Understanding end-user perspectives to enhance perceived value uptake of harm-minimization tools: considering gambler’s views of a pre-commitment system

Harm-minimization strategies reduce the experience of gambling-related harms for individuals and those close to them. Most policies and particularly discussions of tool design and implementation fail to involve end users and consider their concerns and needs. This study aimed to investigate the best way to introduce a harm-minimization tool for electronic gaming machines (EGMs) that will maximize the perceived value and subsequent uptake by the intended audience of gamblers. Focus groups were conducted with 31 Australian regular EGM gamblers experiencing a range of gambling problems. Participants were asked their perspectives of a pre-commitment system (features including accessing activity statements, setting limits, viewing dynamic messages, taking breaks), including concerns, and how to enhance perceived value and usefulness. Positive attitudes about the system were expressed; however, many gamblers saw the tool as relevant only for problem gamblers. Participants indicated that value could be enhanced by making the system flexible and customizable, but still easy to use. Design and implementation strategies such as incorporating flexibility in features, ease of use, appropriate terminology, and educational efforts may address gamblers’ concerns, particularly regarding privacy and potential stigma. This would enhance user perception of harm-minimization tools as relevant and may subsequently enhance effectiveness.     

‘A drop in the bucket‘: Collective efficacy perceptions and environmental behaviour

Environmental degradation is a complex problem, many aspects of which may not be solved unless collective effort is undertaken. Collective Efficacy theory provides a useful framework to investigate how people view their ability and the effectiveness of their actions to solve environmental problems, which has been largely overlooked until now. Six focus groups were conducted to explore efficacy beliefs expressed by environmental Activists and Non‐Activists in Perth, Western Australia, relating to waste management. All participants (n=38) expressed pessimistic views about the abilities of others to perform pro‐environmental behaviours. However, Activists were positive that a collective effort would be effective (‘many drops will fill up the bucket’) while Non‐Activists felt strongly that the problem would still exist even if everyone performed waste‐minimising behaviours (‘it's just a drop in the bucket’). Behaviour change interventions might be more effective if they focus on convincing people that collective effort will be effective in solving environmental problems.     

开关函数最小化累次异或展开式

本文讨论利用异或图求取开关函数最小化累次异或展开式的方法。     

Drug wars down under: the ill-fated struggle for safe injecting facilities in Victoria, Australia

This article analyses the recent debate over the proposed introduction of safe injecting facilities (SIFs) for heroin users in the State of Victoria. It is argued that this debate strongly reflected the increasing globalisation of national social policy debates. Both supporters and opponents of SIFs drew constant attention to the alleged success or failure of existing SIFs in Europe. In addition, the debate saw the direct intervention of international and global agencies including the International Narcotics Control Board, the American Office of National Drug Policy and the Vatican. Some conclusions are also drawn about the reasons for the failure of the SIF campaign, including the conservatism of the opposition Liberal Party, the influence of the tabloid media and the use of ambiguous terminology.     

Joint estimation of multiple high‐dimensional Gaussian copula graphical models

A joint estimation approach for multiple high‐dimensional Gaussian copula graphical models is proposed, which achieves estimation robustness by exploiting non‐parametric rank‐based correlation coefficient estimators. Although we focus on continuous data in this paper, the proposed method can be extended to deal with binary or mixed data. Based on a weighted minimisation problem, the estimators can be obtained by implementing second‐order cone programming. Theoretical properties of the procedure are investigated. We show that the proposed joint estimation procedure leads to a faster convergence rate than estimating the graphs individually. It is also shown that the proposed procedure achieves an exact graph structure recovery with probability tending to 1 under certain regularity conditions. Besides theoretical analysis, we conduct numerical simulations to compare the estimation performance and graph recovery performance of some state‐of‐the‐art methods including both joint estimation methods and estimation methods for individuals. The proposed method is then applied to a gene expression data set, which illustrates its practical usefulness.