Rivard Justin D, Vergis Ashley S, Unger Bertram J, Hardy Krista M, Andrew Chris G, Gillman Lawrence M, Park Jason
Department of Surgery, St. Boniface General Hospital, University of Manitoba, 3rd Floor Z-Block, Winnipeg, MB, R2H 2A6, Canada,
Surg Endosc. 2014 Jun;28(6):1921-8. doi: 10.1007/s00464-013-3414-5. Epub 2014 Jan 18.
Computer-based surgical simulators capture a multitude of metrics based on different aspects of performance, such as speed, accuracy, and movement efficiency. However, without rigorous assessment, it may be unclear whether all, some, or none of these metrics actually reflect technical skill, which can compromise educational efforts on these simulators. We assessed the construct validity of individual performance metrics on the LapVR simulator (Immersion Medical, San Jose, CA, USA) and used these data to create task-specific summary metrics.
Medical students with no prior laparoscopic experience (novices, N = 12), junior surgical residents with some laparoscopic experience (intermediates, N = 12), and experienced surgeons (experts, N = 11) all completed three repetitions of four LapVR simulator tasks. The tasks included three basic skills (peg transfer, cutting, clipping) and one procedural skill (adhesiolysis).
We selected 36 individual metrics on the four tasks that assessed six different aspects of performance, including speed, motion path length, respect for tissue, accuracy, task-specific errors, and successful task completion. Four of seven individual metrics assessed for peg transfer, six of ten metrics for cutting, four of nine metrics for clipping, and three of ten metrics for adhesiolysis discriminated between experience levels. Time and motion path length were significant on all four tasks. We used the validated individual metrics to create summary equations for each task, which successfully distinguished between the different experience levels.
Educators should maintain some skepticism when reviewing the plethora of metrics captured by computer-based simulators, as some but not all are valid. We showed the construct validity of a limited number of individual metrics and developed summary metrics for the LapVR. The summary metrics provide a succinct way of assessing skill with a single metric for each task, but require further validation.
基于计算机的手术模拟器会根据操作表现的不同方面获取大量指标,如速度、准确性和动作效率等。然而,如果没有经过严格评估,可能不清楚这些指标全部、部分还是没有一个能真正反映技术技能,这可能会影响这些模拟器在教育方面的作用。我们评估了LapVR模拟器(美国加利福尼亚州圣何塞市的Immersion Medical公司)上各项个人表现指标的结构效度,并利用这些数据创建特定任务的综合指标。
没有腹腔镜手术经验的医学生(新手,N = 12)、有一定腹腔镜手术经验的初级外科住院医师(中级,N = 12)和经验丰富的外科医生(专家,N = 11)均完成了LapVR模拟器四项任务的三次重复操作。这些任务包括三项基本技能(移钉、切割、夹闭)和一项操作技能(粘连松解)。
我们在四项任务上选取了36个个人指标,这些指标评估了操作表现的六个不同方面,包括速度、运动路径长度、对组织的保护、准确性、特定任务错误和任务成功完成情况。移钉操作评估的七个个人指标中有四个、切割操作的十个指标中有六个、夹闭操作的九个指标中有四个以及粘连松解操作的十个指标中有三个在不同经验水平之间存在差异。时间和运动路径长度在所有四项任务中都具有显著性。我们使用经过验证的个人指标为每项任务创建了综合方程,这些方程成功区分了不同的经验水平。
教育工作者在审查基于计算机的模拟器所获取的大量指标时应保持一定的怀疑态度,因为其中一些但并非全部指标是有效的。我们展示了有限数量的个人指标的结构效度,并为LapVR开发了综合指标。综合指标提供了一种用每个任务的单一指标简洁评估技能的方法,但需要进一步验证。