Cues and knowledge structures used by mental-health professionals when making risk assessments

Background: Research into mental-health risks has tended to focus on epidemiological approaches and to consider pieces of evidence in isolation. Less is known about the particular factors and their patterns of occurrence that influence clinicians’ risk judgements in practice. Aims: To identify the cues used by clinicians to make risk judgements and to explore how these combine within clinicians’ psychological representations of suicide, self-harm, self-neglect, and harm to others. Method: Content analysis was applied to semi-structured interviews conducted with 46 practitioners from various mental-health disciplines, using mind maps to represent the hierarchical relationships of data and concepts. Results: Strong consensus between experts meant their knowledge could be integrated into a single hierarchical structure for each risk. This revealed contrasting emphases between data and concepts underpinning risks, including: reflection and forethought for suicide; motivation for self-harm; situation and context for harm to others; and current presentation for self-neglect. Conclusions: Analysis of experts’ risk-assessment knowledge identified influential cues and their relationships to risks. It can inform development of valid risk-screening decision support systems that combine actuarial evidence with clinical expertise.

Knowledge-based development in leading regions across the globe:an exploratory analysis of the co-evolution of resources, capabilities, and outputs

It is widely observed that the global geography of innovation is rapidly evolving. This paper presents evidence concerning the contemporary evolution of the globe's most productive regions. The paper uncovers the underlying structure and co-evolution of knowledge-based resources, capabilities and outputs across these regions. The analysis identifies two key trends by which the economic evolution and growth patterns of these regions are differentiated-namely, knowledge-based growth and labour market growth. The knowledge-based growth factor represents the underlying commonality found between the growth of economic output, earnings and a range of knowledge-based resources. The labour market growth factor represents the capability of regions to draw on their human capital. Overall, spectacular knowledge-based growth of leading Chinese regions is evident, highlighting a continued shift of knowledge-based resources to Asia. It is concluded that regional growth in knowledge production investment and the capacity to draw on regional human capital reserves are neither necessarily traded-off nor complementary to each other. © 2012 Urban Studies Journal Limited.

The role of SHRM in turning tacit knowledge into explicit knowledge:a cross-national study of the UK and Malta

We propose that strategic human resource management (SHRM) practices nurture a context of knowledge sharing where tacit knowledge can be turned into explicit knowledge and that this type of knowledge sharing promotes innovative behaviours. We draw on the fields of knowledge management and international human resource management to show why organisations need to turn tacit knowledge into explicit knowledge to gain most from their workforce skills and creativity. Findings from a couple of cross-national case studies show how SHRM promotes employees to interact and share knowledge so that there is a conversion of tacit knowledge to explicit knowledge that informs innovative behaviour. In Case Study 1, the focus is on a UK local authority that implemented a bundle of SHRM practices through a people management programme, which resulted in a flattened management structure. In Case Study 2, the focus is on a geriatric hospital in Malta that introduced a management presence to an interdisciplinary team working to improve patient care. The analysis also highlights the methodological contribution of qualitative research for enabling inductive enquiry that yields emergent themes - an approach not typically seen in SHRM innovation studies. © 2013 Taylor & Francis.

Regional evolution and waves of growth:a knowledge-based perspective

The evolution of a regional economy and its competitiveness capacity may involve multiple independent trajectories, through which different sets of resources and capabilities evolve together. However, there is a dearth of evidence concerning how these trends are occurring across the globe. This paper seeks to present evidence in relation to the recent development of the globe’s most productive regions from the viewpoint of their growth trajectories, and the particular form of growth they are experiencing. The aim is to uncover the underlying structure of the changes in knowledge-based resources, capabilities and outputs across regions, and offer an analysis of these regions according to an uncovered set of key trends. The analysis identifies three key trends by which the economic evolution and growth patterns of these regions are differentiated—namely the Fifth Wave Growth, the Third & Fourth Wave Growth, and Government-led Third Wave Growth. Overall, spectacular knowledge-based growth of leading Chinese regions is evident, highlighting a continued shift of knowledge-based resources to Asia. In addition, a superstructure is observed at the global scale, consisting of two separate continuums that explicitly distinguish Chinese regions from the rest in terms of regional growth trajectories.

Explaining process and performance in the co-production of knowledge:a comparative analysis of collaborative research projects

Despite considerable and growing interest in the subject of academic researchers and practising managers jointly generating knowledge (which we term ‘co-production’), our searches of management literature revealed few articles based on primary data or multiple cases. Given the increasing commitment to co-production by academics, managers and those funding research, it seems important to strengthen the evidence base about practice and performance in co-production. Literature on collaborative research was reviewed to develop a framework to structure the analysis of this data and relate findings to the limited body of prior research on collaborative research practice and performance. This paper presents empirical data from four completed, large scale co-production projects. Despite major differences between the cases, we find that the key success factors and the indicators of performances are remarkably similar. We demonstrate many, complex influences between factors, between outcomes, and between factors and outcomes, and discuss the features that are distinctive to co-production. Our empirical findings are broadly consonant with prior literature, but go further in trying to understand success factors’ consequences for performance. A second contribution of this paper is the development of a conceptually and methodologically rigorous process for investigating collaborative research, linking process and performance. The paper closes with discussion of the study’s limitations and opportunities for further research.

Developing a probabilistic graphical structure from a model of mental-health clinical risk expertise

This paper explores the process of developing a principled approach for translating a model of mental-health risk expertise into a probabilistic graphical structure. The Galatean Risk Screening Tool [1] is a psychological model for mental health risk assessment based on fuzzy sets. This paper details how the knowledge encapsulated in the psychological model was used to develop the structure of the probability graph by exploiting the semantics of the clinical expertise. These semantics are formalised by a detailed specification for an XML structure used to represent the expertise. The component parts were then mapped to equivalent probabilistic graphical structures such as Bayesian Belief Nets and Markov Random Fields to produce a composite chain graph that provides a probabilistic classification of risk expertise to complement the expert clinical judgements. © Springer-Verlag 2010.

The structure of the rare-earth phosphate glass(Sm2O3)0.205(P2O5)0.795 studied by anomalous dispersion neutron diffraction

The role of the Sm3+ ions in the structure of vitreous Sm2O3•4P2O5 has been investigated using the neutron diffraction anomalous dispersion technique, which employs the wavelength dependence of the real and imaginary parts of the neutron scattering length close to an absorption resonance. The data described here represent the first successful complete neutron anomalous dispersion study on an amorphous material. This experimental methodology permits one to determine exclusively the closest Sm• •• Sm separation. Knowledge of the R•••R (R = rare-earth) pairwise correlation is key to understanding the optical and magnetic properties of rare-earth phosphate glasses. The anomalous difference correlation function, ΔT''(r), shows a dominant feature pertaining to a Sm•••Sm separation, centred at 4.8 Å. The substantial width and marked asymmetry of this peak indicates that the minimum approach of Sm3+ ions could be as close as 4 Å. Information on other pairwise correlations is also revealed via analysis of T (r) and ΔT (r) correlation functions: Sm3+ ions display an average co-ordination number, n Sm(O), of 7, with a mean Sm–O bond length of 2.375(5) Å whilst the PO4 tetrahedra have a mean P–O bond length of 1.538(2) Å. Second- and third-neighbour correlations are also identified. These results corroborate previous findings. Such consistency lends support to the application of the anomalous dispersion technique to determine separations.

Regional evolution and waves of growth:a knowledge-based perspective

The evolution of a regional economy and its competitiveness capacity may involve multiple independent trajectories through which different sets of resources and capabilities evolve together. However, there is a dearth of evidence concerning how these trends are occurring across the globe. Based on the underlying tenets of the streams of research relating to regional competitiveness, knowledge cities/regions, and knowledge-based urban development, this paper seeks to present an empirical approach to establishing such evidence in relation to the recent development of the globe’s most productive regions from the viewpoint of their growth trajectories and the particular form of growth they are experiencing. The aim is to uncover the underlying structure of the changes in knowledge-based resources, capabilities and outputs across regions, and offer an analysis of these regions according to an uncovered set of key trends. The analysis identifies three key trends by which the economic evolution and growth patterns of these regions are differentiated – namely the Fifth Wave Growth, the Third & Fourth Wave Growth, and Government-led Third Wave Growth. Overall, spectacular knowledge-based growth of leading Chinese regions is evident, highlighting a continued shift of knowledge-based resources to Asia. In addition, a superstructure is observed at the global scale, consisting of two separate continuums that explicitly distinguish Chinese regions from the rest in terms of regional growth trajectories. © 2014 Elsevier Ltd. All rights reserved. © 2014 Elsevier Ltd. All rights reserved.

A Domain-Independent Otology-based Approach to Representation of Courseware Knowledge

This paper proposes an ontology-based approach to representation of courseware knowledge in different domains. The focus is on a three-level semantic graph, modeling respectively the course as a whole, its structure, and domain contents itself. The authors plan to use this representation for flexibie e- learning and generation of different study plans for the learners.

Knowledge-Based Approach to Document Analysis

The paper presents an approach to extraction of facts from texts of documents. This approach is based on using knowledge about the subject domain, specialized dictionary and the schemes of facts that describe fact structures taking into consideration both semantic and syntactic compatibility of elements of facts. Actually extracted facts combine into one structure the dictionary lexical objects found in the text and match them against concepts of subject domain ontology.

INFRAWEBS Semantic Web Service Development on the Base of Knowledge Management Layer

The paper gives an overview about the ongoing FP6-IST INFRAWEBS project and describes the main layers and software components embedded in an application oriented realisation framework. An important part of INFRAWEBS is a Semantic Web Unit (SWU) – a collaboration platform and interoperable middleware for ontology-based handling and maintaining of SWS. The framework provides knowledge about a specific domain and relies on ontologies to structure and exchange this knowledge to semantic service development modules. INFRAWEBS Designer and Composer are sub-modules of SWU responsible for creating Semantic Web Services using Case-Based Reasoning approach. The Service Access Middleware (SAM) is responsible for building up the communication channels between users and various other modules. It serves as a generic middleware for deployment of Semantic Web Services. This software toolset provides a development framework for creating and maintaining the full-life-cycle of Semantic Web Services with specific application support.

New Knowledge Obtaining in Structural-predicate Models of Knowledge

An effective mathematical method of new knowledge obtaining on the structure of complex objects with required properties is developed. The method comprehensively takes into account information on the properties and relations of primary objects, composing the complex objects. It is based on measurement of distances between the predicate groups with some interpretation of them. The optimal measure for measurement of these distances with the maximal discernibleness of different groups of predicates is constructed. The method is tested on solution of the problem of obtaining of new compound with electro-optical properties.

Processing of Knowledge about Optimization of Classical Optimizing Transformations

The article describes the structure of an ontology model for Optimization of a sequential program. The components of an intellectual modeling system for program optimization are described. The functions of the intellectual modeling system are defined.

Designing the System of Remote Knowledge Diagnosing for Students of Technical Specialties

In the article the theoretical aspects of planning of the systems of the controlled from distance diagnosing of level of know ledges of students are resulted on the basis of modern pedagogical theoretical and technological approaches. The practical results of creation of the systems of this type are resulted for organization of testing both in the structure of local networks of higher educational establishments and with access through the global network of Internet.

Representing human expertise by the OWL web ontology language to support knowledge engineering in decision support systems

Clinical decision support systems (CDSSs) often base their knowledge and advice on human expertise. Knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. This paper reports on the development of an ontology specification for managing knowledge engineering in a CDSS for assessing and managing risks associated with mental-health problems. The Galatean Risk and Safety Tool, GRiST, represents mental-health expertise in the form of a psychological model of classification. The hierarchical structure was directly represented in the machine using an XML document. Functionality of the model and knowledge management were controlled using attributes in the XML nodes, with an accompanying paper manual for specifying how end-user tools should behave when interfacing with the XML. This paper explains the advantages of using the web-ontology language, OWL, as the specification, details some of the issues and problems encountered in translating the psychological model to OWL, and shows how OWL benefits knowledge engineering. The conclusions are that OWL can have an important role in managing complex knowledge domains for systems based on human expertise without impeding the end-users' understanding of the knowledge base. The generic classification model underpinning GRiST makes it applicable to many decision domains and the accompanying OWL specification facilitates its implementation.