Discharge Interventions for First Nations People with Injury or Chronic Conditions: A Protocol for a Systematic Review.

Severe injury and chronic conditions require long-term management by multidisciplinary teams. Appropriate discharge planning ensures ongoing care to mitigate the long-term impact of injuries and chronic conditions. However, First Nations peoples in Australia face ongoing barriers to aftercare. This systematic review will locate and analyse global evidence of discharge interventions that have been implemented to improve aftercare and enhance health outcomes among First Nations people with an injury or chronic condition. A systematic search will be conducted using five databases, Google, and Google scholar. Global studies published in English will be included. We will analyse aftercare interventions implemented and the health outcomes associated. Two independent reviewers will screen and select studies and then extract and analyse the data. Quality appraisal of the included studies will be conducted using the Mixed Methods Appraisal Tool and the CONSIDER statement. The proposed study will analyse global evidence on discharge interventions that have been implemented for First Nations people with an injury or chronic conditions and their associated health outcomes. Our findings will guide healthcare quality improvement to ensure Aboriginal and Torres Strait Islander peoples have ongoing access to culturally safe aftercare services.

The role of Indigenous Health Workers in ear health screening programs for Indigenous children: a scoping review.

OBJECTIVE: To identify and describe the involvement of Indigenous Health Workers within ear health screening programs for Indigenous Peoples in Australia, Canada, the US and New Zealand. METHODS: Peer-reviewed and grey literature sources were systematically searched to identify evidence. This scoping review was conducted in accordance with the scoping review extension of the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines. RESULTS: Forty pieces of evidence were included in this review. While almost all included studies identified the critical role of Indigenous Health Workers in ear and hearing health, Indigenous leadership and involvement in research projects and service delivery varied significantly and none of the included studies reported Indigenous health worker perspectives. Approximately half of the authorship teams had at least one Indigenous author. CONCLUSIONS: There is a clear need for Indigenous leadership in ear and hearing health research and programming. Specialist teams involved in health service delivery and research need to enable this transition by understanding and privileging Indigenous leadership and investing in appropriate training for non-Indigenous specialists providing care in Indigenous health contexts. IMPLICATIONS FOR PUBLIC HEALTH: These findings are discussed in terms of opportunities to improve Indigenous ear and hearing health research and programming.

Ironbark: Developing a healthy community program for older Aboriginal people.

ISSUE ADDRESSED: Programs by, with and for Aboriginal older people must be culturally safe and relevant. Successful elements include being Aboriginal specific and group based. Co-design with Aboriginal people and stakeholders is essential. We describe the co-design process of developing the Ironbark: Healthy Community program. METHODS: Aboriginal ways of knowing, being and doing and yarning conversational methods guided the development process, during 2018. A desktop review provided details of current group characteristics and key community stakeholders. Stakeholder engagement regarding views about group operations, participants and benefits also occurred. Aboriginal Elders views of their groups were gathered through yarning circles in New South Wales (NSW). Grounded theory approach was used to ascertain key themes. RESULTS: Initial engagement occurred with 13 different community stakeholders and organisations in three Australian states (NSW, South Australia (SA), Western Australia (WA)). Three yarning circles occurred with Elders from urban (N = 10), regional coastal (N = 10) and regional country (N = 4) groups. Six key themes were organised in three groups according to an Aboriginal ontology. 1. Knowing: groups provide opportunities to share knowledge and connect socially. Adequate program resourcing and sustainability are valued. 2. Being: groups strengthen culture, providing important social, emotional and other forms of support to age well. 3. Doing: previous program experiences inform perceptions for new program operations. Group venues and operational aspects should be culturally safe, acknowledging diversity among Elders, their preferences and community control. Themes were used to develop the program and its resource manual that were finalised with stakeholders, including steering committee approval. CONCLUSIONS: Stakeholder feedback at multiple stages and Aboriginal Elders' perspectives resulted in a new co-designed community program involving weekly yarning circles and social activities. So what?: Co-design, guided by Aboriginal ways of knowing, being and doing, can develop programs relevant for Aboriginal people.

Understanding implementation factors and participant experiences of a cluster randomised controlled trial to prevent falls among older Aboriginal people: a process evaluation protocol.

INTRODUCTION: Process evaluations examining programme implementation are often conducted in conjunction with effectiveness studies. Their inclusion in studies with Aboriginal participants can give an understanding of programme delivery in Aboriginal community contexts. The Ironbark: Standing Strong and Tall programme was codesigned with Aboriginal communities and includes exercise and facilitated 'yarning' discussion about fall risk and prevention strategies. The programme pilot showed favourable outcomes and acceptability for Aboriginal people aged 45 years and over. The Ironbark: Standing Strong and Tall programme is now being compared with a 'Healthy Community' programme in a cluster randomised controlled trial within Aboriginal health and community services. An embedded process evaluation aims to explore relationships between participation and programme outcomes and the quality of programme implementation. METHODS AND ANALYSIS: The process evaluation will use a mixed methods design, guided by Indigenous research methodology. It will evaluate quantitative data (number of completed sessions, site coaching checklist tool, participant and facilitator questionnaire data and a participant habit formation scale), as well as qualitative data (open-ended responses from project and site staff and semistructured interviews using yarning with study participants and site managers). A programme logic model was developed to explain the intended inputs, activities, outputs and outcomes, which guided this process evaluation design. CONCLUSION: This process evaluation of a fall prevention programme for older Aboriginal people using a mixed methods design and data triangulation will allow for a comprehensive understanding of study findings. Multiple study sites allow for generalisability of findings and exploration of variation across sites. TRIAL REGISTRATION NUMBER: ACTRN12619000349145.

Theories of Indigenous and non-Indigenous wellbeing in Australian health policies.

Governments in Australia and internationally show growing interest in wellbeing as a policy goal; however, such interests raise questions about the theories or definitions of wellbeing they will apply. Choices about how wellbeing is defined for policy purposes are likely to delimit the strategies applied. Wholly individualized conceptualizations of wellbeing may lead to policy focused narrowly on 'improving' individuals rather than on creating favourable social conditions. Also, Indigenous theories of wellbeing may have much to offer policy for public wellbeing, but little research has examined whether this potential is considered in contemporary health policy. We report on research examining Indigenous and non-Indigenous theories of wellbeing in a representative sample of current Australian health policy documents. We examine what theories or definitions of wellbeing are present, whether policies recognize social determinants of health; if 'lifestyle drift' is present; how Indigenous and non-Indigenous theories of wellbeing are positioned; and whether policies propose strategies consistent with their definitions of wellbeing. We discuss implications of current approaches for effective policy to promote Indigenous and non-Indigenous wellbeing.

Resetting the Narrative in Australian Aboriginal and Torres Strait Islander Nutrition Research.

As the oldest continuous living civilizations in the world, Aboriginal and Torres Strait Islander peoples have strength, tenacity, and resilience. Initial colonization of the landscape included violent dispossession and removal of people from Country to expand European land tenure and production systems, loss of knowledge holders through frontier violence, and formal government policies of segregation and assimilation designed to destroy ontological relationships with Country and kin. The ongoing manifestations of colonialism continue to affect food systems and food knowledges of Aboriginal peoples, and have led to severe health inequities and disproportionate rates of nutrition-related health conditions. There is an urgent need to collaborate with Aboriginal and Torres Strait Islander peoples to address nutrition and its underlying determinants in a way that integrates Aboriginal and Torres Strait Islander peoples' understandings of food and food systems, health, healing, and well-being. We use the existing literature to discuss current ways that Australian Aboriginal and Torres Strait Islander peoples are portrayed in the literature in relation to nutrition, identify knowledge gaps that require further research, and propose a new way forward.

Adaptive discriminant wavelet packet transform and local binary patterns for meningioma subtype classification.

The inherent complexity and non-homogeneity of texture makes classification in medical image analysis a challenging task. In this paper, we propose a combined approach for meningioma subtype classification using subband texture (macro) features and micro-texture features. These are captured using the Adaptive Wavelet Packet Transform (ADWPT) and Local Binary Patterns (LBPs), respectively. These two different textural features are combined together and used for classification. The effect of various dimensionality reduction techniques on classification performance is also investigated. We show that high classification accuracies can be achieved using ADWPT. Although LBP features do not provide higher overall classification accuracies than ADWPT, it manages to provide higher accuracy for a meningioma subtype that is difficult to classify otherwise.

An unsupervised conditional random fields approach for clustering gene expression time series.

MOTIVATION: There is a growing interest in extracting statistical patterns from gene expression time-series data, in which a key challenge is the development of stable and accurate probabilistic models. Currently popular models, however, would be computationally prohibitive unless some independence assumptions are made to describe large-scale data. We propose an unsupervised conditional random fields (CRF) model to overcome this problem by progressively infusing information into the labelling process through a small variable voting pool. RESULTS: An unsupervised CRF model is proposed for efficient analysis of gene expression time series and is successfully applied to gene class discovery and class prediction. The proposed model treats each time series as a random field and assigns an optimal cluster label to each time series, so as to partition the time series into clusters without a priori knowledge about the number of clusters and the initial centroids. Another advantage of the proposed method is the relaxation of independence assumptions.

Partial mixture model for tight clustering of gene expression time-course.

BACKGROUND: Tight clustering arose recently from a desire to obtain tighter and potentially more informative clusters in gene expression studies. Scattered genes with relatively loose correlations should be excluded from the clusters. However, in the literature there is little work dedicated to this area of research. On the other hand, there has been extensive use of maximum likelihood techniques for model parameter estimation. By contrast, the minimum distance estimator has been largely ignored. RESULTS: In this paper we show the inherent robustness of the minimum distance estimator that makes it a powerful tool for parameter estimation in model-based time-course clustering. To apply minimum distance estimation, a partial mixture model that can naturally incorporate replicate information and allow scattered genes is formulated. We provide experimental results of simulated data fitting, where the minimum distance estimator demonstrates superior performance to the maximum likelihood estimator. Both biological and statistical validations are conducted on a simulated dataset and two real gene expression datasets. Our proposed partial regression clustering algorithm scores top in Gene Ontology driven evaluation, in comparison with four other popular clustering algorithms. CONCLUSION: For the first time partial mixture model is successfully extended to time-course data analysis. The robustness of our partial regression clustering algorithm proves the suitability of the combination of both partial mixture model and minimum distance estimator in this field. We show that tight clustering not only is capable to generate more profound understanding of the dataset under study well in accordance to established biological knowledge, but also presents interesting new hypotheses during interpretation of clustering results. In particular, we provide biological evidences that scattered genes can be relevant and are interesting subjects for study, in contrast to prevailing opinion.

Macroscopic, mesostructured cationic surfactant/neutral polymer films: structure and cross-linking.

Mesostructured films of alkyltrimethylammonium bromides or cetylpyridinium bromide and polyethylenimines that spontaneously self-assemble at the air/water interface have been examined using a range of surface sensitive techniques. These films are unusual in that they can be micrometers thick and are relatively robust. Here we show that the films can be cross-linked and thus removed from the liquid surface where they form, as solid, mesostructured polymer-surfactant membranes. Cross-linking causes little change in the structure of the films but freezes in the metastable mesostructures, enhancing the potential of these films for future applications. Cross-linked films, dried after removal from the solution surface, retain the ordered nanoscale structure within the film. We also report grazing incidence X-ray diffraction (GID), which shows that most films display scattering consistent with 2D-hexagonal phase crystallites of rodlike surfactant micelles encased in polymer. Polymer branching makes little difference to the film structures; however, polymer molecular weight has a significant effect. Films with lower polymer MW are generally thinner and more ordered, while higher polymer MW films were thicker and less ordered. Increased pH causes formation of thicker films and improves the ordering in low MW films, while high MW films lose order. To rationalize these results, we propose a model for the film formation process that relates the kinetic and thermodynamic limits of phase separation and mesophase ordering to the structures observed.

Analysis of retinal vasculature using a multiresolution Hermite model.

This paper presents a vascular representation and segmentation algorithm based on a multiresolution Hermite model (MHM). A two-dimensional Hermite function intensity model is developed which models blood vessel profiles in a quad-tree structure over a range of spatial resolutions. The use of a multiresolution representation simplifies the image modeling and allows for a robust analysis by combining information across scales. Estimation over scale also reduces the overall computational complexity. As well as using MHM for vessel labelling, the local image modeling can accurately represent vessel directions, widths, amplitudes, and branch points which readily enable the global topology to be inferred. An expectation-maximization (EM) type of optimization scheme is used to estimate local model parameters and an information theoretic test is then applied to select the most appropriate scale/feature model for each region of the image. In the final stage, Bayesian stochastic inference is employed for linking the local features to obtain a description of the global vascular structure. After a detailed description and analysis of MHM, experimental results on two standard retinal databases are given that demonstrate its comparative performance. These show MHM to perform comparably with other retinal vessel labelling methods.

Effect of micelle composition on the formation of surfactant-templated polymer films.

Surfactant-templated polymer films prepared from polyethylenimine (PEI), cetyltrimethylammonium bromide (CTAB), and octaethylene glycol monohexadecyl ether (C(16)E(8)) were examined and the effect of increasing the percentage of nonionic surfactant in the micelles measured using both surface and bulk-sensitive techniques. It was found that there is a strong interaction between CTAB and C(16)E(8), although no interaction between the C(16)E(8) and PEI was observed. Generally, increasing the percentage of C(16)E(8) in the micelles decreases both the thickness and degree of order in the films; however, it was observed, depending on the conditions, that films could still be formed with as little as 20% cationic surfactant. Experiments on the CTAB/Brij56/PEI system were also performed and these indicate that it is similar to the CTAB/C(16)E(8)/PEI system.

Adaptive wavelet packet basis selection for zerotree image coding.

Image coding methods based on adaptive wavelet transforms and those employing zerotree quantization have been shown to be successful. We present a general zerotree structure for an arbitrary wavelet packet geometry in an image coding framework. A fast basis selection algorithm is developed; it uses a Markov chain based cost estimate of encoding the image using this structure. As a result, our adaptive wavelet zerotree image coder has a relatively low computational complexity, performs comparably to state-of-the-art image coders, and is capable of progressively encoding images.

Self-similar Neural Networks Based on a Kohonen Learning Rule.

One of the most striking features about the perceptual machinery of mammals is its regularity of structure. This is particularly evident in the mammalian visual system, as the work pioneered by Hubel and Wiesel has demonstrated. The likely source of this regularity is the visual stimulus, which does not change randomly from instant to instant, but is affected primarily by motions of both the animal and objects in the environment. These motions induce structured changes in the visual stimulus, which might well be expected to have a significant effect in shaping the structure of the visual machinery, whether through individual plasticity or longer-term genetic changes.The work reported in this paper is an investigation of the structures that may evolve in a simple artificial neural network driven not by random changes of input pattern, but directly by transformations which are themselves related to transformations of the input signal through an analysis of motion-prediction error. Results are presented which demonstrate that such networks can evolve a remarkable degree of regularity which reflects the underlying symmetry group of the transformations, both in one and two dimensions. An appropriate and visually plausible choice of transformation group can lead to the development of foveal structures in two-dimensional networks. We also present some preliminary results on parametrised function spaces which support the general conclusion that global structure bearing a considerable resemblance to that found in the mammalian visual system can evolve as the result of a simple learning rule in networks driven by transformations similar to those typically encountered in vision. Copyright 1996 Elsevier Science Ltd