Search PubMed⌕ Search
Home/Archive/PubMed

PubMed · 10111953

Using fourth-generation evaluation in nursing.

M M Swenson
View original source ↗Export metadata ↓

Abstract

Evaluation is disciplined inquiry undertaken to determine the value, including merit and worth, of some entity: a curriculum program, a clinical intervention, an academic course, a care plan. An evaluation is conducted to improve or refine the thing being evaluated (evaluand) or to assess its impact and effectiveness. Evaluation in nursing has been designed using various positivistic and post-positivistic models in the first three "generations" in the evolution of evaluation practice. This article describes a new model of nursing evaluation more consistent with a nursing paradigm than with a traditional, scientific, medical paradigm. Responsive nursing evaluation informs and empowers all those involved in its outcomes (the stakeholders) when framed within the research stance called naturalistic or constructivist inquiry. The fourth-generation-evaluation approach of Guba and Lincoln (1989) is consistent with a nursing paradigm and a constructivist approach. Fourth-generation evaluation is presented with specific application to nursing evaluation.

Explore related subjects

Models, TheoreticalNursing Evaluation ResearchUnited StatesJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

M M Swenson. 1991. Using fourth-generation evaluation in nursing.. https://doi.org/10.1177/016327879101400105

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2001

Noise-induced dynamics in bistable systems with delay.

Noise-induced dynamics of a prototypical bistable system with delayed feedback is studied theoretically and numerically. For small noise and magnitude of the feedback, the problem is reduced to the analysis of the two-state model with transition rates depending on the earlier state of the system. Analytical solutions for the autocorrelation function and the power spectrum have been found. The power spectrum has a peak at the frequency corresponding to the inverse delay time, whose amplitude has a maximum at a certain noise level, thus demonstrating coherence resonance. The linear response to the external periodic force also has maxima at the frequencies corresponding to the inverse delay time and its harmonics.

Models, Theoretical↗
PubMed2001

Pore-scale modeling of saturated permeabilities in random sphere packings.

We use two pore-scale approaches, lattice-Boltzmann (LB) and pore-network modeling, to simulate single-phase flow in simulated sphere packings that vary in porosity and sphere-size distribution. For both modeling approaches, we determine the size of the representative elementary volume with respect to the permeability. Permeabilities obtained by LB modeling agree well with Rumpf and Gupte's experiments in sphere packings for small Reynolds numbers. The LB simulations agree well with the empirical Ergun equation for intermediate but not for small Reynolds numbers. We suggest a modified form of Ergun's equation to describe both low and intermediate Reynolds number flows. The pore-network simulations agree well with predictions from the effective-medium approximation but underestimate the permeability due to the simplified representation of the porous media. Based on LB simulations in packings with log-normal sphere-size distributions, we suggest a permeability relation with respect to the porosity, as well as the mean and standard deviation of the sphere diameter.

Models, Theoretical↗
PubMed2001

Exploring complex networks.

The study of networks pervades all of science, from neurobiology to statistical physics. The most basic issues are structural: how does one characterize the wiring diagram of a food web or the Internet or the metabolic network of the bacterium Escherichia coli? Are there any unifying principles underlying their topology? From the perspective of nonlinear dynamics, we would also like to understand how an enormous network of interacting dynamical systems-be they neurons, power stations or lasers-will behave collectively, given their individual dynamics and coupling architecture. Researchers are only now beginning to unravel the structure and dynamics of complex networks.

Models, Theoretical↗