Examining links between cocaine use and street-based sex work in New South Wales, Australia

We examined potential links between cocaine use and street-based sex work in New South Wales (NSW), Australia, following reports of increased cocaine use among injection drug users (IDU). Police data on prostitution and possession/use of cocaine was analysed using time series analysis. Interviews with key informants and IDU were also conducted, and data on cocaine use from ongoing monitoring systems targeted at IDU were analysed. There was a clear increase in cocaine use among IDU which occurred in 2001. This occurred at the same time as an increase in prostitution offenses. Qualitative data suggested that a greater number of primary heroin users were engaging in street-based sex work, which was driven in part by the increases in cocaine use among this group. Subsequent reductions in cocaine availability led to decreased cocaine use and possession offenses, along with reductions in prostitution offenses.     

Direct and Indirect Measures of Learning Outcomes in an MSW Program: What Do We Actually Measure?

Abstract

Rankings of professional schools are often flawed and always controversial. This was certainly the case when, for the first time, U.S. News & World Report published a list based on “reputation” of the “best” schools of social work. This article compares the results of that study with the findings of eight other attempts to rank social work schools over the last 20 years. The similarities and differences among those studies are discussed in terms of what we may learn from them.     

Time out for team practice: structured participation as a method of training for team maintenance and development

The social Work service in most Social Services Departments is organised in distinct geographically based units. Indeed, such units have become synonymous with social work teams. These “teams” rely heavily for their success, as responsive and resourceful units, on their ability to work together. The authors believe there are advantages in a collective approach to a team's decision making and service delivery. They describe a method for developing teamwork, centred around a study day, organised on the basis of structured participation and planned in a way which addresses a range of team concerns.

The programme used on the study day stresses the importance of clear objectives, agreed democratically, and the active involvement of all team members. Although this training method developed gradually and pragmatically it is based on a model of team development which identifies a progression through stages of team functioning. The model of learning emphasises change through participation in a climate of openness and trust.

Examples of a programme used by the authors, together with a report prepared as feedback to a team, are included as appendices.     

Psychology of Promoting Environmentalism: Psychological Contributions toAchieving an Ecologically Sustainable Future for Humanity

The most serious long-term threat facing the world is the danger that human actions are producing irreversible, harmful changes to the environmental conditions that support life on Earth. If this problem is not overcome, there may be no viable world for our descendants to inhabit. Because this threat is caused by human population growth, overconsumption, and lack of resource conservation, social scientists have a vital role in helping our world escape ecological disaster and approach a sustainable level of impact on the environment—one that can be maintained indefinitely. Enormous changes to human lifestyles and cultural practices may be required to reach this goal. This article discusses major obstacles to this goal, describes a variety of motivational approaches toward reaching it, and proposes that we should view the achievement of sustainable living patterns as a superordinate goal—a war against the common enemy of an uninhabitable world.     

“Drunkorexia”: Understanding eating and physical activity behaviors of weight conscious drinkers in a sample of college students

Objective: Behaviors of weight conscious drinkers (BWCD) include disordered eating, excessive physical activity (PA), and heavy episodic drinking. Considering that approximately 25% of the college students report BWCD, it is important to investigate what characteristics increase the likelihood of college students engaged in BWCD for both moderate and vigorous PAs. Participants: A total of 510 college students were recruited from a large, public southeastern university. Methods: Participants completed a cross-sectional survey during the spring 2015 semester. Results: Of 510 respondents, 11.2% reported moderate PA-based BWCD and 14.7% reported vigorous PA-based BWCD. Weight loss intention, BMI and Greek affiliation predicted both moderate and vigorous BWCD. Conclusions: Study findings suggest that Greek-affiliated students and students with weight loss intentions might be at an increased risk for BWCD. Along with promoting lower levels of alcohol consumption, college practitioners should consider discussing issues of weight and body image with college students as they relate to maladaptive drinking behavior.     

THE NEO-LIBERAL REVOLUTION

This essay discusses neo-liberalism as a hegemonic process, offering an interpretation of the past 40 years of British political developments.     

Using auxiliary data for parameter estimation with non-ignorably missing outcomes

We propose a method for estimating parameters in generalized linear models when the outcome variable is missing for some subjects and the missing data mechanism is non-ignorable. We assume throughout that the covariates are fully observed. One possible method for estimating the parameters is maximum likelihood with a non-ignorable missing data model. However, caution must be used when fitting non-ignorable missing data models because certain parameters may be inestimable for some models. Instead of fitting a non-ignorable model, we propose the use of auxiliary information in a likelihood approach to reduce the bias, without having to specify a non-ignorable model. The method is applied to a mental health study.     

Variance estimation in complex survey sampling for generalized linear models

Summary.  Complex survey sampling is often used to sample a fraction of a large finite population. In general, the survey is conducted so that each unit (e.g. subject) in the sample has a different probability of being selected into the sample. For generalizability of the sample to the population, both the design and the probability of being selected into the sample must be incorporated in the analysis. In this paper we focus on non-standard regression models for complex survey data. In our motivating example, which is based on data from the Medical Expenditure Panel Survey, the outcome variable is the subject's 'total health care expenditures in the year 2002'. Previous analyses of medical cost data suggest that the variance is approximately equal to the mean raised to the power of 1.5, which is a non-standard variance function. Currently, the regression parameters for this model cannot be easily estimated in standard statistical software packages. We propose a simple two-step method to obtain consistent regression parameter and variance estimates; the method proposed can be implemented within any standard sample survey package. The approach is applicable to complex sample surveys with any number of stages.     

Effects of a single outlier on arma identification

Fox (1972), Box and Tiao (1975), and Abraham and Box (1979) have proposed methods for detecting outliers in time series whose ARMA form is known (or identified). We show that the existence of a single aberrant observation, innovation, or intervention causes an ARMA model to be misidentified using unadjusted autocorrelation (acf) and partial autocorrelation estimates. The magnitude, location, type of outlier, and in some cases the ARMA's parameters, affect the identification outcome. We use variance inflation, signal-to-noise ratios, and acf critical values to determine an ARMA model's susceptibility to misidentifi-cation. Numerical and simulation examples suggest how to iteratively use the outlier detection methods in practice.