broderick; Ronald C Merrell Journal: J Laparoendosc Adv Surg Tech A Date: 2002-06 Impact factor: 1.878
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Authors: Amine Chellali; Helena Mentis; Amie Miller; Woojin Ahn; Venkata S Arikatla; Ganesh Sankaranarayanan; Suvranu De; Steven D Schwaitzberg; Caroline G L Cao Journal: Int J Hum Comput Stud Date: 2016-07-09 Impact factor: 3.632
Authors: Shilpa C Balikai; Aditya Badheka; Andrea Casey; Eric Endahl; Jennifer Erdahl; Lindsay Fayram; Amanda Houston; Paula Levett; Howard Seigel; Niranjan Vijayakumar; Christina L Cifra Journal: Pediatr Qual Saf Date: 2020-12-28
Authors: Kivanc Atesok; Shepard Hurwitz; Donald D Anderson; Richard Satava; Geb W Thomas; Ted Tufescu; Michael J Heffernan; Efstathios Papavassiliou; Steven Theiss; J Lawrence Marsh Journal: Adv Orthop Date: 2019-09-02