Implementing low intensity CBT in case management of clients with severe mental illness

In a previous chapter (Dean and Kavanagh, Chapter 37), the authors made a case for applying low intensity (LI) cognitive behaviour therapy (CBT) to people with serious mental illness (SMI). As in other populations, LI CBT interventions typically deal with circumscribed problems or behaviours. LI CBT retains an emphasis on self-management, has restricted content and segment length, and does not necessarily require extensive CBT training. In applying these interventions to SMI, adjustments may be needed to address cognitive and symptomatic difficulties often faced by these groups. What may take a single session in a less affected population may require several sessions or a thematic application of the strategy within case management. In some cases, the LI CBT may begin to appear more like a high-intensity (HI) intervention, albeit simple and with many LI CBT characteristics still retained. So, if goal setting were introduced in one or two sessions, it could clearly be seen as an LI intervention. When applied to several different situations and across many sessions, it may be indistinguishable from a simple HI treatment, even if it retains the same format and is effectively applied by a practitioner with limited CBT training. ----- ----- In some ways, LI CBT should be well suited to case management of patients with SMI. treating staff typically have heavy workloads, and find it difficult to apply time-consuming treatments (Singh et al. 2003). LI CBT may allow provision of support to greater numbers of service users, and allow staff to spend more time on those who need intensive and sustained support. However, the introduction of any change in practice has to address significant challenges, and LI CBT is no exception. ----- ----- Many of the issues that we face in applying LI CBT to routine case management in a mnetal health service and their potential solutions are essentially the same as in a range of other problem domains (Turner and Sanders 2006)- and, indeed, are similar to those in any adoption of innovation (Rogers 2003). Over the last 20 years, several commentators have described barriers to implementing evidence-based innovations in mental health services (Corrigan et al. 1992; Deane et al. 2006; Kavanagh et al. 1993). The aim of the current chapter is to present a cognitive behavioural conceptualisation of problems and potential solutions for dissemination of LI CBT.

Adapting low intensity CBT interventions for clients with severe mental illness

Many people with severe mental illness (SMI) such as schizophrenia, whose psychotic symptoms are effectively managed, continue to experience significant functional problems. This chapter argues that low intensity (LI) cognitive behaviour therapy (CBT; e.g. for depression, anxiety, or other issues) is applicable to these clients, and that LI CBT can be consistent with long-term case management. However, adjustments to LI CBT strategies are often necessary and boundaries between LI CBT and high intensity (HI) CBT (with more extensive practitioner contact and complexity) may become blurred. Our focus is on LI CBT's self-management emphasis, its restricted content and segment length, and potential use after limited training. In addition to exploring these issues, it draws on the authors' Collaborative Recovery (CR; Oades et al. 2005) and 'Start Over and Survive' programs (Kavanagh et al. 2004) as examples. ----- ----- Evidence for the effectiveness of LI CBT with severe mental illness is often embedded within multicomponent programs. For example, goal setting and therapeutic homework are common components of such programs, but they can also be used as discrete LI CBT interventions. A review of 40 randomised controlled trials involving recipients with schizophrenia or other sever mental illnesses has identified key components of illness management programs (Mueser et al. 2002). However, it is relatively rare for specific components of these complex interventions to be assessed in isolation. Given these constraints, the evidence for specific LI CBT interventions with severe mental ilnness is relatively limited.

Brief motivational interviewing for depression and anxiety

Motivational interviewing (MI)can be applied as a brief, low intensity (LI) intervention of 1-4 individualised sessions (typically 45-60 minutes in duration), including screening, assessment feedback, and psycho-education. MI is a client-centred, directive therapeutic style that enhances readiness for change by helping clients explore and resolve ambivalence (Miller and Rollnick 2002). A summary of the key components of brief MI interventions is provided in Table 16.1. There is a well-established evidence base for MI in the treatment of substance misuse (particularly alcohol misuse; Moyer et al. 2002), as well as a growing evidence for the use of MI in the treatment of other mental disorders (e.g. depression, PTSD, OCD), as well as suicidality and physical health problems (Hettema et al. 2005). Brief MI intervention can be delivered as a standalone treatment or as a motivational prelude to pharmacological and/or other psychological treatments (Hettema et al. 2005). MI has been used as an accompaniment to cognitive behavioural therapy (CBT) in the treatment of both depression and anxiety for resolving ambivalence about change and developing strategies for responding to resistance (e.g. treatment attendance, homework/medication compliance; Arkowitz et al. 2008a, 2008b). This chapter will describe how to apply brief MI interventions to the treatment of depression and anxiety as applied to the case of Megan (see Box 16.1) along with some of the challenges and potential solutions to applying MI in practice.

Design of a model-generated repository as a service for USDL

SAP and its research partners have been developing a lan- guage for describing details of Services from various view- points called the Unified Service Description Language (USDL). At the time of writing, version 3.0 describes technical implementation aspects of services, as well as stakeholders, pricing, lifecycle, and availability. Work is also underway to address other business and legal aspects of services. This language is designed to be used in service portfolio management, with a repository of service descriptions being available to various stakeholders in an organisation to allow for service prioritisation, development, deployment and lifecycle management. The structure of the USDL metadata is specified using an object-oriented metamodel that conforms to UML, MOF and EMF Ecore. As such it is amenable to code gener-ation for implementations of repositories that store service description instances. Although Web services toolkits can be used to make these programming language objects available as a set of Web services, the practicalities of writing dis- tributed clients against over one hundred class definitions, containing several hundred attributes, will make for very large WSDL interfaces and highly inefficient “chatty” implementations. This paper gives the high-level design for a completely model-generated repository for any version of USDL (or any other data-only metamodel), which uses the Eclipse Modelling Framework’s Java code generation, along with several open source plugins to create a robust, transactional repository running in a Java application with a relational datastore. However, the repository exposes a generated WSDL interface at a coarse granularity, suitable for distributed client code and user-interface creation. It uses heuristics to drive code generation to bridge between the Web service and EMF granularities.

Frequency decomposition techniques for increased discriminative 3D facial information capture

Eigen-based techniques and other monolithic approaches to face recognition have long been a cornerstone in the face recognition community due to the high dimensionality of face images. Eigen-face techniques provide minimal reconstruction error and limit high-frequency content while linear discriminant-based techniques (fisher-faces) allow the construction of subspaces which preserve discriminatory information. This paper presents a frequency decomposition approach for improved face recognition performance utilising three well-known techniques: Wavelets; Gabor / Log-Gabor; and the Discrete Cosine Transform. Experimentation illustrates that frequency domain partitioning prior to dimensionality reduction increases the information available for classification and greatly increases face recognition performance for both eigen-face and fisher-face approaches.

Parallel user profiling based on folksonomy for Large Scaled Recommender Systems : an implimentation of Cascading MapReduce

The Large scaled emerging user created information in web 2.0 such as tags, reviews, comments and blogs can be used to profile users’ interests and preferences to make personalized recommendations. To solve the scalability problem of the current user profiling and recommender systems, this paper proposes a parallel user profiling approach and a scalable recommender system. The current advanced cloud computing techniques including Hadoop, MapReduce and Cascading are employed to implement the proposed approaches. The experiments were conducted on Amazon EC2 Elastic MapReduce and S3 with a real world large scaled dataset from Del.icio.us website.

Biomashups: the new world of exploratory bioinformatics?

Bioinformatics is dominated by online databases and sophisticated web-accessible tools. As such, it is ideally placed to benefit from the rapid, purpose specific combination of services achievable via web mashups. The recent introduction of a number of sophisticated frameworks has greatly simplified the mashup creation process, making them accessible to scientists with limited programming expertise. In this paper we investigate the feasibility of mashups as a new approach to bioinformatic experimentation, focusing on an exploratory niche between interactive web usage and robust workflows, and attempting to identify the range of computations for which mashups may be employed. While we treat each of the major frameworks, we illustrate the ideas with a series of examples developed under the Popfly framework

Managing wetlands sustainably as ecosystems : The contribution of the law (part 1)

The ways in which a society set standards of behaviour and of conduct for its members vary hugely. For example, accepted practices, recognised customs, spiritually or morally inspired norms, judicially declared rules, executively formulated edicts, formal legislative enactments or constitutionally embedded rights and duties. Whatever form they assume, these standards are the artificial construction of the human mind. Accordingly the law - whatever its form - can do no more and no less than regulate or set standards for human behaviour, human conduct, and human decision-making. The law cannot regulate the environment. It can only regulate human activities that impact directly or indirectly upon the environment. This applies as much to wetlands as components of the environment as it does to any other components of the environment or the environment at large. The capacity of the law to protect the environment and therefore wetlands is thus totally dependent upon the capacity of the law to regulate human behaviour, human conduct and human decision-making. At the same time the law needs to reflect the specific nature, functions and locations of wetlands. A wetland is an ecosystem by itself; it comprises a range of ecosystems within it; and it is part of a wider set of ecosystems. Hence, the significant ecological functions performed by wetlands. Then there are the benefits flowing to humans from wetlands. These may be social, economic, cultural, aesthetic, or a combination of some or of all of these. It is a challenge for a society acting through its legal system to find the appropriate balance between these ecological and these human values. But that is what sustainability requires.The ways in which a society set standards of behaviour and of conduct for its members vary hugely. For example, accepted practices, recognised customs, spiritually or morally inspired norms, judicially declared rules, executively formulated edicts, formal legislative enactments or constitutionally embedded rights and duties. Whatever form they assume, these standards are the artificial construction of the human mind. Accordingly the law - whatever its form - can do no more and no less than regulate or set standards for human behaviour, human conduct, and human decision-making. The law cannot regulate the environment. It can only regulate human activities that impact directly or indirectly upon the environment. This applies as much to wetlands as components of the environment as it does to any other components of the environment or the environment at large. The capacity of the law to protect the environment and therefore wetlands is thus totally dependent upon the capacity of the law to regulate human behaviour, human conduct and human decision-making. At the same time the law needs to reflect the specific nature, functions and locations of wetlands. A wetland is an ecosystem by itself; it comprises a range of ecosystems within it; and it is part of a wider set of ecosystems. Hence, the significant ecological functions performed by wetlands. Then there are the benefits flowing to humans from wetlands. These may be social, economic, cultural, aesthetic, or a combination of some or of all of these. It is a challenge for a society acting through its legal system to find the appropriate balance between these ecological and these human values. But that is what sustainability requires.

Managing Wetlands Sustainably as Ecosystems: The Contribution of the Law (Part 2)

In this Part 2 attention is turned towards the legal arrangements in nation states for managing wetlands. These national arrangements have effect within the international arrangements already mentioned and any regional arrangements that are relevant. However, each national system is a reflection of its own historical, cultural, political and constitutional background. It is the purpose of this Part 2 to review and assess the national approaches to wetlands management. This involves an analysis of a range of instruments. These are: constitutional rules; strategic rules; regulatory rules; and management rules. Each of these sets of rules performs different functions, assumes different forms and is differentially capable of enforcement.

Convexity, Classification, and Risk Bounds

Many of the classification algorithms developed in the machine learning literature, including the support vector machine and boosting, can be viewed as minimum contrast methods that minimize a convex surrogate of the 0–1 loss function. The convexity makes these algorithms computationally efficient. The use of a surrogate, however, has statistical consequences that must be balanced against the computational virtues of convexity. To study these issues, we provide a general quantitative relationship between the risk as assessed using the 0–1 loss and the risk as assessed using any nonnegative surrogate loss function. We show that this relationship gives nontrivial upper bounds on excess risk under the weakest possible condition on the loss function—that it satisfies a pointwise form of Fisher consistency for classification. The relationship is based on a simple variational transformation of the loss function that is easy to compute in many applications. We also present a refined version of this result in the case of low noise, and show that in this case, strictly convex loss functions lead to faster rates of convergence of the risk than would be implied by standard uniform convergence arguments. Finally, we present applications of our results to the estimation of convergence rates in function classes that are scaled convex hulls of a finite-dimensional base class, with a variety of commonly used loss functions.