The development of the physicians' end-of-life care attitude scale

The Physicians' End-of-Life Care Attitude Scale (PEAS) was developed as an outcome measure for palliative care education. PEAS assesses the willingness of medical trainees to care for dying patients. Sixty-four Likert-type questions were created on the basis of discussions with focus groups of medical trainees, then administered to sixty-two medical students and residents. Total PEAS scores as well as personal preparation and professional role subscales (where higher scores indicated greater concern) possessed excellent internal consistency and reliability. In addition, there were substantial correlations between PEAS scores and the CA-Dying scale, a measurement of laypersons' fears about interacting with dying persons. Thus, PEAS adequately assesses the unique communication concerns of physicians in training regarding working with dying persons and their families. Correlations between PEAS scores and age were negative, while those who had experienced the death of a loved one had higher PEAS scores than those who did not. This suggests that for some persons, life experiences may lessen difficulties in dealing with dying persons, while for others, personal losses may exacerbate such concerns. The utility of PEAS in evaluating the efficacy of palliative care education as well as its potential to measure medical trainee's willingness to care for the terminally ill is discussed.     

Clive's Kids: An Employment Scheme for Unemployable Youth

In eighteen months, one man with a second-hand utility, two worn lawn mowers, community and employer support, resulted in over sixty-eight ‘unemployable’ youth entering the workforce on a permanent basis. Clive's program is unique to Australia. (It was considered that anonymity should be maintained because adverse publicity resulted in youth programs in the area being closely scrutinized regarding participants ‘working’ and earning money.—Ed.)     

How planning and capital budgeting improve SME performance

This paper focuses on the use of strategic planning among small and medium sized enterprises (SMEs) in the UK manufacturing sector. It analyses the relationship between the intensity of strategic planning, business objectives, perceived performance, changes in the business environment and the use of capital budgeting techniques. Capital budgeting is of particular interest as an area of investigation, and is one which has seldom featured in previous studies of strategic planning behaviour. These issues were investigated via a survey of UK manufacturing SMEs carried out in the winter of 1996/97.

The key results suggest that SMEs incorporate a range of objectives into their strategic planning process, with profit improvement perceived to be the most important objective, followed by sales growth. SMEs engaged in detailed strategic planning are more likely to use formal capital budgeting techniques, including the net present value method, which is consistent with maximising the companys' value. Perceived profitability and success in achieving organisational objectives were positively associated with planning detail, suggesting that strategic planning is a key component improving performance. Planning detail was also associated with a significantly higher level of perceived change in the business environment.     

Contraception and the medical profession

Birth control practice is to-day regarded by a substantial and influential majority of doctors as an important element in preventive medicine and the provision of contraceptive advice an appropriate activity for the medical practitioner. This viewpoint is, however, a product of the last forty years and its adoption represents one of the major achievements of the English birth control movement whose past activities have been as much impeded by the hostility of the medical profession as by the opposition of religious groups and the indifference of public opinion.     

Variable precision rough set theory and data discretisation: an application to corporate failure prediction

Since the seminal work of Pawlak (International Journal of Information and Computer Science, 11 (1982) 341–356) rough set theory (RST) has evolved into a rule-based decision-making technique. To date, however, relatively little empirical research has been conducted on the efficacy of the rough set approach in the context of business and finance applications. This paper extends previous research by employing a development of RST, namely the variable precision rough sets (VPRS) model, in an experiment to predict between failed and non-failed UK companies. It also utilizes the FUSINTER discretisation method which neglates the influence of an ‘expert’ opinion. The results of the VPRS analysis are compared to those generated by the classical logit and multivariate discriminant analysis, together with more closely related non-parametric decision tree methods. It is concluded that VPRS is a promising addition to existing methods in that it is a practical tool, which generates explicit probabilistic rules from a given information system, with the rules offering the decision maker informative insights into classification problems.     

Robust mixture modelling using the t distribution

Normal mixture models are being increasingly used to model the distributions of a wide variety of random phenomena and to cluster sets of continuous multivariate data. However, for a set of data containing a group or groups of observations with longer than normal tails or atypical observations, the use of normal components may unduly affect the fit of the mixture model. In this paper, we consider a more robust approach by modelling the data by a mixture of t distributions. The use of the ECM algorithm to fit this t mixture model is described and examples of its use are given in the context of clustering multivariate data in the presence of atypical observations in the form of background noise.     

Modelling Political Popularity: an Analysis of Long-range Dependence in Opinion Poll Series

A simple model of political popularity, as recorded by opinion polls of voting intentions, is proposed. We show that, as a consequence of aggregating heterogeneous poll responses under certain assumptions about the evolution of individual opinions, the time series of poll data should exhibit long memory characteristics. In an analysis of the monthly Gallup data on party support in the UK, we confirm that the series have long memory and further show them to be virtually pure 'fractional noise' processes. An explanation of the latter result is offered. We study the role of economic indicators in predicting swings in support, perform event analyses and use our estimates to generate post-sample forecasts to April 1997.     

Modelling political popularity: a correction

Summary. The paper supplies a missing step in the aggregation argument that was used in our 1997 paper in this journal. We show that monthly poll data representing the average of a sample of voter preferences, evolving in different ways in the face of new information, should follow a fractionally integrated process.     

The political business cycle— have we seen the end of it?

This article is concerned to explain why governments have been reluctant to restrict the expansion of the money supply as a control on inflation. The author argues that future governments should be concerned to reduce monetary expansion at the cost of conflict over the level and distribution of government expenditure and tax revenues and the form of monetary stabilization.