http://nova.newcastle.edu.au/vital/access/services/Feed ${session.getAttribute("locale")} 5 http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:12371 Aim: To determine whether distinct symptom groupings exist in a constipated population and whether such grouping might correlate with quantifiable pathophysiological measures of colonic dysfunction. Methods: One hundred and ninety-one patients presenting to a Gastroenterology clinic with constipation and 32 constipated patients responding to a newspaper advertisement completed a 53-item, wide-ranging self-report questionnaire. One hundred of these patients had colonic transit measured scintigraphically. Factor analysis determined whether constipation-related symptoms grouped into distinct aspects of symptomatology. Cluster analysis was used to determine whether individual patients naturally group into distinct subtypes. Results: Cluster analysis yielded a 4 cluster solution with the presence or absence of pain and laxative unresponsiveness providing the main descriptors. Amongst all clusters there was a considerable proportion of patients with demonstrable delayed colon transit, irritable bowel syndrome positive criteria and regular stool frequency. The majority of patients with these characteristics also reported regular laxative use. Conclusion: Factor analysis identified four constipation subgroups, based on severity and laxative unresponsiveness, in a constipated population. However, clear stratification into clinically identifiable groups remains imprecise. 2013-03-06T22:50:11.528Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:7471 Objective: To develop and validate a scale to measure patients’ trust in pharmacists for use as an outcomes predictor in pharmacoeconomic and pharmaceutical care studies. Methods: Literature review, study team discussion and focus group discussions were conducted to generate items of a candidate version to be pilot-tested for content validity. An amended candidate version was then tested among eligible Singaporeans across different ethnic and age groups. Score distributions were assessed for discriminatory power and item analyses for fi nalizing items. Exploratory factor analysis was used to identify dimensionality and homogeneous items. Cronbach’s alpha was measured for internal consistency and Pearson’s correlation coefficients for convergent validity. Results: Eighteen items were generated with good variability (SD ≻ 1.0) and symmetry (means ranged from −1 to 1) for score distribution. After minor changes to improve content clarity, the amended questionnaire was self-administered among 1196 respondents [mean (SD) age: 38.6 (14.9) years, 51.6% female, 87% ≻6 years of education]. Six items were dropped due to inadequate item-total correlation coefficients, leaving 12-item scale for factor analysis. Three factors (“benevolence”, “technical competence” and “global trust”) were identifi ed, accounting for 55% of the total variance. Cronbach’s alpha was 0.83, indicating high internal consistency. Convergent validity was demonstrated by statistically signifi cant positive correlations between trust and patients’ satisfaction with pharmacists’ service (r = 0.54), returning for care (r = 0.30) and preference of medical decision-making pattern (r = 0.16). Conclusion: The 12-item trust in pharmacists scale demonstrated high reliability and convergent validity. Further studies among other populations are suggested to confi rm the robustness and even improve the current scale. 2012-01-30T05:16:30.633Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:7018 This study explores the longitudinal and subgroup measurement properties of a 10-item, physical activity decisional balance scale, previously published by Plotnikoff, Blanchard, Hotz, and Rhodes (2001), within a diabetic sample of Canadian adults. Results indicated that a three-factor measurement model consistently improved model fit compared to the previously published two-factor model. Evidence of configural, metric, and scalar measurement invariance across time and among subgroups suggests that the 10-item decisional balance scale is appropriate for investigating associative relationships with other constructs and for comparing group means of the pros and cons subscales among a variety of diabetic population subgroups. 2012-01-30T05:05:54.938Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:8599 Evolving factor analysis (EFA), as the name implies, is a particular variant of factor analysis (FA). There are different versions of FA and they serve several different purposes; some of them are presented in detail in this monograph. One immediate and important information revealed by FA is the rank of the matrix of data that are analyzed. This rank is an indication of the complexity of the process represented by the data. Often it can be understood as the number of components in the system, but as we will see later, this is not a rule; often it is better to see the rank as related to the number of processes followed by the measurements. In mathematical terms, the definition of rank is straightforward – it is the number of linearly independent rows/columns. In chemistry, there is a considerable variety of situations and no clear and general statements can be made; we then use the expression ‘chemical rank’. 2011-08-10T06:10:03.999Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:8071 It is suggested that, in spite the logical inconsistencies, factor analysis can be applied in many cases to fluorescence and absorption spectra of dyes in binary solvent mixtures. Limits as to when this application will be successful are derived. This idea was applied to four different dyes in two different binary solvent mixtures and was generally found to generate smoother curves, plotting the contribution of one of the two contributing bands to the experimental spectrum vs. solvent component mole fraction, as compared to those that are generated when one uses the normally applied method of plotting maximum peak position vs. solvent component mole fraction. 2011-07-05T05:50:31.904Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:1266 Bilinear data matrices may be resolved into abstract factors by factor analysis. The underlying chemical processes that generated the data may be deduced from the abstract factors by hard (model fitting) or soft (model-free) analyses. We propose a novel approach that combines the advantages of both hard and soft methods, in that only a few parameters have to be fitted, but the assumptions made about the system are very general and common to a range of possible models: The true chemical factors span the same space as the abstract factors and may be mapped onto the abstract factors by a transformation matrix T, since they are a linear combination of the abstract factors. The difference between the true factors and any other linear combination of the abstract factors is that the true factors conform to known chemical constraints (for instance, nonnegativity of absorbance spectra or monomodality of chromatographic peaks). Thus, by excluding linear combinations of the abstract factors that are not physically possible (assuming a unique solution), we can find the true chemical factors. This is achieved by passing the elements of a transformation matrix to a nonlinear optimization routine, to find the best estimate of T that fits the criteria. The optimization routine usually converges to the correct minimum with random starting parameters, but more difficult problems require starting parameters based on some other method, for instance EFA. We call the new method resolving factor analysis (RFA). The use of RFA is demonstrated with computer-generated kinetic and chromatographic data and with real chromatographic (HPLC) data. RFA produces correct solutions with data sets that are refractory to other methods, for instance, data with an embedded nonconstant baseline. 2010-04-27T06:55:00.428Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:1381 This paper investigates relationships between candidate and examiner characteristics, the texts of examiner reports on Ph.D. theses and examiner recommendations made on theses. The data were related to 804 examiner reports on 301 theses submitted at three Australian universities. Thesis topics ranged across ten Broad Fields of Study or discipline areas. Simple bivariate analyses were first undertaken to identify candidate, examiner and university variables significantly related to the examiner recommendation—three candidate variables, examiner location and, in some cases, the university attended were identified. Next, these variables were regressed on examiner recommendation. The text categories were then factor analysed to confirm five constructs identified in previous work—positive summation, negative summation, prescription, formative evaluation and dialogic elements. These were added to the regression equation. A multilevel regression analysis with examiner recommendation as response variable indicated that four of the five constructs (not including the dialogic elements construct), holding a scholarship and two examiner-country variables explained a total of 43% of the variance in examiner recommendation on the thesis. Implications of the results are discussed. 2010-04-27T06:51:40.313Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:469 An understanding of the species that form in mixtures of alcohol and water is important for their use in liquid chromatography applications. In reverse-phase liquid chromatography the retention of solutes on a chromatography column is influenced by the composition of the mobile phase, and in the case of alcohol and water mobile phases, the amount of free alcohol and water present. Previous and similar modeling studies of methanol (MeOH) and water mixtures by near-infrared (NIR) spectroscopy have found up to four species present including free MeOH and water and MeOH and water complexes formed by hydrogen bonding associations. In this work an equilibrium model has been applied to NIR measurements of MeOH and water mixtures. A high-performance liquid chromatography (HPLC) pump was coupled to an NIR flow cell to produce a gradual change in mixture composition. This resulted in a greater mixture resolution than has been achieved previously by manual mixture preparation. It was determined that five species contributed to the data. An equilibria model consisting of MeOH, MeOH H2O, MeOH(H2O) (log K-H2O(MeOH) = 0.10 +/- 0.03), MeOH(H2O)(4) (log K-4H2O(MeOH) = -2.14 +/- 0.08), and MeOH(H2O)(9) (log K-9H2O(MeOH) = -8.6 +/- 0.1) was successfully fitted to the data. The model supports the results of previous work and highlights the progressive formation of MeOH and water complexes that occur with changing mixture composition. The model also supports that mixtures of MeOH and water are not simple binary mixtures and that this is responsible for observed deviations from expected elution behavior. 2010-04-27T05:44:06.173Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:3198 We present a novel approach for kinetic, spectral and chromatographic resolution of trilinear data sets acquired from slow chemical reaction processes via repeated chromatographic analysis with diode array detection. The method is based on fitting rate constants of distinct chemical model reactions (hard-modelled, integrated rate laws) by a Newton-Gauss-Levenberg/Marquardt (NGL/M) optimization in combination with principal component analysis (PCA) and/or evolving factor analysis (EFA), both known as powerful methods from bilinear data analysis. We call our method hard-modelled trilinear decomposition (HTD). Compared with classical bilinear hard-modelled kinetic data analysis, the additional chromatographic resolution leads to two major advantages: (1) the differentiation of indistinguishable rate laws, as they can occur in consecutive first-order reactions; and (2) the circumvention of many problems due to rank deficiencies in the kinetic concentration profiles. In this paper we present the theoretical background of the algorithm and discuss selected chemical rate laws. 2010-04-27T05:24:59.331Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:5460 Objective: To investigate the association between a vegetable-rich food pattern and obesity among Chinese adults. Design: A food pattern rich in vegetables is associated with lower risk of obesity and non-communicable chronic disease in Western countries. A similar food pattern is found in the Chinese population but the cooking method is different. A crosssectional household survey of 2849 men and women aged 20 years and over was undertaken in 2002 in Jiangsu Province (response rate, 89.0%). Food intake was assessed by food frequency questionnaire. Factor analysis was used to identify food patterns. Nutrient intake was measured by food weighing plus consecutive individual 3-day food records. Height, weight and waist circumference were measured. Results: The prevalence of general obesity (BMI ≽28 kgm⁻²) was 8.0% in men and 12.7% in women, central obesity was 19.5% (≽90 cm) and 38.2% (≽80 cm), respectively. A four-factor solution explained 28.5% of the total variance in food frequency intake. The vegetable-rich food pattern (whole grains, fruits and vegetables) was positively associated with vegetable oil and energy intake. Prevalence of obesity/central obesity increased across the quartiles of vegetable-rich food pattern. After adjusting for sociodemographic factors and four distinct food patterns, the vegetable-rich pattern was independently associated with obesity. Compared with the lowest quartile of vegetable-rich pattern, the highest quartile had higher risk of general obesity (men, prevalence ratio (PR): 1.82, 95% confidence interval (CI): 1.05–3.14; women, PR: 2.25, 95% CI: 1.45–3.49). Conclusion: The vegetable-rich food pattern was associated with higher risk of obesity/central obesity in Chinese adults in both genders. This association can be linked to the high intake of energy due to generous use of oil for stir-frying the vegetables. 2010-04-27T04:48:13.407Z ]]>