Development of a core competency evaluation index system for specialist nurses in robot-assisted surgery: a Delphi study

作者：Wen Qin, Xiaoyun Dai, Peipei Huang, Jun Luo, Shen Yang, Qin Zhu · 发表于：BMC Nursing · 年份：2025 · DOI：10.1186/s12912-025-03729-y · 被引用次数：5 · 研究领域：Surgical Simulation and Training、Simulation-Based Education in Healthcare、Delphi Technique in Research

BACKGROUND: The rapid rise of robot-assisted surgery (RAS), especially with the Da Vinci Surgical System (DVSS), has transformed surgical practices, enhanced precision and improving patient outcomes. As this technology becomes more prevalent, operating room nurses have taken on more specialized roles. However, there is a lack of standardized training and competency evaluation for these nurses, leading to inconsistencies in their preparedness. AIM: The current study aimed at developing a competency evaluation index system for nurses in RAS: a Delphi study. METHODS: This study employed a modified Delphi method to develop a competency evaluation index system for nurses in RAS. The study was conducted across seven tertiary-level hospitals in China, all equipped with the Da Vinci Surgical System. Three groups of participants were involved: nursing educators and managers, surgeons, and an expert panel. Data were collected through a literature review, semi-structured interviews, and two rounds of Delphi expert consultations. The importance of competency indicators was measured using a 5-point Likert scale in the survey. RESULTS: The positive coefficient of experts in both rounds of the Delphi survey was 100%, with an authority coefficient of 0.9125, the Kendall's coordination coefficients of the first, second, and third level indexes were 0.467, 0.324, and 0.260 (P < 0.001), 0.454, 0.257, and 0.331 (P < 0.001). The final index system includes three primary indicators (basic nursing ...