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Predictors of Academic Difficulties of Osteopathic Medical Students in the Preclinical Curriculum

Journal: Unpublished Dissertation Drake University, Date: 1993/08, Pages: 80, type of study: retrospective study

Free full text   (https://escholarshare.drake.edu/handle/2092/304)

Keywords:

academic difficulties [1]
admission [25]
curriculum [229]
medical students [402]
osteopathic medicine [1540]
retrospective study [213]
USA [1086]

Abstract:

The problem: This research examined the relationship of admission characteristics with indicators of academic performance during the first year of an osteopathic medical curriculum. This was done in order to identify factors that might suggest that osteopathic students will experience academic difficulties early in their enrollment. Procedures: Ex post facto research in the form of a retrospective correlational study was conducted. Admission and grade records were reviewed for 50 students who had two or more course failures during the first year of the curriculum and 50 students who had no course failures during the same period. Correlation coefficients and coefficients of determination were calculated for the relationships of the number of course failures and eight admission variables. The same procedure was used between each of the admission variables and the first year grade point average. Findines: There were statistically significant but low negative correlations between each of the eight admission variables and the number of course failures. There were statistically significant but low positive correlations with the first year grade point average. The admission variables explained 30 percent of the variability in the number of course failures or first year grade point average. Conclusions and Recornmendations: The admission characteristics were individually of limited value in predicting performance during the first year preclinical curriculum of an osteopathic medical school. Future research needs to expand the variables for study. Studies done at individual institutions should not only look at traditional predictors, but should also look at variables that are unique to their applicant pool and their institutions.


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