{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,26]],"date-time":"2026-04-26T13:40:10Z","timestamp":1777210810421,"version":"3.51.4"},"reference-count":24,"publisher":"Walter de Gruyter GmbH","issue":"5","license":[{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,4,22]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec id=\"j_jom-2024-0157_abs_001\">\n                    <jats:title>Context<\/jats:title>\n                    <jats:p>As Comprehensive Osteopathic Medical Licensing Examination-USA (COMLEX-USA) Level 1 has changed to Pass\/Fail scoring, residency programs that required minimum Level 1 scores for applicant consideration may choose to focus on COMLEX-USA Level 2-Cognitive Evaluation (Level 2-CE) target scores for applicant selection. Therefore, finding ways to predict passing and high Level 2-CE performance based on students\u2019 past performance and to guide their study accordingly is essential for helping students succeed in and beyond medical school.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_jom-2024-0157_abs_002\">\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>The purpose of this retrospective study is to evaluate the predictive value of major performance measures from pre-admission to clerkship years on Level 2-CE. Then, based on the predictive value of those measures, the objective is to establish a predictive model and optimal cutoff scores with strong predictors to advise students on their preparation of Level\u00a02-CE.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_jom-2024-0157_abs_003\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>School-based performance measures for 948\u00a0first-time takers of the Level 2-CE Testing Cycles of 2019\/20 to 2023\/24 were analyzed. Correlational and multiple regression analyses were utilized to establish a predictive model utilizing: (1) preadmission and preclerkship performance (Medical College Admission Test [MCAT], undergraduate science grade point average [GPA], and preclerkship examination average); (2) national examination performance including the new COMLEX-USA Level 1 pass\/fail-only status, individual and average clinical subject Comprehensive Osteopathic Medical Achievement Test (COMAT) scores, and the less studied Comprehensive Osteopathic Medical Self-Assessment Examination (COMSAE) Phase 2; and (3) clinical evaluation scores by preceptors. Then, receiver operating characteristic (ROC) curves were utilized to identify the optimal cutoff scores on the average clinical subject COMATs and COMSAE Phase 2 for student advising.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_jom-2024-0157_abs_004\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A predictive model of COMLEX Level 2-CE was established with average clinical subject COMAT scores, first-time COMSAE Phase 2, preclerkship examination mean, and COMLEX Level 1 Pass\/Fail status as the significant predictors. This model explained 73.9\u202f% of the variance in Level 2-CE performance. Optimal cutoffs of the average clinical subject COMAT scores and first-time COMSAE Phase 2 performance were identified for passing Level 2-CE (COMSAE=447, average COMAT score=94.4) as well as having a high performance of Level 2-CE (650 &amp; 700, respectively).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_jom-2024-0157_abs_005\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study not only added evidence in support of previous studies on the bivariate associations between Level 2-CE and individual major performance measures from the preadmission to clerkship years, but also explored the use of the less-studied COMSAE Phase 2 in predicting Level 2-CE outcomes and provided a better predictive model utilizing the combination of individual performance measures. Most importantly, the current study also demonstrated a way to set optimal cutoff scores on strong predictors during the clerkship years to help the school guide students to better success on COMLEX Level 2-CE and long-term residency goals.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1515\/jom-2024-0157","type":"journal-article","created":{"date-parts":[[2025,10,3]],"date-time":"2025-10-03T08:56:14Z","timestamp":1759481774000},"page":"213-219","source":"Crossref","is-referenced-by-count":0,"title":["Predicting COMLEX-USA Level 2-CE using medical school performance and use for student advising"],"prefix":"10.1515","volume":"126","author":[{"given":"Shiyuan","family":"Wang","sequence":"first","affiliation":[{"name":"Rowan-Virtua School of Osteopathic Medicine, One Medical Center Drive , Stratford , NJ \u00a0 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pamela","family":"Basehore","sequence":"additional","affiliation":[{"name":"Rowan-Virtua School of Osteopathic Medicine, One Medical Center Drive , Stratford , NJ \u00a0 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2025,10,1]]},"reference":[{"key":"2026042613172101812_j_jom-2024-0157_ref_001","doi-asserted-by":"crossref","unstructured":"Baniadam, K, Elkadi, S, Towfighi, P, Aminpour, N, Sutariya, R, Chen, HC. 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