Collaborative care : the role of practice nurses

Background
Comorbid depression can occur with diabetes and heart disease. This article reports on a feasibility study focusing on additional roles for practice nurses in detecting and monitoring depression with other chronic diseases.
Method
A convenience sample of six practices in southeast Australia was identified. Practice nurses received training via a workshop, which included training in the use of the Patient Health Questionnaire, to detect depression.
Results
The 332 patients who participated in the project each received a comprehensive health summary to assist with self management. Depression was identified in 34% of patients in this convenience sample. After 18 months implementation, practice nurses were strongly in favour of continuing the model of care. General
practitioners gave highly favourable ratings for effectiveness and willingness to continue this model of care.
Discussion
Practice nurses can include depression monitoring alongside systematic care of diabetes and heart disease. A randomised trial is currently underway to compare the clinical outcomes of this model with usual care.

Examining partner experience in cross-sector collaborative projects focused on the commercialization of R & D

The paper reports key findings from a four year study of cross-sector collaborative R&D projects in Australia testing a theoretical model formulated to explain partner collaboration experience and perceived project success. The study contributes to the understanding of knowledge-intensive collaborations, and indicates how their benefits can be sustained under conditions of high uncertainty. The study was of cross-sector collaborative projects within the Australian Cooperative Research Centre (CRC) Program which involved multiple partners and which were focused on the commercialization of R&D. The model was empirically tested through a survey of project leaders and the results provided support for the three main effects hypothesized. The theoretical, methodological and practical implications of the study's findings for the field of interorganizational relations (IOR) are discussed, and a new construct of project management competence is proposed as a determinant of positive partner experiences at the project level. This study adds to the growing body of work on interorganizational collaborative arrangements by providing systematic empirical support for a theoretical model of cross-sector R&D collaboration at the project level and at the completion or near completion phase of project development.

The TrueBlue study : is practice nurse-led collaborative care effective in the management of depression for patients with heart disease or diabetes?

Background: In the presence of type 2 diabetes (T2DM) or coronary heart disease (CHD), depression is under diagnosed and under treated despite being associated with worse clinical outcomes. Our earlier pilot study demonstrated that it was feasible, acceptable and affordable for practice nurses to extend their role to include screening for and monitoring of depression alongside biological and lifestyle risk factors. The current study will compare the clinical outcomes of our model of practice nurse-led collaborative care with usual care for patients with depression and T2DM or CHD.

Methods: This is a cluster-randomised intervention trial. Eighteen general practices from regional and metropolitan areas agreed to join this study, and were allocated randomly to an intervention or control group. We aim to recruit 50 patients with co-morbid depression and diabetes or heart disease from each of these practices. In the intervention group, practice nurses (PNs) will be trained for their enhanced roles in this nurse-led collaborative care study. Patients will be invited to attend a practice nurse consultation every 3 months prior to seeing their usual general practitioner. The PN will assess psychological, physiological and lifestyle parameters then work with the patient to set management goals. The outcome of this assessment will form the basis of a GP Management Plan document. In the control group, the patients will continue to receive their usual care for the first six months of the study before the PNs undergo the training and switch to the intervention protocol. The primary clinical outcome will be a reduction in the depression score. The study will also measure the impact on physiological measures, quality of life and on patient attitude to health care delivered by practice nurses.

Conclusion: The strength of this programme is that it provides a sustainable model of chronic disease management with monitoring and self-management assistance for physiological, lifestyle and psychological risk factors for high-risk patients with co-morbid depression, diabetes or heart disease. The study will demonstrate whether nurse-led collaborative care achieves better outcomes than usual care.

Creating collaborative spaces : the pleasures and perils of doing multi-disciplinary, multi-partner qualitative research

This paper describes our experience of managing a two-year research project that involved University staff from two different disciplines and three industry partners. It describes the benefits we gained from the involvement of multiple parties, such as the ability to call upon diverse expertise, the capacity to study a complex issue and the ability to make a direct contribution to industry practice. It also describes some of the difficulties such as managing across University structures, maintaining the collaborators' interest in the project, gaining approval from multiple ethics committees and managing the expectations of various stakeholders. The paper concludes with a number of recommendations for senior University staff and for researchers and points to ways universities could better facilitate involvement in these types of complex research projects.

Collaborative research training : a global challenge

Research training for postgraduate research students has entered a new era as the training process becomes a multi-dimensional practice, involving not just research students and supervisors from universities but also other stakeholders such as industry, funding agents, government, and in some cases, international stakeholders. Such a transition has created some challenges but also exciting opportunities. Centre for Material and Fibre Innovation (CMFI) at Deakin University, Australia has developed a number of innovative and effective paradigms on research training, producing high quality research scientists of improved employability and strong leadership. Successful models are outlined and challenging issues and prospective strategies are presented.

Improving the practicum through collaborative action

Using international concepts of best practice, the research showed that Thai student teacher's practicum is enhanced if there are systematic and sustained opportunities to participate in reflective discussion with peers and lecturers. The research used the Buddhist concept of Kalayanamitr as a metaphor for the relationship between professional practice and reflection on that practice. This research sets new directions for teacher education and educational research in Thailand.

Cross talk : collaborative indigenous life writing in Australia and Canada

This thesis argues that the critical reading of Indigenous life writing needs to move beyond its concern for power relations operating between the narrators and editors of collaboratively produced texts. It discusses the role of Indigenous families and communities in both the production and the reading of Indigenous texts.

Spam filtering using classification algorithms

This thesis proposes an innovative adaptive multi-classifier spam filtering model, with a grey-list analyser and a dynamic feature selection method, to overcome false-positive problems in email classification. It also presents additional techniques to minimize the added complexity. Empirical evidence indicates the success of this model over existing approaches.

Study on ensemble classification methods towards spam filtering

Recently, many scholars make use of fusion of filters to enhance the performance of spam filtering. In the past several years, a lot of effort has been devoted to different ensemble methods to achieve better performance. In reality, how to select appropriate ensemble methods towards spam filtering is an unsolved problem. In this paper, we investigate this problem through designing a framework to compare the performances among various ensemble methods. It is helpful for researchers to fight spam email more effectively in applied systems. The experimental results indicate that online based methods perform well on accuracy, while the off-line batch methods are evidently influenced by the size of data set. When a large data set is involved, the performance of off-line batch methods is not at par with online methods, and in the framework of online methods, the performance of parallel ensemble is better when using complex filters only.

Spam filtering for network traffic security on a multi-core environment

This paper presents an innovative fusion-based multi-classifier e-mail classification on a ubiquitous multicore architecture. Many previous approaches used text-based single classifiers to identify spam messages from a large e-mail corpus with some amount of false positive tradeoffs. Researchers are trying to prevent false positive in their filtering methods, but so far none of the current research has claimed zero false positive results. In e-mail classification false positive can potentially cause serious problems for the user. In this paper, we use fusion-based multi-classifier classification technique in a multi-core framework. By running each classifier process in parallel within their dedicated core, we greatly improve the performance of our multi-classifier-based filtering system in terms of running time, false positive rate, and filtering accuracy. Our proposed architecture also provides a safeguard of user mailbox from different malicious attacks. Our experimental results show that we achieved an average of 30% speedup at an average cost of 1.4 ms. We also reduced the instances of false positives, which are one of the key challenges in a spam filtering system, and increases e-mail classification accuracy substantially compared with single classification techniques.

An approach to filtering RFID data streams

RFID is gaining significant thrust as the preferred choice of automatic identification and data collection system. However, there are various data processing and management problems such as missed readings and duplicate readings which hinder wide scale adoption of RFID systems. To this end we propose an approach that filters the captured data including both noise removal and duplicate elimination. Experimental results demonstrate that the proposed approach improves missed data restoration process when compared with the existing method.

Information provenance for open distributed collaborative system

In autonomously managed distributed systems for collaboration, provenance can facilitate reuse of information that are interchanged, repetition of successful experiments, or to provide evidence for trust mechanisms that certain information existed at a certain period during collaboration. In this paper, we propose domain independent information provenance architecture for open collaborative distributed systems. The proposed system uses XML for interchanging information and RDF to track information provenance. The use of XML and RDF also ensures that information is universally acceptable even among heterogeneous nodes. Our proposed information provenance model can work on any operating systems or workflows.