Towards Bayesian experimental design for nonlinear models that require a large number of sampling times

The use of Bayesian methodologies for solving optimal experimental design problems has increased. Many of these methods have been found to be computationally intensive for design problems that require a large number of design points. A simulation-based approach that can be used to solve optimal design problems in which one is interested in finding a large number of (near) optimal design points for a small number of design variables is presented. The approach involves the use of lower dimensional parameterisations that consist of a few design variables, which generate multiple design points. Using this approach, one simply has to search over a few design variables, rather than searching over a large number of optimal design points, thus providing substantial computational savings. The methodologies are demonstrated on four applications, including the selection of sampling times for pharmacokinetic and heat transfer studies, and involve nonlinear models. Several Bayesian design criteria are also compared and contrasted, as well as several different lower dimensional parameterisation schemes for generating the many design points.

An integrated educational model for continuing nurse education

Aim This paper reports on the development and evaluation of an integrated clinical learning model to inform ongoing education for surgical nurses. The research aim was to evaluate the effectiveness of implementing a Respiratory Skills Update (ReSKU) education program, in the context of organisational utility, on improving surgical nurses' practice in the area of respiratory assessment. Background Continuous development and integration of technological innovations and research in the healthcare environment mandate the need for continuing education for nurses. Despite an increased worldwide emphasis on this, there is scant empirical evidence of program effectiveness. Methods A quasi experimental pre test, post test non–equivalent control group design evaluated the impact of the ReSKU program on surgical nurses' clinical practice. The 2008 study was conducted in a 400 bed regional referral public hospital and was consistent with contemporary educational approaches using multi-modal, interactive teaching strategies. Findings The study demonstrated statistically significant differences between groups regarding reported use of respiratory skills, three months after ReSKU program attendance. Between group data analysis indicated that the intervention group's reported beliefs and attitudes pertaining to subscale descriptors showed statistically significant differences in three of the six subscales. Conclusion The construct of critical thinking in the clinical context, combined with clinical reasoning and purposeful reflection, was a powerful educational strategy to enhance competency and capability in clinicians.

Curriculum design and higher order skills : challenging assumptions

This paper is based on an Australian Learning & Teaching Council (ALTC) funded evaluation in 13 universities across Australia and New Zealand of the use of Engineers Without Borders (EWB) projects in first-year engineering courses. All of the partner institutions have implemented this innovation differently and comparison of these implementations affords us the opportunity to assemble "a body of carefully gathered data that provides evidence of which approaches work for which students in which learning environments". This study used a mixed-methods data collection approach and a realist analysis. Data was collected by program logic analysis with course co-ordinators, observation of classes, focus groups with students, exit survey of students and interviews with staff as well as scrutiny of relevant course and curriculum documents. Course designers and co-ordinators gave us a range of reasons for using the projects, most of which alluded to their presumed capacity to deliver experience in and learning of higher order thinking skills in areas such as sustainability, ethics, teamwork and communication. For some students, however, the nature of the projects decreased their interest in issues such as ethical development, sustainability and how to work in teams. We also found that the projects provoked different responses from students depending on the nature of the courses in which they were embedded (general introduction, design, communication, or problem-solving courses) and their mode of delivery (lecture, workshop or online).

Surviving an avalanche of data

Open the sports or business section of your daily newspaper, and you are immediately bombarded with an array of graphs, tables, diagrams, and statistical reports that require interpretation. Across all walks of life, the need to understand statistics is fundamental. Given that our youngsters’ future world will be increasingly data laden, scaffolding their statistical understanding and reasoning is imperative, from the early grades on. The National Council of Teachers of Mathematics (NCTM) continues to emphasize the importance of early statistical learning; data analysis and probability was the Council’s professional development “Focus of the Year” for 2007–2008. We need such a focus, especially given the results of the statistics items from the 2003 NAEP. As Shaughnessy (2007) noted, students’ performance was weak on more complex items involving interpretation or application of items of information in graphs and tables. Furthermore, little or no gains were made between the 2000 NAEP and the 2003 NAEP studies. One approach I have taken to promote young children’s statistical reasoning is through data modeling. Having implemented in grades 3 –9 a number of model-eliciting activities involving working with data (e.g., English 2010), I observed how competently children could create their own mathematical ideas and representations—before being instructed how to do so. I thus wished to introduce data-modeling activities to younger children, confi dent that they would likewise generate their own mathematics. I recently implemented data-modeling activities in a cohort of three first-grade classrooms of six year- olds. I report on some of the children’s responses and discuss the components of data modeling the children engaged in.

Modeling and multiway analysis of chatroom tensors

This work identifies the limitations of n-way data analysis techniques in multidimensional stream data, such as Internet chat room communications data, and establishes a link between data collection and performance of these techniques. Its contributions are twofold. First, it extends data analysis to multiple dimensions by constructing n-way data arrays known as high order tensors. Chat room tensors are generated by a simulator which collects and models actual communication data. The accuracy of the model is determined by the Kolmogorov-Smirnov goodness-of-fit test which compares the simulation data with the observed (real) data. Second, a detailed computational comparison is performed to test several data analysis techniques including svd [1], and multi-way techniques including Tucker1, Tucker3 [2], and Parafac [3].

Collective sampling and analysis of high order tensors for chatroom communications

This work investigates the accuracy and efficiency tradeoffs between centralized and collective (distributed) algorithms for (i) sampling, and (ii) n-way data analysis techniques in multidimensional stream data, such as Internet chatroom communications. Its contributions are threefold. First, we use the Kolmogorov-Smirnov goodness-of-fit test to show that statistical differences between real data obtained by collective sampling in time dimension from multiple servers and that of obtained from a single server are insignificant. Second, we show using the real data that collective data analysis of 3-way data arrays (users x keywords x time) known as high order tensors is more efficient than centralized algorithms with respect to both space and computational cost. Furthermore, we show that this gain is obtained without loss of accuracy. Third, we examine the sensitivity of collective constructions and analysis of high order data tensors to the choice of server selection and sampling window size. We construct 4-way tensors (users x keywords x time x servers) and analyze them to show the impact of server and window size selections on the results.

A snapshot of radiation therapy techniques and technology in Queensland : an aid to mapping undergraduate curriculum

Introduction: Undergraduate students studying the Bachelor of Radiation Therapy at Queensland University of Technology (QUT) attend clinical placements in a number of department sites across Queensland. To ensure that the curriculum prepares students for the most common treatments and current techniques in use in these departments, a curriculum matching exercise was performed. Methods: A cross-sectional census was performed on a pre-determined “Snapshot” date in 2012. This was undertaken by the clinical education staff in each department who used a standardized proforma to count the number of patients as well as prescription, equipment, and technique data for a list of tumour site categories. This information was combined into aggregate anonymized data. Results: All 12 Queensland radiation therapy clinical sites participated in the Snapshot data collection exercise to produce a comprehensive overview of clinical practice on the chosen day. A total of 59 different tumour sites were treated on the chosen day and as expected the most common treatment sites were prostate and breast, comprising 46% of patients treated. Data analysis also indicated that intensity-modulated radiotherapy (IMRT) use is relatively high with 19.6% of patients receiving IMRT treatment on the chosen day. Both IMRT and image-guided radiotherapy (IGRT) indications matched recommendations from the evidence. Conclusion: The Snapshot method proved to be a feasible and efficient method of gathering useful

Regression and hypothesis tests for multivariate GNSS state time series

A satellite based observation system can continuously or repeatedly generate a user state vector time series that may contain useful information. One typical example is the collection of International GNSS Services (IGS) station daily and weekly combined solutions. Another example is the epoch-by-epoch kinematic position time series of a receiver derived by a GPS real time kinematic (RTK) technique. Although some multivariate analysis techniques have been adopted to assess the noise characteristics of multivariate state time series, statistic testings are limited to univariate time series. After review of frequently used hypotheses test statistics in univariate analysis of GNSS state time series, the paper presents a number of T-squared multivariate analysis statistics for use in the analysis of multivariate GNSS state time series. These T-squared test statistics have taken the correlation between coordinate components into account, which is neglected in univariate analysis. Numerical analysis was conducted with the multi-year time series of an IGS station to schematically demonstrate the results from the multivariate hypothesis testing in comparison with the univariate hypothesis testing results. The results have demonstrated that, in general, the testing for multivariate mean shifts and outliers tends to reject less data samples than the testing for univariate mean shifts and outliers under the same confidence level. It is noted that neither univariate nor multivariate data analysis methods are intended to replace physical analysis. Instead, these should be treated as complementary statistical methods for a prior or posteriori investigations. Physical analysis is necessary subsequently to refine and interpret the results.

What relationships exist between general self efficacy, locus of control and the nursing practice environment and caring efficacy and job satisfaction?

Research Question: What relationships exist between general self efficacy, locus of control and the nursing practice environment and caring efficacy and job satisfaction? Background: Important characteristics of current nursing practice include nurses having the ability to develop and continue therapeutic relationships with patients, nurses having autonomy and control over the practice environment and nurses having more involvement in decision making. In addition, employee satisfaction is enhanced when organisations offer access to authority. Despite this, nurses continue to complain of feeling powerless in their ability to make decisions. Sample: The study population and criteria for selection included Registered Nurses in Australia who were at the time members of an Australian professional and industrial organisation. Methods: A cross-sectional survey was undertaken. Data analysis was conducted using descriptive and bivariate statistics, and structural equation modeling. Results: The model fit the data well (χ² = 2.3594, χ²/df = 2.3594 and CFI = 0.9987). Twenty four percent of variation in caring efficacy (CE) can be accounted for by general self-efficacy (GSE); work locus of control (WLC) and practice environment (PE) and 62% of the variation in job satisfaction (JS) can be accounted for by GSE, WLC and PE. All pathways were found to be significant except PE to CE. GSE positively explained CE (β = 0.38). WLC was negatively related to CE i.e., as CE scores increased WLC scores decreased (β = -0.23). Further testing of the model found CE was positively related to GSE (βZ = 0.38, p < 0.001) and negatively related to WLC (βZ = - 0.23, p = 0.001). PE was not significantly associated with CE (βZ = - 0.01, p = 0.85). JS was explained by PE, which was positively related (βZ = 0.69, p = < 0.001); GSE which was negatively related (βZ - 0 .09, p < 0.001) and WLC, which was also negatively related (βZ = - 0.20, p < 0.001). Implications for Practice Nursing and organisational leaders should ensure the development of strategies for professional development and orientation programmes which may enhance nurses’ ability to develop caring relationships and express caring behaviours to their patients and as a result improve organisational and patient outcomes. Nursing shortages and turnover rates are associated with job satisfaction and the nursing practice environment. Improving the nursing environment can produce benefits to the health system such as better job satisfaction, improved workforce retention and better patient outcomes.

Examination of factors affecting caring efficacy, job satisfaction in Australian registered nurses

Research Question: What relationships exist between general self efficacy, locus of control and the nursing practice environment and caring efficacy and job satisfaction? Background: Important characteristics of current nursing practice include nurses having the ability to develop and continue therapeutic relationships with patients, nurses having autonomy and control over the practice environment and nurses having more involvement in decision making. In addition, employee satisfaction is enhanced when organisations offer access to authority. Despite this, nurses continue to complain of feeling powerless in their ability to make decisions. Sample: The study population and criteria for selection included Registered Nurses in Australia who were at the time members of an Australian professional and industrial organisation. Methods: A cross-sectional survey was undertaken. Data analysis was conducted using descriptive and bivariate statistics, and structural equation modelling. Results: The model fit the data well (χ² = 2.3594, χ²/df = 2.3594 and CFI = 0.9987). Twenty four percent of variation in caring efficacy (CE) can be accounted for by general self-efficacy (GSE); work locus of control (WLC) and practice environment (PE) and 62% of the variation in job satisfaction (JS) can be accounted for by GSE, WLC and PE. All pathways were found to be significant except PE to CE. GSE positively explained CE (β = 0.38). WLC was negatively related to CE i.e., as CE scores increased WLC scores decreased (β = -0.23). Further testing of the model found CE was positively related to GSE (βZ = 0.38, p < 0.001) and negatively related to WLC (βZ = - 0.23, p = 0.001). PE was not significantly associated with CE (βZ = - 0.01, p = 0.85). JS was explained by PE, which was positively related (βZ = 0.69, p = < 0.001); GSE which was negatively related (βZ - 0 .09, p < 0.001) and WLC, which was also negatively related (βZ = - 0.20, p < 0.001). Implications for Practice Nursing and organisational leaders should ensure the development of strategies for professional development and orientation programmes which may enhance nurses’ ability to develop caring relationships and express caring behaviours to their patients and as a result improve organisational and patient outcomes. Nursing shortages and turnover rates are associated with job satisfaction and the nursing practice environment. Improving the nursing environment can produce benefits to the health system such as better job satisfaction, improved workforce retention and better patient outcomes.

Language affects length of stay in emergency departments in Queensland public hospitals

BACKGROUND: A long length of stay (LOS) in the emergency department (ED) associated with overcrowding has been found to adversely affect the quality of ED care. The objective of this study is to determine whether patients who speak a language other than English at home have a longer LOS in EDs compared to those whose speak only English at home. METHODS: A secondary data analysis of a Queensland state-wide hospital EDs dataset (Emergency Department Information System) was conducted for the period, 1 January 2008 to 31 December 2010. RESULTS: The interpreter requirement was the highest among Vietnamese speakers (23.1%) followed by Chinese (19.8%) and Arabic speakers (18.7%). There were significant differences in the distributions of the departure statuses among the language groups (Chi-squared=3236.88, P<0.001). Compared with English speakers, the Beta coeffi cient for the LOS in the EDs measured in minutes was among Vietnamese, 26.3 (95%CI: 22.1–30.5); Arabic, 10.3 (95%CI: 7.3–13.2); Spanish, 9.4 (95%CI: 7.1–11.7); Chinese, 8.6 (95%CI: 2.6–14.6); Hindi, 4.0 (95%CI: 2.2–5.7); Italian, 3.5 (95%CI: 1.6–5.4); and German, 2.7 (95%CI: 1.0–4.4). The fi nal regression model explained 17% of the variability in LOS. CONCLUSION: There is a close relationship between the language spoken at home and the LOS at EDs, indicating that language could be an important predictor of prolonged LOS in EDs and improving language services might reduce LOS and ease overcrowding in EDs in Queensland's public hospitals.

Distinguishing new science from calibration effects in the electron-volt neutron spectrometer VESUVIO at ISIS

The "standard" procedure for calibrating the Vesuvio eV neutron spectrometer at the ISIS neutron source, forming the basis for data analysis over at least the last decade, was recently documented in considerable detail by the instrument’s scientists. Additionally, we recently derived analytic expressions of the sensitivity of recoil peak positions with respect to fight-path parameters and presented neutron–proton scattering results that together called in to question the validity of the "standard" calibration. These investigations should contribute significantly to the assessment of the experimental results obtained with Vesuvio. Here we present new results of neutron–deuteron scattering from D2 in the backscattering angular range (theata > 90 degrees) which are accompanied by a striking energy increase that violates the Impulse Approximation, thus leading unequivocally the following dilemma: (A) either the "standard" calibration is correct and then the experimental results represent a novel quantum dynamical effect of D which stands in blatant contradiction of conventional theoretical expectations; (B) or the present "standard" calibration procedure is seriously deficient and leads to artificial outcomes. For Case(A), we allude to the topic of attosecond quantumdynamical phenomena and our recent neutron scattering experiments from H2 molecules. For Case(B),some suggestions as to how the "standard" calibration could be considerably improved are made.

Improving the measurement and surveillance of child abuse in Queensland emergency departments

There are no population studies of prevalence or incidence of child maltreatment in Australia. Child protection data gives some understanding but is restricted by system capacity and definitional issues across jurisdictions. Child protection data currently suggests that numbers of reports are increasing yearly, and the child protection system then becomes focussed on investigating all reports and diluting available resources for those children who are most in need of intervention. A public health response across multiple agencies enables responses to child safety across the entire population. All families are targeted at the primary level; examples include ensuring all parents know the dangers of shaking a baby or teaching children to say no if a situation makes them uncomfortable. The secondary level of prevention targets families with a number of risk factors, for example subsidised child care so children aren't left unsupervised after school when both parents have to be at work or home visiting for drug-addicted parents to ensure children are cared for. The tertiary response then becomes the responsibility of the child protection system and is reserved for those children where abuse and neglect are identified. This model requires that child safety is seen in a broader context than just the child protection system, and increasingly health professionals are being identified as an important component in the public health framework. If all injury is viewed as preventable and considered along a continuum of 'accidental' through to 'inflicted', it becomes possible to conceptualise child maltreatment in an injury context. Parental intent may not be to cause harm to the child, but by lack of insight or concern about risk, the potential for injury is high. The mechanisms for unintentional and intentional injury overlap and some suggest that by segregating child abuse (with the possible exception of sexual abuse) from unintentional injury, child abuse is excluded from the broader injury prevention initiative that is gaining momentum in the community. This research uses a public health perspective, specifically that of injury prevention, to consider the problem of child abuse. This study employed a mixed method design that incorporates secondary data analysis, data linkage and structured interviews of different professional groups. Datasets from the Queensland Injury Surveillance Unit (QISU) and The Department of Child Safety (DCS) were evaluated. Coded injury data was grouped according to intent of injury according to those with a code that indicated the ED presentation was due to child abuse, a code indicating that the injury was possibly due to abuse or, in the third group, the intent code indicated that the injury was unintentional and not due to abuse. Primary data collection from ED records was undertaken and information recoded to assess reliability and completeness. Emergency department data (QISU) was linked to Department of Child Safety Data to examine concordance and data quality. Factors influencing the collection and collation of these data were identified through structured interview methodology and analysed using qualitative methods. Secondary analysis of QISU data indicated that codes lacking specific information on the injury event were more likely to also have an intent code indicating abuse than those records where there was specific information on the injury event. Codes for abuse appeared in only 1.2% of the 84,765 records analysed. Unintentional injury was the most commonly coded intent (95.3%). In the group with a definite abuse code assigned at triage, 83% linked to a record with DCS and cases where documentation indicated police involvement were significantly more likely to be associated with a DCS record than those without such documentation. In those coded with an unintentional injury code, 22% linked to a DCS record with cases assigned an urgent triage category more likely to link than those with a triage category for resuscitation and children who presented to regional or remote hospitals more likely to link to a DCS record than those presenting to urban hospitals. Twenty-nine per cent of cases with a code indicating possible abuse linked to a DCS record. In documentation that indicated police involvement in the case, a code for unspecified activity when compared to cases with a code indicating involvement in a sporting activity and children less than 12 months of age compared to those in the 13-17 year old age group were all variables significantly associated with linkage to a DCS record. Only 13% of records contained documentation indicating that child abuse and neglect were considered in the diagnosis of the injury despite almost half of the sample having a code of abuse or possible abuse. Doctors and nurses were confident in their knowledge of the process of reporting child maltreatment but less confident about identifying child abuse and neglect and what should be reported. Many were concerned about implications of reporting, for the child and family and for themselves. A number were concerned about the implications of not reporting, mostly for the wellbeing of the child and a few in terms of their legal obligations as mandatory reporters. The outcomes of this research will help improve the knowledge of barriers to effective surveillance of child abuse in emergency departments. This will, in turn, ensure better identification and reporting practises; more reliable official statistical collections and the potential of flagging high-risk cases to ensure adequate departmental responses have been initiated.

Multi-criteria ranking and source apportionment of airborne particulate matter

Particulate matter research is essential because of the well known significant adverse effects of aerosol particles on human health and the environment. In particular, identification of the origin or sources of particulate matter emissions is of paramount importance in assisting efforts to control and reduce air pollution in the atmosphere. This thesis aims to: identify the sources of particulate matter; compare pollution conditions at urban, rural and roadside receptor sites; combine information about the sources with meteorological conditions at the sites to locate the emission sources; compare sources based on particle size or mass; and ultimately, provide the basis for control and reduction in particulate matter concentrations in the atmosphere. To achieve these objectives, data was obtained from assorted local and international receptor sites over long sampling periods. The samples were analysed using Ion Beam Analysis and Scanning Mobility Particle Sizer methods to measure the particle mass with chemical composition and the particle size distribution, respectively. Advanced data analysis techniques were employed to derive information from large, complex data sets. Multi-Criteria Decision Making (MCDM), a ranking method, drew on data variability to examine the overall trends, and provided the rank ordering of the sites and years that sampling was conducted. Coupled with the receptor model Positive Matrix Factorisation (PMF), the pollution emission sources were identified and meaningful information pertinent to the prioritisation of control and reduction strategies was obtained. This thesis is presented in the thesis by publication format. It includes four refereed papers which together demonstrate a novel combination of data analysis techniques that enabled particulate matter sources to be identified and sampling site/year ranked. The strength of this source identification process was corroborated when the analysis procedure was expanded to encompass multiple receptor sites. Initially applied to identify the contributing sources at roadside and suburban sites in Brisbane, the technique was subsequently applied to three receptor sites (roadside, urban and rural) located in Hong Kong. The comparable results from these international and national sites over several sampling periods indicated similarities in source contributions between receptor site-types, irrespective of global location and suggested the need to apply these methods to air pollution investigations worldwide. Furthermore, an investigation into particle size distribution data was conducted to deduce the sources of aerosol emissions based on particle size and elemental composition. Considering the adverse effects on human health caused by small-sized particles, knowledge of particle size distribution and their elemental composition provides a different perspective on the pollution problem. This thesis clearly illustrates that the application of an innovative combination of advanced data interpretation methods to identify particulate matter sources and rank sampling sites/years provides the basis for the prioritisation of future air pollution control measures. Moreover, this study contributes significantly to knowledge based on chemical composition of airborne particulate matter in Brisbane, Australia and on the identity and plausible locations of the contributing sources. Such novel source apportionment and ranking procedures are ultimately applicable to environmental investigations worldwide.

A nurse-led model of oncogeriatric assessment

Background There is growing consensus that a multidisciplinary, comprehensive and standardised process for assessing the fitness of older patients for chemotherapy should be undertaken to determine appropriate cancer treatment. Aim This study tested a model of cancer care for the older patient incorporating Comprehensive Geriatric Assessment (CGA), which aimed to ensure that 'fit' individuals amenable to active treatment were accurately identified; 'vulnerable' patients more suitable for modified or supportive regimens were determined; and 'frail 'individuals who would benefit most from palliative regimens were also identified and offered the appropriate level of care. Methods A consecutive-series n=178 sample of patients >65 years was recruited from a major Australian cancer centre. The following instruments were administered by an oncogeriatric nurse prior to treatment: Vulnerable Elders Survey-13; Cumulative Illness Rating Scale (Geriatric); Malnutrition Screening Tool; Mini-mental State Examination; Geriatric Depression Scale; Barthel Index; and Lawton Instrumental Activities of Daily Living Scale. Scores from these instruments were aggregated to predict patient fitness, vulnerability or frailty for chemotherapy. Physicians provided a concurrent (blinded) prediction of patient fitness, vulnerability or frailty based on their clinical assessment. Data were also collected on actual patient outcomes (eg treatment completed as predicted, treatment reduced) during monthly audits of patient trajectories. Data analysis Data analysis is underway. A sample of 178 is adequate to detect, with 90% power, kappa coefficients of agreement between CGA and physician assessments of K>0.90 ("almost perfect agreement"). Primary endpoints comprise a) whether the nurse-led CGA determination of fit, vulnerable or frail agrees with the oncologist's assessments of fit, vulnerable or frail and b) whether the CGA and physician assessments accurately predict actual patient outcomes. Conclusion An oncogeriatric nurse-led model of care is currently being developed from the results. We conclude with a discussion of the pivotal role of nurses in CGA-based models of care.