867 resultados para information practice
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OBJECTIVE. We sought to describe the clinical use of n-of-1 trials for attention-deficit/hyperactivity disorder in publicly and privately funded family and specialized pediatric practice in Australia. METHODS. We used a within-patient randomized, double-blind, crossover comparison of stimulant (dexamphetamine or methylphenidate) versus placebo or alternative stimulant using 3 pairs of treatment periods. Trials were conducted from a central location using mail and telephone communication, with local supervision by the patients' clinicians. PATIENTS. Our study population included children with clinically diagnosed attention-deficit/ hyperactivity disorder who were aged 5 to 16 years and previously stabilized on an optimal dose of stimulant. They were selected because treatment effectiveness was uncertain. MAIN OUTCOME MEASURES. Our measures included number of patients recruited, number of doctors who used the service, geographic spread, completion rates, response rate, and post-n-of-1 trial decisions. RESULTS. Forty-five doctors across Australia requested 108 n-of-1 trials, of which 86 were completed. In 69 drug-versus-placebo comparisons, 29 children responded better to stimulant than placebo. Immediately posttrial, 19 of 25 drug-versus-placebo responders stayed on the same stimulant, and 13 of 24 nonresponders ceased or switched stimulants. In 40 of 63 for which data were available, posttrial management was consistent with the trial results. For all types of n-of-1 trials, management changed for 28 of 64 children for whom information was available. DISCUSSION. Attention-deficit/hyperactivity disorder n-of-1 trials can be implemented successfully by mail and telephone communication. This type of trial can be valuable in clarifying treatment effect when it is uncertain, and in this series, they had a noticeable impact on short-term management.
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This paper reflects upon our attempts to bring a participatory design approach to design research into interfaces that better support dental practice. The project brought together design researchers, general and specialist dental practitioners, the CEO of a dental software company and, to a limited extent, dental patients. We explored the potential for deployment of speech and gesture technologies in the challenging and authentic context of dental practices. The paper describes the various motivations behind the project, the negotiation of access and the development of the participant relationships as seen from the researchers' perspectives. Conducting participatory design sessions with busy professionals demands preparation, improvisation, and clarity of purpose. The paper describes how we identified what went well and when to shift tactics. The contribution of the paper is in its description of what we learned in bringing participatory design principles to a project that spanned technical research interests, commercial objectives and placing demands upon the time of skilled professionals. Copyright © 2010 ACM, Inc
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Research in verification and validation (V&V) for concurrent programs can be guided by practitioner information. A survey was therefore run to gain state-of-practice information in this context. The survey presented in this paper collected state-of-practice information on V&V technology in concurrency from 35 respondents. The results of the survey can help refine existing V&V technology by providing a better understanding of the context of V&V technology usage. Responses to questions regarding the motivation for selecting V&V technologies can help refine a systematic approach to V&V technology selection.
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The Clinician Development Program (CDP) is an initiative of Queensland Health’s Quality Improvement and Enhancement Program. At the Royal Brisbane & Royal Women's Hospital Health Service Districts, evidence-base practice (EBP) is an important CDP area in which several projects were carried out in 2002. This paper describes one such project. A medical librarian was invited to accompany the clinical team on morning rounds in the Medical Assessment & Planning Unit (MAPU). The librarian conducted information skills training in the ward and helped clinicians to answer questions directly related to patient care. Questions not answered during the round were followed-up, usually within 48 hours, and responses emailed to the consultant who led the rounds. At the project’s conclusion the librarian was invited to continue as a member of the MAPU clinical team, thus acknowledging the valuable role an information specialist can play in incorporating research evidence into patient care. Clinical librarianship (CL) creates a space, albeit a contentious one, for the health librarian at the bedside. This paper describes an Australian CL project and attempts to demystify the role of an information specialist in EBP. It also highlights some of the challenges facing librarians and clinicians attempting to embed EBP in clinical settings.
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We analyse the dynamics of a number of second order on-line learning algorithms training multi-layer neural networks, using the methods of statistical mechanics. We first consider on-line Newton's method, which is known to provide optimal asymptotic performance. We determine the asymptotic generalization error decay for a soft committee machine, which is shown to compare favourably with the result for standard gradient descent. Matrix momentum provides a practical approximation to this method by allowing an efficient inversion of the Hessian. We consider an idealized matrix momentum algorithm which requires access to the Hessian and find close correspondence with the dynamics of on-line Newton's method. In practice, the Hessian will not be known on-line and we therefore consider matrix momentum using a single example approximation to the Hessian. In this case good asymptotic performance may still be achieved, but the algorithm is now sensitive to parameter choice because of noise in the Hessian estimate. On-line Newton's method is not appropriate during the transient learning phase, since a suboptimal unstable fixed point of the gradient descent dynamics becomes stable for this algorithm. A principled alternative is to use Amari's natural gradient learning algorithm and we show how this method provides a significant reduction in learning time when compared to gradient descent, while retaining the asymptotic performance of on-line Newton's method.
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A major problem in modern probabilistic modeling is the huge computational complexity involved in typical calculations with multivariate probability distributions when the number of random variables is large. Because exact computations are infeasible in such cases and Monte Carlo sampling techniques may reach their limits, there is a need for methods that allow for efficient approximate computations. One of the simplest approximations is based on the mean field method, which has a long history in statistical physics. The method is widely used, particularly in the growing field of graphical models. Researchers from disciplines such as statistical physics, computer science, and mathematical statistics are studying ways to improve this and related methods and are exploring novel application areas. Leading approaches include the variational approach, which goes beyond factorizable distributions to achieve systematic improvements; the TAP (Thouless-Anderson-Palmer) approach, which incorporates correlations by including effective reaction terms in the mean field theory; and the more general methods of graphical models. Bringing together ideas and techniques from these diverse disciplines, this book covers the theoretical foundations of advanced mean field methods, explores the relation between the different approaches, examines the quality of the approximation obtained, and demonstrates their application to various areas of probabilistic modeling.
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This review is structured in three sections and provides a conceptual framework for the empirical analysis of strategy tools as they are used in practice. Examples of strategy tools are SWOT analysis or Porter’s Five Forces, among others. Section one reviews empirical research into the use of strategy tools, classifying them according to variations in their use. Section two explains the concept of boundary objects as the basis for our argument that strategy tools may be understood as boundary objects. Boundary objects are artefacts that are meaningfully and usefully incorporated to enable sharing of information and transfer of knowledge across intra-organizational boundaries, such as laterally across different strategic business units or vertically across hierarchical levels. Section three draws the two bodies of literature together, conceptualizing strategy tools in practice as boundary objects. This review contributes to knowledge on using strategy tools in practice.
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Few works address methodological issues of how to conduct strategy-as-practice research and even fewer focus on how to analyse the subsequent data in ways that illuminate strategy as an everyday, social practice. We address this gap by proposing a quantitative method for analysing observational data, which can complement more traditional qualitative methodologies. We propose that rigorous but context-sensitive coding of transcripts can render everyday practice analysable statistically. Such statistical analysis provides a means for analytically representing patterns and shifts within the mundane, repetitive elements through which practice is accomplished. We call this approach the Event Database (EDB) and it consists of five basic coding categories that help us capture the stream of practice. Indexing codes help to index or categorise the data, in order to give context and offer some basic information about the event under discussion. Indexing codes are descriptive codes, which allow us to catalogue and classify events according to their assigned characteristics. Content codes are to do with the qualitative nature of the event; this is the essence of the event. It is a description that helps to inform judgements about the phenomenon. Nature codes help us distinguish between discursive and tangible events. We include this code to acknowledge that some events differ qualitatively from other events. Type events are codes abstracted from the data in order to help us classify events based on their description or nature. This involves significantly more judgement than the index codes but consequently is also more meaningful. Dynamics codes help us capture some of the movement or fluidity of events. This category has been included to let us capture the flow of activity over time.