Attrition in respiratory therapy programs is a waste of both human and economic resources and may be one cause of the current shortage of qualified personnel. Poor academic performance has been shown to be the leading cause of program attrition. The purposes of this study were to establish the predictive abilities of aptitude and performance measures for classroom and laboratory performance in a respiratory therapy program and to describe a methodology for the development of academic admissions criteria. Methods: The preprogram college cumulative grade point average (pPGPA), the preprogram science-mathematics grade point average (S-M GPA), the American College Test (ACT) composite, and four ACT subtest scores of 39 graduates of The Ohio State University Respiratory Therapy Division were compared to their program grade point average (PGPA). We applied a multiple regression analysis and derived regression equations. Results: Multiple regression analysis demonstrated that the S-M GPA is the most significant predictor of program academic performance (P<0.05). The derived regression equation was applied to calculate the minimum S-M GPA for admission by using the standard error of the estimate (SEE) of the regression equation and the mean minimum acceptable PGPA at a 95% confidence interval. For those students who have met the minimum S-M GPA, we have experienced no academic attrition. Conclusion: Multiple regression analysis of student data and the derived regression equations may be used to determine program-specific admissions criteria . (Respir Care 1985;30:334-338.)
K. Flanigan (Wed,) studied this question.
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