Kim Hyejin, Yu Hyeong Won, Ahn Jong-Hyuk, Lee Tae Seon, Lee Kyu Eun
Department of Public Health, Graduate School, Yonsei University, Seoul, Republic of Korea.
Department of Surgery, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
Gland Surg. 2024 Mar 27;13(3):340-350. doi: 10.21037/gs-23-467. Epub 2024 Mar 22.
The changing medical education environment emphasizes the need for time efficiency, increasing the demand for competency-based medical education to improve trainees' learning strategies. This study was performed to determine the competencies required for successful performance of robotic thyroidectomy (RT) and to determine the consensus of experts for performance of RT.
Data were collected through 12 semi-structured interviews with RT experts and 11 field observations. Cognitive task analysis was performed to determine the competencies required for experts to perform RT. A modified Delphi methodology was used to determine how 20 experts rated the importance of each item of RT performance on a Likert 7-point scale. The criteria for the Delphi consensus were set at a Cronbach's α≥0.80 with two survey rounds.
After 11 field observations and 12 semi-structured interviews, 89 items were identified within six modules. These items were grouped into sub-modules according to their theme. The modified Delphi survey, involving 21 experts, reached the consensus standard during the second round (Cronbach's α=0.954), enabling the identification of the 64 most important items within six modules related to RT performance: midline incision to isthmectomy (MID module; n=8), lateral dissection (LAT module; n=7), preservation of inferior parathyroid glands (INF module; n=16), preservation of recurrent laryngeal nerve and dissection of the ligament of Berry (BER module; n=21), dissection of the thyroid upper pole (SUP module; n=10), and specimen removal and closure (END module; n=2).
This mixed-method study combining qualitative and quantitative methodology identified modules of core competencies required to perform RT. These modules can be used as a standard and objective guide to train surgeons to perform RT and evaluate outcomes.
不断变化的医学教育环境强调时间效率的必要性,这增加了对基于能力的医学教育的需求,以改善学员的学习策略。本研究旨在确定成功实施机器人甲状腺切除术(RT)所需的能力,并确定专家对RT实施的共识。
通过对RT专家进行12次半结构化访谈和11次现场观察收集数据。进行认知任务分析以确定专家实施RT所需的能力。采用改良的德尔菲法,让20位专家以李克特7分制对RT表现的各项内容的重要性进行评分。德尔菲共识的标准设定为两轮调查的克朗巴赫α系数≥0.80。
经过11次现场观察和12次半结构化访谈,在六个模块中确定了89项内容。这些内容根据主题分组为子模块。涉及21位专家的改良德尔菲调查在第二轮达到了共识标准(克朗巴赫α系数=0.954),从而确定了与RT表现相关的六个模块中最重要的64项内容:中线切口至峡部切除术(MID模块;n=8)、侧方解剖(LAT模块;n=7)、保留甲状旁腺下腺(INF模块;n=16)、保留喉返神经和Berry韧带解剖(BER模块;n=21)、甲状腺上极解剖(SUP模块;n=10)以及标本取出和关闭(END模块;n=2)。
这项结合定性和定量方法的混合方法研究确定了实施RT所需的核心能力模块。这些模块可作为培训外科医生实施RT和评估结果的标准和客观指南。