Literature DB >> 20881707

Validity of four approaches of using repeaters' MCAT scores in medical school admissions to predict USMLE Step 1 total scores.

Xiaohui Zhao1, Scott Oppler, Dana Dunleavy, Marc Kroopnick.   

Abstract

BACKGROUND: This study investigated the validity of four approaches (the average, most recent, highest-within-administration, and highest-across-administration approaches) of using repeaters' Medical College Admission Test (MCAT) scores to predict Step 1 scores.
METHOD: Using the differential predication method, this study investigated the magnitude of differences in the expected Step 1 total scores between MCAT nonrepeaters and three repeater groups (two-time, three-time, and four-time test takers) for the four scoring approaches.
RESULTS: For the average score approach, matriculants with the same MCAT average are expected to achieve similar Step 1 total scores regardless of whether the individual attempted the MCAT exam one or multiple times. For the other three approaches, repeaters are expected to achieve lower Step 1 scores than nonrepeaters; for a given MCAT score, as the number of attempts increases, the expected Step 1 decreases. The effect was strongest for the highest-across-administration approach, followed by the highest-within-administration approach, and then the most recent approach.
CONCLUSIONS: Using the average score is the best approach for considering repeaters' MCAT scores in medical school admission decisions.

Mesh:

Year:  2010        PMID: 20881707     DOI: 10.1097/ACM.0b013e3181ed38fc

Source DB:  PubMed          Journal:  Acad Med        ISSN: 1040-2446            Impact factor:   6.893


  5 in total

1.  Class-Wide Access to a Commercial Step 1 Question Bank During Preclinical Organ-Based Modules: A Pilot Project.

Authors:  James H Baños; Mark E Pepin; Nicholas Van Wagoner
Journal:  Acad Med       Date:  2018-03       Impact factor: 6.893

2.  Institutional differences in USMLE Step 1 and 2 CK performance: Cross-sectional study of 89 US allopathic medical schools.

Authors:  Jesse Burk-Rafel; Ricardo W Pulido; Yousef Elfanagely; Joseph C Kolars
Journal:  PLoS One       Date:  2019-11-04       Impact factor: 3.240

3.  Identifying and supporting students at risk of failing the National Medical Licensure Examination in Japan using a predictive pass rate.

Authors:  Koji Tsunekawa; Yasuyuki Suzuki; Toshiki Shioiri
Journal:  BMC Med Educ       Date:  2020-11-10       Impact factor: 2.463

4.  Using Markov chain model to evaluate medical students' trajectory on progress tests and predict USMLE step 1 scores---a retrospective cohort study in one medical school.

Authors:  Ling Wang; Heather S Laird-Fick; Carol J Parker; David Solomon
Journal:  BMC Med Educ       Date:  2021-04-09       Impact factor: 2.463

5.  Signatures of medical student applicants and academic success.

Authors:  Tal Baron; Robert I Grossman; Steven B Abramson; Martin V Pusic; Rafael Rivera; Marc M Triola; Itai Yanai
Journal:  PLoS One       Date:  2020-01-15       Impact factor: 3.240

  5 in total

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