926 resultados para Evaluations
Resumo:
The SWAT (Study Within A Trial) programme has been established to develop a series of studies that would embed research within research, so as to resolve uncertainties about the effects of different ways of designing, conducting, analyzing and interpreting evaluations of health and social care. It was described in an Education piece in the Journal of Evidence-Based Medicine in 2012. We have now prepared the first example of the design summary for a SWAT, using the template that will be used for other SWAT. This is presented in this article.
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The present study investigated the effects of a continuing professional development (CPD) initiative that provided collaborative group work skills training for primary school teachers. The study collected data from 24 primary school classrooms in different schools in a variety of urban and rural settings. The sample was composed of 332 pupils, aged 9-12 years old, and 24 primary school teachers. Results indicated that the CPD initiative had a significant impact on the attainment of pupils in science. In addition, data indicated that the CPD promoted effective discourse and pupil dialogue during science lessons. Pre-test and post-test observation scores were significantly different in terms of children giving of suggestions or courses of actions, offering of explanations, and telling someone to say something or carry out an action. Increases in effective dialogue were significantly correlated to increased science attainment, and teacher evaluations of the impact of the CPD were positive. Significant correlations were found between teacher evaluation of impact upon pupil learning and increased attainment in science. The design and structure of CPD initiatives and the implications for practice, policy and future research are explored.
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This poster explores the impact of growing up in different socio-political environments in the border areas of the Republic of Ireland (RoI) and Northern Ireland (NI) on adolescents’ evaluations of their religious and national identities. The vast majority of the population of the Republic of Ireland are Catholic and Irish whereas in Northern Ireland, the majority are Protestant and British. 713 adolescents (NI= 415; RoI=298), who categorised their religious identity as Catholic and their nationality as Irish completed the Collective Self – Esteem (CSE) scale (Crocker & Luhtanen, 1990) with reference to either their religious (N=350) or national identity (n=363). The overall rating of CSE for the Irish identity was significantly higher than the rating of CSE for the Catholic Identity. This result was modified by a significant interaction - adolescents in the Republic of Ireland rated the CSE of their Irish nationality higher than those in Northern Ireland (20.99 vs. 19.95), whereas adolescents in Northern Ireland rated the CSE of their Catholic religious identity higher than their peers in the Republic of Ireland (19.97 vs 18.87). Further analysis of the CSE subscales revealed differing patterns of relationships according to the scale. The evaluation of the Public Collective Self-Esteem of national and religious identities were significantly higher in the Republic of Ireland than in Northern Ireland, however Private Collective Self-esteem did not differ according to jurisdiction. These findings are discussed in relation to the social context and current theoretical accounts of collective identification processes.
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This paper presents the preliminary results of geological and geomechanical studies on the laterite stone exploited at Dano quarry in Burkina Faso. The field work described the geological structure of quarry sites and their environment to determine the rocks alteration and the links between the bedrock and lateritic material. Physic-mechanical properties have been studied for assessing the potentiality of this material for lightweight housing, to be completed with thermal and environmental considerations. Some social and economic evaluations are in progress in order to foster its utilization under local conditions. © (2014) Trans Tech Publications, Switzerland.
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Objective: Development and validation of a selective and sensitive LCMS method for the determination of methotrexate polyglutamates in dried blood spots (DBS).
Methods: DBS samples [spiked or patient samples] were prepared by applying blood to Guthrie cards which was then dried at room temperature. The method utilised 6-mm disks punched from the DBS samples (equivalent to approximately 12 μl of whole blood). The simple treatment procedure was based on protein precipitation using perchloric acid followed by solid phase extraction using MAX cartridges. The extracted sample was chromatographed using a reversed phase system involving an Atlantis T3-C18 column (3 μm, 2.1x150 mm) preceded by Atlantis guard column of matching chemistry. Analytes were subjected to LCMS analysis using positive electrospray ionization.
Key Results: The method was linear over the range 5-400 nmol/L. The limits of detection and quantification were 1.6 and 5 nmol/L for individual polyglutamates and 1.5 and 4.5 nmol/L for total polyglutamates, respectively. The method has been applied successfully to the determination of DBS finger-prick samples from 47 paediatric patients and results confirmed with concentrations measured in matched RBC samples using conventional HPLC-UV technique.
Conclusions and Clinical Relevance: The methodology has a potential for application in a range of clinical studies (e.g. pharmacokinetic evaluations or medication adherence assessment) since it is minimally invasive and easy to perform, potentially allowing parents to take blood samples at home. The feasibility of using DBS sampling can be of major value for future clinical trials or clinical care in paediatric rheumatology. © 2014 Hawwa et al.
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n the context of psychosocial oncology research, disseminating study findings to a range of knowledge “end-users” can advance the well-being of diverse patient subgroups and their families. This article details how findings drawn from a study of prostate cancer support groups were repackaged in a knowledge translation website—www.prostatecancerhelpyourself.ubc.ca—using Web 2.0 features. Detailed are five lessons learned from developing the website: the importance of pitching a winning but feasible idea, keeping a focus on interactivity and minimizing text, negotiating with the supplier, building in formal pretests or a pilot test with end-users, and completing formative evaluations based on data collected through Google™ and YouTube™ Analytics. The details are shared to guide the e-knowledge translation efforts of other psychosocial oncology researchers and clinicians.
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Aims: Palliative care in long-term care (LTC) homes is an area of growing concern. Little work has been done to explore innovative ways to identify and care for residents who become palliative. The purpose of this intervention study was to evaluate the implementation of the Palliative Performance Scale (PPS) in LTC. Specifically we explored staff perceptions about implementing the PPS and how it cued staff to initiate palliative care discussion with residents and family when a resident’s health declined.
Methods: This study utilized a qualitative descriptive design that included data from four separate sources: journals of three ‘champions’ who were responsible for leading the implementation of the PPS; staff evaluations of three educational training sessions; minutes from meetings; and 11 interviews from key staff who were involved in the implementation process. Data were analyzed using thematic content analysis.
Results: Staff generally felt positively about using the PPS in LTC and stated that it increased awareness of palliative care and helped identify those residents who were nearing the end of life. There were some barriers to implementing it, such as staff resistance and lack of time to complete it. The importance of having a designated ‘champion’ and effective interdisciplinary communication in addition to widespread training, were identified as successful strategies to facilitate the implementation process.
Conclusion: These study findings support the use of the PPS in LTC and offer some perspective about ways to implement it successfully. Future work is needed to evaluate the PPS in LTC using more rigorous designs.
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There is increasing research and policy interest in the importance of attitudes to learning, learning orientations and learning dispositions (however they are labelled), not only because they influence traditional measures of school achievement but also because they facilitate how well children function at school, with implications for their future learning. This paper reports the findings on pupils’ learning dispositions and attitudes from two separate cohorts of pupils as they progress through upper primary school (Key Stage 2) in 50 schools in Northern Ireland. (These data are drawn from two different longitudinal studies and the data collection period predates the introduction of the new Northern Ireland Curriculum.) Approximately 1200 pupils completed seven scales from the Assessment of Learner-Centred Practices, ALCPs (McCombs and Lauer, 1997) at three time points, at the end of P5 (9 year olds), at the end of P6 (10 years olds) and at the end of P7 (11 year olds). ALCPs draws on an extensive research base that has identified cognitive and motivational dispositions and attitudes that are associated with a positive orientation to learning, and ultimately with positive progress in school (Alexander and Murphy, 1998). Although each scale can be considered separately, the seven scales cluster into two groups: self-efficacy, mastery orientation, active learning strategies and curiosity are all predicted to be pro-learning; and challenge avoidance, work avoidance, and – to a lesser extent – performance orientation, are predicted to be negatively associated with learning. The general trajectory in the children’s self-evaluations shows that they are becoming less pro-learning over time, with significant decreases in their self-ratings of active learning, curiosity, mastery orientation and self-efficacy. At the same time, there is some evidence that they work harder and put more effort into their work but this is not accompanied by maintaining their previous pro-learning motivations and strategies. The pattern is consistently more negative for boys than for girls. There are very few differences between the two cohorts indicating that the pattern is not confined to a specific cohort. These findings are challenging and will be interrogated with regard to two questions – are the changes related to the influence of the children’s school experiences per se or are they more related to developmental differences as children adopt more critical appraisals of their personal attributes and efforts as they get older? Whatever the reason, these learning dispositions and attitudes are important as they contribute significantly to school achievement even when the more traditional predictors like gender and ability are taken into account.
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This paper argues that biometric verification evaluations can obscure vulnerabilities that increase the chances that an attacker could be falsely accepted. This can occur because existing evaluations implicitly assume that an imposter claiming a false identity would claim a random identity rather than consciously selecting a target to impersonate. This paper shows how an attacker can select a target with a similar biometric signature in order to increase their chances of false acceptance. It demonstrates this effect using a publicly available iris recognition algorithm. The evaluation shows that the system can be vulnerable to attackers targeting subjects who are enrolled with a smaller section of iris due to occlusion. The evaluation shows how the traditional DET curve analysis conceals this vulnerability. As a result, traditional analysis underestimates the importance of an existing score normalisation method for addressing occlusion. The paper concludes by evaluating how the targeted false acceptance rate increases with the number of available targets. Consistent with a previous investigation of targeted face verification performance, the experiment shows that the false acceptance rate can be modelled using the traditional FAR measure with an additional term that is proportional to the logarithm of the number of available targets.
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When applying biometric algorithms to forensic verification, false acceptance and false rejection can mean a failure to identify a criminal, or worse, lead to the prosecution of individuals for crimes they did not commit. It is therefore critical that biometric evaluations be performed as accurately as possible to determine their legitimacy as a forensic tool. This paper argues that, for forensic verification scenarios, traditional performance measures are insufficiently accurate. This inaccuracy occurs because existing verification evaluations implicitly assume that an imposter claiming a false identity would claim a random identity rather than consciously selecting a target to impersonate. In addition to describing this new vulnerability, the paper describes a novel Targeted.. FAR metric that combines the traditional False Acceptance Rate (FAR) measure with a term that indicates how performance degrades with the number of potential targets. The paper includes an evaluation of the effects of targeted impersonation on an existing academic face verification system. This evaluation reveals that even with a relatively small number of targets false acceptance rates can increase significantly, making the analysed biometric systems unreliable.
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In a Bayesian learning setting, the posterior distribution of a predictive model arises from a trade-off between its prior distribution and the conditional likelihood of observed data. Such distribution functions usually rely on additional hyperparameters which need to be tuned in order to achieve optimum predictive performance; this operation can be efficiently performed in an Empirical Bayes fashion by maximizing the posterior marginal likelihood of the observed data. Since the score function of this optimization problem is in general characterized by the presence of local optima, it is necessary to resort to global optimization strategies, which require a large number of function evaluations. Given that the evaluation is usually computationally intensive and badly scaled with respect to the dataset size, the maximum number of observations that can be treated simultaneously is quite limited. In this paper, we consider the case of hyperparameter tuning in Gaussian process regression. A straightforward implementation of the posterior log-likelihood for this model requires O(N^3) operations for every iteration of the optimization procedure, where N is the number of examples in the input dataset. We derive a novel set of identities that allow, after an initial overhead of O(N^3), the evaluation of the score function, as well as the Jacobian and Hessian matrices, in O(N) operations. We prove how the proposed identities, that follow from the eigendecomposition of the kernel matrix, yield a reduction of several orders of magnitude in the computation time for the hyperparameter optimization problem. Notably, the proposed solution provides computational advantages even with respect to state of the art approximations that rely on sparse kernel matrices.
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The momentum term has long been used in machine learning algorithms, especially back-propagation, to improve their speed of convergence. In this paper, we derive an expression to prove the O(1/k2) convergence rate of the online gradient method, with momentum type updates, when the individual gradients are constrained by a growth condition. We then apply these type of updates to video background modelling by using it in the update equations of the Region-based Mixture of Gaussians algorithm. Extensive evaluations are performed on both simulated data, as well as challenging real world scenarios with dynamic backgrounds, to show that these regularised updates help the mixtures converge faster than the conventional approach and consequently improve the algorithm’s performance.
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We describe, for the first time, hydrogel-forming microneedle arrays prepared from "super swelling" polymeric compositions. We produced a microneedle formulation with enhanced swelling capabilities from aqueous blends containing 20% w/w Gantrez S-97, 7.5% w/w PEG 10,000 and 3% w/w Na2CO3 and utilised a drug reservoir of a lyophilised wafer-like design. These microneedle-lyophilised wafer compositions were robust and effectively penetrated skin, swelling extensively, but being removed intact. In in vitro delivery experiments across excised neonatal porcine skin, approximately 44 mg of the model high dose small molecule drug ibuprofen sodium was delivered in 24 h, equating to 37% of the loading in the lyophilised reservoir. The super swelling microneedles delivered approximately 1.24 mg of the model protein ovalbumin over 24 h, equivalent to a delivery efficiency of approximately 49%. The integrated microneedle-lyophilised wafer delivery system produced a progressive increase in plasma concentrations of ibuprofen sodium in rats over 6 h, with a maximal concentration of approximately 179 µg/ml achieved in this time. The plasma concentration had fallen to 71±6.7 µg/ml by 24 h. Ovalbumin levels peaked in rat plasma after only 1 hour at 42.36±17.01 ng/ml. Ovalbumin plasma levels then remained almost constant up to 6 h, dropping somewhat at 24 h, when 23.61±4.84 ng/ml was detected. This work represents a significant advancement on conventional microneedle systems, which are presently only suitable for bolus delivery of very potent drugs and vaccines. Once fully developed, such technology may greatly expand the range of drugs that can be delivered transdermally, to the benefit of patients and industry. Accordingly, we are currently progressing towards clinical evaluations with a range of candidate molecules.
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Evidence is mounting on the association between the built environment and physical activity (PA) with a call for intervention research. A broader approach which recognizes the role of supportive environments that can make healthy choices easier is required. A systematic review was undertaken to assess the effectiveness of interventions to encourage PA in urban green space. Five databases were searched independently by two reviewers using search terms relating to 'physical activity', 'urban green space' and 'intervention' in July 2014. Eligibility criteria included: (i) intervention to encourage PA in urban green space which involved either a physical change to the urban green space or a PA intervention to promote use of urban green space or a combination of both; and (ii) primary outcome of PA. Of the 2405 studies identified, 12 were included. There was some evidence (4/9 studies showed positive effect) to support built environment only interventions for encouraging use and increasing PA in urban green space. There was more promising evidence (3/3 studies showed positive effect) to support PAprograms or PA programs combined with a physical change to the built environment, for increasing urban green space use and PAof users. Recommendations for future research include the need for longer term follow-up post-intervention, adequate control groups, sufficiently powered studies, and consideration of the social environment, which was identified as a significantly under-utilized resource in this area. Interventions that involve the use of PA programs combined with a physical change to the built environment are likely to have a positive effect on PA. Robust evaluations of such interventions are urgently required. The findings provide a platform to inform the design, implementation and evaluation of future urban green space and PAintervention research.
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Vector space models (VSMs) represent word meanings as points in a high dimensional space. VSMs are typically created using a large text corpora, and so represent word semantics as observed in text. We present a new algorithm (JNNSE) that can incorporate a measure of semantics not previously used to create VSMs: brain activation data recorded while people read words. The resulting model takes advantage of the complementary strengths and weaknesses of corpus and brain activation data to give a more complete representation of semantics. Evaluations show that the model 1) matches a behavioral measure of semantics more closely, 2) can be used to predict corpus data for unseen words and 3) has predictive power that generalizes across brain imaging technologies and across subjects. We believe that the model is thus a more faithful representation of mental vocabularies.