In meeting the challenges of fashioning a new health care system, South Africa stands poised to contribute to a better future for its own citizens and the subcontinent.

Background and aim With the increasing interest in lifestyle, health and consequences of unhealthy lifestyles for the healthcare system, a new kind of solidarity is gaining importance: lifestyle solidarity. While it might not seem fair to let other people pay for the costs arising from an unhealthy lifestyle, it does not seem fair either to punish people for their lifestyle. However, it is not clear how solidarity is assessed by people, when considering disease risks or lifestyle risks. The aim of (...) this study was to investigate the degree of solidarity with lifestyle as well as with other factors that are related to health outcomes—for example, old age—and the relation between this degree of solidarity and various characteristics. Methods This cross-sectional study is part of the Dutch longitudinal SMILE study. Data on the degree of solidarity with different lifestyles and old age, and the relation between the degree of solidarity and various demographic and other variables were obtained in a questionnaire survey. Results Solidarity with smokers and overweight people was moderate, as was solidarity with older people. Respondents were ambivalent about athletes. Respondents who were younger, male and highly educated, and those with a healthy lifestyle, a small social network, high quality of life and an internal locus of control, showed low solidarity. Conclusions Solidarity with an unhealthy lifestyle and old age is moderate and the degree of solidarity varies among the different subgroups. (shrink)

This note is viewing survival data of a natural cohort as being generated by a possibly nonlinear, nonhomogeneous death process. It proves that the usual conditional distributions of the number of survivors at a certain age are binomial if and only if the death process is linear. Thus the customary statistical methods for the analysis of life table data are, strictly speaking, invalid whenever the underlying death process is nonlinear. For example, if a contagious disease is the cause of some (...) or all of the deaths, the deaths will not be independent and the death process, not linear. One should then base the statistical analysis on a model for the spread of the disease rather than the routine binomial model. (shrink)

Because of the important role which the ‘autocatalytic’ or ‘logistic’ equation has played in determining the direction of a good deal of research both in demography and in the study of individual growth phenomena, a critical and comparative evaluation of those leading ideas inRobertson's book which pertain to this equation and of some of the criticisms levelled against it seemed to be of interest. The present paper shows that, contrary to common belief,Robertson did not really assume that the autocatalytic reactions (...) to which he compared growth processes, took place in closed systems . On the other hand, he does not seem to have found a satisfactory representation of how the growth phenomena of the individual cells in an organism might interact to yield the overall growth of the organism as a whole. Nor is the manner in which he made his equation account for the openness of the individual cells free from possible criticism. An alternative equation is here proposed, which will be discussed in another paper. The properties of the solutions of this equation are such that the autocatalytic theory might never have gained a foothold if this, more realistic, equation would have been the object of the initial studies. (shrink)

Rapid developments in Artificial Intelligence are leading to an increasing human reliance on machine decision making. Even in collaborative efforts with Decision Support Systems (DSSs), where a human expert is expected to make the final decisions, it can be hard to keep the expert actively involved throughout the decision process. DSSs suggest their own solutions and thus invite passive decision making. To keep humans actively ‘on’ the decision-making loop and counter overreliance on machines, we propose a ‘reflection machine’ (RM). This (...) system asks users questions about their decision strategy and thereby prompts them to evaluate their own decisions critically. We discuss what forms RMs can take and present a proof-of-concept implementation of a RM that can produce feedback on users’ decisions in the medical and law domains. We show that the prototype requires very little domain knowledge to create reasonably intelligent critiquing questions. With this prototype, we demonstrate the technical feasibility to develop RMs and hope to pave the way for future research into their effectiveness and value. (shrink)