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美国医师执照考试第一步(USMLE Step 1)分数的预测模型。

A Predictive Model for USMLE Step 1 Scores.

作者信息

Giordano Christin, Hutchinson David, Peppler Richard

机构信息

Faculty and Academic Affairs, University of Central Florida College of Medicine.

出版信息

Cureus. 2016 Sep 7;8(9):e769. doi: 10.7759/cureus.769.

Abstract

PURPOSE

The United States Medical Licensing Examination (USMLE) Step 1 plays a pivotal role in one's residency application. While prior literature has investigated which factors influence performance on the examination, the authors sought to include factors such as performance on a well-used question bank and financial need to develop a predictive model.

METHOD

After obtaining institutional review board approval, the authors surveyed two consecutive second-year medical school classes and correlated the data to the students' Step 1 and National Board of Medical Examiners (NBME) Comprehensive Basic Science Examination (CBSE) scores. The survey included questions such as how many days they studied per week, how many days they studied in total, which resources they used, how they performed on question banks, group studying habits, and whether they were receiving financial aid. The authors also assessed whether the students received only A letter grades during the first year of medical school. The authors used SPSS® Statistics V22.0 (IBM® Corporation, NY, USA ) and included one-way analysis of covariance (ANOVA) and multiple linear regression for statistical analysis.

RESULTS

Eighty-one students completed the survey with an average Step 1 score of 240.5 and with an average study time of 39.5 days. The Step 1 Scores significantly correlated with the CBSE taken immediately preceding the dedicated study period (r=0.711, =<0.001), UWorld Question Bank (UWorld) percentage correct (r = 0.622, <0.001), straight As during first-year (r=0.356, =0.001), and financial need (r=0.318, =0.01). The scores were not correlated with age, gender, Medical College Admissions Test (MCAT), prior medical training, number of days studied, or the students' perception of appropriate time studied. The authors developed a predictive model accounting for 62.3% of the variability. 140.625+(0.319xCBSE)-(3.817xA)+(5.845xN)+(0.452xU), where A=1 if straight As, N=1 if receiving need-based scholarship, U=UWorld percent-correct, and CBSE=the three-digit score of the CBSE taken prior to the dedicated study period.

CONCLUSIONS

Academic performance and financial need may predict Step 1 scores. Interestingly, the number of days studied did not have a correlation with scores, suggesting that increased length of study may not ameliorate poor grades.

摘要

目的

美国医师执照考试(USMLE)第一步在住院医师申请过程中起着关键作用。尽管先前的文献研究了哪些因素会影响考试成绩,但作者试图纳入诸如在常用题库中的表现以及经济需求等因素来建立一个预测模型。

方法

在获得机构审查委员会的批准后,作者对连续两届医学院二年级学生进行了调查,并将数据与学生的第一步考试成绩以及美国国家医学考试委员会(NBME)综合基础科学考试(CBSE)成绩进行关联。调查包括他们每周学习的天数、总共学习的天数、使用的资源、在题库中的表现、小组学习习惯以及是否获得经济援助等问题。作者还评估了学生在医学院第一年是否只获得了A等成绩。作者使用SPSS® Statistics V22.0(IBM® Corporation,纽约,美国),并采用单因素协方差分析(ANOVA)和多元线性回归进行统计分析。

结果

81名学生完成了调查,第一步考试的平均成绩为240.5分,平均学习时间为39.5天。第一步考试成绩与在专门学习期之前立即进行的CBSE成绩显著相关(r = 0.711,P<0.001)、UWorld题库(UWorld)的正确率(r = 0.622,P<0.001)、一年级时全得A(r = 0.356,P = 0.001)以及经济需求(r = 0.318,P = 0.01)。成绩与年龄、性别、医学院入学考试(MCAT)、先前的医学培训、学习天数或学生对适当学习时间的认知无关。作者建立了一个解释62.3%变异性的预测模型。140.625 +(0.319×CBSE)-(3.817×A)+(5.845×N)+(0.452×U),其中如果全得A则A = 1,如果获得基于需求的奖学金则N = 1,U = UWorld的正确率,CBSE = 在专门学习期之前进行的CBSE的三位数成绩。

结论

学业成绩和经济需求可能预测第一步考试成绩。有趣的是,学习天数与成绩无关,这表明学习时间的增加可能无法改善成绩不佳的情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c3f/5059149/1532239688d2/cureus-0008-000000000769-i01.jpg

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