Premium will continue to be on performance. Interview by Wesley Curry.

With a new name for its professional organization (the American College of Physician Executives) and a new certifying organization (the American Board of Medical Management), the profession of medical management is in the throes of significant and far-reaching change. At the College's National Conference in Washington, D.C. in May, we talked to two leaders of the profession, Michael B. Guthrie, MD, MBA, FACPE, and Robert H. Hodge, Jr., MD, FACPE about what the future holds for physician executives and what physician executives can do to position themselves for success. Dr. Guthrie, the Immediate Past President of the College is Vice President for Business Development, Penrose/St. Francis Healthcare System, Colorado Springs, Colo. Dr. Hodge, the new President of the College, is a Program Director, W.K. Kellogg Foundation, Battle Creek, Mich.     

A meta-analysis of the California school-based risk reduction program

Prominent nonquantitative reviews of research evaluating school-based interventions designed to deter adolescents from the use of tobacco, alcohol and other drugs found the methodology to be flawed and thus little evidence existed that the interventions had the desired impact. Recent meta-analytic reviews indicate that information-focused interventions have more impact upon knowledge but less upon attitudes and behavior whereas alternative interventions have less impact upon knowledge but more upon attitudes and behavior. This result is replicated by the current meta-analysis performed upon eight risk-reduction programs meeting six standard methodological requirements for evaluation research.     

Theory & Methods: Incomplete detection in enumeration surveys: Whither distance sampling?

This paper considers the problem of undercount or incomplete detection in enumeration surveys that are intended to estimate population counts or population abundance. The problem is widespread in ecology but also occurs in other surveys: the census undercount is a well-known example of the problem. After framing the problem in a general context, the paper focuses on line transect sampling and the distance sampling method which has been widely applied in surveys of ecological populations. It describes distance sampling data and presents a graphical derivation of the distance sampling estimator. The graphical analysis leads to a new expression for the distance sampling estimator which gives useful insights into the nature of the estimator. The paper discusses the uniformity assumption on which distance sampling depends and describes the properties of the distance sampling estimator when uniformity does not hold. It then explores the relationship between this and other evaluations of distance sampling and mentions briefly some statistical ideas for treating the general incomplete detection problem. The paper concludes with some reflections on general insights arising from the research.     

Effects of non-normality on the power function in a one-way random model

The effects of non-normality on type-I and type-II errors in a one-way random model are investigated for moderate departures from normality. It is found that the probabilities of both errors are more sensitive to the kurtosis of between group effects than that of within group effects.     

Transfer programs and aggregate household formations

The number of households in the United States increased by over fifty percent in the 1960s and 1970s, nearly double the rate of population growth. Part of the increase is explained by the movement of large cohort groups of the population into prime household-forming age categories, but higher headship rates also contribute. Age-specific headship rate increases result from non-demographic factors, and this paper focuses on the role of government transfer payment programs. Specifically considered are Social Security, Aid to Families with Dependent Children, and Food Stamps. These programs are found to have accounted for as many as 4 million net household formations between 1961 and 1984. The findings have implications for expected households formations in the 1990s.     

Some results concerning off-training-set and IID error for the Gibbs and the Bayes optimal generalizers

In this paper we analyse the average behaviour of the Bayes-optimal and Gibbs learning algorithms. We do this both for off-training-set error and conventional IID (independent identically distributed) error (for which test sets overlap with training sets). For the IID case we provide a major extension to one of the better known results. We also show that expected IID test set error is a non-increasing function of training set size for either algorithm. On the other hand, as we show, the expected off-training-set error for both learning algorithms can increase with training set size, for non-uniform sampling distributions. We characterize the relationship the sampling distribution must have with the prior for such an increase. We show in particular that for uniform sampling distributions and either algorithm, the expected off-training-set error is a non-increasing function of training set size. For uniform sampling distributions, we also characterize the priors for which the expected error of the Bayes-optimal algorithm stays constant. In addition we show that for the Bayes-optimal algorithm, expected off-training-set error can increase with training set size when the target function is fixed, but if and only if the expected error averaged over all targets decreases with training set size. Our results hold for arbitrary noise and arbitrary loss functions.     

Stigma Management Among Gay/Bisexual Men with HIV/AIDS

People with HIV infection are subjected to prejudice, discrimination and hostility related to the stigmatization of AIDS. To manage the stigma of their disease, they mount complex coping strategies. This paper reports results from a qualitative study that examined gay/bisexual men's experiences of living with HIV infection. Unstructured interviews from a diverse sample of 139 men were analyzed to examine how men coped with AIDS-related stigma. We discerned a variety of stigma management strategies that could be arranged along a continuum from reactive to proactive based on the extent to which they implicitly accepted or challenged the social norms and values that underlie the stigmatization of HIV/AIDS. Reactive strategies to cope with stigma involve defensive attempts to avoid or mitigate the impact of stigma, but imply acceptance of the underlying social norms and values that construct the stigma. Examples of reactive strategies include hiding one's HIV status, presenting one's illness as a less stigmatizing one (e.g., cancer), or distancing one's self from more damaging aspects of AIDS-stigma (e.g., attributing infection to blood transfusion). Proactive strategies challenge the validity of the stigma and imply disavowal and resistance of the social norms and values that underlie the stigma. Examples of proactive strategies include engaging in public educational efforts that address misperceptions about HIV transmission and social activism to change the social and political conditions that affect PWA/HIV.