901 resultados para Gross Rating Points (GRP’s)
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Background The use of mobile apps for health and well being promotion has grown exponentially in recent years. Yet, there is currently no app-quality assessment tool beyond “star”-ratings. Objective The objective of this study was to develop a reliable, multidimensional measure for trialling, classifying, and rating the quality of mobile health apps. Methods A literature search was conducted to identify articles containing explicit Web or app quality rating criteria published between January 2000 and January 2013. Existing criteria for the assessment of app quality were categorized by an expert panel to develop the new Mobile App Rating Scale (MARS) subscales, items, descriptors, and anchors. There were sixty well being apps that were randomly selected using an iTunes search for MARS rating. There were ten that were used to pilot the rating procedure, and the remaining 50 provided data on interrater reliability. Results There were 372 explicit criteria for assessing Web or app quality that were extracted from 25 published papers, conference proceedings, and Internet resources. There were five broad categories of criteria that were identified including four objective quality scales: engagement, functionality, aesthetics, and information quality; and one subjective quality scale; which were refined into the 23-item MARS. The MARS demonstrated excellent internal consistency (alpha = .90) and interrater reliability intraclass correlation coefficient (ICC = .79). Conclusions The MARS is a simple, objective, and reliable tool for classifying and assessing the quality of mobile health apps. It can also be used to provide a checklist for the design and development of new high quality health apps.
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The Australian housing sector contributes about a fifth of national greenhouse gas (GHG) emissions. GHG emissions contribute to climate change which leads to an increase in the occurrence or intensity of natural disasters and damage of houses. To ensure housing performance in the face of climate change, various rating tools for residential property have been introduced in different countries. The aim of this paper is to present a preliminary comparison between international and Australian rating tools in terms of purpose, use and sustainability elements for residential property. The methodologies used are to review, classify, compare and identify similarities and differences between rating tools. Two international tools, Building Research Establishment Environmental Assessment Methodology (BREEAM) (UK) and Leadership in Energy and Environmental Design for Homes (LEED-Homes) (USA), will be compared to two Australian tools, Green Star – Multi Unit Residential v1 and EnviroDevelopment. All four rating tools include management, energy, water and material aspects. The findings reveal thirteen elements that fall under three categories: spatial planning, occupants’ health and comfort, and environmental conditions. The variations in different tools may result from differences in local prevailing climate. Not all sustainability elements covered by international rating tools are included in the Australian rating tools. The voluntary nature of the tools implies they are not broadly applied in their respective market and that there is a policy implementation gap. A comprehensive rating tool could be developed in Australia to promote and lessen the confusion about sustainable housing, which in turn assist in improving the supply and demand of sustainable housing.
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The community is the basic unit of urban development, and appropriate assessment tools are needed for communities to evaluate and facilitate decision making concerning sustainable community development and reduce the detrimental effects of urban community actions on the environment. Existing research into sustainable community rating tools focuses primarily on those that are internationally recognized to describe their advantages and future challenges. However, the differences between rating tools due to different regional conditions, situations and characteristics have yet to be addressed. In doing this, this paper examines three sustainable community rating tools in Australia, namely Green Star-Communities PILOT, EnviroDevelopment and VicUrban Sustainability Charter (Master Planned Community Assessment Tool). In order to identify their similarities, differences and advantages these are compared in terms of sustainability coverage, prerequisites, adaptation to locality, scoring and weighting, participation, presentation of results, and application process. These results provide the stakeholders of sustainable community development projects with a better understanding of the available rating tools in Australia and assist with evaluation and decision making.
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Objective Evaluation of scapular posture is an integral component of the clinical assessment of painful neck disorders. The aim of this study was to evaluate agreement between therapist judgements of scapula posture in multiple biomechanical planes in individuals with neck pain. Design Inter-therapist reliability study. Setting Research laboratory. Participants Fifteen participants with chronic neck pain. Main outcome measures Four physiotherapists recorded ratings of scapular orientation (relative to the thorax) in five different scapula postural planes (plane of scapula, sagittal plane, transverse plane, horizontal plane, and vertical plane) under four test conditions (at rest, and during three isometric shoulder conditions) in all participants. Inter-therapist reliability was expressed using both generalized and paired kappa coefficient. Results Following adjustment for expected agreement and the high prevalence of neutral ratings (81%), on average both the generalised kappa (0.37) as well as Cohen's Kappa for the two therapist pairs (0.45 and 0.42) demonstrated only slight to moderate inter-therapist reliability. Conclusions The findings suggest that ratings of scapular posture in individuals with neck pain by visual inspection has only slight to moderate reliability and should only be used in conjunction with other clinical tests when judging scapula function in these patients.
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The safety and performance of bridges could be monitored and evaluated by Structural Health Monitoring (SHM) systems. These systems try to identify and locate the damages in a structure and estimate their severities. Current SHM systems are applied to a single bridge, and they have not been used to monitor the structural condition of a network of bridges. This paper propose a new method which will be used in Synthetic Rating Procedures (SRP) developed by the authors of this paper and utilizes SHM systems for monitoring and evaluating the condition of a network of bridges. Synthetic rating procedures are used to assess the condition of a network of bridges and identify their ratings. As an additional part of the SRP, the method proposed in this paper can continuously monitor the behaviour of a network of bridges and therefore it can assist to prevent the sudden collapses of bridges or the disruptions to their serviceability. The method could be an important part of a bridge management system (BMS) for managers and engineers who work on condition assessment of a network of bridges.
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It is well known that different arguments appeal to different people. We all process information in ways that are adapted to be consistent with our underlying ideologies. These ideologies can sometimes be framed in terms of particular axes or dimensions, which makes it possible to represent some aspects of an ideology as a region in the kind of vector space that is typical of many generalised quantum models. Such models can then be used to explain and predict, in broad strokes, whether a particular argument or proposal is likely to appeal to an individual with a particular ideology. The choice of suitable arguments to bring about desired actions is traditionally part of the art or science of rhetoric, and today's highly polarised society means that this skill is becoming more important than ever. This paper presents a basic model for understanding how different goals will appeal to people with different ideologies, and thus how different rhetorical positions can be adopted to promote the same desired outcome. As an example, we consider different narratives and hence actions with respect to the environment and climate change, an important but currently highly controversial topic.
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Many websites presently provide the facility for users to rate items quality based on user opinion. These ratings are used later to produce item reputation scores. The majority of websites apply the mean method to aggregate user ratings. This method is very simple and is not considered as an accurate aggregator. Many methods have been proposed to make aggregators produce more accurate reputation scores. In the majority of proposed methods the authors use extra information about the rating providers or about the context (e.g. time) in which the rating was given. However, this information is not available all the time. In such cases these methods produce reputation scores using the mean method or other alternative simple methods. In this paper, we propose a novel reputation model that generates more accurate item reputation scores based on collected ratings only. Our proposed model embeds statistical data, previously disregarded, of a given rating dataset in order to enhance the accuracy of the generated reputation scores. In more detail, we use the Beta distribution to produce weights for ratings and aggregate ratings using the weighted mean method. Experiments show that the proposed model exhibits performance superior to that of current state-of-the-art models.
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Ninety-two strong-motion earthquake records from the California region, U.S.A., have been statistically studied using principal component analysis in terms of twelve important standardized strong-motion characteristics. The first two principal components account for about 57 per cent of the total variance. Based on these two components the earthquake records are classified into nine groups in a two-dimensional principal component plane. Also a unidimensional engineering rating scale is proposed. The procedure can be used as an objective approach for classifying and rating future earthquakes.
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The APSIM-Wheat module was used to investigate our present capacity to simulate wheat yields in a semi-arid region of eastern Australia (the Victorian Mallee), where hostile subsoils associated with salinity, sodicity, and boron toxicity are known to limit grain yield. In this study we tested whether the effects of subsoil constraints on wheat growth and production could be modelled with APSIM-Wheat by assuming that either: (a) root exploration within a particular soil layer was reduced by the presence of toxic concentrations of salts, or (b) soil water uptake from a particular soil layer was reduced by high concentration of salts through osmotic effects. After evaluating the improved predictive capacity of the model we applied it to study the interactions between subsoil constraints and seasonal conditions, and to estimate the economic effect that subsoil constraints have on wheat farming in the Victorian Mallee under different climatic scenarios. Although the soils had high levels of salinity, sodicity, and boron, the observed variability in root abundance at different soil layers was mainly related to soil salinity. We concluded that: (i) whether the effect of subsoil limitations on growth and yield of wheat in the Victorian Mallee is driven by toxic, osmotic, or both effects acting simultaneously still requires further research, (ii) at present, the performance of APSIM-Wheat in the region can be improved either by assuming increased values of lower limit for soil water extraction, or by modifying the pattern of root exploration in the soil pro. le, both as a function of soil salinity. The effect of subsoil constraints on wheat yield and gross margin can be expected to be higher during drier than wetter seasons. In this region the interaction between climate and soil properties makes rainfall information alone, of little use for risk management and farm planning when not integrated with cropping systems models.
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Approximately one-third of stroke patients experience depression. Stroke also has a profound effect on the lives of caregivers of stroke survivors. However, depression in this latter population has received little attention. In this study the objectives were to determine which factors are associated with and can be used to predict depression at different points in time after stroke; to compare different depression assessment methods among stroke patients; and to determine the prevalence, course and associated factors of depression among the caregivers of stroke patients. A total of 100 consecutive hospital-admitted patients no older than 70 years of age were followed for 18 months after having their first ischaemic stroke. Depression was assessed according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-III-R), Beck Depression Inventory (BDI), Hamilton Rating Scale (HRSD), Visual Analogue Mood Scale (VAMS), Clinical Global Impression (CGI) and caregiver ratings. Neurological assessments and a comprehensive neuropsychological test battery were performed. Depression in caregivers was assessed by BDI. Depressive symptoms had early onsets in most cases. Mild depressive symptoms were often persistent with little change during the 18-month follow-up, although there was an increase in major depression over the same time interval. Stroke severity was associated with depression especially from 6 to 12 months post-stroke. At the acute phase, older patients were at higher risk of depression, and a higher proportion of men were depressed at 18 months post-stroke. Of the various depression assessment methods, none stood clearly apart from the others. The feasibility of each did not differ greatly, but prevalence rates differed widely according to the different criteria. When compared against DSM-III-R criteria, sensitivity and specificity were acceptable for the CGI, BDI, and HRSD. The CGI and BDI had better sensitivity than the more specific HRSD. The VAMS seemed not to be a reliable method for assessing depression among stroke patients. The caregivers often rated patients depression as more severe than did the patients themselves. Moreover, their ratings seemed to be influenced by their own depression. Of the caregivers, 30-33% were depressed. At the acute phase, caregiver depression was associated with the severity of the stroke and the older age of the patient. The best predictor of caregiver depression at later follow-up was caregiver depression at the acute phase. The results suggest that depression should be assessed during the early post-stroke period and that the follow-up of those at risk of poor emotional outcome should be extended beyond the first year post-stroke. Further, the assessment of well-being of the caregivers of stroke patients should be included as a part of a rehabilitation plan for stroke patients.
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Objective: Attention deficit hyperactivity disorder (ADHD) is a life-long condition, but because of its historical status as a self-remitting disorder of childhood, empirically validated and reliable methods for the assessment of adults are scarce. In this study, the validity and reliability of the Wender Utah Rating Scale (WURS) and the Adult Problem Questionnaire (APQ), which survey childhood and current symptoms of ADHD, respectively, were studied in a Finnish sample. Methods: The self-rating scales were administered to adults with an ADHD diagnosis (n = 38), healthy control participants (n = 41), and adults diagnosed with dyslexia (n = 37). Items of the self-rating scales were subjected to factor analyses, after which the reliability and discriminatory power of the subscales, derived from the factors, were examined. The effects of group and gender on the subscales of both rating scales were studied. Additionally, the effect of age on the subscales of the WURS was investigated. Finally, the diagnostic accuracy of the total scores was studied. Results: On the basis of the factor analyses, a four-factor structure for the WURS and five-factor structure for the APQ had the best fit to the data. All of the subscales of the APQ and three of the WURS achieved sufficient reliability. The ADHD group had the highest scores on all of the subscales of the APQ, whereas two of the subscales of the WURS did not statistically differ between the ADHD and the Dyslexia group. None of the subscales of the WURS or the APQ was associated with the participant's gender. However, one subscale of the WURS describing dysthymia was positively correlated with the participant's age. With the WURS, the probability of a correct positive classification was .59 in the current sample and .21 when the relatively low prevalence of adult ADHD was taken into account. The probabilities of correct positive classifications with the APQ were .71 and .23, respectively. Conclusions: The WURS and the APQ can provide accurate and reliable information of childhood and adult ADHD symptoms, given some important constraints. Classifications made on the basis of the total scores are reliable predictors of ADHD diagnosis only in populations with a high proportion of ADHD and a low proportion of other similar disorders. The subscale scores can provide detailed information of an individual's symptoms if the characteristics and limitations of each domain are taken into account. Improvements are suggested for two subscales of the WURS.
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The current study explored the reasons that primary school teachers reported were tipping points for them in deciding whether or not and when to refer a child to the school student support team for excessive anxiety. Twenty teachers in two Queensland primary schools were interviewed. Content analysis of interview transcripts revealed six themes reflecting teachers' perceived reasons for deciding to refer anxious children: 1)impact on learning; 2)atypical child behavior; 3)repeated difficulties that do not improve over time; 4)poor response to strategies; 5)teachers' need for support; and 6)information from parents/carers. Teachers considered different combinations of reasons, and had many different tipping points for making a referral. Both teacher-and system-level influences impacted referral decisions. Implications and future research are discussed.
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We present a new algorithm for continuation of limit cycles of autonomous systems as a system parameter is varied. The algorithm works in phase space with an ordered set of points on the limit cycle, along with spline interpolation. Currently popular algorithms in bifurcation analysis packages compute time-domain approximations of limit cycles using either shooting or collocation. The present approach seems useful for continuation near saddle homoclinic points, where it encounters a corner while time-domain methods essentially encounter a discontinuity (a relatively short period of rapid variation). Other phase space-based algorithms use rescaled arclength in place of time, but subsequently resemble the time-domain methods. Compared to these, we introduce additional freedom through a variable stretching of arclength based on local curvature, through the use of an auxiliary index-based variable. Several numerical examples are presented. Comparisons with results from the popular package, MATCONT, are favorable close to saddle homoclinic points.
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OBJECTIVES: 1. Analyse current monitoring and logbook data sets, as well as survey and other information,to establish whether these data provide sufficient power to develop critical indicators of fishery performance. 2. Provide a risk analysis that examines the use of age structure and catch rate information for development of critical indicators, and response rules for those criteria, in the absence of other fishery information. 3. Develop a monitoring program that uses commercial vessels from the fishery to provide independent data.
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PURPOSE To develop and test decision tree (DT) models to classify physical activity (PA) intensity from accelerometer output and Gross Motor Function Classification System (GMFCS) classification level in ambulatory youth with cerebral palsy (CP); and 2) compare the classification accuracy of the new DT models to that achieved by previously published cut-points for youth with CP. METHODS Youth with CP (GMFCS Levels I - III) (N=51) completed seven activity trials with increasing PA intensity while wearing a portable metabolic system and ActiGraph GT3X accelerometers. DT models were used to identify vertical axis (VA) and vector magnitude (VM) count thresholds corresponding to sedentary (SED) (<1.5 METs), light PA (LPA) (>/=1.5 and <3 METs) and moderate-to-vigorous PA (MVPA) (>/=3 METs). Models were trained and cross-validated using the 'rpart' and 'caret' packages within R. RESULTS For the VA (VA_DT) and VM decision trees (VM_DT), a single threshold differentiated LPA from SED, while the threshold for differentiating MVPA from LPA decreased as the level of impairment increased. The average cross-validation accuracy for the VC_DT was 81.1%, 76.7%, and 82.9% for GMFCS levels I, II, and III, respectively. The corresponding cross-validation accuracy for the VM_DT was 80.5%, 75.6%, and 84.2%, respectively. Within each GMFCS level, the decision tree models achieved better PA intensity recognition than previously published cut-points. The accuracy differential was greatest among GMFCS level III participants, in whom the previously published cut-points misclassified 40% of the MVPA activity trials. CONCLUSION GMFCS-specific cut-points provide more accurate assessments of MVPA levels in youth with CP across the full spectrum of ambulatory ability.