Is more better? The relationship between outcomes achieved by problem gamblers and the number of counselling sessions attended

This paper addresses the question of how much intervention is necessary for the effective treatment of problem gambling by exploring the relationship between the number of counselling sessions attended and the degree of problem resolution achieved for 613 individuals who attended problem gambling counselling services in Victoria. While those who achieved partial or full resolution of presenting problems attended more sessions than those who finished counselling with their problems still unresolved, problems were typically reported as being resolved in fewer than five sessions. It is concluded that for some problem gamblers a relatively brief intervention may be sufficient.

The influence of demographic, behavioural and treatments characteristics on problem gambling counselling outcomes

The paper considers the influence of client characteristics and gambling behaviour as well as treatment modality on the resolution of gambling behaviour for 591 clients who sought help from the publicly funded BreakEven counselling services in the state of Victoria between 1 July 1996 and 30 June 1997. Statistical data about clients and their consultations was collected in the form of a Minimum Data Set. On their own, client demographics accounting for 12% of the variance were identified as discriminating between problem gamblers who achieved some resolution of their gambling behaviour and those whose behaviour did not change. Variables associated with gambling behaviour accounted for 10% of variance and treatment variables for 12% of variance in treatment outcomes. Collectively, the three types of data could explain 26% of the variance in problem resolution. Importantly, these findings demonstrate that the resolution of problematic gambling behaviour is affected by a complex interplay of client characteristics, their gambling behaviour and the treatment they receive. It is argued that the evaluation of treatment programs for problem gambling, and potentially all counselling programs in the primary health arena, needs to include measures from each of these domains.

A manifold approach to face recognition from low quality video across illumination and pose using implicit super-resolution

We consider the problem of matching a face in a low resolution query video sequence against a set of higher quality gallery sequences. This problem is of interest in many applications, such as law enforcement. Our main contribution is an extension of the recently proposed Generic Shape-Illumination Manifold (gSIM) framework. Specifically, (i) we show how super-resolution across pose and scale can be achieved implicitly, by off-line learning of subsampling artefacts; (ii) we use this result to propose an extension to the statistical model of the gSIM by compounding it with a hierarchy of subsampling models at multiple scales; and (iii) we describe an extensive empirical evaluation of the method on over 1300 video sequences – we first measure the degradation in performance of the original gSIM algorithm as query sequence resolution is decreased and then show that the proposed extension produces an error reduction in the mean recognition rate of over 50%.