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At least 307 records · Page 17Linked to original sources
PubMed1992

From novice to expert: the use of intuitive knowledge as a basis for district nurse education.

Curriculum development in nursing should be a dynamic process set within a context which unites theory and practice. Nursing is operating within a climate of ubiquitous change and reliance must be placed upon a robust and professionally enhancing curriculum framework. At the University of Liverpool, the recently validated Diploma in District Nursing has been based upon the work of Patricia Benner 'From Novice to Expert' (1984). Benner's proposals are gaining considerable international credence and, whilst acknowledging that North American models are not always readily transferable into practice within the United Kingdom, the author explains why the combination of skills acquisition and clinical expertise provide an exciting framework pertinent to post registration courses such as district nursing. Those limitations of interpretation derived from culture and the institutional settings of the research are identified. The article which follows explains the reasons which underpin the adaptation of Benner's model to the education and practice of district nursing, identifies the advantages and limitations and concludes by describing how the educational change process was managed to support practice.

Clinical Competence↗
PubMedDate not supplied

A versatile, inexpensive, intuitive and simple system for computer-assisted instruction in radiology.

A system for constructing courseware in Radiology is described. It uses widely available, inexpensive hardware and software to produce material that is versatile and easy to use. The computer-naive student readily interacts with both text and images. We briefly describe the hardware, the software, the development process, and the different prototype applications developed at this time.

Computer Graphics↗
PubMed2006

Intuitive interference in quantitative reasoning.

It is well known that surface features of a task can queue multiple reasoning strategies. Interference or conflict among the strategies is signaled by increasing reaction times and error rates. To determine the neural basis of this interference, we studied 14 volunteers using event-related fMRI, as they compared the perimeters of geometrical shapes in congruent (where the shapes' perimeter changed in the same direction as its area) and incongruent (where the shapes' perimeter was conserved but its area changed) conditions. We found evidence for the engagement of bilateral parietal lobe systems during congruent trials and incorrect incongruent trials. Activation of bilateral orbital frontal cortex was evident when subjects inhibited interference associated with processing the salient feature 'area' and correctly completed the perimeters in the incongruent condition. Varying the level of interference exerted by the unattended feature 'area' (filled vs. unfilled shapes) affected the relative level of activation of right parietal regions but not orbital frontal cortex suggesting that the former is responding to the degree of facilitation while the latter is responsive to the presence of conflict (rather than the degree of conflict).

Adult↗
PubMed2000

An intuitive formulation for the reproductive number for the spread of diseases in heterogeneous populations.

The thresholds for mathematical epidemiology models specify the critical conditions for an epidemic to grow or die out. The reproductive number can provide significant insight into the transmission dynamics of a disease and can guide strategies to control its spread. We define the mean number of contacts, the mean duration of infection, and the mean transmission probability appropriately for certain epidemiological models, and construct a simplified formulation of the reproductive number as the product of these quantities. When the spread of the epidemic depends strongly upon the heterogeneity of the populations, the epidemiological models must account for this heterogeneity, and the expressions for the reproductive number become correspondingly more complex. We formulate several models with different heterogeneous structures and demonstrate how to define the mean quantities for an explicit expression for the reproductive number. In complex heterogeneous models, it seems necessary to define the reproductive number for each structured subgroup or cohort and then use the average of these reproductive numbers weighted by their heterogeneity to estimate the reproductive number for the total population.

Disease Outbreaks↗
PubMed2002

Number needed to treat: easily understood and intuitively meaningful? Theoretical considerations and a randomized trial.

Graphic representation was used to explore to what extent the number needed to treat (NNT) conveys the appropriate notion of benefit for the individual patient in interventions aimed at delaying adverse events. A sample of the Danish population (n = 675) was interviewed face to face, and asked whether they would consent to a hypothetical drug that reduces the risk of heart attack. The benefit of the drug was expressed in terms of NNT and was randomly set at 10, 25, 50, 100, 200, and 400. NNT does not convey information on the proportion of patients being helped by an intervention or the size of the delay of the adverse event intended to be prevented. The proportion of people consenting to the hypothetical drug was about 80%, irrespective of NNT, and some of those who rejected the drug misinterpreted the meaning of NNT. Lay people may have difficulties in understanding the meaning of NNT, and clinicians may do well to use the NNT with caution until more is known about how patients comprehend it.

Adult↗
PubMedDate not supplied

The likelihood approach to compare populations: a study on DNA evidence and pitfalls of intuitions.

The paper follows on from earlier work [Taroni F and Aitken CGG. Probabilistic reasoning in the law, Part 1: assessment of probabilities and explanation of the value of DNA evidence. Science & Justice 1998; 38: 165-177]. Different explanations of the value of DNA evidence were presented to students from two schools of forensic science and to members of fifteen laboratories all around the world. The responses were divided into two groups; those which came from a school or laboratory identified as Bayesian and those which came from a school or laboratory identified as non-Bayesian. The paper analyses these responses using a likelihood approach. This approach is more consistent with a Bayesian analysis than one based on a frequentist approach, as was reported by Taroni F and Aitken CGG. [Probabilistic reasoning in the law, Part 1: assessment of probabilities and explanation of the value of DNA evidence] in Science & Justice 1998.

Bayes Theorem↗
PubMedDate not supplied

R-NN curves: an intuitive approach to outlier detection using a distance based method.

Libraries of chemical structures are used in a variety of cheminformatics tasks such as virtual screening and QSAR modeling and are generally characterized using molecular descriptors. When working with libraries it is useful to understand the distribution of compounds in the space defined by a set of descriptors. We present a simple approach to the analysis of the spatial distribution of the compounds in a library in general and outlier detection in particular based on counts of neighbors within a series of increasing radii. The resultant curves, termed R-NN curves, appear to follow a logistic model for any given descriptor space, which we justify theoretically for the 2D case. The method can be applied to data sets of arbitrary dimensions. The R-NN curves provide a visual method to easily detect compounds lying in a sparse region of a given descriptor space. We also present a method to numerically characterize the R-NN curves thus allowing identification of outliers in a single plot.

Journal Article↗
PubMed2003

Simple, intuitive calculations of free energy of binding for protein-ligand complexes. 2. Computational titration and pH effects in molecular models of neuraminidase-inhibitor complexes.

One factor that can strongly influence predicted free energy of binding is the ionization state of functional groups on the ligands and at the binding site at which calculations are performed. This analysis is seldom performed except in very detailed computational simulations. In this work, we address the issues of (i) modeling the complexity resulting from the different ionization states of ligand and protein residues involved in binding, (ii) if, and how, computational methods can evaluate the pH dependence of ligand inhibition constants, and (iii) how to score the protonation-dependent models. We developed a new and fairly rapid protocol called "computational titration" that enables parallel modeling of multiple ionization ensembles for each distinct protonation level. Models for possible protonation combinations for site/ligand ionizable groups are built, and the free energy of interaction for each of them is quantified by the HINT (Hydropathic INTeractions) software. We applied this procedure to the evaluation of the binding affinity of nine inhibitors (six derived from 2,3-didehydro-2-deoxy-N-acetylneuraminic acid, DANA) of influenza virus neuraminidase (NA), a surface glycoprotein essential for virus replication and thus a pharmaceutically relevant target for the design of anti-influenza drugs. The three-dimensional structures of the NA enzyme-inhibitor complexes indicate considerable complexity as the ligand-protein recognition site contains several ionizable moieties. Each computational titration experiment reveals a peak HINT score as a function of added protons. This maximum HINT score indicates the optimum pH (or the optimum protonation state of each inhibitor-protein binding site) for binding. The pH at which inhibition is measured and/or crystals were grown and analyzed can vary from this optimum. A protonation model is proposed for each ligand that reconciles the experimental complex structure with measured inhibition and the free energy of binding. Computational titration methods allow us to analyze the effect of pH in silico and may be helpful in improving ligand binding free energy prediction when protonation or deprotonation of the residues or ligand functional groups at the binding site might be significant.

Algorithms↗