The predictors of academic performance of the medical students of upcm: class1990 to class 2013 lateral entrants.
- Author:
Carlo G. CATABIJAN
1
;
Sharon D. IGNACIO
1
;
Johanna Patricia A. CANAL
1
Author Information
- Publication Type:Journal Article, Original
- Keywords: Medical College Admission, Admissions Criteria, Medical Education, Academic Performance, Up College Of Medicine
- MeSH: Medical College Admission, Admissions Criteria, Medical Education, Academic Performance, Up College Of Medicine
- From: Philippine Journal of Health Research and Development 2017;21(3):1-9
- CountryPhilippines
- Language:English
-
Abstract:
Background: The criteria for admission at the University of the Philippine College of Medicine (UPCM) are sixty
percent premed general weighted average grade (PMGWAG), thirty percent National Medical Admission Test
(NMAT) scores and ten percent Interview Scores. Through the years, because of the highly competitive nature
of the selection process, the admissions cut-offs in PMGWAG and average NMAT has continuously risen.
Objectives: This study that covered a twenty four year period, aimed to determine the correlation and
predictive value between the admissions criteria (%Pre-med GWAG, NMAT and Interview Score) with
academic performance parameters (%Med GWAG and Class Ranking) and Board Rating.
Methods: The pre-admission and academic records of accepted lateral entrants from Class 1990 to Class 2013
were retrieved, reviewed and analyzed. These included the pre-med GWAG (%PMGWAG), NMAT and
Interview Scores, Med GWAG (%MGWAG), Class Ranking and Board Rating. Pearsons Correlation and Multiple
Linear regression analysis were done.
Results: All criteria (%PMGWAG, NMAT, Interview Score) for admissions were correlated with the academic
performance parameters (%MGWAG, Class Rank) and Board Rating. The strongest correlation was observed in
%PMGWAG with %MGWAG and Class Rank. Interview score correlated weakly with the academic
performance. Strong correlations between %MGWAG, Class Rank and Board Rating were likewise observed.
Rank upon admission also correlated strongly with Class Rank upon graduation. On linear regression analysis,
%PMGWAG and NMAT were more predictive of %MGWAG, Class Rank and Board Rating.
Conclusion: The weight distribution of the different admissions criteria should be adjusted accordingly.
Interview score, a weak predictor of academic performance and a measure of non-cognitive traits, should be
treated separately and independently as an admission criteria.