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Successful Modeling of Factors Related to Recruitment and Retention of Prenursing Students
Jo-Ann Stankus1, Mark Hamner, Michael Stankey
1Author Affiliations: Coordinator, RN BS/MS Program, and Assistant Professor (Dr Stankus), College of Nursing; Associate Provost of Institutional Research & Improvement (Dr Hamner); Director of Analytics (Dr Stankey); and Associate Dean for Research and Clinical Scholarship/Professor (Dr Mancuso), College of Nursing, Texas Woman's University, Denton.
Background:
The traditional admission methodology used by many schools of nursing is the second-tier admission based on specified criteria. This method has been associated with a student body that is predominately female, white, and English speaking.
Problem:
Rational judgment modeling (points assigned to criteria) used to evaluate applicants for admission into prenursing programs potentially overlooks students who do not fit into the traditional model.
Approach:
This study compared predictive logistic regression with traditional rational judgment models to classify potential nursing school applicants.
Outcomes:
A higher number of Hispanic and black prenursing students were identified for potential upper-level nursing program admission.
Conclusions:
The use of logistic regression modeling can identify a more diverse student population. Advisors at both high school and university/college levels can use results of this model to help students determine their progress, identify academic weaknesses, and develop individual plans of action to help students successfully complete the prenursing curriculum requirements.
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