Who thinks what about capitalism? Class consciousness and attitudes to economic institutions

Attitudes to the fundamental economic institutions of capitalism, private ownership of productive property, markets as arenas for securing economic outcomes, and working class rights to associate and to strike, are key dimensions of class consciousness. This paper investigates how class location shapes these attitudes in combination with other factors like employment sector and trade union membership. Using data from the 1995 National Social Science Survey, the paper finds systematic class variation on attitudes to economic institutions that is consistent with respondents endorsing or rejecting class-specific strategies of interest realisation according to their own class circumstances. On some attitudes, class structural effects are additionally moderated by organisational norms associated with public sector employment and mediated by the impact of trade union membership.

Self-awareness and psychosocial functioning following acquired brain injury: An evaluation of a group support programme

This study investigated a group support programme designed to improve self-awareness deficits and psychosocial functioning in a group of chronic patients (N = 21) with acquired brain injury (ABI). The participants were on average 8.6 years (range: 1-36 years) post-injury and were seen at the Brain Injury Association of Queensland, Australia. The assessment of participants involved two standardised measures of intellectual self-awareness with collateral reports from relatives. The present study introduced a new measure called the Self-Regulation Skills Interview (SRSI) which assessed higher levels of self awareness and self-regulation skills. Psychosocial functioning was assessed using a standardised self-report measure. At baseline the group had a relatively high level of intellectual self-awareness regarding their deficits, a low to moderate level of self-regulation skills, and significant psychosocial impairment. The participants were involved in a 16-week group programme which involved components of cognitive rehabilitation, cognitive-behavioural therapy, and social skills training. A post-intervention assessment indicated that participants had significantly improved levels of self-regulation skills and psychosocial functioning. A 6-month follow-up assessment indicated that overall, participants had maintained the gains made during the programme. The important role of self-regulation skills is emphasised as the principle factor contributing to the maintenance of the gains observed.

Variation in mortality rates in Australia: correlation with Indigenous status, remoteness and socio-economic deprivation

Background The aim of this study was to study ecological correlations between age-adjusted all-cause mortality rates in Australian statistical divisions and (1) the proportion of residents that self-identify as Indigenous, (2) remoteness, and (3) socio-economic deprivation. Methods All-cause mortality rates for 57 statistical divisions were calculated and directly standardized to the 1997 Australian population in 5-year age groups using Australian Bureau of Statistics (ABS) data. The proportion of residents who self-identified as Indigenous was obtained from the 1996 Census. Remoteness was measured using ARIA (Accessibility and Remoteness Index for Australia) values. Socioeconomic deprivation was measured using SEIFA (Socio-Economic index for Australia) values from the ABS. Results Age-standardized all-cause mortality varies twofold from 5.7 to 11.3 per 1000 across Australian statistical divisions. Strongest correlation was between Indigenous status and mortality (r = 0.69, p < 0.001). correlation between remoteness and mortality was modest (r = 0.39, p = 0.002) as was correlation between socio-economic deprivation and mortality (r = -0.42, p = 0.001). Excluding the three divisions with the highest mortality, a multiple regression model using the logarithm of the adjusted mortality rate as the dependent variable showed that the partial correlation (and hence proportion of the variance explained) for Indigenous status was 0.03 (9 per cent; p = 0.03), for SEIFA score was -0.17 (3 per cent; p = 0.22); and for remoteness was -0.22 (5 per cent; p = 0.13). Collectively, the three variables studied explain 13 per cent of the variability in mortality. Conclusions Ecological correlation exists between all-cause mortality, Indigenous status, remoteness and disadvantage across Australia. The strongest correlation is with indigenous status, and correlation with all three characteristics is weak when the three statistical divisions with the highest mortality rates are excluded. intervention targeted at these three statistical divisions could reduce much of the variability in mortality in Australia.

Small area population disease burden

Small area health statistics has assumed increasing importance as the focus of population and public health moves to a more individualised approach of smaller area populations. Small populations and low event occurrence produce difficulties in interpretation and require appropriate statistical methods, including for age adjustment. There are also statistical questions related to multiple comparisons. Privacy and confidentiality issues include the possibility of revealing information on individuals or health care providers by fine cross-tabulations. Interpretation of small area population differences in health status requires consideration of migrant and Indigenous composition, socio-economic status and rural-urban geography before assessment of the effects of physical environmental exposure and services and interventions. Burden of disease studies produce a single measure for morbidity and mortality - disability adjusted life year (DALY) - which is the sum of the years of life lost (YLL) from premature mortality and the years lived with disability (YLD) for particular diseases (or all conditions). Calculation of YLD requires estimates of disease incidence (and complications) and duration, and weighting by severity. These procedures often mean problematic assumptions, as does future discounting and age weighting of both YLL and YLD. Evaluation of the Victorian small area population disease burden study presents important cross-disciplinary challenges as it relies heavily on synthetic approaches of demography and economics rather than on the empirical methods of epidemiology. Both empirical and synthetic methods are used to compute small area mortality and morbidity, disease burden, and then attribution to risk factors. Readers need to examine the methodology and assumptions carefully before accepting the results.

Variation in cervical cancer screening by region, socio-economic, migrant and Indigenous status in women in New South Wales

The purpose of this study was to estimate the extent of association of cervical screening in NSW women with socio-economic status (SES), rurality, and proportions of non-English speaking background (NESB) and Indigenous status. Data on women who had at least one Pap test over two years (January 1998-December 1999) were obtained from the NSW Pap test Register. Each local government area (LGA) was allocated to categories of population proportions of NESB and Indigenous status, a rurality classification based on population density and remoteness, and to an SES quintile. The odds ratios (OR) of having a Pap test were estimated and confounding adjusted by multiple logistic regression analysis. Implied Pap test rates in urban NESB and in rural Indigenous women were estimated from the modelled estimates. The adjusted OR for a Pap test in large rural centres (1.14) was significantly higher than those for metropolitan or capital city residents (0.9 and 1.0 respectively). Adjusted OR for a Pap test in other rural centres (0.73) and other remote areas (0.64) were significantly lower than those for metropolitan or capital city residents. In urban populations the lowest OR were in areas with both low SES and high proportion of NESB. The lowest OR for Pap screening in rural populations occurred in the most remote areas with the highest proportion of Indigenous women. For urban NESB women the biennial Pap test rate was estimated as 50%, and for rural Indigenous women 29%, compared with the NSW average of 59%.

An economic evaluation of plasma production via erythroplasmapheresis and whole blood collection

This paper presents cost-effectiveness analyses (CEAs) of plasma collection via two alternative methods: whole blood collection (WBC) and erythroplasmapheresis collection (EPC). The objective of the study is to provide an answer to the question 'What is the least-cost method of plasma production'. This question is answered, both from the viewpoint of the blood collection agency (using financial CEA) and from that of 'society' as a whole (using economic CEA). We employ detailed financial data and economic survey data for collections made by a blood collection agency and to WBC and EPC donors in Brisbane, Australia. The results indicate that, despite the superior yield provided by EPC, WBC is actually more cost-effective. This result is robust to thorough sensitivity analysis and arises regardless of whether an economic or financial perspective is taken. We conclude that, ceteris paribus, the cost of recruiting new plasma donors would need to be quite substantial for marginal investments in EPC to be considered cost-effective. Crown Copyright (C) 2002 Published by Elsevier Science Ltd. All rights reserved.

Epidemiological modelling (including economic modelling) and its role in preventive drug therapy

In contrast to curative therapies, preventive therapies are administered to largely healthy individuals over long periods. The risk-benefit and cost-benefit ratios are more likely to be unfavourable, making treatment decisions difficult. Drug trials provide insufficient information for treatment decisions, as they are conducted on highly selected populations over short durations, estimate only relative benefits of treatment and offer little information on risks and costs. Epidemiological modelling is a method of combining evidence from observational epidemiology and clinical trials to assist in clinical and health policy decision-making. It can estimate absolute benefits, risks and costs of long-term preventive strategies, and thus allow their precise targeting to individuals for whom they are safest and most cost-effective. Epidemiological modelling also allows explicit information about risks and benefits of therapy to be presented to patients, facilitating informed decision-making.

Modelling the Distribution of Ischaemic Stroke-Specific Survival Time Using an EM-based Mixture Approach with Random Effects Adjustment

A two-component survival mixture model is proposed to analyse a set of ischaemic stroke-specific mortality data. The survival experience of stroke patients after index stroke may be described by a subpopulation of patients in the acute condition and another subpopulation of patients in the chronic phase. To adjust for the inherent correlation of observations due to random hospital effects, a mixture model of two survival functions with random effects is formulated. Assuming a Weibull hazard in both components, an EM algorithm is developed for the estimation of fixed effect parameters and variance components. A simulation study is conducted to assess the performance of the two-component survival mixture model estimators. Simulation results confirm the applicability of the proposed model in a small sample setting. Copyright (C) 2004 John Wiley Sons, Ltd.