Validation of Composite Score for Student Selection and Successful Completion of Credentialing Exams in a Baccalaureate Respiratory Therapy Program

Abstract

Background: Choosing data to use when selecting students for a respiratory therapy (RT) program can be a difficult task. Information such as program grade point average (PGPA), Test of Essential Academic Skills (TEAS), core curriculum grades, and essay composition can be used for this task. Can combining these data points into one composite score (CS) predict successful completion of a respiratory therapy program and success on national credentialing exams?

Methods: Georgia State University (GSU) data was used for this study. A retrospective analysis of data submitted by students as part of the application process to GSU Respiratory Therapy (RT) program for years 2018-2020 was used. Admission data used for this study was TEAS, GPA, and calculated CS. Also used in the analysis were the Therapist Multiple Choice (TMC) exam and the Clinical Simulation Exam (CSE) taken after graduation from the program. Descriptive statistics and correlational analysis were used with SPSS 25 to examine data.

Results: A total of 101 students completed GSU RT program in the 2018, 2019, and 2020 cohorts. Descriptive statistics for these cohorts reveal 21.8% (22) male and 78.2% (79) female. Additionally, 87.1% (88) identified as minority and 12.9% (13) identified as Caucasian. Means for this study are as follows: CS 31.09 (SD = 7.55), TEAS 75.43 (SD = 6.92), and PGPA 3.41 (SD = 0.31). Pearson correlation coefficient was computed to assess the linear relationship between CS and TEAS and CS and PGPA. There was a positive correlation between CS and TEAS r(98) = 0.378, P = < .001 and CS and PGPA r(98) = 0.818, P = < .001. Pearson correlation coefficient was also computed to assess the linear relationship between CS and TMC and CS and CSE. There was a positive correlation between CS and TMC, r(96) = 0.290, P = .004 and CS and CSE, r(93) = 0.245, P = .018.

Conclusions: Georgia State University (GSU) RT program is diverse and substantially female. The GSU derived CS had a positive correlation and was statistically significant between TEAS, PGPA, TMC and CSE. These finds suggests that CS is useful in selecting prospective RT students.