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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...
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Published in: | Advances in medical education and practice 2017-01, Vol.8, p.385-391 |
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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. |
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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.</description><identifier>ISSN: 1179-7258</identifier><identifier>EISSN: 1179-7258</identifier><identifier>DOI: 10.2147/AMEP.S138557</identifier><identifier>PMID: 28670150</identifier><language>eng</language><publisher>New Zealand: Dove Medical Press Limited</publisher><subject>assessment ; At risk students ; Curricula ; Educational research ; Enrollments ; Licenses ; Licensing examinations ; licensure exam ; Medical education ; Medical schools ; Original Research ; Professional examinations ; Science ; Step 2 CK ; Studies ; Tutoring ; USMLE ; Validity</subject><ispartof>Advances in medical education and practice, 2017-01, Vol.8, p.385-391</ispartof><rights>COPYRIGHT 2017 Dove Medical Press Limited</rights><rights>2017. This work is licensed under https://creativecommons.org/licenses/by-nc/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2017 Monteiro et al. This work is published and licensed by Dove Medical Press Limited 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c545t-22d8a8d58c7e5a82f82c6a392b30e5ea8a894900420f9c937d4e466ef03e435d3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2223357945/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2223357945?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28670150$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Monteiro, Kristina A</creatorcontrib><creatorcontrib>George, Paul</creatorcontrib><creatorcontrib>Dollase, Richard</creatorcontrib><creatorcontrib>Dumenco, Luba</creatorcontrib><title>Predicting United States Medical Licensure Examination Step 2 clinical knowledge scores from previous academic indicators</title><title>Advances in medical education and practice</title><addtitle>Adv Med Educ Pract</addtitle><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.</description><subject>assessment</subject><subject>At risk students</subject><subject>Curricula</subject><subject>Educational research</subject><subject>Enrollments</subject><subject>Licenses</subject><subject>Licensing examinations</subject><subject>licensure exam</subject><subject>Medical education</subject><subject>Medical schools</subject><subject>Original Research</subject><subject>Professional examinations</subject><subject>Science</subject><subject>Step 2 CK</subject><subject>Studies</subject><subject>Tutoring</subject><subject>USMLE</subject><subject>Validity</subject><issn>1179-7258</issn><issn>1179-7258</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNptkk1vEzEQhlcIRKvSG2dkiQsHEvy5u74gRVUolVJRqfRsTbyzwWHXDvam0H9fb5OWBuGLrZl3ntG8nqJ4y-iUM1l9ml3Or6bXTNRKVS-KY8YqPam4ql8-ex8VpymtaT5SC8706-KI12VFmaLHxd1VxMbZwfkVufFuwIZcDzBgIpdjHDqycBZ92kYk8z_QOw-DCz6LcEM4sZ3zD6qfPvzusFkhSTbEXN7G0JNNxFsXtomAhQZ7Z4nzI3UIMb0pXrXQJTzd3yfFzZf597Ovk8W384uz2WJilVTDhPOmhrpRta1QQc3bmtsShOZLQVEh5KSWOs_GaautFlUjUZYltlSgFKoRJ8XFjtsEWJtNdD3EOxPAmYdAiCsDcXC2Q0Ol4EvgJXBrpeZ0idq2JbQVYvYNbGZ93rE222WPTTZmiNAdQA8z3v0wq3BrlKy5pDwDPuwBMfzaYhpM75LFrgOP2SfDNFP5K6ViWfr-H-k6bKPPVhnOuRCq0lL9Va0gD-B8G3JfO0LNTAlGlSr12Hb6H9XjpwSPrcvxg4KPuwIbQ0oR26cZGTXj5plx88x-87L83XNfnsSPeybuAYmJ07w</recordid><startdate>20170101</startdate><enddate>20170101</enddate><creator>Monteiro, Kristina A</creator><creator>George, Paul</creator><creator>Dollase, Richard</creator><creator>Dumenco, Luba</creator><general>Dove Medical Press Limited</general><general>Taylor & Francis Ltd</general><general>Dove Medical Press</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TS</scope><scope>7XB</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>M2O</scope><scope>MBDVC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20170101</creationdate><title>Predicting United States Medical Licensure Examination Step 2 clinical knowledge scores from previous academic indicators</title><author>Monteiro, Kristina A ; 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subjects | assessment At risk students Curricula Educational research Enrollments Licenses Licensing examinations licensure exam Medical education Medical schools Original Research Professional examinations Science Step 2 CK Studies Tutoring USMLE Validity |
title | Predicting United States Medical Licensure Examination Step 2 clinical knowledge scores from previous academic indicators |
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