Use of focus group technique to investigate infection control practice

Use of focus groups as a technique of inquiry is gaining attention in the area of health-care research. This paper will report on the technique of focus group interviewing to investigate the role of the infection control practitioner. Infection control is examined as a specialty area of health-care practice that has received little research attention to date. Additionally, it is an area of practice that is expanding in response to social, economic and microbiological forces. The focus group technique in this study helped a group of infection control practitioners from urban, regional and rural areas throughout Queensland identify and categorise their daily work activities. The outcomes of this process were then analysed to identify the growth in breadth and complexity of the role of the infection control practitioner in the contemporary health-care environment. Findings indicate that the role of the infection control practitioner in Australia has undergone changes consistent with and reflecting changing models of health-care delivery.

Credentialing the infection control practitioner

The following proposal is submitted by the AICA's credentialling and certification subcommittee for your consideration. It outlines a process and procedure for interim credentialling of infection control practitioners. In submitting this proposal, the subcommittee acknowledges that, while competency-based education is the preferred process for credentialling, there are clinicians who, in the absence of educational opportunities, have developed a specialist level of competency in infection control practice through self education and experience. Committee members also recognise the need for self-regulation of accrediting processes, to maintain standards in practice and support members in their clinical roles. We ask you to review the following proposal and invite your comments and critique, to be received by the last week in January 1998.

The importance of mosquito behavioural adaptations to malaria control in Africa

Over the past decade the use of long-lasting insecticidal nets (LLINs), in combination with improved drug therapies, indoor residual spraying (IRS) and better health infrastructure, has helped reduce malaria in many African countries for the first time in a generation. However, insecticide resistance in the vector is an evolving threat to these gains. We review emerging and historical data on behavioural resistance in response to LLINs and IRS. Overall the current literature suggests behavioural and species changes may be emerging, but the data are sparse and, at times unconvincing. However, preliminary modelling has demonstrated that behavioural resistance could have significant impacts on the effectiveness of malaria control. We propose seven recommendations to improve understanding of resistance in malaria vectors. Determining the public health impact of physiological and behavioural insecticide resistance is an urgent priority if we are to maintain the significant gains made in reducing malaria morbidity and mortality.

Key priorities for Australian infection control : summary of findings from the launch of the Centre for Research Excellence in Reducing Healthcare Associated Infections

The launch of the Centre of Research Excellence in Reducing Healthcare Associated Infection (CRE-RHAI) took place in Sydney on Friday 12 October 2012. The mission of the CRE-RHAI is to generate new knowledge about strategies to reduce healthcare associated infections and to provide data on the cost-effectiveness of infection control programs. As well as launching the CRE-RHAI, an important part of this event was a stakeholder Consultation Workshop, which brought together several experts in the Australian infection control community. The aims of this workshop were to establish the research and clinical priorities in Australian infection control, assess the importance of various multi-resistant organisms, and to gather information about decision making in infection control. We present here a summary and discussion of the responses we received.

Effects of type 2 diabetes behavioural telehealth interventions on glycaemic control and adherence : a systematic review

We reviewed the effect of behavioural telehealth interventions on glycaemic control and diabetes self-management in patients with type 2 diabetes. The databases CINAHL, Medline and psychINFO were searched in August 2012. Journal articles were selected that had been published in English with a randomized controlled trial design using a usual care comparison group, and in which the primary intervention component was delivered by telehealth. Relevant outcome measures were glycaemic control and one or more of the following diabetes self-care areas: diet, physical activity, blood glucose self-monitoring (BGSM) or medication adherence. Interventions were excluded if they were primarily based on telemonitoring. The search retrieved 1027 articles, from which 49 were selected based on their title and abstract. Fourteen articles (reporting 13 studies) met the eligibility criteria for inclusion. Four studies reported significant improvements in glycaemic control. Five of eight studies on dietary adherence reported significant treatment effects, as did five of eight on physical activity, four of nine on blood glucose self-monitoring, and three of eight on medication adherence. Overall, behavioural telehealth interventions show promise in improving the diabetes self-care and glycaemic control of people with type 2 diabetes.

Identification of evidence-based biospecimen quality-control tools

Control of biospecimen quality that is linked to processing is one of the goals of biospecimen science. Consensus is lacking, however, regarding optimal sample quality-control (QC) tools (ie, markers and assays). The aim of this review was to identify QC tools, both for fluid and solid-tissue samples, based on a comprehensive and critical literature review. The most readily applicable tools are those with a known threshold for the preanalytical variation and a known reference range for the QC analyte. Only a few meaningful markers were identified that meet these criteria, such as CD40L for assessing serum exposure at high temperatures and VEGF for assessing serum freeze-thawing. To fully assess biospecimen quality, multiple QC markers are needed. Here we present the most promising biospecimen QC tools that were identified.

A New DER coordination in LV network based on the concept of distributed control

Given the paradigm of smart grid as the promising backbone for future network, this paper uses this paradigm to propose a new coordination approach for LV network based on distributed control algorithm. This approach divides the LV network into hierarchical communities where each community is controlled by a control agent. Different level of communication has been proposed for this structure to control the network in different operation modes.

Rule-based transit signal priority control method using a real-time transit travel time prediction model

An advanced rule-based Transit Signal Priority (TSP) control method is presented in this paper. An on-line transit travel time prediction model is the key component of the proposed method, which enables the selection of the most appropriate TSP plans for the prevailing traffic and transit condition. The new method also adopts a priority plan re-development feature that enables modifying or even switching the already implemented priority plan to accommodate changes in the traffic conditions. The proposed method utilizes conventional green extension and red truncation strategies and also two new strategies including green truncation and queue clearance. The new method is evaluated against a typical active TSP strategy and also the base case scenario assuming no TSP control in microsimulation. The evaluation results indicate that the proposed method can produce significant benefits in reducing the bus delay time and improving the service regularity with negligible adverse impacts on the non-transit street traffic.

An intervention study to improve pain management by nurses : normative beliefs and perceived control

Based on a predictive model of nurses' intentions regarding pain management, an intervention was developed to improve nurses' pain management. The intervention involved a series of workshops with cohorts of nurses working in acute care wards to address the important antecedents to their intentions: normative beliefs and perceived control. Pre- and post-intervention measures demonstrate the effectiveness of the intervention. The effectiveness of this intervention in improving the management of patients' pain is compared with a patient education program group and a control group. The findings provide support for further developing interventions based on the theory of planned behavior.

Effect of attitudes, subjective norms and perceived control on nurses' intention to assess patients' pain

This study examines the underlying determinants of nurses' behaviour regarding the conduct of pain assessments. One hundred nurses in a variety of health care facilities were invited to complete an Attitude Intention Questionnaire based upon the theory of planned action which is an extension of the theory of reasoned action. Results provide some support for the theory of planned action, as nurses' intention to conduct pain assessment was shown to be predicted by attitude, subjective norms and perceived control, although the latter was the only variable to make an independent contribution to intention. Additional support for the importance of perceived control was provided by the analysis of 'intenders' and 'non-intenders' (to conduct pain assessments), as perceived control was the only variable which differed significantly between the groups. The findings are consistent with earlier studies which showed that the variables in the theory of planned behaviour provided reasonably accurate predictions of behavioural intention.

A reliable real-time transport protocol for control systems over wireless networks

Deploying networked control systems (NCSs) over wireless networks is becoming more and more popular. However, the widely-used transport layer protocols, Transmission Control Protocol (TCP) and User Datagram Protocol (UDP), are not designed for real-time applications. Therefore, they may not be suitable for many NCS application scenarios because of their limitations on reliability and/or delay performance, which real-control systems concern. Considering a typical type of NCSs with periodic and sporadic real-time traffic, this paper proposes a highly reliable transport layer protocol featuring a packet loss-sensitive retransmission mechanism and a prioritized transmission mechanism. The packet loss-sensitive retransmission mechanism is designed to improve the reliability of all traffic flows. And the prioritized transmission mechanism offers differentiated services for periodic and sporadic flows. Simulation results show that the proposed protocol has better reliability than UDP and improved delay performance than TCP over wireless networks, particularly when channel errors and congestions occur.

Active and reactive power control of synchronous generator for the realization of a virtual power plant

This paper presents a novel power control strategy that decouples the active and reactive power for a synchronous generator connected to a power network. The proposed control paradigm considers the capacitance of the transmission line along with its resistance and reactance as-well. Moreover the proposed controller takes into account all cases of R-X relationships, thus allowing it to function in Virtual Power Plant (VPP) structures which operate at both medium voltage (MV) and low voltage (LV) levels. The independent control of active and reactive power is achieved through rotational transformations of the terminal voltages and currents at the synchronous generator's output. This paper details the control technique by first presenting the mathematical and electrical network analysis of the methodology and then successfully implementing the control using MATLAB-SIMULINK simulation.

Adaptive stepsize based on control theory for stochastic differential equations

The numerical solution of stochastic differential equations (SDEs) has been focused recently on the development of numerical methods with good stability and order properties. These numerical implementations have been made with fixed stepsize, but there are many situations when a fixed stepsize is not appropriate. In the numerical solution of ordinary differential equations, much work has been carried out on developing robust implementation techniques using variable stepsize. It has been necessary, in the deterministic case, to consider the "best" choice for an initial stepsize, as well as developing effective strategies for stepsize control-the same, of course, must be carried out in the stochastic case. In this paper, proportional integral (PI) control is applied to a variable stepsize implementation of an embedded pair of stochastic Runge-Kutta methods used to obtain numerical solutions of nonstiff SDEs. For stiff SDEs, the embedded pair of the balanced Milstein and balanced implicit method is implemented in variable stepsize mode using a predictive controller for the stepsize change. The extension of these stepsize controllers from a digital filter theory point of view via PI with derivative (PID) control will also be implemented. The implementations show the improvement in efficiency that can be attained when using these control theory approaches compared with the regular stepsize change strategy.

Locally weighted learning model predictivek control for elastic joint robots

This paper proposes an efficient and online learning control system that uses the successful Model Predictive Control (MPC) method in a model based locally weighted learning framework. The new approach named Locally Weighted Learning Model Predictive Control (LWL-MPC) has been proposed as a solution to learn to control complex and nonlinear Elastic Joint Robots (EJR). Elastic Joint Robots are generally difficult to learn to control due to their elastic properties preventing standard model learning techniques from being used, such as learning computed torque control. This paper demonstrates the capability of LWL-MPC to perform online and incremental learning while controlling the joint positions of a real three Degree of Freedom (DoF) EJR. An experiment on a real EJR is presented and LWL-MPC is shown to successfully learn to control the system to follow two different figure of eight trajectories.