Lay Understanding of Synergistic Risk: The Case of Radon and Cigarette Smoking

The combination of radon and smoking produces a synergistic risk of lung cancer. Lay understanding of this risk was examined from the perspectives of mental models theory, the psychometric approach to risk perception, and optimistic bias. As assessed by interview, participants ( N = 50) had more extensive mental models for the risks of smoking than for the risks of radon or the combination of radon and smoking; 32% knew little or nothing about radon. Despite reading an informational brochure, their risk-perception ratings of the three hazards showed no perception of the synergy between smoking and radon risk, although the combined hazard was rated as less familiar but more controllable than the average of the single hazards ( p < .01). No evidence of optimistic bias for the health consequences of radon, or the combination of radon and smoking was observed. Participants appeared to be combining the single-hazard risks subadditively to arrive at their combined-hazard risk perceptions. Further research on the integration of perceived risks would be beneficial for designing optimal communications about synergistic risk.     

Union wages, rents, and skills in health care labor markets

We examine the effect of unions on the earnings of health care workers, with emphasis on the measurement and sources of union wage premiums. Using data constructed from the 1973 though 1994 Current Population Surveys, standard union premium estimates are found to be substantially lower among workers in health care than in other sectors of the economy, and to be smaller among higher skill than among lower skill occupational groups. Longitudinal analysis of workers switching union status, which controls for worker-specific skills, indicates a small impact of unions on earnings within both high and low skilled health care occupations. Evidence is found for small, but significant, union threat effects in health care labor markets. It has been argued that recent legal changes in bargaining unit determination should enhance union organizing and bargaining power. Although we cannot rule this out, such effects are not readily apparent in our data. The authors appreciate the assistance of David Macpherson, who helped develop the CPS data files used in the paper.     

Discretionary Use of Involuntary Commitment by Case Managers of Mental Health Clients: A Case Study of Divergent Views

In an exploratory study, case managers held divergent views about their appropriate roles in involuntarily committing clients to psychiatric care. In light of vague organizational guidelines about appropriate use of involuntary commitment, case managers drew on professional social work values to form views about commitment. These values supported client self-determination, but did not clearly delineate ways for case managers' use of power and discretion concerning involuntary hospitalization, resulting in a range of understandings among case managers. This article provides a history of discretionary choices in the helping professions, cases illustrating divergent views about commitment among case managers and consequences for clients, and a discussion of ways this range may be narrowed in the future.     

Predicting random effects with an expanded finite population mixed model

Prediction of random effects is an important problem with expanding applications. In the simplest context, the problem corresponds to prediction of the latent value (the mean) of a realized cluster selected via two-stage sampling. Recently, Stanek and Singer [Predicting random effects from finite population clustered samples with response error. J. Amer. Statist. Assoc. 99, 119–130] developed best linear unbiased predictors (BLUP) under a finite population mixed model that outperform BLUPs from mixed models and superpopulation models. Their setup, however, does not allow for unequally sized clusters. To overcome this drawback, we consider an expanded finite population mixed model based on a larger set of random variables that span a higher dimensional space than those typically applied to such problems. We show that BLUPs for linear combinations of the realized cluster means derived under such a model have considerably smaller mean squared error (MSE) than those obtained from mixed models, superpopulation models, and finite population mixed models. We motivate our general approach by an example developed for two-stage cluster sampling and show that it faithfully captures the stochastic aspects of sampling in the problem. We also consider simulation studies to illustrate the increased accuracy of the BLUP obtained under the expanded finite population mixed model.     

Immigrants,Natives and Social Assistance: Comparable Take‐Up Under Comparable Circumstances

Are immigrants on welfare because they are more likely to be eligible or because they are more likely to claim benefits for which they are eligible? The answer is politically important, but because most current research on immigration and welfare is based on data from the United States, the answer is difficult due to the complexities of the transfer system which make eligibility determinations difficult. In Germany, by contrast, eligibility for the main cash transfer program, Sozialhilfe (Social Assistance), is determined by a comparatively simple nationwide formula. We use data from the German Socio‐Economic Panel to test whether immigrants to Germany are more likely than natives to claim welfare benefits for which they are eligible. We find that immigrants are more likely than native Germans to receive welfare, both because immigrants are more likely to be eligible and because they are more likely, when eligible, to claim their benefits. However, we also find that this greater propensity to take‐up benefits is not related to immigrant status per se: when other sociodemographic factors are accounted for in an appropriate manner, immigrant households are no more likely to take‐up benefits than native households.     

Empirical Bayes vs. fully Bayes variable selection

For the problem of variable selection for the normal linear model, fixed penalty selection criteria such as AIC, _Cp${\mathrm{C}}_p$, BIC and RIC correspond to the posterior modes of a hierarchical Bayes model for various fixed hyperparameter settings. Adaptive selection criteria obtained by empirical Bayes estimation of the hyperparameters have been shown by George and Foster [2000. Calibration and Empirical Bayes variable selection. Biometrika 87(4), 731–747] to improve on these fixed selection criteria. In this paper, we study the potential of alternative fully Bayes methods, which instead margin out the hyperparameters with respect to prior distributions. Several structured prior formulations are considered for which fully Bayes selection and estimation methods are obtained. Analytical and simulation comparisons with empirical Bayes counterparts are studied.     

Palliative healthcare: cost reduction and quality enhancement using end-of-life survey methodology

American medical institutions throughout the 20th century prescribed high customer satisfaction, but when it came to death, largely ignored it. An accelerated accumulation of esoteric medical information and the application of this knowledge to affect new cures and longer lives instilled an unquestioning reverence for the medical community among the patient population. Diminishing marginal gains in life expectancy, escalating costs related to life sustaining technologies, and a psychographic shift in the dominant consumer base have challenged this traditional reverence. Armed with unprecedented access to medical information, a more knowledgeable and assertive patient population has emerged in the 21st century to institute its own standards of what constitutes quality health care. In terms of end of life care, this has meant recognition that the emotional needs of the dying have been largely underserved by the current American medical model. Patients and their families are no longer willing to accept the traditional medical perspective of death as failure and have numerous international palliative care models that serve as benchmarks of success when it comes to quality of dying. When cure is a possibility, Americans will pursue it at all costs, but when it is not a possibility, they want honest communication and the opportunity to say good-bye to their loved ones. In the context of these emergent needs, life review is offered as a solution. The value proposition targets not only dying patients and their families, but also society as a whole.