IDENTIFICATION OF PRE-ADMISSION CRITERIA PREDICTIVE OF SUCCESS IN GRADUATE NURSE ANESTHESIOLOGY PROGRAMS.
Contributors: State University of New York at Albany.
Published: 1995
Number of pages: 94
Subjects: Education, Higher.; Health Sciences, Nursing.; Health Sciences, Education.
Description: The purpose of this study was to determine the feasibility of identifying admission criteria that could predict success in a graduate nurse anesthesiology program and on the Council on Certification's National Certifying Examination. The study population was comprised of forty-three percent of the first time exam takers who took and passed the December, 1992 certifying examination. Thirty-one point five percent were males and sixty-eight point five percent were females.

Survey letters were sent to all accredited nurse anesthesia programs (n = 85) requesting the following information: AANA ID #, age, gender, years of clinical experience, undergraduate GPA, and graduate GPA. Nursing educational background, GRE-Verbal; Quantitative; Analytical; and Total scores, and certification examination scores were obtained from the office of the Council on Certification.

The data were analyzed using descriptive statistics, ANOVA, Pearson's correlation coefficient, and multiple regression analysis. The findings of this study were as follows: there was a positive correlation between GRE-Q, UGPA, and GGPA and certifying examination scores. The study showed that prior achievement in an undergraduate educational program is an important indicator of future achievement in a graduate program and on the certifying examination. It also reinforced the importance of using multiple criteria to make admission decisions. While aggregate GRE scores did not prove to be predictive for this study population, they have been shown to be predictive of achievement in many other fields.
Notes: Source: Dissertation Abstracts International, Volume: 56-05, Section: A, page: 1674.

Thesis (ED.D.)--STATE UNIVERSITY OF NEW YORK AT ALBANY, 1995.

School code: 0668.