670 research outputs found
A comparison of two methods for generating artificial multi-assemblage ecological datasets
No full textSimulated ecological datasets have been widely used to assess the ability of ordination techniques to portray patterns in ecological assemblage data. Such datasets typically contain a single assemblage sampled over an environmental gradient or set of gradients. Little has been done on the generation of artificial datasets that contain a number of different species assemblages, to aid in the evaluation of multivariate techniques that test for differences between assemblages of species. This paper describes and compares two simulation methods that generate ecologically realistic artificial multi-assemblage datasets. Both methods provide multivariate data (e.g. species abundances) for replicate sites within discretely different assemblages. The first technique is a coenocline model based on species' responses to variation modeled by a five-parameter ߭function, where variation in species abundances both within and between assemblages is governed by differences in the positions of sites and assemblages along environmental gradients. The second technique, the resampling method, involves bootstrap resampling of real assemblage datasets, with the addition of selected types of controlled differences between assemblages. Here we use it to generate turnover in species composition. We calibrate both simulation methods based on a field assemblage of bird species. The two different simulation methods portray different levels and types of between-assemblage variation. The resampling method allows greater control over some aspects of assemblage difference (e.g. independently varying differences in species richness and compositional turnover) than the coenocline method. Both can generate usable replicated simulated datasets for assessing the ability of multivariate tests to detect ecological variation among assemblages.No Full Tex
The University Stress Scale: Measuring Domains and Extent of Stress in University Students
No full textObjective\ud
\ud
Excessive stress and poor coping skills can put university students at risk for mental health problems. The University Stress Scale (USS) provides a measure of both the categories of stress experienced by university students as well as the overall intensity of the stress experienced.\ud
\ud
Methods\ud
\ud
This study evaluated the psychometric properties of the USS and its clinical utility. Participants were a convenience cross-sectional sample of 2,596 Australian university students.\ud
\ud
Results\ud
\ud
Exploratory factor analysis provided support for a six-factor model comprising the categories of academic, relationships, equity, parenting, practical, and health. This structure was confirmed using confirmatory factor analysis. The measure had good discriminant and convergent validity and good internal consistency. A cut-off of 13 on the USS indicates students most likely to be experiencing depression and anxiety symptoms as a result of excessive stress. This study used a broad sample of Australian students; however, further replication is needed to confirm the utility of the measure for students in other countries.\ud
\ud
Conclusions\ud
\ud
The total stress score and the categorical breakdown of stressors makes the USS a useful, brief screening measure for clinicians working with university students
Examination of socio-demographics and job satisfaction in Australian registered nurses
No full textAims and Objectives\ud
\ud
To examine relationships between socio-demographic factors and job satisfaction and to identify if these factors predict job satisfaction levels in an Australian registered nurses.\ud
\ud
Background\ud
\ud
Reports indicate that in Australia there are 30,000 qualified nurses no longer working in the healthcare and that current nursing shortages vary as a result of certain socio-demographic variables including type of nurse, geographic, location, sector, service and organisation. Furthermore it has been revealed that there is not only a real shortage but also a pseudo-shortage (i.e. either there are not enough nurses are available, or not enough are willing to work under existing workplace conditions). International studies have found significant relationships exist between some socio-demographic factors and job satisfaction in registered nurses however there is limited information available on relationships between socio-demographic factors and job satisfaction in nurses in the Australian context.\ud
\ud
Design\ud
\ud
A cross sectional survey was undertaken of Australian registered nurses. \ud
\ud
Methods\ud
\ud
Two thousand Australian registered nurses who were members of an industrial and professional organisation were sent the questionnaire in 2008. They were stratified and randomised according to gender. Six hundred and thirty-nine registered nurses responded. Descriptive analyses, correlation analyses, one- way ANOVA tests, simple linear regression and multivariable analyses were conducted to examine further if any relationships existed between the variables.\ud
\ud
Results\ud
\ud
The majority of respondents showed positive job satisfaction scores. An ANOVA found significant positive relationships existed between job satisfaction, specialty area, health sector and Australian states. Multivariable analyses found relationships existed between specialty area, health sector, and job satisfaction. \ud
\ud
Conclusions\ud
\ud
The variables specialty area and health sector were found to be significantly associated with job satisfaction. The different specialty areas and health sectors in relation to job satisfaction should be investigated further.\ud
\ud
Clinical Relevance\ud
\ud
The study results have provided new knowledge for policy makers, organisational and nursing leaders of the socio-demographic variables that may affect job satisfaction in registered nurses in the Australian context
A gazetteer and summary of French pottery imported into Scotland c. 1150 to c. 1650 a ceramic contribution to Scotland's economic history Ceramic Resource Disc 3
No full textThe proposal for a series of published inventories, by countries, of all the imported medieval and post medieval pottery recovered from excavations and field walking in Scotland, was advanced on the final day of the Medieval Pottery Research Group’s conference held in Edinburgh in May 2001. Taking on the roll of creating a gazetteer and catalogue of French pottery in Scotland, it was the authors aim to build on the pioneering work of John Hurst and other medieval ceramicists and in the process make a contribution to the ongoing research on identifiable medieval and post-medieval ceramics traded around the North and Irish Sea
Correlation between sample entropy and Hurst exponent, and ROC curves.
No full text<p>(A) Linear regression curve estimation between the mean whole brain sample entropy and mean whole brain Hurst exponent for the whole population. (B) ROC curve for Sample entropy. (C) ROC curve for Hurst exponent.</p
Testing the psychometric properties of the Brisbane Practice Environment Measure using Exploratory Factor Analysis and Confirmatory Factor Analysis in an Australian registered nurse population
No full textA cross-sectional survey was conducted, and the construct validity and reliability of the Brisbane Practice Environment Measure in an Australian sample of registered nurses were examined. Nurses were randomly selected from the database of an Australian nursing organization. The original 33 items of the Brisbane Practice Environment Measure were utilized to inform the psychometric properties using confirmatory factor analysis. The Cronbach's alpha was 0.938 for the total scale and ranged 0.657–0.887 for the subscales. A five-factor structure of the measure was confirmed, χ2 = 944.622, (P < 0.01), χ2/d.f. ratio = 2.845, Tucker Lewis Index 0.929, Root Mean Square Error = 0.061 and Comparative Fit Index = 0.906. The selected 28 items of the measure proved reliable and valid in measuring effects of the practice environment upon Australian nurses. The implications are that regular measurement of the practice environment using these 28 items might assist in the development of strategies which might improve job satisfaction and retention of registered nurses in Australia
Modeling factors that influence exercise and dietary change among midlife Australian women: results from the Healthy Aging of Women Study
No full textThe objective of this study was to investigate the factors that influence midlife women to make positive exercise and dietary changes. In late 2005 questionnaires were mailed to 866 women aged 51–66 years from rural and urban locations in Queensland, Australia and participating in Stage 2 of the Healthy Aging of Women Study.\ud
\ud
The questionnaires sought data on socio-demographics, body mass index (BMI), chronic health conditions, self-efficacy, exercise and dietary behavior change since age 40, and health-related quality of life. Five hundred and sixty four (69%) were completed and returned by early 2006. Data analysis comprised descriptive and bivariate statistics and structural equation modeling.\ud
\ud
The results showed that midlife is a significant time for women to make positive health behavior changes. Approximately one-third of the sample (34.6%) indicated that they had increased their exercise and around 60% had made an effort to eat more healthily since age 40. Modeling showed self-efficacy to be important in making both exercise and dietary changes. Although education appeared to influence self-efficacy in relation to exercise change, this was not the case for dietary change.\ud
\ud
The study has application for programs promoting healthy aging among women, and implies that those with low education, high BMI and poor mental health may need considerable support to improve their lifestyles.\ud
\u
A comparison of methods for classifying clinical samples based on proteomics data: a case study for statistical and machine learning approaches.
No full textThe discovery of protein variation is an important strategy in disease diagnosis within the biological sciences. The current benchmark for elucidating information from multiple biological variables is the so called "omics" disciplines of the biological sciences. Such variability is uncovered by implementation of multivariable data mining techniques which come under two primary categories, machine learning strategies and statistical based approaches. Typically proteomic studies can produce hundreds or thousands of variables, p, per observation, n, depending on the analytical platform or method employed to generate the data. Many classification methods are limited by an n≪p constraint, and as such, require pre-treatment to reduce the dimensionality prior to classification. Recently machine learning techniques have gained popularity in the field for their ability to successfully classify unknown samples. One limitation of such methods is the lack of a functional model allowing meaningful interpretation of results in terms of the features used for classification. This is a problem that might be solved using a statistical model-based approach where not only is the importance of the individual protein explicit, they are combined into a readily interpretable classification rule without relying on a black box approach. Here we incorporate statistical dimension reduction techniques Partial Least Squares (PLS) and Principal Components Analysis (PCA) followed by both statistical and machine learning classification methods, and compared them to a popular machine learning technique, Support Vector Machines (SVM). Both PLS and SVM demonstrate strong utility for proteomic classification problems
Whose problem? Disability narratives and available identities
No full textIn this article, the author demonstrates that contemporary cultural disability discourses offer few positive resources for people with impairments to draw upon in constructing positive personal and social identities. Examining the emergence of the Disability Arts Movement in Britain, consideration is given to alternative discourses developed by disabled people who have resisted the passive roles expected of them and developed a disability identity rooted in notions of power, respect and control. It is suggested that these alternative discourses provide an empowering rather than a disabling basis for community development and community arts practice and should be embraced by workers in these fields
The Queensland cancer risk study: general population norms for the functional assessment of cancer therapy-general (FACT-G)
No full textObjective: To derive Australian normative scores for the Functional Assessment of Cancer\ud
Therapy-General Population (FACT-GP) and to confirm its factor structure.\ud
Methods: Quality of life (QoL) data (as measured by the FACT-GP) were collected\ud
within the Queensland Cancer Risk Study (QCRS) in 2004. The QCRS explored cancer\ud
screening and cancer risk behaviours among 9419 English-speaking residents of Queensland\ud
aged 20–75 years. Information was collected through computer-assisted telephone interviews\ud
and augmented by mailed, Self-Administered Questionnaires (SAQ). A total of 2727\ud
participants largely comparable to the general population of Queensland self-completed the\ud
FACT-GP; however, participants were somewhat higher educated, more likely to have had\ud
cancer and less likely to be of indigenous heritage.\ud
Results: The Queensland population reported a FACT-GP summary score of 85.9\ud
(SD515.1), with subscale scores (range: 19.2 for social well-being to 25.1 for physical wellbeing\ud
(PWB)). In this study, men and women within different age groups reported similar QoL.\ud
QoL was clinically and significantly lower among participants not married, with a body mass\ud
index (BMI) deviating from normal weight and with one or more self-reported morbidities. A\ud
four-factor solution was confirmed with good goodness-of-fit indices (RSMEAo0.05 for all\ud
three age groups).\ud
Conclusions: The reference values from the general population reported here can be used\ud
for comparison with the QoL measured in populations of cancer patients, providing a\ud
benchmark against which clinicians can evaluate the impact of the disease and/or the\ud
treatments on QoL
- …
