Stephen D Bigach 1,2 , Robert D Winkelman 2 , Jonathan C Savakus 2,3 , Klara K Papp 2 Show Affiliations »
Abstract
BACKGROUND: Comprehensive Basic Science Self-Assessments (CBSSAs) offered by the National Board of Medical Examiners (NBME) are used by students to gauge preparedness for the United States Medical Licensing (USMLE) Step 1. Because residency programs value Step 1 scores, students expend many resources attempting to score highly on this exam. We sought to generate a predicted Step 1 score from a single CBSSA taken several days out from a planned exam date to inform student testing and study plans. METHODS: 2016 and 2017 Step 1 test takers at one US medical school were surveyed. The average daily score improvement from CBSSA to Step 1 during the 2016 study period was calculated and used to generate a predicted Step 1 score as well as mean absolute prediction errors (MAPEs). The predictive model was validated on 2017 data. RESULTS: In total, 43 of 61 respondents totaling 141 CBSSAs in 2016 and 37 of 43 respondents totaling 122 CBSSAs in 2017 were included. The final prediction model was [Predicted Step 1 = 292 - (292 - CBSSA score) * 0.987527 ^ (number of days out)]. In 2016, the average difference between predicted and actual scores was -0.81 (10.2) and the MAPE was 7.8. In 2017, 88 (72.1%) and 118 (96.7%) of true Step 1 scores fell within one and two standard deviations of a student's predicted score. There was a MAPE of 7.7. Practice form used (p = 0.19, 0.07) and how far out from actual Step 1 it was taken (p = 0.82, 0.38) were not significant in either year of study. CONCLUSION: This projection model is reasonable for students to use to gauge their readiness for Step 1 while it remains a scored exam and provides a framework for future predictive model generation as the landscape of standardized testing changes in medical education. © International Association of Medical Science Educators 2020.
BACKGROUND: Comprehensive Basic Science Self-Assessments (CBSSAs) offered by the National Board of Medical Examiners (NBME) are used by students to gauge preparedness for the United States Medical Licensing (USMLE) Step 1. Because residency programs value Step 1 scores, students expend many resources attempting to score highly on this exam. We sought to generate a predicted Step 1 score from a single CBSSA taken several days out from a planned exam date to inform student testing and study plans. METHODS: 2016 and 2017 Step 1 test takers at one US medical school were surveyed. The average daily score improvement from CBSSA to Step 1 during the 2016 study period was calculated and used to generate a predicted Step 1 score as well as mean absolute prediction errors (MAPEs). The predictive model was validated on 2017 data. RESULTS: In total, 43 of 61 respondents totaling 141 CBSSAs in 2016 and 37 of 43 respondents totaling 122 CBSSAs in 2017 were included. The final prediction model was [Predicted Step 1 = 292 - (292 - CBSSA score) * 0.987527 ^ (number of days out)]. In 2016, the average difference between predicted and actual scores was -0.81 (10.2) and the MAPE was 7.8. In 2017, 88 (72.1%) and 118 (96.7%) of true Step 1 scores fell within one and two standard deviations of a student's predicted score. There was a MAPE of 7.7. Practice form used (p = 0.19, 0.07) and how far out from actual Step 1 it was taken (p = 0.82, 0.38) were not significant in either year of study. CONCLUSION: This projection model is reasonable for students to use to gauge their readiness for Step 1 while it remains a scored exam and provides a framework for future predictive model generation as the landscape of standardized testing changes in medical education. © International Association of Medical Science Educators 2020.
Entities: Chemical
Keywords:
Projection modeling; Step 1; Testing; USMLE
Year: 2020
PMID： 34457866 PMCID： PMC8368818 DOI： 10.1007/s40670-020-01097-7
Source DB: PubMed Journal: Med Sci Educ ISSN： 2156-8650