Diagnostic sequence of cocaine use disorder in relation to other mental health conditions among college students

Abstract

Objective: Cocaine use is increasing. Comorbidities and diagnostic sequencing are needed among college students to inform treatment of cocaine use disorder (CUD). Method: Using electronic medical records from the psychiatric clinic at the student health care center of a large, public university from 2005 to 2015, patients diagnosed with CUD were identified. Their top mental health conditions were identified and assessed to see whether the first diagnosis of these conditions was made (1) before, (2) at the same time as, or (3) after the first diagnosis of CUD. Results: Among the 50 CUD patients, their most common mental health comorbidities were alcohol use disorder, anxiety, depression, and cannabis use disorder. Anxiety and depression were likely to be diagnosed before CUD; alcohol and cannabis use disorders were likely to be diagnosed concurrently with CUD. Conclusion: Diagnostic sequencing can be used to inform screening, workup, and treatment for patients with CUD.     

How many Australians have slept rough?

How many Australians have experienced homelessness during their lifetime and how many people have slept rough? This paper draws on evidence from a random sample of the Australian population to answer these questions (N=1349). First, we explain the methodology for the research. Then we focus on the number of people who have experienced homelessness and the different experiences of men and women. Next, we investigate how many people have slept rough. We conclude that about 2.35 million people have experienced homelessness during their lifetime, and that 59 per cent of them (about 1.4 million people) have slept rough.     

The changing intra-household resource allocation in Russia

During the transition period, Russian workers witnessed important changes in their real earnings. In the process, the wage gap between men and women has varied wildly and the family decision-making process may have been significantly altered. To investigate this issue, we estimate a collective labour supply model using data from the RLMS. The specification allows the sharing rule to change in a discrete manner between the pre- and post-1998 financial crisis. Our results indicate that the parameters of the sharing-rule have shifted to a new equilibrium in the post-1998 period. Indeed, when their relative wage increases, husbands (wives) transfer relatively less (more) to their spouse than was previously the case.     

Spectral estimation for locally stationary time series with missing observations

Time series arising in practice often have an inherently irregular sampling structure or missing values, that can arise for example due to a faulty measuring device or complex time-dependent nature. Spectral decomposition of time series is a traditionally useful tool for data variability analysis. However, existing methods for spectral estimation often assume a regularly-sampled time series, or require modifications to cope with irregular or ‘gappy’ data. Additionally, many techniques also assume that the time series are stationary, which in the majority of cases is demonstrably not appropriate. This article addresses the topic of spectral estimation of a non-stationary time series sampled with missing data. The time series is modelled as a locally stationary wavelet process in the sense introduced by Nason et al. (J. R. Stat. Soc. B 62(2):271–292, 2000) and its realization is assumed to feature missing observations. Our work proposes an estimator (the periodogram) for the process wavelet spectrum, which copes with the missing data whilst relaxing the strong assumption of stationarity. At the centre of our construction are second generation wavelets built by means of the lifting scheme (Sweldens, Wavelet Applications in Signal and Image Processing III, Proc. SPIE, vol. 2569, pp. 68–79, 1995), designed to cope with irregular data. We investigate the theoretical properties of our proposed periodogram, and show that it can be smoothed to produce a bias-corrected spectral estimate by adopting a penalized least squares criterion. We demonstrate our method with real data and simulated examples.     

Lower bounds and a tabu search algorithm for the minimum deficiency problem

An edge coloring of a graph G=(V,E) is a function c:E→ℕ that assigns a color c(e) to each edge e∈E such that c(e)≠c(e′) whenever e and e′ have a common endpoint. Denoting S _v (G,c) the set of colors assigned to the edges incident to a vertex v∈V, and D _v (G,c) the minimum number of integers which must be added to S _v (G,c) to form an interval, the deficiency D(G,c) of an edge coloring c is defined as the sum ∑ _v∈V D _v (G,c), and the span of c is the number of colors used in c. The problem of finding, for a given graph, an edge coloring with a minimum deficiency is NP-hard. We give new lower bounds on the minimum deficiency of an edge coloring and on the span of edge colorings with minimum deficiency. We also propose a tabu search algorithm to solve the minimum deficiency problem and report experiments on various graph instances, some of them having a known optimal deficiency.     

Enough is Enough: Race,Cricket and Protest in the UK

Abstract

This piece considers ethnicity in sport from the perspective of grass roots efforts to confront racism within the quintessentially English game of cricket. Cricket has a long history of discrimination, originally predicated on the basis of class, although recent events have very publicly raised issues of race and national identity. This piece explores how and why cricket became a positive focal point for successful protest against the apartheid regime of South Africa and proceeds to trace the current expression of racism within English cricket. By contrasting the anti-racist campaigns of the late 1960s and early 1970s with a currently emerging movement, we will show that legislative change in the UK has radically altered the ability to effectively demonstrate and campaign on such causes.     

Social capital: A useful concept for social work?

Abstract

In recent years, Australian governments at all levels have adopted social capital and related concepts to frame social policy. Hence, these ideas provide the backdrop within which much contemporary social work practice and social policy development occurs. Despite extensive coverage of social capital concepts in the social science literature there has been limited discussion of their application to social work practice. In this paper we review the origins and meaning of social capital. We then turn to a discussion of its application to progressive social work as well as a consideration of the criticisms of social capital concepts. We introduce a synergy model of social capital formation that incorporates a dual focus on local community networks and the role of the institutions of government, non-government agencies and business in the creation of social capital. The paper concludes with consideration of how a synergy approach can be applied in, and developed through, social work practice.

Karen Healy and Anne Hampshire lead a three year research project entitled: ‘Creating Better Communities: A Study of Social Capital Creation in Four Communities’. The study examines processes of social capital creation in urban, regional and rural contexts. The study is jointly funded by The Australian Research Council and The Benevolent Society     

Forecasting environmental migration to the United Kingdom: an exploration using Bayesian models

Over the next 50 years, the potential impact of environmental change on human livelihoods could be considerable, with one possible consequence being increased levels of human mobility. This paper explores how uncertainty about the level of immigration to the United Kingdom as a consequence of environmental factors elsewhere may be forecast using a methodology involving Bayesian models. The conceptual understanding of forecasting is advanced in three ways. First, the analysis is believed to be the first time that the Bayesian modelling approach has been attempted in relation to environmental mobility. Second, the paper considers the expediency of this approach by comparing the responses to a Delphi survey with conventional expectations about environmental mobility in the research literature. Finally, the values and assumptions of the expert evidence provided in the Delphi survey are interrogated to illustrate the limited set of conditions under which forecasts of environmental mobility, as set out in this paper, are likely to hold.     

Understanding lifetime homeless duration: investigating wave 1 findings from the Journeys Home project

The variation in the amount of time people remain homeless has important policy implications with respect to reducing long‐term homelessness and designing more effective early intervention approaches. This paper examines the factors that influence lifetime homeless duration in Australia using data from the first wave of Journeys Home, a new national survey of individuals exposed to high levels of housing insecurity that employs more rigorous sampling methods than previously used. Those at increased risk of long durations of homelessness over their lifetimes include people who had less family support in childhood, shorter work histories and lower education levels. We also find evidence supporting the idea that people who first experience homelessness at a young age are more likely to experience persistent homelessness.     

Do conditional cash transfers influence migration? A study using experimental data from the Mexican progresa program

Prior research on Mexican migration has shown that social networks and economic incentives play an important role in determining migration outcomes. We use experimental data from PROGRESA, Mexico's primary poverty-reduction program, to evaluate the effects of conditional cash transfers on migration both domestically and to the United States. Our study complements a growing body of literature aimed at overcoming longstanding hurdles to the establishment of causal validity in empirical studies of migration. Analysis based on the data collected before and after the program's onset shows that conditional transfers reduce U.S. migration but not domestic migration. The data also enable us to explore the role of existing family and community migration networks. The results show that migration networks strongly influence migration, but that the effect of conditional transfers on migration is apparently not mediated by existing migration network structures. Our results suggest that conditional transfers may be helpful in managing rural out-migration, particularly to the United States.