Literature DB >> 18481186

Aptitude, achievement and competence in medicine: a latent variable path model.

V Terri Collin1, Claudio Violato, Kent Hecker.   

Abstract

To develop and test a latent variable path model of general achievement, aptitude for medicine and competence in medicine employing data from the Medical College Admission Test (MCAT), pre-medical undergraduate grade point average (UGPA) and demographic characteristics for competence in pre-clinical and measures of competence (United States Licensure Examination {USMLE} Steps 1, 2, and 3). Data were gathered on 839,710 participants from 1991 to 2000 on demographic and school variables, UGPA, MCAT subtest scores and Steps 1, 2, and 3 of the United Stated Licensure Examination (USMLE). However, subsets of the total 839,710 participants included in the database were used for various analyses and the testing of a latent variable path model (LVPA). A number of preliminary descriptive and inferential techniques were used to confirm previous hypotheses and stated relationships amongst the variables of interest to the present study. Through development and testing of a latent variable path model, three latent variables measured by UGPA (general achievement), subscales of the MCAT (aptitude for medicine), and Steps 1, 2, and 3 of the USMLE (competence in medicine) were identified which resulted in a comparative fit index = .932 of the model to a large sample (n = 20,714). In a confirmatory latent variable path model we were able to identify theoretical constructs, aptitude for medicine, general achievement, and competence in medicine and their interrelationships. These are distinct but interrelated latent variables.

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Year:  2008        PMID: 18481186     DOI: 10.1007/s10459-008-9121-7

Source DB:  PubMed          Journal:  Adv Health Sci Educ Theory Pract        ISSN: 1382-4996            Impact factor:   3.853


  4 in total

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2.  Effects of environmental levels of cadmium, lead and mercury on human renal function evaluated by structural equation modeling.

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Journal:  Toxicol Lett       Date:  2014-04-21       Impact factor: 4.372

3.  Structural equation modeling highlights the potential of Kim-1 as a biomarker for chronic kidney disease.

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4.  The UKCAT-12 study: educational attainment, aptitude test performance, demographic and socio-economic contextual factors as predictors of first year outcome in a cross-sectional collaborative study of 12 UK medical schools.

Authors:  I C McManus; Chris Dewberry; Sandra Nicholson; Jonathan S Dowell
Journal:  BMC Med       Date:  2013-11-14       Impact factor: 8.775

  4 in total

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