'I'm Like a Tree a Million Miles from the Water's Edge': Social Care and Inclusion of Older People with Visual Impairment

The care and support of older people with visual impairmentis a neglected public-policy issue, despite the growing numbersaffected by sight loss in later life. A recently completed studyof four hundred people aged over fifty-five has gathered dataabout experiences of sight loss, coping strategies, supportneeds, home environments, social contacts and information needs.This paper reports on a prominent concern arising from research—theconnection between unmet social-care needs and social exclusion.Discussion focuses on identifying and assessing needs, majorproblems and priorities raised by interviewees, and serviceinitiatives that promote inclusive social care. Conclusionsare reached that social workers and other allied professionalscan best promote socially inclusive support through inter-agencyco-operation, and practical suggestions are presented as tothe possible shape and direction of collaborative work.     

A positive outlook? The housing needs and aspirations of working age people with visual impairments

This paper arises from research, funded by the Housing Corporation and the Thomas Pocklington Trust, which investigated the housing needs and priorities of visually impaired people of working age, a population that has received little public policy attention. We report on the housing circumstances and aspirations of 121 people living in London. In-depth study discovered that people of working age who have vision impairment can be disadvantaged by inflexible procedures that adversely affect their transition to independence, as well as their self-determination with respect to family issues. The study also learned that this population has particular needs in relation to domestic and outside space, home location and safety and security measures. Furthermore, the interviewees indicated that specialist supported housing may develop a stronger role if it diversifies and provides non-institutional stepping stones towards greater autonomy.     

Neighborhood Sectarian Displacement and the Battle for Baghdad: A Self‐Fulfilling Prophecy of Fear and Crimes Against Humanity in Iraq

We use two unique Iraq data sets to show how fear and uncertainty served to motivate the self‐fulfilling, neighborhood‐specific forces that followed the U.S.‐led invasion of Iraq. Sectarian criminal violence by armed Shia and Sunni organizations created a situation of ethnic/religious cleansing that reconfigured much of Baghdad. The article focuses on the case of how one particularly violent group, the Mahdi Army, mobilized through the coercive entrepreneurship of Muqtada al‐Sadr, used organized crime tactics of killing, torture, rape, kidnapping, harassment, threats, and forced displacement in a widespread and systematic attack against civilians that forced Sunni residents from their Baghdad neighborhoods. Ordinary Iraqis were victims of an amplified “self‐fulfilling prophecy of fear” that created the momentum for massive sectarian displacement in the battle for Baghdad. We demonstrate that there is a neighborhood specific effect of early postinvasion neighborhood fear net of intervening violence on displacement three years later, following the Al‐Qaeda Samara Shrine attack, confirming an effect of a self‐fulfilling prophecy of fear in the neighborhoods of Baghdad that compounded in a self‐reinforcing way. The changed demography of Baghdad was effectively consolidated by the later surge of U.S. forces that left in place the territorial gains made by the Shia‐led Mahdi Army at the expense of former Sunni residents. We conclude that this continues to matter because the resulting grievances have contributed to renewed violence.     

Trends in child support outcomes

This paper examines trends in child support award rates, award amounts, and receipts, We investigate four hypotheses that have been proposed to explain the downward trend in these outcomes during the 1980s: (1) changes in the demographic composition of the population eligible for child support, (2) increases in mothers/ income, (3) decreases in fathers’ income, and (4) inflation. Our results indicate that trends in nonmarital fertility can explain much of the decline in award rates. The steady downward trend in fathers’ incomes during the 1980s also explains a considerable portion of the decline in award rates, award amounts, and receipts. Our results are also consistent with the notion that persistent money illusion is responsible for the decline in real child support awards.     

The Antecedents of Teenage Fatherhood

The High School and Beyond Survey was used to describe young men who are at risk of becoming teenage fathers and examine the causal process leading to early fathering for young men. Bivariate results show that men who are at risk of fathering children at a young age have unique attitudes and family, school, and dating experiences. Multivariate analyses suggest that the most cogent factors affecting teenage fathering include being black, going steady, and having unorthodox views about parenting outside of marriage.     

A Semiparametric Bayesian Approach to Multivariate Longitudinal Data

We extend the standard multivariate mixed model by incorporating a smooth time effect and relaxing distributional assumptions. We propose a semiparametric Bayesian approach to multivariate longitudinal data using a mixture of Polya trees prior distribution. Usually, the distribution of random effects in a longitudinal data model is assumed to be Gaussian. However, the normality assumption may be suspect, particularly if the estimated longitudinal trajectory parameters exhibit multimodality and skewness. In this paper we propose a mixture of Polya trees prior density to address the limitations of the parametric random effects distribution. We illustrate the methodology by analyzing data from a recent HIV-AIDS study.     

Correction of Bias in Imputing Missing Values of Categorical Variables

Markov Chain Monte Carlo (MCMC) is the most common method used in multiple imputation. However, it is not unbiased when it is applied to imputations of categorical variables. The literature has considered the problem for binary variables with only two levels. In this article, we consider more general situations. We not only evaluate the bias associated with the imputation of categorical variables using the MCMC method, but also introduce a method to correct the bias. A simulation study is conducted and an application is provided to demonstrate the advantages of using the correction factors proposed in this article.     

Low back pain in physical therapists: a cultural approach to analysis and intervention

Low back pain is one of the most prevalent work related injuries in the physical therapy profession. New graduates and therapists working in rehabilitation and acute care hospitals are at the highest risk for developing low back pain [9]. Although physical therapists are trained in maintaining proper body mechanics and preventing work related injuries, between 30% and 63% of therapists will experience low back pain at some point in their careers [2,4,9]. The culture of physical therapy is one of the primary factors contributing to this problem, with many therapists reporting that their decision to use back pain preventive strategies depends on their colleagues' use of these strategies. The authors will use Green and Kreuter's PRECEDE-PROCEED model to identify behavioral, environmental, educational and ecological factors contributing to the problem; then will propose a health promotion intervention using the social action theory at the community level to decrease work-related low back pain in physical therapists while simultaneously addressing the culture of physical therapy.     

Computationally tractable approximate and smoothed Polya trees

A discrete approximation to the Polya tree prior suitable for latent data is proposed that enjoys surprisingly simple and efficient conjugate updating. This approximation is illustrated in two applied contexts: the implementation of a nonparametric meta-analysis involving studies on the relationship between alcohol consumption and breast cancer, and random intercept Poisson regression for Ache armadillo hunting treks. The discrete approximation is then smoothed with Gaussian kernels to provide a smooth density for use with continuous data; the smoothed approximation is illustrated on a classic dataset on galaxy velocities and on recent data involving breast cancer survival in Louisiana.