Clinical environment : a source of stress for undergraduate nurses

The clinical area is an important learning environment for undergraduate nursing students. Unfortunately, it can also be a source of significant stress and anxiety for students and there are a number of reasons for this. Much can be done to help alleviate this stress and create a positive learning environment for students. This paper explores the literature to ascertain the common sources of stress for undergraduate students in the clinical area. It also reviews strategies for improving the quality of the learning experience.<br /

Robust M-ary detection filters and smoothers for continuous-time jump Markov systems

In this paper, we consider a dynamic M-ary detection problem when Markov chains are observed through a Wiener process. These systems are fully specified by a candidate set of parameters, whose elements are, a rate matrix for the Markov chain and a parameter for the observation model. Further, we suppose these parameter sets can switch according to the state of an unobserved Markov chain and thereby produce an observation process generated by time varying (jump stochastic) parameter sets. Given such an observation process and a specified collection of models, we estimate the probabilities of each model parameter set explaining the observation. By defining a new augmented state process, then applying the method of reference probability, we compute matrix-valued dynamics, whose solutions estimate joint probabilities for all combinations of candidate model parameter sets and values taken by the indirectly observed state process. These matrix-valued dynamics satisfy a stochastic integral equation with a Wiener process integrator. Using the gauge transformation techniques introduced by Clark and a pointwise matrix product, we compute robust matrix-valued dynamics for the joint probabilities on the augmented state space. In these new dynamics, the observation Wiener process appears as a parameter matrix in a linear ordinary differential equation, rather than an integrator in a stochastic integral equation. It is shown that these robust dynamics, when discretised, enjoy a deterministic upper bound which ensures nonnegative probabilities for any observation sample path. In contrast, no such upper bounds can be computed for Taylor expansion approximations, such as the Euler-Maryauana and Milstein schemes. Finally, by exploiting a duality between causal and anticausal robust detector dynamics, we develop an algorithm to compute smoothed mode probability estimates without stochastic integrations. A computer simulation demonstrating performance is included.Robert J. Elliott and W. P. Malcol

Confirming the position of a nasogastric tube what does the literature say?

Nasogastric tubes are a medical device that can be used for a number of purposes. The process of inserting them however can be complicated. Nurses must therefore use an evidence based approach to confirm the correct position of nasogastric tubes and there are three main techniques described in the literature to do so. To date, one group of authors has published the majority of the studies on these techniques. This paper reviews their work. <br /

Use of medical orders in acute care oxygen therapy

The life of every living organism is sustained by the presence of oxygen and the acute deprivation of oxygen will, therefore, result in hypoxia and ultimately death. Although oxygen is normally present in the air, higher concentrations are required to treat many disease processes. Oxygen is therefore considered to be a drug requiring a medical prescription and is subject to any law that covers its use and prescription. Administration is typically authorized by a physician following legal written instructions to a qualified nurse. This standard procedure helps prevent incidence of misuse or oxygen deprivation which could worsen the patients hypoxia and ultimate outcome. Delaying the administration of oxygen until a written medical prescription is obtained could also have the same effect. Clearly, defined protocols should exist to allow for the legal administration of oxygen by nurses without a physicians order because any delay in administering oxygen to patients can very well lead to their death.<br /

Risk-sensitive filtering and smoothing for continuous-time Markov processes

© 2005 IEEE.We consider risk sensitive filtering and smoothing for a dynamical system whose output is a vector process in 2. The components of the observation process are a Markov process observed through a Brownian motion and a Markov process observed through a Poisson process. Risk-sensitive filters for the robust estimation of an indirectly observed Markov state processes are given. These filters are stochastic partial differential equations for which robust discretizations are obtained. Computer simulations are given which demonstrate the benefits of risk sensitive filtering.W. Paul Malcolm, Robert J. Elliott, and Matthew R. James

A deterministic discretisation-step upper bound for state estimation via Clark transformations

Copyright © 2004 Hindawi Publishing CorporationWe consider the numerical stability of discretisation schemes for continuous-time state estimation filters. The dynamical systems we consider model the indirect observation of a continuous-time Markov chain. Two candidate observation models are studied. These models are (a) the observation of the state through a Brownian motion, and (b) the observation of the state through a Poisson process. It is shown that for robust filters (via Clark's transformation), one can ensure nonnegative estimated probabilities by choosing a maximum grid step to be no greater than a given bound. The importance of this result is that one can choose an a priori grid step maximum ensuring nonnegative estimated probabilities. In contrast, no such upper bound is available for the standard approximation schemes. Further, this upper bound also applies to the corresponding robust smoothing scheme, in turn ensuring stability for smoothed state estimates.W. P. Malcolm, R. J. Elliott, and J. van der Hoe

Exploring the response to diversity and equality in English prisons

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