Development and pilot test of a peer-support based Cardiac-Diabetes Self-Management program : a study protocol

Background: People with cardiac disease and type 2 diabetes have higher hospital readmission rates (22%)compared to those without diabetes (6%). Self-management is an effective approach to achieve better health outcomes; however there is a lack of specifically designed programs for patients with these dual conditions. This project aims to extend the development and pilot test of a Cardiac-Diabetes Self-Management Program incorporating user-friendly technologies and the preparation of lay personnel to provide follow-up support. Methods/Design: A randomised controlled trial will be used to explore the feasibility and acceptability of the Cardiac-Diabetes Self-Management Program incorporating DVD case studies and trained peers to provide follow-up support by telephone and text-messaging. A total of 30 cardiac patients with type 2 diabetes will be randomised, either to the usual care group, or to the intervention group. Participants in the intervention group will received the Cardiac-Diabetes Self-Management Program in addition to their usual care. The intervention consists of three faceto- face sessions as well as telephone and text-messaging follow up. The face-to-face sessions will be provided by a trained Research Nurse, commencing in the Coronary Care Unit, and continuing after discharge by trained peers. Peers will follow up patients for up to one month after discharge using text messages and telephone support. Data collection will be conducted at baseline (Time 1) and at one month (Time 2). The primary outcomes include self-efficacy, self-care behaviour and knowledge, measured by well established reliable tools. Discussion: This paper presents the study protocol of a randomised controlled trial to pilot evaluates a Cardiac- Diabetes Self-Management program, and the feasibility of incorporating peers in the follow-ups. Results of this study will provide directions for using such mode in delivering a self-management program for patients with both cardiac condition and diabetes. Furthermore, it will provide valuable information of refinement of the intervention program.

HyperCard test engine using Rasch Analysis

This paper will focus on the development of an interactive test engine using Rasch analysis of item responses for question selection and reporting of results. The Rasch analysis is used to determine student ability and question difficulty. This model is widely used in the preparation of paper-based tests and has been the subject of particular use and development at the Australian Council for Education Research (ACER). This paper presents an overview of an interactive implementation of the Rasch analysis model in HyperCard, where student ability estimates are generated 'on the fly' and question difficulty values updated from time to time. The student ability estimates are used to determine question selection and are the basis of scoring and reporting schemes.

Prognostic modelling options for remaining useful life estimation by industry

Over recent years a significant amount of research has been undertaken to develop prognostic models that can be used to predict the remaining useful life of engineering assets. Implementations by industry have only had limited success. By design, models are subject to specific assumptions and approximations, some of which are mathematical, while others relate to practical implementation issues such as the amount of data required to validate and verify a proposed model. Therefore, appropriate model selection for successful practical implementation requires not only a mathematical understanding of each model type, but also an appreciation of how a particular business intends to utilise a model and its outputs. This paper discusses business issues that need to be considered when selecting an appropriate modelling approach for trial. It also presents classification tables and process flow diagrams to assist industry and research personnel select appropriate prognostic models for predicting the remaining useful life of engineering assets within their specific business environment. The paper then explores the strengths and weaknesses of the main prognostics model classes to establish what makes them better suited to certain applications than to others and summarises how each have been applied to engineering prognostics. Consequently, this paper should provide a starting point for young researchers first considering options for remaining useful life prediction. The models described in this paper are Knowledge-based (expert and fuzzy), Life expectancy (stochastic and statistical), Artificial Neural Networks, and Physical models.

Latent degradation indicators estimation and prediction : a Monte Carlo approach

Asset health inspections can produce two types of indicators: (1) direct indicators (e.g. the thickness of a brake pad, and the crack depth on a gear) which directly relate to a failure mechanism; and (2) indirect indicators (e.g. the indicators extracted from vibration signals and oil analysis data) which can only partially reveal a failure mechanism. While direct indicators enable more precise references to asset health condition, they are often more difficult to obtain than indirect indicators. The state space model provides an efficient approach to estimating direct indicators by using indirect indicators. However, existing state space models to estimate direct indicators largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires fixed inspection intervals. The discrete state assumption entails discretising continuous degradation indicators, which often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This paper proposes a state space model without these assumptions. Monte Carlo-based algorithms are developed to estimate the model parameters and the remaining useful life. These algorithms are evaluated for performance using numerical simulations through MATLAB. The result shows that both the parameters and the remaining useful life are estimated accurately. Finally, the new state space model is used to process vibration and crack depth data from an accelerated test of a gearbox. During this application, the new state space model shows a better fitness result than the state space model with linear and Gaussian assumption.

Re-conceiving the good life : the key to sustainable globalisation

Resource-intensive, high-carbon, Western lifestyles are frequently criticised as unsustainable and deeply unsatisfying. However, these lifestyles are still attractive to the majority of Westerners and to a high proportion of the developing world’s middle classes. This paper argues that the imminent threat of catastrophic climate change constitutes an immediate political, economic and ethical challenge for citizens of the developed world that cannot be tackled by appeals to asceticism or restraint. There can be no solution to climate change until sustainable conceptions of the good life are developed that those in the west want to live and which others might want to live. While the ultimate solution to climate change is the development of low carbon lifestyles, it is important that government initiatives, governance arrangements and economic incentives support rather than undermine that search. Like the global financial crisis, the climate change crisis also demonstrates what happens when weaknesses in national, corporate and professional governance are exacerbated by weaknesses in global governance. In tackling the latter, it is critical the mistakes now evidenced in the former are avoided – including a rethinking of carbon market and carbon tax alternatives. It is also critical that individuals must take responsibility for their actions as consumers, voters and investors.

Ending the life of the act/omission dispute: Causation in withholding and withdrawing life-sustaining measures

My aim in this paper is to challenge the increasingly common view in the literature that the law on end of life decision making is in disarray and is in need of urgent reform. My argument is that this assessment of the law is based on assumptions about the relationship between the identity of the defendant and their conduct, and about the nature of causation, which, on examination, prove to be indefensible. I then provide a clarification of the relationship between causation and omissions which proves that the current legal position does not need modification, at least on the grounds that are commonly advanced for the converse view. This enables me, in conclusion, to clarify important conceptual and moral differences between withholding, refusing and withdrawing life-sustaining measures on the one hand, and assisted suicide and euthanasia, on the other.