979 resultados para Stated preference methods
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Early intervention for hazardous alcohol use has been shown repeatedly to be effective in reducing alcohol consumption, limiting alcohol-related problems and improving biochemical parameters. However, in most studies the follow-up period has been 2 years or less. The current paper presents progress on a 10-year follow-up of a randomized controlled trial of early intervention. Methods used for tracing subjects and ensuring minimal refusals are detailed. The intensity of effort required to locate subjects is documented and recommendations for ensuring good follow-up rates are made. At completion of follow-up, 72.5% of the sample reviewed here and 78.2% of the total cohort had been traced. Our experiences demonstrate that long-term follow-up is feasible, given sufficient planning and persistence.
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I noted with interest the article by Drs Perrin and Guex, entitled &dquo;Edema and leg volume: Methods of assessment,&dquo; published in Angiology 51:9-12, 2000. This was a timely and comprehensive review of the various methods in clinical use for the assessment of peripheral edema, notably in the leg. I would like to take this opportunity to alert readers to a further technique useful for this purpose, namely, bioelectrical impedance analysis. An early reportl described its use for the measurement of edema in the leg, but other than its successful use for the assessment of edema in the arm following masteCtoMy,2,1 the potential of the method remains to be fully realized. This is unfortunate since the method directly and quantifiably measures edema.
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Depending on the size and shape of the materials, methods employed to achieve effective fluidization during fluid bed drying varies from use of simple hole distributors for small, light weight materials to special techniques for lager and/or moist materials. This paper reviews common air distributors used in fluidized bed drying of food particulates. Also it reviews special methods of fluidizing larger irregular food particulates.
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A number of techniques have been developed to study the disposition of drugs in the head and, in particular, the role of the blood-brain barrier (BBB) in drug uptake. The techniques can be divided into three groups: in-vitro, in-vivo and in-situ. The most suitable method depends on the purpose(s) and requirements of the particular study being conducted. In-vitro techniques involve the isolation of cerebral endothelial cells so that direct investigations of these cells can be carried out. The most recent preparations are able to maintain structural and functional characteristics of the BBB by simultaneously culturing endothelial cells with astrocytic cells,The main advantages of the in-vitro methods are the elimination of anaesthetics and surgery. In-vivo methods consist of a diverse range of techniques and include the traditional Brain Uptake Index and indicator diffusion methods, as well as microdialysis and positron emission tomography. In-vivo methods maintain the cells and vasculature of an organ in their normal physiological states and anatomical position within the animal. However, the shortcomings include renal acid hepatic elimination of solutes as well as the inability to control blood flow. In-situ techniques, including the perfused head, are more technically demanding. However, these models have the ability to vary the composition and flow rate of the artificial perfusate. This review is intended as a guide for selecting the most appropriate method for studying drug uptake in the brain.
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Background: A variety of methods for prediction of peptide binding to major histocompatibility complex (MHC) have been proposed. These methods are based on binding motifs, binding matrices, hidden Markov models (HMM), or artificial neural networks (ANN). There has been little prior work on the comparative analysis of these methods. Materials and Methods: We performed a comparison of the performance of six methods applied to the prediction of two human MHC class I molecules, including binding matrices and motifs, ANNs, and HMMs. Results: The selection of the optimal prediction method depends on the amount of available data (the number of peptides of known binding affinity to the MHC molecule of interest), the biases in the data set and the intended purpose of the prediction (screening of a single protein versus mass screening). When little or no peptide data are available, binding motifs are the most useful alternative to random guessing or use of a complete overlapping set of peptides for selection of candidate binders. As the number of known peptide binders increases, binding matrices and HMM become more useful predictors. ANN and HMM are the predictive methods of choice for MHC alleles with more than 100 known binding peptides. Conclusion: The ability of bioinformatic methods to reliably predict MHC binding peptides, and thereby potential T-cell epitopes, has major implications for clinical immunology, particularly in the area of vaccine design.
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Background. The importance of general practice involvement in the care of attention-deficit/hyperactivity disorder (ADHD) is increasing due to the rising numbers of patients who present with the disorder. It has been suggested by consensus bodies that GPs should be identifying and referring patients at the severe end of the ADHD spectrum and managing those with less severe symptoms. However, GPs' views of their role in ADHD care are unknown. Objective. Our aim was to explore the attitudes and practices of Australian GPs towards the diagnosis and management of ADHD. Methods. We conducted a series of focus groups to explore GPs' beliefs regarding the causes of ADHD, their perceived role in ADHD diagnosis and management and their views on the role of behaviour therapies and pharmacotherapies in ADHD management. The subjects were 28 GPs in six focus groups. Results. GPs in this study did not want to be the primary providers of care for patients with ADHD. Participants indicated a preference to refer the patient to medical specialists for diagnosis and treatment of ADHD, and expressed low levels of interest in becoming highly involved in ADHD care. Concerns about overdiagnosis and misdiagnosis of the disorder, diagnostic complexity, time constraints, insufficient education and training about the disorder, and concerns regarding misuse and diversion of stimulant medications were the reasons cited for their lack of willingness. Conclusions. The Australian GPs in this study identify a role for themselves in ADHD care which is largely supportive in nature, and involves close liaison with specialist services.
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Estimating energy requirements is necessary in clinical practice when indirect calorimetry is impractical. This paper systematically reviews current methods for estimating energy requirements. Conclusions include: there is discrepancy between the characteristics of populations upon which predictive equations are based and current populations; tools are not well understood, and patient care can be compromised by inappropriate application of the tools. Data comparing tools and methods are presented and issues for practitioners are discussed. (C) 2003 International Life Sciences Institute.
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Taking functional programming to its extremities in search of simplicity still requires integration with other development (e.g. formal) methods. Induction is the key to deriving and verifying functional programs, but can be simplified through packaging proofs with functions, particularly folds, on data (structures). Totally Functional Programming avoids the complexities of interpretation by directly representing data (structures) as platonic combinators - the functions characteristic to the data. The link between the two simplifications is that platonic combinators are a kind of partially-applied fold, which means that platonic combinators inherit fold-theoretic properties, but with some apparent simplifications due to the platonic combinator representation. However, despite observable behaviour within functional programming that suggests that TFP is widely-applicable, significant work remains before TFP as such could be widely adopted.
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Objective: The Assessing Cost-Effectiveness - Mental Health (ACE-MH) study aims to assess from a health sector perspective, whether there are options for change that could improve the effectiveness and efficiency of Australia's current mental health services by directing available resources toward 'best practice' cost-effective services. Method: The use of standardized evaluation methods addresses the reservations expressed by many economists about the simplistic use of League Tables based on economic studies confounded by differences in methods, context and setting. The cost-effectiveness ratio for each intervention is calculated using economic and epidemiological data. This includes systematic reviews and randomised controlled trials for efficacy, the Australian Surveys of Mental Health and Wellbeing for current practice and a combination of trials and longitudinal studies for adherence. The cost-effectiveness ratios are presented as cost (A$) per disability-adjusted life year (DALY) saved with a 95% uncertainty interval based on Monte Carlo simulation modelling. An assessment of interventions on 'second filter' criteria ('equity', 'strength of evidence', 'feasibility' and 'acceptability to stakeholders') allows broader concepts of 'benefit' to be taken into account, as well as factors that might influence policy judgements in addition to cost-effectiveness ratios. Conclusions: The main limitation of the study is in the translation of the effect size from trials into a change in the DALY disability weight, which required the use of newly developed methods. While comparisons within disorders are valid, comparisons across disorders should be made with caution. A series of articles is planned to present the results.
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It is largely known that the range of an insect diet is mostly determined by oviposition behavior, mainly in species with endophytic larvae such as Zabrotes subfasciatus. However, the proximate factors determining host choice and the subsequent steps leading to the expansion or reduction of the host number and occasional host shifts are largely unknown. We analyzed various factors determining host preference of Z. subfasciatus through the evaluation of: (i) oviposition preference of a wild population of Z subfasciatus on the usual host (bean) and unusual hosts (lentil, chickpea and soy), and the performance of the offspring; (ii) artificial selection for increasing preference for hosts initially less frequently chosen; (iii) comparison of oviposition behavior between two different populations (reared for similar to 30 generations in beans or chickpeas, respectively); (iv) oviposition timing on usual and unusual hosts; and (v) identification of preference hierarchies. We found that when using unusual hosts, there is no correlation between performance and preference and that the preference hierarchy changes only slightly when the population passes through several generations on the less frequently accepted host. We also found a positive response to artificial selection for increasing oviposition on the less preferred host; however, when the host-choice experiment involved two varieties of the usual host, the response was faster than when the choice involved usual and unusual hosts. Finally, beetles reared on an unusual host (chickpea) for 26 generations showed similar good fitness on both usual and unusual hosts, indicating that the use of a new host does not necessarily result in the loss of performance on the original host. Nevertheless, this population showed lower fitness on the usual host than that of the original population, suggesting an underlying partial trade-off phenomenon which may contribute to a broadening of diet of this insect species.
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Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.
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Analytical and bioanalytical methods of high-performance liquid chromatography with fluorescence detection (HPLC-FLD) were developed and validated for the determination of chloroaluminum phthalocyanine in different formulations of polymeric nanocapsules, plasma and livers of mice. Plasma and homogenized liver samples were extracted with ethyl acetate, and zinc phthalocyanine was used as internal standard. The results indicated that the methods were linear and selective for all matrices studied. Analysis of accuracy and precision showed adequate values, with variations lower than 10% in biological samples and lower than 2% in analytical samples. The recoveries were as high as 96% and 99% in the plasma and livers, respectively. The quantification limit of the analytical method was 1.12 ng/ml, and the limits of quantification of the bioanalytical method were 15 ng/ml and 75 ng/g for plasma and liver samples, respectively. The bioanalytical method developed was sensitive in the ranges of 15-100 ng/ml in plasma and 75-500 ng/g in liver samples and was applied to studies of biodistribution and pharmacokinetics of AlClPc. (C) 2011 Elsevier B.V. All rights reserved.
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The elevated plus-maze is an animal model of anxiety used to study the effect of different drugs on the behavior of the animal It consists of a plus-shaped maze with two open and two closed arms elevated 50 cm from the floor The standard measures used to characterize exploratory behavior in the elevated plus-maze are the time spent and the number of entries in the open arms In this work we use Markov chains to characterize the exploratory behavior of the rat in the elevated plus-maze under three different conditions normal and under the effects of anxiogenic and anxiolytic drugs The spatial structure of the elevated plus-maze is divided into squares which are associated with states of a Markov chain By counting the frequencies of transitions between states during 5-min sessions in the elevated plus-maze we constructed stochastic matrices for the three conditions studied The stochastic matrices show specific patterns which correspond to the observed behaviors of the rat under the three different conditions For the control group the stochastic matrix shows a clear preference for places in the closed arms This preference is enhanced for the anxiogenic group For the anxiolytic group the stochastic matrix shows a pattern similar to a random walk Our results suggest that Markov chains can be used together with the standard measures to characterize the rat behavior in the elevated plus-maze (C) 2010 Elsevier B V All rights reserved