Reference bias : presentation of extreme health states prior to EQ-VAS improves health-related quality of life scores. A randomised crossover trial.

Background: Clinical practice and clinical research has made a concerted effort to move beyond the use of clinical indicators alone and embrace patient focused care through the use of patient reported outcomes such as healthrelated quality of life. However, unless patients give consistent consideration to the health states that give meaning to measurement scales used to evaluate these constructs, longitudinal comparison of these measures may be invalid. This study aimed to investigate whether patients give consideration to a standard health state rating scale (EQ-VAS) and whether consideration of good and poor health state descriptors immediately changes their selfreport. Methods: A randomised crossover trial was implemented amongst hospitalised older adults (n = 151). Patients were asked to consider descriptions of extremely good (Description-A) and poor (Description-B) health states. The EQ-VAS was administered as a self-report at baseline, after the first descriptors (A or B), then again after the remaining descriptors (B or A respectively). At baseline patients were also asked if they had considered either EQVAS anchors. Results: Overall 106/151 (70%) participants changed their self-evaluation by ≥5 points on the 100 point VAS, with a mean (SD) change of +4.5 (12) points (p < 0.001). A total of 74/151 (49%) participants did not consider the best health VAS anchor, of the 77 who did 59 (77%) thought the good health descriptors were more extreme (better) then they had previously considered. Similarly 85/151 (66%) participants did not consider the worst health anchor of the 66 who did 63 (95%) thought the poor health descriptors were more extreme (worse) then they had previously considered. Conclusions: Health state self-reports may not be well considered. An immediate significant shift in response can be elicited by exposure to a mere description of an extreme health state despite no actual change in underlying health state occurring. Caution should be exercised in research and clinical settings when interpreting subjective patient reported outcomes that are dependent on brief anchors for meaning. Trial Registration: Australian and New Zealand Clinical Trials Registry (#ACTRN12607000606482) http://www.anzctr. org.au

Response shift, recall bias and their effect on measuring change in health-related quality of life amongst older hospital patients

Background: Assessments of change in subjective patient reported outcomes such as health-related quality of life (HRQoL) are a key component of many clinical and research evaluations. However, conventional longitudinal evaluation of change may not agree with patient perceived change if patients' understanding of the subjective construct under evaluation changes over time (response shift) or if patients' have inaccurate recollection (recall bias). This study examined whether older adults' perception of change is in agreement with conventional longitudinal evaluation of change in their HRQoL over the duration of their hospital stay. It also investigated this level of agreement after adjusting patient perceived change for recall bias that patients may have experienced. Methods: A prospective longitudinal cohort design nested within a larger randomised controlled trial was implemented. 103 hospitalised older adults participated in this investigation at a tertiary hospital facility. The EQ-5D utility and Visual Analogue Scale (VAS) scores were used to evaluate HRQoL. Participants completed EQ-5D reports as soon as they were medically stable (within three days of admission) then again immediately prior to discharge. Three methods of change score calculation were used (conventional change, patient perceived change and patient perceived change adjusted for recall bias). Agreement was primarily investigated using intraclass correlation coefficients (ICC) and limits of agreement. Results: Overall 101 (98%) participants completed both admission and discharge assessments. The mean (SD) age was 73.3 (11.2). The median (IQR) length of stay was 38 (20-60) days. For agreement between conventional longitudinal change and patient perceived change: ICCs were 0.34 and 0.40 for EQ-5D utility and VAS respectively. For agreement between conventional longitudinal change and patient perceived change adjusted for recall bias: ICCs were 0.98 and 0.90 respectively. Discrepancy between conventional longitudinal change and patient perceived change was considered clinically meaningful for 84 (83.2%) of participants, after adjusting for recall bias this reduced to 8 (7.9%). Conclusions: Agreement between conventional change and patient perceived change was not strong. A large proportion of this disagreement could be attributed to recall bias. To overcome the invalidating effect of response shift (on conventional change) and recall bias (on patient perceived change) a method of adjusting patient perceived change for recall bias has been described.

Evidence of disagreement between patient-perceived change and conventional longitudinal evaluation of change in health-related quality of life among older adults

Objective: To identify agreement levels between conventional longitudinal evaluation of change (post–pre) and patient-perceived change (post–then test) in health-related quality of life. Design: A prospective cohort investigation with two assessment points (baseline and six-month follow-up) was implemented. Setting: Community rehabilitation setting. Subjects: Frail older adults accessing community-based rehabilitation services. Intervention: Nil as part of this investigation. Main measures: Conventional longitudinal change in health-related quality of life was considered the difference between standard EQ-5D assessments completed at baseline and follow-up. To evaluate patient-perceived change a ‘then test’ was also completed at the follow-up assessment. This required participants to report (from their current perspective) how they believe their health-related quality of life was at baseline (using the EQ-5D). Patient-perceived change was considered the difference between ‘then test’ and standard follow-up EQ-5D assessments. Results: The mean (SD) age of participants was 78.8 (7.3). Of the 70 participants 62 (89%) of data sets were complete and included in analysis. Agreement between conventional (post–pre) and patient-perceived (post–then test) change was low to moderate (EQ-5D utility intraclass correlation coefficient (ICC)¼0.41, EQ-5D visual analogue scale (VAS) ICC¼0.21). Neither approach inferred greater change than the other (utility P¼0.925, VAS P¼0.506). Mean (95% confidence interval (CI)) conventional change in EQ-5D utility and VAS were 0.140 (0.045,0.236) and 8.8 (3.3,14.3) respectively, while patient-perceived change was 0.147 (0.055,0.238) and 6.4 (1.7,11.1) respectively. Conclusions: Substantial disagreement exists between conventional longitudinal evaluation of change in health-related quality of life and patient-perceived change in health-related quality of life (as measured using a then test) within individuals.

Physical function and health-related quality of life of older adults undergoing hospital rehabilitation : how strong is the association?

The purpose of this research is to report preliminary empirical evidence regarding the association between common physical performance measures and health-related quality of life (HRQoL) of hospitalized older adults recovering from illness and injury. Frequently, these patients do not return to premorbid levels of independence and physical ability. Rehabilitation for this population often focuses on improving physical functioning and mobility with the intention of maximizing their HRQoL for discharge and thereafter. For this reason, longitudinal use of physical performance measures as an indicator of improvement in physical functioning (and thus HRQoL) is common. Although this is a logical approach, there have been mixed results from previous investigations into the association between common measures of physical function and HRQoL amongst other adult patient populations.1,2 There has been no previous investigation reporting the association between HRQoL and a variety of common physical performance measures in hospitalized older adults.

Preparing quality teachers : making learning visible

Teacher quality is recognised as a lynchpin for education reforms internationally, and both Federal and State governments in Australia have turned their attention to teacher education institutions: the starting point for preparing quality teachers. Changes to policy and shifts in expectations impact on Faculties of Education, despite the fact that little is known about what makes a quality teacher preparation program effective. New accountability measures, mandated Professional Standards, and proposals to test all graduates before registration, mean that teacher preparation programs need capacity for flexibility and responsiveness. The risk is that undergraduate degree programs can become ‘patchwork quilts’ with traces of the old and new stitched together, sometimes at the expense of coherence and integrity. This paper provides a roadmap used by one large Faculty of Education in Queensland for reforming and reconceptualising the curriculum for a 4-year undergraduate program, in response to new demands from government and the professional bodies.

Clinical indicators of quality for Australian residential aged care facilities : establishing reliability, validity, and quality thresholds

Background: In response to the need for more comprehensive quality assessment within Australian residential aged care facilities, the Clinical Care Indicator (CCI) Tool was developed to collect outcome data as a means of making inferences about quality. A national trial of its effectiveness and a Brisbane-based trial of its use within the quality improvement context determined the CCI Tool represented a potentially valuable addition to the Australian aged care system. This document describes the next phase in the CCI Tool.s development; the aims of which were to establish validity and reliability of the CCI Tool, and to develop quality indicator thresholds (benchmarks) for use in Australia. The CCI Tool is now known as the ResCareQA (Residential Care Quality Assessment). Methods: The study aims were achieved through a combination of quantitative data analysis, and expert panel consultations using modified Delphi process. The expert panel consisted of experienced aged care clinicians, managers, and academics; they were initially consulted to determine face and content validity of the ResCareQA, and later to develop thresholds of quality. To analyse its psychometric properties, ResCareQA forms were completed for all residents (N=498) of nine aged care facilities throughout Queensland. Kappa statistics were used to assess inter-rater and test-retest reliability, and Cronbach.s alpha coefficient calculated to determine internal consistency. For concurrent validity, equivalent items on the ResCareQA and the Resident Classification Scales (RCS) were compared using Spearman.s rank order correlations, while discriminative validity was assessed using known-groups technique, comparing ResCareQA results between groups with differing care needs, as well as between male and female residents. Rank-ordered facility results for each clinical care indicator (CCI) were circulated to the panel; upper and lower thresholds for each CCI were nominated by panel members and refined through a Delphi process. These thresholds indicate excellent care at one extreme and questionable care at the other. Results: Minor modifications were made to the assessment, and it was renamed the ResCareQA. Agreement on its content was reached after two Delphi rounds; the final version contains 24 questions across four domains, enabling generation of 36 CCIs. Both test-retest and inter-rater reliability were sound with median kappa values of 0.74 (test-retest) and 0.91 (inter-rater); internal consistency was not as strong, with a Chronbach.s alpha of 0.46. Because the ResCareQA does not provide a single combined score, comparisons for concurrent validity were made with the RCS on an item by item basis, with most resultant correlations being quite low. Discriminative validity analyses, however, revealed highly significant differences in total number of CCIs between high care and low care groups (t199=10.77, p=0.000), while the differences between male and female residents were not significant (t414=0.56, p=0.58). Clinical outcomes varied both within and between facilities; agreed upper and lower thresholds were finalised after three Delphi rounds. Conclusions: The ResCareQA provides a comprehensive, easily administered means of monitoring quality in residential aged care facilities that can be reliably used on multiple occasions. The relatively modest internal consistency score was likely due to the multi-factorial nature of quality, and the absence of an aggregate result for the assessment. Measurement of concurrent validity proved difficult in the absence of a gold standard, but the sound discriminative validity results suggest that the ResCareQA has acceptable validity and could be confidently used as an indication of care quality within Australian residential aged care facilities. The thresholds, while preliminary due to small sample size, enable users to make judgements about quality within and between facilities. Thus it is recommended the ResCareQA be adopted for wider use.

Infrared and infrared emission spectroscopy of nesquehonite Mg(OH)(HCO3)•2H2O : implications for the formula of nesquehonite

The mineral nesquehonite Mg(OH)(HCO3)•2H2O has been analysed by a combination of infrared (IR) and infrared emission spectroscopy (IES). Both techniques show OH vibrations, both stretching and deformation modes. IES proves the OH units are stable up to 450°C. The strong IR band at 934 cm-1 is evidence for MgOH deformation modes supporting the concept of HCO3- units in the molecular structure. Infrared bands at 1027, 1052 and 1098 cm-1 are attributed to the symmetric stretching modes of HCO3- and CO32- units. Infrared bands at 1419, 1439, 1511, and 1528 cm-1 are assigned to the antisymmetric stretching modes of CO32- and HCO3- units. IES supported by thermoanalytical results defines the thermal stability of nesquehonite IES defines the changes in the molecular structure of nesquehonite with temperature. The results of IR and IES supports the concept that the formula of nesquehonite is better defined as Mg(OH)(HCO3)•2H2O.

An analytical method to solve a general class of nonlinear reactive transport models

Three recent papers published in Chemical Engineering Journal studied the solution of a model of diffusion and nonlinear reaction using three different methods. Two of these studies obtained series solutions using specialized mathematical methods, known as the Adomian decomposition method and the homotopy analysis method. Subsequently it was shown that the solution of the same particular model could be written in terms of a transcendental function called Gauss’ hypergeometric function. These three previous approaches focused on one particular reactive transport model. This particular model ignored advective transport and considered one specific reaction term only. Here we generalize these previous approaches and develop an exact analytical solution for a general class of steady state reactive transport models that incorporate (i) combined advective and diffusive transport, and (ii) any sufficiently differentiable reaction term R(C). The new solution is a convergent Maclaurin series. The Maclaurin series solution can be derived without any specialized mathematical methods nor does it necessarily involve the computation of any transcendental function. Applying the Maclaurin series solution to certain case studies shows that the previously published solutions are particular cases of the more general solution outlined here. We also demonstrate the accuracy of the Maclaurin series solution by comparing with numerical solutions for particular cases.

The conversion of lignocellulosics to levulinic acid

Biomass represents an abundant and relatively low cost carbon resource that can be utilized to produce platform chemicals such as levulinic acid. Current processing technology limits the cost-effective production of levulinic acid in commercial quantities from biomass. The key to improving the yield and effi ciency of levulinic acid production from biomass lies in the ability to optimize and isolate the intermediate products at each step of the reaction pathway and reduce re-polymerization and side reactions. New technologies (including the use of microwave irradiation and ionic liquids) and the development of highly selective catalysts would provide the necessary step change for the optimization of key reactions. A processing environment that allows the use of biphasic systems and/or continuous extraction of products would increase reaction rates, yields and product quality. This review outlines the chemistry of levulinic acid synthesis and discusses current and potential technologies for producing levulinic acid from lignocellulosics.

Variability of input parameters related to pollutants build-up in stormwater quality modelling

The variability of input parameters is the most important source of overall model uncertainty. Therefore, an in-depth understanding of the variability is essential for uncertainty analysis of stormwater quality model outputs. This paper presents the outcomes of a research study which investigated the variability of pollutants build-up characteristics on road surfaces in residential, commercial and industrial land uses. It was found that build-up characteristics vary highly even within the same land use. Additionally, industrial land use showed relatively higher variability of maximum build-up, build-up rate and particle size distribution, whilst the commercial land use displayed a relatively higher variability of pollutant-solid ratio. Among the various build-up parameters analysed, D50 (volume-median-diameter) displayed the relatively highest variability for all three land uses.

Establishing a quality franchise relationship in Taiwan : Investigating relationships between relationship quality, loyalty and cooperation

Franchised convenience stores successfully operate throughout Taiwan, but the convenience store market is approaching saturation point. Creating a cooperative long-term franchising relationship between franchisors and franchisees is essential to maintain the proportion of convenience stores...

Essays on irrigation development, farm production and unaccounted costs : theory and empirical evidence

A review of the literature related to issues involved in irrigation induced agricultural development (IIAD) reveals that: (1) the magnitude, sensitivity and distribution of social welfare of IIAD is not fully analysed; (2) the impacts of excessive pesticide use on farmers’ health are not adequately explained; (3) no analysis estimates the relationship between farm level efficiency and overuse of agro-chemical inputs under imperfect markets; and (4) the method of incorporating groundwater extraction costs is misleading. This PhD thesis investigates these issues by using primary data, along with secondary data from Sri Lanka. The overall findings of the thesis can be summarised as follows. First, the thesis demonstrates that Sri Lanka has gained a positive welfare change as a result of introducing new irrigation technology. The change in the consumer surplus is Rs.48,236 million, while the change in the producer surplus is Rs. 14,274 millions between 1970 and 2006. The results also show that the long run benefits and costs of IIAD depend critically on the magnitude of the expansion of the irrigated area, as well as the competition faced by traditional farmers (agricultural crowding out effects). The traditional sector’s ability to compete with the modern sector depends on productivity improvements, reducing production costs and future structural changes (spillover effects). Second, the thesis findings on pesticides used for agriculture show that, on average, a farmer incurs a cost of approximately Rs. 590 to 800 per month during a typical cultivation period due to exposure to pesticides. It is shown that the value of average loss in earnings per farmer for the ‘hospitalised’ sample is Rs. 475 per month, while it is approximately Rs. 345 per month for the ‘general’ farmers group during a typical cultivation season. However, the average willingness to pay (WTP) to avoid exposure to pesticides is approximately Rs. 950 and Rs. 620 for ‘hospitalised’ and ‘general’ farmers’ samples respectively. The estimated percentage contribution for WTP due to health costs, lost earnings, mitigating expenditure, and disutility are 29, 50, 5 and 16 per cent respectively for hospitalised farmers, while they are 32, 55, 8 and 5 per cent respectively for ‘general’ farmers. It is also shown that given market imperfections for most agricultural inputs, farmers are overusing pesticides with the expectation of higher future returns. This has led to an increase in inefficiency in farming practices which is not understood by the farmers. Third, it is found that various groundwater depletion studies in the economics literature have provided misleading optimal water extraction quantity levels. This is due to a failure to incorporate all production costs in the relevant models. It is only by incorporating quality changes to quantity deterioration, that it is possible to derive socially optimal levels. Empirical results clearly show that the benefits per hectare per month considering both the avoidance costs of deepening agro-wells by five feet from the existing average, as well as the avoidance costs of maintaining the water salinity level at 1.8 (mmhos/Cm), is approximately Rs. 4,350 for farmers in the Anuradhapura district and Rs. 5,600 for farmers in the Matale district.

Evaluating the influences of stakeholder management on construction project quality

The issue of ensuring that construction projects achieve high quality outcomes continues to be an important consideration for key project stakeholders. Although a lot of quality practices have been done within the industry, establishment and achievement of reasonable levels of quality in construction projects continues to be a problem. While some studies into the introduction and development of quality practices and stakeholder management in the construction industry have been undertaken separately, no major studies have so far been completed that examine in depth how quality management practices that specifically address stakeholders’ perspectives of quality can be utilised to contribute to the ultimate constructed quality of projects. This paper encompasses and summarizes a review of the literature related to previous research undertaken on quality within the industry, focuses on the benefits and shortcomings, together with examining the concept of integrating stakeholder perspectives of project quality for improvement of outcomes throughout the project lifecycle. Findings discussed in this paper reveal a pressing need for investigation, development and testing of a framework to facilitate better implementation of quality management practices and thus achievement of better quality outcomes within the construction industry. The framework will incorporate and integrate the views of stakeholders on what constitutes final project quality to be utilised in developing better quality management planning and systems aimed ultimately at achieving better project quality delivery.

Machine learning techniques to improve software quality

A significant proportion of the cost of software development is due to software testing and maintenance. This is in part the result of the inevitable imperfections due to human error, lack of quality during the design and coding of software, and the increasing need to reduce faults to improve customer satisfaction in a competitive marketplace. Given the cost and importance of removing errors improvements in fault detection and removal can be of significant benefit. The earlier in the development process faults can be found, the less it costs to correct them and the less likely other faults are to develop. This research aims to make the testing process more efficient and effective by identifying those software modules most likely to contain faults, allowing testing efforts to be carefully targeted. This is done with the use of machine learning algorithms which use examples of fault prone and not fault prone modules to develop predictive models of quality. In order to learn the numerical mapping between module and classification, a module is represented in terms of software metrics. A difficulty in this sort of problem is sourcing software engineering data of adequate quality. In this work, data is obtained from two sources, the NASA Metrics Data Program, and the open source Eclipse project. Feature selection before learning is applied, and in this area a number of different feature selection methods are applied to find which work best. Two machine learning algorithms are applied to the data - Naive Bayes and the Support Vector Machine - and predictive results are compared to those of previous efforts and found to be superior on selected data sets and comparable on others. In addition, a new classification method is proposed, Rank Sum, in which a ranking abstraction is laid over bin densities for each class, and a classification is determined based on the sum of ranks over features. A novel extension of this method is also described based on an observed polarising of points by class when rank sum is applied to training data to convert it into 2D rank sum space. SVM is applied to this transformed data to produce models the parameters of which can be set according to trade-off curves to obtain a particular performance trade-off.

Discovery & effective use of quality association rules in multi-level datasets

In today’s electronic world vast amounts of knowledge is stored within many datasets and databases. Often the default format of this data means that the knowledge within is not immediately accessible, but rather has to be mined and extracted. This requires automated tools and they need to be effective and efficient. Association rule mining is one approach to obtaining knowledge stored with datasets / databases which includes frequent patterns and association rules between the items / attributes of a dataset with varying levels of strength. However, this is also association rule mining’s downside; the number of rules that can be found is usually very big. In order to effectively use the association rules (and the knowledge within) the number of rules needs to be kept manageable, thus it is necessary to have a method to reduce the number of association rules. However, we do not want to lose knowledge through this process. Thus the idea of non-redundant association rule mining was born. A second issue with association rule mining is determining which ones are interesting. The standard approach has been to use support and confidence. But they have their limitations. Approaches which use information about the dataset’s structure to measure association rules are limited, but could yield useful association rules if tapped. Finally, while it is important to be able to get interesting association rules from a dataset in a manageable size, it is equally as important to be able to apply them in a practical way, where the knowledge they contain can be taken advantage of. Association rules show items / attributes that appear together frequently. Recommendation systems also look at patterns and items / attributes that occur together frequently in order to make a recommendation to a person. It should therefore be possible to bring the two together. In this thesis we look at these three issues and propose approaches to help. For discovering non-redundant rules we propose enhanced approaches to rule mining in multi-level datasets that will allow hierarchically redundant association rules to be identified and removed, without information loss. When it comes to discovering interesting association rules based on the dataset’s structure we propose three measures for use in multi-level datasets. Lastly, we propose and demonstrate an approach that allows for association rules to be practically and effectively used in a recommender system, while at the same time improving the recommender system’s performance. This especially becomes evident when looking at the user cold-start problem for a recommender system. In fact our proposal helps to solve this serious problem facing recommender systems.