Managing post-discharge care at home: an analysis of patients' and their carers' perceptions of information received during their stay in hospital

This small-scale study carried out in a Melbourne metropolitan hospital explored patients’ and their carers’ perceptions of information, adequacy of information, and their utilization of information concerning post-discharge care received from health professionals during their stay in hospital. The research design consisted of two stages. Stage one involved a qualitative approach using focused interviews of five pairs of patients and their carers, 2 weeks after discharge from hospital. Five main themes emerged from the content analysis of the interview transcripts: information given by health professionals to patients and carers, patients’ and carers’ psychological well-being, activities of daily living, caring tasks of the patients, and community linkages. A quantitative approach was used for stage two involving two sets of questionnaires, one for the patient and one for the carer, developed from the themes identified in stage one. A pilot study was conducted on three pairs of patients and their carers, 2 weeks after discharge from hospital. The main study consisted of a convenience sample of 40 pairs of patients and their carers who completed the questionnaires 2 weeks post-discharge. Data analysis of stage two of the study consisted of descriptive statistics and cross-tabulations. The main findings suggested that carers received very little information from health professionals concerning their patients’ health problems and care at home. The carers’ health and employment states were often not considered in their patients’ discharge plan. Carers who were present with their patients when they received information concerning post-discharge care experienced a decrease in anxiety during their patients’ convalescence at home, greater satisfaction with the information they received, and their patients experienced fewer medical problems post-discharge. The implications for nursing practice and research include recommendations for a more effective system of discharge planning, and further research to include a larger population with a more varied group of participants.

Policy and practice impacts of applied research: a case study analysis of the New South Wales Health Promotion Demonstration Research Grants Scheme 2000-2006

Background
Intervention research provides important information regarding feasible and effective interventions for health policy makers, but few empirical studies have explored the mechanisms by which these studies influence policy and practice. This study provides an exploratory case series analysis of the policy, practice and other related impacts of the 15 research projects funded through the New South Wales Health Promotion Demonstration Research Grants Scheme during the period 2000 to 2006, and explored the factors mediating impacts.

Methods
Data collection included semi-structured interviews with the chief investigators (n = 17) and end-users (n = 29) of each of the 15 projects to explore if, how and under what circumstances the findings had been used, as well as bibliometric analysis and verification using documentary evidence. Data analysis involved thematic coding of interview data and triangulation with other data sources to produce case summaries of impacts for each project. Case summaries were then individually assessed against four impact criteria and discussed at a verification panel meeting where final group assessments of the impact of research projects were made and key influences of research impact identified.

Results
Funded projects had variable impacts on policy and practice. Project findings were used for agenda setting (raising awareness of issues), identifying areas and target groups for interventions, informing new policies, and supporting and justifying existing policies and programs across sectors. Reported factors influencing the use of findings were: i) nature of the intervention; ii) leadership and champions; iii) research quality; iv) effective partnerships; v) dissemination strategies used; and, vi) contextual factors.

Conclusions
The case series analysis provides new insights into how and under what circumstances intervention research is used to influence real world policy and practice. The findings highlight that intervention research projects can achieve the greatest policy and practice impacts if they address proximal needs of the policy context by engaging end-users from the inception of projects and utilizing existing policy networks and structures, and using a range of strategies to disseminate findings that go beond traditional peer review publications.

Removing the ambiguity of data processing methods: Optimizing the location of peak boundaries for accurate moment calculations

The calculation of the first few moments of elution peaks is necessary to determine: the amount of component in the sample (peak area or zeroth moment), the retention factor (first moment), and the column efficiency (second moment). It is a time consuming and tedious task for the analyst to perform these calculations, thus data analysis is generally completed by data stations associated to modern chromatographs. However, data acquisition software is a black box which provides no information to chromatographers on how their data are treated. These results are too important to be accepted on blind faith. The location of the peak integration boundaries is most important. In this manuscript, we explore the relationships between the size of the integration area, the relative position of the peak maximum within this area, and the accuracy of the calculated moments. We found that relationships between these parameters do exist and that computers can be programmed with relatively simple routines to automatize the extraction of key peak parameters and to select acceptable integration boundaries. It was also found that the most accurate results are obtained when the S/N exceeds 200.

Scaffolding, analysis and materials: contributing factors in an unexpected finding of advanced infant/toddler pretend play?

As part of a longitudinal study, infant/toddler pretend play development and maternal play modelling were investigated in dyadic context. A total of 21 children were videotaped in monthly play sessions with their mothers, from age 8 to 17 months. Child and mother pretend play frequencies and levels were measured using Brown’s Pretend Play Observation Scale. Child IQ assessments at 5 years (Stanford–Binet IV) indicated average to high ability levels (M = 122.62). Descriptive analyses showed that children’s levels of pretend development were markedly in advance of age-typical expectations. With a previous analysis showing no specific associations between play levels and IQ, intensive maternal scaffolding, data analysis approaches and use of abstract play materials are proposed as possible contributory factors to the children’s advanced pretend play development.

Interpretative phenomenological analysis

Protocol for a collaborative meta-analysis of 5-HTTLPR, stress, and depression

Background: Debate is ongoing about what role, if any, variation in the serotonin transporter linked polymorphic region (5-HTTLPR) plays in depression. Some studies report an interaction between 5-HTTLPR variation and stressful life events affecting the risk for depression, others report a main effect of 5-HTTLPR variation on depression, while others find no evidence for either a main or interaction effect. Meta-analyses of multiple studies have also reached differing conclusions.

Methods/Design: To improve understanding of the combined roles of 5-HTTLPR variation and stress in the development of depression, we are conducting a meta-analysis of multiple independent datasets. This coordinated approach utilizes new analyses performed with centrally-developed, standardized scripts. This publication documents the protocol for this collaborative, consortium-based meta-analysis of 5-HTTLPR variation, stress, and depression.

Study eligibility criteria: Our goal is to invite all datasets, published or unpublished, with 5-HTTLPR genotype and assessments of stress and depression for at least 300 subjects. This inclusive approach is to minimize potential impact from publication bias.

Data sources: This project currently includes investigators from 35 independent groups, providing data on at least N = 33,761 participants.  The analytic plan was determined prior to starting data analysis. Analyses of individual study datasets will be performed by the investigators who collected the data using centrally-developed standardized analysis scripts to ensure a consistent analytical approach across sites. The consortium as a group will review and interpret the meta-analysis results.

Discussion: Variation in 5-HTTLPR is hypothesized to moderate the response to stress on depression. To test specific hypotheses about the role of 5-HTTLPR variation on depression, we will perform coordinated meta-analyses of de novo results obtained from all available data, using variables and analyses determined a priori. Primary analyses, based on the original 2003 report by Caspi and colleagues of a GxE interaction will be supplemented by secondary analyses to help interpret and clarify issues ranging from the mechanism of effect to heterogeneity among the contributing studies. Publication of this protocol serves to protect this project from biased reporting and to improve the ability of readers to interpret the results of this specific meta-analysis upon its completion.

Synchrotron-FTIR microspectroscopy enables the distinction of lipid accumulation in thraustochytrid strains through analysis of individual live cells

The superior characteristics of high photon flux and diffraction-limited spatial resolution achieved by synchrotron-FTIR microspectroscopy allowed molecular characterization of individual live thraustochytrids. Principal component analysis revealed distinct separation of the single live cell spectra into their corresponding strains, comprised of new Australasian thraustochytrids (AMCQS5-5 and S7) and standard cultures (AH-2 and S31). Unsupervised hierarchical cluster analysis (UHCA) indicated close similarities between S7 and AH-7 strains, with AMCQS5-5 being distinctly different. UHCA correlation conformed well to the fatty acid profiles, indicating the type of fatty acids as a critical factor in chemotaxonomic discrimination of these thraustochytrids and also revealing the distinctively high polyunsaturated fatty acid content as key identity of AMCQS5-5. Partial least squares discriminant analysis using cross-validation approach between two replicate datasets was demonstrated to be a powerful classification method leading to models of high robustness and 100% predictive accuracy for strain identification. The results emphasized the exceptional S-FTIR capability to perform real-time in vivo measurement of single live cells directly within their original medium, providing unique information on cell variability among the population of each isolate and evidence of spontaneous lipid peroxidation that could lead to deeper understanding of lipid production and oxidation in thraustochytrids for single-cell oil development.

Performing research as a method of analysis

This paper outlines a theatre-based research method undertaken as a means of analysing and representing data from a study into first-year teachers’ identity transformation. It reports on the processes employed, and the attempt by the researcher to bring together complimentary and innovative ways of interpreting interview data. Interview data from twelve teachers throughout their first year of teaching were scripted, rehearsed and performed to ‘expert’ audiences. The written script provided the basis for analysis of the teachers’ identity transformation as seen through their firsts – epiphanic and/or revelatory experiences that marked a moment of transition or transformation. The script served as an effective tool for data analysis, particularly when developing an understanding of the process of data reduction. Initially dissatisfied with the term ‘data reduction’, believing it to be counter-intuitive to ‘reduce’ the participants’ descriptions of their experiences, the process of scripting emphasised the importance of honing in on meaning, and reconciled such concerns by creating a snapshot of each participant’s first as representative of their experiences. Later, the performance revealed more nuanced understandings of the participants’ experiences as viewed through the eyes of the teacher-actors and audiences. The actors selected to represent the experiences of the first-year teachers in the performance were also teachers. The process of casting, and the teacher-actors’ experiences of rehearsing and performing the work ‘The First Time’ over the past two years will also be discussed. This paper concludes with some of the feedback from various audiences of both the performance and the written thesis from arts- and non-arts-based practitioners. Some feedback contends that the theatre-based method was less rigorous than other more ‘traditional’ methods. Such feedback prompts the consideration of weighing the benefits of employing theatre-based research against the risk of alienating some members of the audiences (both of the performance and the page). This paper includes live/digital excerpts of the theatre-based performance ‘The First Time’.

Structural damage identification based on self-fitting ARMAX model and multi-sensor data fusion

Statistical time series methods have proven to be a promising technique in structural health monitoring, since it provides a direct form of data analysis and eliminates the requirement for domain transformation. Latest research in structural health monitoring presents a number of statistical models that have been successfully used to construct quantified models of vibration response signals. Although a majority of these studies present viable results, the aspects of practical implementation, statistical model construction and decision-making procedures are often vaguely defined or omitted from presented work. In this article, a comprehensive methodology is developed, which essentially utilizes an auto-regressive moving average with exogenous input model to create quantified model estimates of experimentally acquired response signals. An iterative self-fitting algorithm is proposed to construct and fit the auto-regressive moving average with exogenous input model, which is capable of integrally finding an optimum set of auto-regressive moving average with exogenous input model parameters. After creating a dataset of quantified response signals, an unlabelled response signal can be identified according to a 'closest-fit' available in the dataset. A unique averaging method is proposed and implemented for multi-sensor data fusion to decrease the margin of error with sensors, thus increasing the reliability of global damage identification. To demonstrate the effectiveness of the developed methodology, a steel frame structure subjected to various bolt-connection damage scenarios is tested. Damage identification results from the experimental study suggest that the proposed methodology can be employed as an efficient and functional damage identification tool. © The Author(s) 2014.

Interactive exploration of data with visual metaphors

Visual Analytics (VA) is an approach to data analysis by means of visual manipulation of data representation, which relies on innate human abilities of perception and cognition. Even though current visual toolkits in the Business Analytics (BA) domain have improved the effectiveness of data exploration, analysis and reporting, their features are often not intuitive, and can be confusing and difficult to use. Moreover, visualizations generated from these toolkits are mostly accessible to specialist users. Thus, there is a need for analytic environments that support data exploration, interpretation and communication of insight that do not add to the cognitive load of the analyst and their non-technical clients. In this conceptual paper, we explore the potential of primary metaphors, which arise out of human lived and sensory-motor experiences, in the design of immersive visual analytics environments. Primary metaphors provide ideas for representation of time, space, quantity, similarity, actions and team work. Using examples developed in our own work, we also explain how to combine such metaphors to create complex and cognitively acceptable visual metaphors, such as 3D data terrains that approximate our intuition of reality and create opportunities for data to be viewed, navigated, explored, touched, changed, discussed, reported and described to others, individually or collaboratively.

Confocal laser scanning microscopy elucidation of the micromorphology of the leaf cuticle and analysis of its chemical composition

Electron microscopy techniques such as transmission electron microscopy (TEM) and scanning electron microscopy (SEM) have been invaluable tools for the study of the micromorphology of plant cuticles. However, for electron microscopy, the preparation techniques required may invariably introduce artefacts in cuticle preservation. Further, there are a limited number of methods available for quantifying the image data obtained through electron microscopy. Therefore, in this study, optical microscopy techniques were coupled with staining procedures and, along with SEM were used to qualitatively and quantitatively assess the ultrastructure of plant leaf cuticles. Leaf cryosections of Triticum aestivum (wheat), Zea mays (maize), and Lupinus angustifolius (lupin) were stained with either fat-soluble azo stain Sudan IV or fluorescent, diarylmethane Auramine O and were observed under confocal laser scanning microscope (CLSM). For all the plant species tested, the cuticle on the leaf surfaces could be clearly resolved in many cases into cuticular proper (CP), external cuticular layer (ECL), and internal cuticular layer (ICL). Novel image data analysis procedures for quantifying the epicuticular wax micromorphology were developed, and epicuticular waxes of L. angustifolius were described here for the first time. Together, application of a multifaceted approach involving the use of a range of techniques to study the plant cuticle has led to a better understanding of cuticular structure and provides new insights into leaf surface architecture.

Preference mining techniques for customer behavior analysis

The thesis has studied a number of critical problems in data mining for customer behavior analysis and has proposed novel techniques for better modeling of the customers’ decision making process, more efficient analysis of their travel behavior, and more effective identification of their emerging preference.

A study and a directory of energy consumption data sets of buildings

Energy consumption data are required to perform analysis, modelling, evaluation, and optimisation of energy usage in buildings. While a variety of energy consumption data sets have been examined and reported in the literature, there is a lack of a comprehensive categorisation and analysis of the available data sets. In this study, an overview of energy consumption data of buildings is provided. Three common strategies for generating energy consumption data, i.e., measurement, survey, and simulation, are described. A number of important characteristics pertaining to each strategy and the resulting data sets are discussed. In addition, a directory of energy consumption data sets of buildings is developed. The data sets are collected from either published papers or energy related organisations. The main contributions of this study include establishing a resource pertaining to energy consumption data sets and providing information related to the characteristics and availability of the respective data sets; therefore facilitating and promoting research activities in energy consumption data analysis.

Farmland prices, structural breaks and panel data

Previous time series evidence has indicated that farmland prices and cash rents are not cointegrated, a finding at odds with the present value model of farmland prices. We argue that this failure to find cointegration may be due to low power of tests and to the presence of structural change representing a shifting risk premium on farmland investments. To accommodate this possibility, we use panel unit root and cointegration methods that are more powerful than conventional time series methods and allow for breaks in the cointegration relationship. Our results, based on a large panel covering 31 US states between 1960 and 2000, suggest that the present value model of farmland prices cannot be rejected. © Oxford University Press and Foundation for the European Review of Agricultural Economics 2007; all rights reserved.