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<p>This qualitative exploratory study evaluated 25 nursing team members experienced in Robotic-Assisted Surgery (RAS) at a Brazilian university hospital. Data collection used a validated instrument (CVI = 1.0), and Bardin’s thematic analysis identified three competency domains: clinical practice/system configuration, management of inputs/logistics, and handling of complications/learning curve indicators. Participants were predominantly female (88%), averaging three years of RAS experience with high heterogeneity (CV ≈ 68%). All participants performed patient positioning and endoscope connection; 92% managed electrosurgical settings; and 80% handled decoupling and pre-cleaning. Basic system proficiency required a weighted average of 16 procedures, whereas safe intraoperative performance required 13.5 weeks of immersion. Emergency undocking was reported by 28% of participants, primarily caused by power failures or system instability. The perceived learning curve was non-linear and dependent on procedure frequency, specialty complexity, and institutional support. In conclusion, the learning curve is multidimensional and cannot be reduced to single targets. Brazilian nursing teams operate beyond formal regulatory boundaries, highlighting the need for competency-based training, specialty exposure, and emergency simulation protocols. The gap between perceived proficiency and objective thresholds shows self-reported learning reflects operational familiarity rather than complete clinical safety. Standardizing emergency undocking preparedness remains an essential patient safety priority. These findings establish a baseline for standardized nursing RAS training programs.</p>

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Perceived learning curve of the nursing team using the da vinci XI surgical system in a Brazilian university hospital

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月31日

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  • Ricardo de Oliveira Meneses,
  • Letícia Perfeito Ramos,
  • Lisandra Rodrigues Risi,
  • Rosilene Alves Ferreira,
  • Camila Castanho Cardinelli,
  • Fernanda Ferreira e Silva

摘要

This qualitative exploratory study evaluated 25 nursing team members experienced in Robotic-Assisted Surgery (RAS) at a Brazilian university hospital. Data collection used a validated instrument (CVI = 1.0), and Bardin’s thematic analysis identified three competency domains: clinical practice/system configuration, management of inputs/logistics, and handling of complications/learning curve indicators. Participants were predominantly female (88%), averaging three years of RAS experience with high heterogeneity (CV ≈ 68%). All participants performed patient positioning and endoscope connection; 92% managed electrosurgical settings; and 80% handled decoupling and pre-cleaning. Basic system proficiency required a weighted average of 16 procedures, whereas safe intraoperative performance required 13.5 weeks of immersion. Emergency undocking was reported by 28% of participants, primarily caused by power failures or system instability. The perceived learning curve was non-linear and dependent on procedure frequency, specialty complexity, and institutional support. In conclusion, the learning curve is multidimensional and cannot be reduced to single targets. Brazilian nursing teams operate beyond formal regulatory boundaries, highlighting the need for competency-based training, specialty exposure, and emergency simulation protocols. The gap between perceived proficiency and objective thresholds shows self-reported learning reflects operational familiarity rather than complete clinical safety. Standardizing emergency undocking preparedness remains an essential patient safety priority. These findings establish a baseline for standardized nursing RAS training programs.