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Predicting United States Medical Licensure Examination Step 2 clinical knowledge scores from previous academic indicators
The use of multiple academic indicators to identify students at risk of experiencing difficulty completing licensure requirements provides an opportunity to increase support services prior to high-stakes licensure examinations, including the United States Medical Licensure Examination (USMLE) Step 2...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5482402/ https://www.ncbi.nlm.nih.gov/pubmed/28670150 http://dx.doi.org/10.2147/AMEP.S138557 |
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author | Monteiro, Kristina A George, Paul Dollase, Richard Dumenco, Luba |
author_facet | Monteiro, Kristina A George, Paul Dollase, Richard Dumenco, Luba |
author_sort | Monteiro, Kristina A |
collection | PubMed |
description | The use of multiple academic indicators to identify students at risk of experiencing difficulty completing licensure requirements provides an opportunity to increase support services prior to high-stakes licensure examinations, including the United States Medical Licensure Examination (USMLE) Step 2 clinical knowledge (CK). Step 2 CK is becoming increasingly important in decision-making by residency directors because of increasing undergraduate medical enrollment and limited available residency vacancies. We created and validated a regression equation to predict students’ Step 2 CK scores from previous academic indicators to identify students at risk, with sufficient time to intervene with additional support services as necessary. Data from three cohorts of students (N=218) with preclinical mean course exam score, National Board of Medical Examination subject examinations, and USMLE Step 1 and Step 2 CK between 2011 and 2013 were used in analyses. The authors created models capable of predicting Step 2 CK scores from academic indicators to identify at-risk students. In model 1, preclinical mean course exam score and Step 1 score accounted for 56% of the variance in Step 2 CK score. The second series of models included mean preclinical course exam score, Step 1 score, and scores on three NBME subject exams, and accounted for 67%–69% of the variance in Step 2 CK score. The authors validated the findings on the most recent cohort of graduating students (N=89) and predicted Step 2 CK score within a mean of four points (SD=8). The authors suggest using the first model as a needs assessment to gauge the level of future support required after completion of preclinical course requirements, and rescreening after three of six clerkships to identify students who might benefit from additional support before taking USMLE Step 2 CK. |
format | Online Article Text |
id | pubmed-5482402 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-54824022017-06-30 Predicting United States Medical Licensure Examination Step 2 clinical knowledge scores from previous academic indicators Monteiro, Kristina A George, Paul Dollase, Richard Dumenco, Luba Adv Med Educ Pract Original Research The use of multiple academic indicators to identify students at risk of experiencing difficulty completing licensure requirements provides an opportunity to increase support services prior to high-stakes licensure examinations, including the United States Medical Licensure Examination (USMLE) Step 2 clinical knowledge (CK). Step 2 CK is becoming increasingly important in decision-making by residency directors because of increasing undergraduate medical enrollment and limited available residency vacancies. We created and validated a regression equation to predict students’ Step 2 CK scores from previous academic indicators to identify students at risk, with sufficient time to intervene with additional support services as necessary. Data from three cohorts of students (N=218) with preclinical mean course exam score, National Board of Medical Examination subject examinations, and USMLE Step 1 and Step 2 CK between 2011 and 2013 were used in analyses. The authors created models capable of predicting Step 2 CK scores from academic indicators to identify at-risk students. In model 1, preclinical mean course exam score and Step 1 score accounted for 56% of the variance in Step 2 CK score. The second series of models included mean preclinical course exam score, Step 1 score, and scores on three NBME subject exams, and accounted for 67%–69% of the variance in Step 2 CK score. The authors validated the findings on the most recent cohort of graduating students (N=89) and predicted Step 2 CK score within a mean of four points (SD=8). The authors suggest using the first model as a needs assessment to gauge the level of future support required after completion of preclinical course requirements, and rescreening after three of six clerkships to identify students who might benefit from additional support before taking USMLE Step 2 CK. Dove Medical Press 2017-06-19 /pmc/articles/PMC5482402/ /pubmed/28670150 http://dx.doi.org/10.2147/AMEP.S138557 Text en © 2017 Monteiro et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. |
spellingShingle | Original Research Monteiro, Kristina A George, Paul Dollase, Richard Dumenco, Luba Predicting United States Medical Licensure Examination Step 2 clinical knowledge scores from previous academic indicators |
title | Predicting United States Medical Licensure Examination Step 2 clinical knowledge scores from previous academic indicators |
title_full | Predicting United States Medical Licensure Examination Step 2 clinical knowledge scores from previous academic indicators |
title_fullStr | Predicting United States Medical Licensure Examination Step 2 clinical knowledge scores from previous academic indicators |
title_full_unstemmed | Predicting United States Medical Licensure Examination Step 2 clinical knowledge scores from previous academic indicators |
title_short | Predicting United States Medical Licensure Examination Step 2 clinical knowledge scores from previous academic indicators |
title_sort | predicting united states medical licensure examination step 2 clinical knowledge scores from previous academic indicators |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5482402/ https://www.ncbi.nlm.nih.gov/pubmed/28670150 http://dx.doi.org/10.2147/AMEP.S138557 |
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