Reznick R K, Dillon R F, Folse J R
Department of Surgery, Southern Illinois University School of Medicine, Springfield.
Surgery. 1988 Jun;103(6):671-5.
A new system for predicting success of surgical student performance has been developed. A test of surgical knowledge, with questions given in the form of analogies, was administered to 16 students in their fourth week of clerkship. While solving test items, students' eye movements and fixations were tracked. By analysis of the recordings, eight scores of information-processing capabilities were derived. The processing scores and conventional predictors of medical school clinical performance were analyzed to determine their power to predict success, defined by ratings given on a 1 to 10 scale by 21 faculty members based on three tests of cognitive knowledge, two performance-based examinations, and faculty reports. The ratings were reliable (generalizability coefficient = 0.72; p less than 0.001). Stepwise regression analysis of all variables selected one MCAT score (science problems) and two information-processing scores to the statistical model that maximally predicted success. Regression coefficient for the science problem subset of the MCAT was 0.42. This was augmented to R2 = 0.77 when information processing variables were included. The increment was significant, F (2, 11) = 9.25; p less than 0.01. A newly developed test, coupled with techniques that made possible the derivation of components of information processing, nearly doubled the power of conventional tests to predict success in surgical clerkship.
一种用于预测外科学生手术表现成功率的新系统已被开发出来。在实习的第四周，对16名学生进行了一次外科知识测试，测试问题采用类比形式。在学生解答测试题时，对他们的眼球运动和注视点进行了跟踪。通过对记录的分析，得出了八项信息处理能力得分。分析了这些处理得分以及医学院临床成绩的传统预测指标，以确定它们预测成功的能力，成功的定义是由21名教员根据三项认知知识测试、两项基于表现的考试以及教员报告给出的1至10分的评分。这些评分是可靠的（概化系数=0.72；p小于0.001）。对所有变量进行逐步回归分析，将一个医学院入学考试（MCAT）成绩（科学问题部分）和两项信息处理得分选入能最大程度预测成功的统计模型。MCAT科学问题部分的回归系数为0.42。当纳入信息处理变量时，这一系数提高到R2=0.77。增量显著，F(2, 11)=9.25；p小于0.01。一项新开发的测试，再加上能够得出信息处理组成部分的技术，使传统测试预测外科实习成功的能力几乎提高了一倍。
