Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.
The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.
Int J Gynaecol Obstet. 2023 May;161(2):499-508. doi: 10.1002/ijgo.14528. Epub 2022 Nov 16.
To prove the potentialities of an integrated and sensorized childbirth platform as an innovative simulator for education of inexperienced gynecological and obstetrical medical students.
A total of 152 inexperienced medical students were recruited to a simulation program on labor progression evaluation. After an introductory lecture on basic concepts of labor and birth given by an expert gynecologist, three different gynecologic scenarios were simulated using both a traditional obstetric simulator and the innovative proposed platform, for a total of six tests for each student. A score was assigned for each performed scenario, based on its correctness. Self-assessment questionnaires were compiled before and after the simulation program for additional subjective assessment.
Median score of the simulations performed with our platform was significantly higher than that of the simulations performed with a traditional simulator, for all the three experimented scenarios (P < 0.001).
The use of a sensorized platform for labor progression allowed for an accurate and faster diagnosis if compared with a traditional simulator even for inexperienced operators, supporting its use in clinical training, which could be realistically introduced into the clinical practice for medical student education.
证明集成化和传感器式分娩平台作为一种创新性的教育工具，用于培训缺乏经验的妇科和产科医学生的潜力。
共招募了 152 名缺乏经验的医学生参加分娩进展评估模拟项目。在由专家妇科医生进行的关于分娩基本概念的介绍性讲座之后，使用传统产科模拟器和创新的拟议平台模拟了三个不同的妇科场景，每个学生总共进行了六次测试。根据每个场景的正确性为每个执行的场景分配了一个分数。在模拟项目前后编制了自我评估问卷，以进行额外的主观评估。
与传统模拟器相比，在所有三个实验场景中，使用我们的平台进行的模拟的中位数评分明显更高（P<0.001）。
与传统模拟器相比，使用传感器式平台进行分娩进展评估可以进行更准确和更快的诊断，即使对于缺乏经验的操作人员也是如此，这支持了其在临床培训中的应用，这在医学学生教育中可以实际引入到临床实践中。
