DRUG POLICY IN THE TIME OF AIDS:

In 1985, the National Institute on Drug Abuse (NIDA) funded an ethnographic research project in San Francisco to study the needle sharing behavior of injection drug users (IDUs). The goal of the research was to develop a strategy to slow the spread of HIV among this hidden and hard to reach population of drug users and their sexual partners. This small-scale project grew into a model intervention in which bleach, condoms, and street-based education by outreach workers were employed to inform IDUs of the risk of AIDS and of methods for protecting themselves. The "reach and teach bleach" model was adopted by NIDA and implemented in a number of American cities. This study describes the development of the model intervention, the adoption of the model by NIDA as part of its National AIDS Demonstration Research (NADR) project, and the political circumstances under which the city of San Francisco applied for the NADR grant. Drawing on Social Worlds/Arena theory, and based on extensive interviews and participant observation, a sociohistorical analysis examines the initial development, implementation, and disintegration of the model outreach project and the impact of the program on drug policy in the city of San Francisco.     

Naturally occurring play patterns in groups of latency aged children

This study examines the influence of the socialization of aggression among different gender and social class groupings and the influence of psychosocial stage on cognitive developmental play preferences among groups of school aged children. Observations of 143 play groups were coded for play preference (symbolic play, practice play, games with rules) and play performance (cooperative or competitive). Findings of the log-linear data analysis suggest a middle class and masculine bias in Piaget's cognitive model (i.e., that as age increases children prefer more games with rules). This model held only for middle class and affluent boys. Girls (both latency and prepubertal) and lower socioeconomic groups tended to prefer practice play. Girls were more likely to play cooperatively; boys more likely to play competitively. Implications for theory development and clinical practice are explored.     

The Impact of Items and Anchors on Parent–Child Reports of Problem Behavior

Research has repeatedly demonstrated that parent and child reports of child behavior and emotional functioning often do not agree in terms of symptom severity or even symptom presence. Given the potential clinical impact that discrepant reports may have on the therapeutic process, a significant amount of research has addressed the factors influencing this observed discrepancy. Traditionally, this research has evaluated the impact of demographic factors on mean differences and obtained correlation coefficients between parent and child reports. The current research improves upon previous research in this area in two ways. First, the current research uses parent and child measures with identical rather than similar items as is commonly found in previous research. Second, the current research moves beyond identifying demographic influences on discrepant reports by explaining observed discrepancies in terms of differences in parent and child perceptions of typical child behavior.David Carlston and Benjamin Ogles are affiliated with Department of Psychology, Ohio University, Athens, USA.Funding for this project was provided by the Ohio Department of Mental Health.     

The current state of the labor queue: National and regional Evidence

We employ vector autoregressive techniques to determine the current state of the labor queue. Unemployment rate differentials have narrowed in recent years, potentially due to a change in the queue ordering, though a tight labor market and a stable queue would yield similar results. We find no evidence that the queue ordering has changed, which brings into question the resiliency of gains made by minority groups. We employ the same techniques to reveal the state of the queue across geographic regions and find that substantial differences exist across regions, implying variation in the relative labor force status of demographic groups.     

International guidelines and the inclusion of disabled people. The Ugandan story

Uganda has made much progress towards including disabled people in its mainstream development, particularly in the political agenda. The exact process by which this has been achieved and the relationship between this and international guidelines and legislation are not known. This study undertakes to examine this from two specific perspectives: (1) How do international documents relevant to disabled people relate to national legislation in Uganda? (2) What can this comparison, together with the perceptions of stakeholders, tell us about how the legislation and services could improve? International legislation and Ugandan legislation is reviewed and compared. Data from 5 semi‐structured key informant interviews and 6 focus group discussions involving a total of 38 people are collected and analysed. The themes arising from the data are related to the documents, legislation, policies and other relevant literature. The results examine the barriers to service provision; the role of change; the importance of representation; policy and legislation issues; and the effects of devolution. Five specific findings relate to how legislation and services can improve: more resources to increase access for disabled people; strong leadership and collaboration between Disabled People’s Organisations (DPOs) funding bodies and governments; awareness raising and training; representation from all impairment groups; and raising the profile of disabled people through further legislation.     

Statistics for weighing benefits and harms in a proposed genetic substudy of a randomized cancer prevention trial

Summary.  When evaluating potential interventions for cancer prevention, it is necessary to compare benefits and harms. With new study designs, new statistical approaches may be needed to facilitate this comparison. A case in point arose in a proposed genetic substudy of a randomized trial of tamoxifen versus placebo in asymptomatic women who were at high risk for breast cancer. Although the randomized trial showed that tamoxifen substantially reduced the risk of breast cancer, the harms from tamoxifen were serious and some were life threaten-ing. In hopes of finding a subset of women with inherited risk genes who derive greater bene-fits from tamoxifen, we proposed a nested case–control study to test some trial subjects for various genes and new statistical methods to extrapolate benefits and harms to the general population. An important design question is whether or not the study should target common low penetrance genes. Our calculations show that useful results are only likely with rare high penetrance genes.     

Factor analysis for ranked data with application to a job selection attitude survey

Summary.  Factor analysis is a powerful tool to identify the common characteristics among a set of variables that are measured on a continuous scale. In the context of factor analysis for non-continuous-type data, most applications are restricted to item response data only. We extend the factor model to accommodate ranked data. The Monte Carlo expectation–maximization algorithm is used for parameter estimation at which the E-step is implemented via the Gibbs sampler. An analysis based on both complete and incomplete ranked data (e.g. rank the top q out of k items) is considered. Estimation of the factor scores is also discussed. The method proposed is applied to analyse a set of incomplete ranked data that were obtained from a survey that was carried out in GuangZhou, a major city in mainland China, to investigate the factors affecting people's attitude towards choosing jobs.     

Bayesian analysis of a marked point process: Application in seismic hazard assessment

Point processes are the stochastic models most suitable for describing physical phenomena that appear at irregularly spaced times, such as the earthquakes. These processes are uniquely characterized by their conditional intensity, that is, by the probability that an event will occur in the infinitesimal interval (t, t+Δt), given the history of the process up tot. The seismic phenomenon displays different behaviours on different time and size scales; in particular, the occurrence of destructive shocks over some centuries in a seismogenic region may be explained by the elastic rebound theory. This theory has inspired the so-called stress release models: their conditional intensity translates the idea that an earthquake produces a sudden decrease in the amount of strain accumulated gradually over time along a fault, and the subsequent event occurs when the stress exceeds the strength of the medium. This study has a double objective: the formulation of these models in the Bayesian framework, and the assignment to each event of a mark, that is its magnitude, modelled through a distribution that depends at timet on the stress level accumulated up to that instant. The resulting parameter space is constrained and dependent on the data, complicating Bayesian computation and analysis. We have resorted to Monte Carlo methods to solve these problems.