The Science Journal of the American Association for Respiratory Care

2009 OPEN FORUM Abstracts

PREDICTING STUDENTS‘ PERFORMANCE ON THE CLINICAL SIMULATION EXAMINATIONS

Arzu Ari, Douglas Gardenhire, Brent Murray, Lynda Goodfellow, Chip Zimmerman; Georgia State University, Atlanta, GA

Background: The success of a respiratory therapy (RT) student is often measured by his or her graduating from a RT program and successfully passing the National Board for Respiratory Care (NBRC) examinations. Although many RT students struggle in passing clinical simulation (CS) examinations given by the NBRC, to date there has been no published research on the predictability of RT students in passing CS examinations. The objective of this study was to determine the factors that are most accurate at predicting a student’s performance for information gathering (IG) and decision making (DM) skills on the CS examinations. Method: A longitudinal database was created including a total of 47 students admitted to a 4-year RT program from 2007 through 2009. Independent variables of this study were the students’ entering- GPA, exit-GPA, and their scores on the clinical examinations in their first and second year in the program. Pearson product-moment correlations and multiple regression analysis at a 0.05 level of significance were utilized for data analysis in this study. Results: Both students’ exit-GPAs and their scores on the clinical exams at the end of their 1st year had a statistically significant positive relationship with their IG skills on the CS examination (p=0.005 and p=0.008, respectively). Also, students’ DM skills had a significant positive relationship with students’ exit-GPAs (p=0.001) and their scores on the clinical exams at the end of their 2nd year in the program (p=0.036). Exit-GPA was the solitary predictor of students’ performance on the CS examinations and had a significant impact on students’ ability to perform IG skills (p=0.007) and DM skills (p=0.008). Multiple regression analysis identified that exit-GPA accounted for 28.2% of the total variance (R2) on students’ IG skills, whereas it was responsible for 27.6% of the total variation on students’ DM skills on the CS examinations. Conclusion: This study determined that a student’s exit-GPA will predict their performance at IG and DM on the CS examination. Also, clinical exams given to students at the end of their clinical rotations of 1st and 2nd year had a positive relationship to the students’ IG and DM skills as determined by CS examinations. Therefore, consideration of these results can be helpful in reenforcing a student’s IG and DM skills in patient management and strengthen their ability to perform well on the CS examinations. Sponsored Research - None

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