Predicting Successful Progression of Nursing Students: Differences Between Associate and Baccalaureate Programs

2.50
Hdl Handle:
http://hdl.handle.net/10755/156411
Type:
Presentation
Title:
Predicting Successful Progression of Nursing Students: Differences Between Associate and Baccalaureate Programs
Abstract:
Predicting Successful Progression of Nursing Students: Differences Between Associate and Baccalaureate Programs
Conference Sponsor:Sigma Theta Tau International
Conference Year:2006
Author:Curl, Eileen Deges, PhD, ARNP-CNS
P.I. Institution Name:Lamar University
Title:Chairperson, Dept. of Nursing
Co-Authors:Gina Hale, MSN, RN
Predicting nursing students? progression in school is critical to graduating the most students possible. Due to the nursing shortage, predictors of success were explored for associate (ADN) and baccalaureate (BSN) students admitted to a southern USA university in Fall 2003 and 2004. The indicators examined included cumulative grade point average (GPA), science pre-requisite GPA, pre-requisite credit hours taken at the university, and the HESI Admission AssessmentTM (A2) exam. Stepwise regression analysis was used to identify the best predictors for the first two semesters of both programs, when the attrition rate is the highest.   For ADN students (N = 75), the best predictor of success for foundations, health assessment, pathophysiology, and the first two medical-surgical courses was the A2 cumulative score (R2 range .32 to .52). The second predictor was students? cumulative GPA, except for pathophysiology where science GPA was the second predictor. For the pharmacology course, the best predictor was students? science GPA, followed by the A2 cumulative score. Of the A2 scores, reading was most predictive of success in foundations, health assessment and pharmacology. A2 anatomy/physiology scores were predictive for pathophysiology and the first medical-surgical course, while vocabulary was predictive for the second medical-surgical course. For the BSN students (N = 166), the best predictor for fundamentals and the medical-surgical course was the A2 cumulative score (R2 .37 & .12). The second predictor for fundamentals was the cumulative GPA, while there was no second predictor for the medical-surgical course. The science GPA was most predictive for pharmacology, and for pathophysiology it was cumulative GPA. Of the A2 scores, vocabulary was most predictive for fundamentals, and grammar was most predictive for the medical-surgical course.  The results have implications for admission selection criteria in ADN and BSN programs. Using predictive admission indicators may increase the number of graduates entering the workforce.
Repository Posting Date:
26-Oct-2011
Date of Publication:
17-Oct-2011
Sponsors:
Sigma Theta Tau International

Full metadata record

DC FieldValue Language
dc.typePresentationen_GB
dc.titlePredicting Successful Progression of Nursing Students: Differences Between Associate and Baccalaureate Programsen_GB
dc.identifier.urihttp://hdl.handle.net/10755/156411-
dc.description.abstract<table><tr><td colspan="2" class="item-title">Predicting Successful Progression of Nursing Students: Differences Between Associate and Baccalaureate Programs</td></tr><tr class="item-sponsor"><td class="label">Conference Sponsor:</td><td class="value">Sigma Theta Tau International</td></tr><tr class="item-year"><td class="label">Conference Year:</td><td class="value">2006</td></tr><tr class="item-author"><td class="label">Author:</td><td class="value">Curl, Eileen Deges, PhD, ARNP-CNS</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">Lamar University</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">Chairperson, Dept. of Nursing</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">eileen.curl@lamar.edu</td></tr><tr class="item-co-authors"><td class="label">Co-Authors:</td><td class="value">Gina Hale, MSN, RN</td></tr><tr><td colspan="2" class="item-abstract">Predicting nursing students? progression in school is critical to graduating the most students possible. Due to the nursing shortage, predictors of success were explored for associate (ADN) and baccalaureate (BSN) students admitted to a southern USA university in Fall 2003 and 2004. The indicators examined included cumulative grade point average (GPA), science pre-requisite GPA, pre-requisite credit hours taken at the university, and the HESI Admission AssessmentTM (A2) exam. Stepwise regression analysis was used to identify the best predictors for the first two semesters of both programs, when the attrition rate is the highest. &nbsp; For ADN students (N = 75), the best predictor of success for foundations, health assessment, pathophysiology, and the first two medical-surgical courses was the A2 cumulative score (R2 range .32 to .52). The second predictor was students? cumulative GPA, except for pathophysiology where science GPA was the second predictor. For the pharmacology course, the best predictor was students? science GPA, followed by the A2 cumulative score. Of the A2 scores, reading was most predictive of success in foundations, health assessment and pharmacology. A2 anatomy/physiology scores were predictive for pathophysiology and the first medical-surgical course, while vocabulary was predictive for the second medical-surgical course. For the BSN students (N = 166), the best predictor for fundamentals and the medical-surgical course was the A2 cumulative score (R2 .37 &amp; .12). The second predictor for fundamentals was the cumulative GPA, while there was no second predictor for the medical-surgical course. The science GPA was most predictive for pharmacology, and for pathophysiology it was cumulative GPA. Of the A2 scores, vocabulary was most predictive for fundamentals, and grammar was most predictive for the medical-surgical course.&nbsp; The results have implications for admission selection criteria in ADN and BSN programs. Using predictive admission indicators may increase the number of graduates entering the workforce.</td></tr></table>en_GB
dc.date.available2011-10-26T14:45:23Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T14:45:23Z-
dc.description.sponsorshipSigma Theta Tau Internationalen_GB
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