Predicting nursing turnover with catastrophe theory

Journal of Advanced Nursing
Cheryl M Wagner

Abstract

This paper is a report of a study comparing an innovative nonlinear model and a traditional linear model for accuracy in prediction of nursing turnover. An international, sustained nursing shortage creates a need to target accurately the staff population at risk for turnover. Existing linear methodology is cumbersome with the number of variables needed, while producing inadequate results. Nonlinear modelling methods offer increased simplicity and accuracy in predictability. A correlational survey with a longitudinal cohort prospective study was carried out in 2005-2006 with a convenience sample of 1033 Registered Nurses from the Midwest region of the United States of America. At time 1, 756 usable questionnaires were returned and 496 at time 2. Data analysis included analyses of a cusp catastrophe model, a cube-shaped four-dimensional figure with a top that provided a down-turning slope area (the catastrophe/cusp zone). This fluid, dynamic cusp version employed the smallest number of control and dependent variables. The exceedingly small turnover sample preempted the use of the computerized program Cuspfit; a proven quasi-quantitative methodology demonstrated 80.4% predictability in the cusp catastrophe model overall and 53.6% ...Continue Reading

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Citations

Aug 10, 2013·International Journal of Nursing Studies·Lina Daouk-ÖyryIbrahim Osman
Nov 29, 2011·Journal of Advanced Nursing·Carol Hall Ellenbecker, Margaret Cushman
Oct 14, 2017·International Journal of Environmental Research and Public Health·Ding-Geng Chen, Xinguang Chen
Aug 5, 2014·Research and Theory for Nursing Practice·Joseph OsujiMohammed El-Hussein

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