Palliative care at home: general practitioners working with palliative care teams

Home care is the preferred option for most people with a terminal illness. Providing home care relies on good community-based services, and a general practice workforce competent in palliative care practice and willing to accommodate patients' needs. Structured palliative care training of general practitioners is needed at undergraduate and postgraduate level, with attention to barriers to teamwork and communication. Good palliative care-can be delivered to patients at home by GPs (supported by specialist palliative care teams) and community nurses, with access to an inpatient facility when required. To optimise patient care, careful planning and good communication between all members of the healthcare team is crucial.

Gender equality and participation in housework: A cross-national perspective

This paper examines men's and women's participation in housework in the United States, Sweden, Norway, Canada and Australia. While there has been considerable research into the factors relating to the division of housework between husbands and wives within countries, very little research has examined the way in which housework patterns vary across countries. The results show that women continue to undertake the bulk of domestic labor in all five countries, and that the factors determining men's and women's participation in housework do not vary markedly across countries. This suggests that variations across countries in levels of gender equality at a broader level have only very limited effects on levels of gender equality in the home.

A Comparison of Bayesian and Sampling Theory Inferences in a Probit Model

HE PROBIT MODEL IS A POPULAR DEVICE for explaining binary choice decisions in econometrics. It has been used to describe choices such as labor force participation, travel mode, home ownership, and type of education. These and many more examples can be found in papers by Amemiya (1981) and Maddala (1983). Given the contribution of economics towards explaining such choices, and given the nature of data that are collected, prior information on the relationship between a choice probability and several explanatory variables frequently exists. Bayesian inference is a convenient vehicle for including such prior information. Given the increasing popularity of Bayesian inference it is useful to ask whether inferences from a probit model are sensitive to a choice between Bayesian and sampling theory techniques. Of interest is the sensitivity of inference on coefficients, probabilities, and elasticities. We consider these issues in a model designed to explain choice between fixed and variable interest rate mortgages. Two Bayesian priors are employed: a uniform prior on the coefficients, designed to be noninformative for the coefficients, and an inequality restricted prior on the signs of the coefficients. We often know, a priori, whether increasing the value of a particular explanatory variable will have a positive or negative effect on a choice probability. This knowledge can be captured by using a prior probability density function (pdf) that is truncated to be positive or negative. Thus, three sets of results are compared:those from maximum likelihood (ML) estimation, those from Bayesian estimation with an unrestricted uniform prior on the coefficients, and those from Bayesian estimation with a uniform prior truncated to accommodate inequality restrictions on the coefficients.