Health professional students' occupational exposures to blood-borne pathogens: primary and secondary prevention strategies

Health science students, along with the health professionals they hope to become, are at increased risk for certain occupational injuries and illnesses. One of these risks is occupational exposure to blood-borne pathogens, such as human immunodeficiency virus (HIV) and hepatitis, which may result in severe illnesses or even death. Two case studies demonstrate postexposure care of exposed individuals at the University of Texas Medical Branch Student Health Services before and after policy changes and prevention strategies were strengthened in response to exposure incidents.     

Evaluating basic research strategies

A model has been developed to describe the pharmaceutical research and drug innovation process. The model originally served to show the range of results that could arise from research in the field of infectious disease chemotherapy over a sustained period of time. The main goal of the model was to illuminate the risk/reward/time tradeoff faced by management in selecting a particular research strategy. The results obtained with this model were one of several considerations influencing the research strategy decision of CIBA-GEIGY in 1976 to adapt and strengthen its research effort in infectious disease chemotherapy.This model has so far been applied only for the comparative evaluation of infectious disease chemotherapy research strategies. However, there is no conceptual reason why it should be limited to this field of drug research or indeed to pharmaceutical research at all. This type of analysis should be applicable wherever clear, product-oriented research goals can be identified and defined, where some reasonable financial reward can be attached to achieving these goals, and where an assessment—albeit subjective—can be made of the likelihood of achieving these goals.     

A Taxometric Analysis of Problem Gambling Data from a South African National Urban Sample

We investigate the question whether problem gambling (PG) in a recent South African sample, as measured by the Problem Gambling Severity Index (PGSI), is dimensional or categorical. We use two taxometric procedures, Mean Above Minus Below A Cut (MAMBAC) and Maxim Covariance (MAXCOV), to investigate the taxonic structure of PG as constructed by the PGSI. Data are from the 2010 South African National Urban Prevalence Study of Gambling Behavior. A representative sample of the urban adult population in South Africa (N = 3,000). Responses are to the 9 item PGSI. MAMBAC provided positive but modest evidence that PG as measured by the PGSI was taxonic. MAXCOV pointed more strongly to the same conclusion. These analyses also provide evidence that a PGSI cutoff score of 10 rather than the standard 8 may be called for. PG as constructed by the PGSI may best be thought of as categorical, but further studies with more theory based measurements are needed to determine whether this holds in a wider range of samples and for other screens. A higher cutoff score may be called for on the PGSI when it is used for research purposes to avoid false positives.     

Aging with HIV: Historical and Intra-Community Differences in Experience of Aging with HIV

Gay men living with HIV/AIDS face a complex of health issues, including those associated with the aging process, long-term HIV infection (25 years or more), and side effects from Highly Active Anti-Retroviral Therapy (HAART). If aging can increase marginalization, this is more likely for the aging HIV positive gay man, who is already marginalized for being queer and living with a stigmatizing disease. This article presents findings from a study of a long-running HIV support group. It locates the members, all gay men living with HIV, in a specific historical and political context to explore how feelings of loss and the struggle to sustain community affect long-term survivors and other older HIV+ gay men. We identify specific challenges presented by aging for men who contracted HIV early in the epidemic, contrasting them with those faced by men infected with the virus later in life. While both groups appear to struggle with a vision of what life could have been, had AIDS not forced loss and change, they also celebrate the community their shared plight has enabled.     

Approximate optimal allocation in repeated sampling from a finite population

Samples of size n are drawn from a finite population on each of two occasions. On the first occasion a variate x is measured, and on the second a variate y. In estimating the population mean of y, the variance of the best linear unbiased combination of means for matched and unmatched samples is itself minimized, with respect to the sampling design on the second occasion, by a certain degree of matching. This optimal allocation depends on the population correlation coefficient, which previous authors have assumed known. We estimate the correlation from an initial matched sample, then an approximately optimal allocation is completed and an estimator formed which, under a bivariate normal superpopulation model, has model expected mean square error equal, apart from an error of order n^-2, to the minimum enjoyed by any linear, unbiased estimator.     

On the relative accuracy of certain bootstrap procedures

We show the second-order relative accuracy, on bounded sets, of the Studentized bootstrap, exponentially tilted bootstrap and nonparametric likelihood tilted bootstrap, for means and smooth functions of means. We also consider the relative errors for larger deviations. Our method exploits certain connections between Edgeworth and saddlepoint approximations to simplify the computations.     

Robust F-tests for linear models

The author presents a robust F-test for comparing nested linear models. It is suggested that the approach will be attractive to practitioners because it is based on the familiar F-statistic and corresponds to the common practice of reporting F-statistics after removing obvious outliers. It is calibrated in terms of a real parameter that can be directly interpreted as the willingness of the data analyst to remove observations, and the sensitivity of the F-statistic to this parameter is easily examined. The procedure is evaluated with a simulation study where a scale mixture distribution is used to generate outliers. The procedure is also applied to some data where the occurrence of an outlier is confounded with the significance of a regression term. This provides a comparison of two competing models for the data: one removing an outlier and the other including an additional regression term instead.