Why do Queenslanders seek care in emergency departments? A population study

Objective This study aims to identify the main reasons for which first time and multiple users seek medical care through Queensland emergency departments (ED). Methods A cross-sectional survey was conducted at eight public EDs among presenting patients (n = 911). The questions measured the socio-demographic characteristics of patients, their beliefs and attitudes towards EDs services, and perceptions of health status. Bivariate and binary logistic regression analyses were performed to examine the differences between first time and multiple users of EDs. Results First time and multiple users accounted for 55.5% and 44.5%, respectively. Multiple users themselves believed to be sicker, have poorer health status, and additional and/or chronic health conditions. Multiple users more strongly believed that their condition required treatment at an ED and perceived their condition as being very serious. Multiple users reported weekly household incomes below $600, and half of the multiple users were not working as compared to 35% first time users. Multivariate analysis showed that multiple use was significantly associated with the existence of additional health problems, having chronic condition, lower self-efficacy, and need for ED treatment. Conclusions Patients who sought care for multiple times at EDs more often than first time users suffered from additional and chronic conditions. Their opinion of an ED as the most suitable place to address their current health problem was stronger than first time users. Any proposed demand management strategies need to address these beliefs together with the reasoning of patients to provide effective and appropriate care outside or within ED services.

What influences a patients decision to use custom-made orthopaedic shoes?

Background Despite potential benefits, some patients decide not to use their custom-made orthopaedic shoes (OS). Factors are known in the domains ‘usability’, ‘communication and service’, and ‘opinion of others’ that influence a patient’s decision to use OS. However, the interplay between these factors has never been investigated. The aim of this study was to explore the interplay between factors concerning OS, and the influences thereof on a patient’s decision to use OS. Methods A mixed-methods design was used, combining qualitative and quantitative data by means of sequential data analysis and triangulation. Priority was given to the qualitative part. Qualitative data was gathered with a semi-structured interview covering the three domains. Data was analysed using the framework approach. Quantitative data concerned the interplay between factors and determining a rank-order for the importance of factors of ‘usability’. Results A patient’s decision to use OS was influenced by various factors indicated as being important and by acceptance of their OS. Factors of ‘usability’ were more important than factors of ‘communication’; the ‘opinion of others’ was of limited importance. An improvement of walking was indicated as the most important factor of ‘usability’. The importance of other factors (cosmetic appearance and ease of use) was determined by reaching a compromise between these factors and an improvement of walking. Conclusions A patient’s decision to use OS is influenced by various factors indicated as being important and by acceptance of their OS. An improvement of walking is the most important factor of ‘usability’, the importance of other factors (cosmetic appearance and ease of use) is determined by reaching compromises between these factors and an improvement of walking. Communication is essential to gain insight in a patient’s acceptance and in the compromises they are willing to reach. This makes communication the key for clinicians to influence a patient’s decision to use OS.

State-of-the-Art Review on Opinion Mining from Online Customers’ Feedback

Dealing with the ever-growing information overload in the Internet, Recommender Systems are widely used online to suggest potential customers item they may like or find useful. Collaborative Filtering is the most popular techniques for Recommender Systems which collects opinions from customers in the form of ratings on items, services or service providers. In addition to the customer rating about a service provider, there is also a good number of online customer feedback information available over the Internet as customer reviews, comments, newsgroups post, discussion forums or blogs which is collectively called user generated contents. This information can be used to generate the public reputation of the service providers’. To do this, data mining techniques, specially recently emerged opinion mining could be a useful tool. In this paper we present a state of the art review of Opinion Mining from online customer feedback. We critically evaluate the existing work and expose cutting edge area of interest in opinion mining. We also classify the approaches taken by different researchers into several categories and sub-categories. Each of those steps is analyzed with their strength and limitations in this paper.

Inducing shades of meaning by matrix methods : a first step towards thematic analysis of opinion

This article explores two matrix methods to induce the ``shades of meaning" (SoM) of a word. A matrix representation of a word is computed from a corpus of traces based on the given word. Non-negative Matrix Factorisation (NMF) and Singular Value Decomposition (SVD) compute a set of vectors corresponding to a potential shade of meaning. The two methods were evaluated based on loss of conditional entropy with respect to two sets of manually tagged data. One set reflects concepts generally appearing in text, and the second set comprises words used for investigations into word sense disambiguation. Results show that for NMF consistently outperforms SVD for inducing both SoM of general concepts as well as word senses. The problem of inducing the shades of meaning of a word is more subtle than that of word sense induction and hence relevant to thematic analysis of opinion where nuances of opinion can arise.

How useful is expert opinion for predicting the distribution of a species within and beyond the region of expertise? A case study using brush-tailed rock-wallabiesPetrogale penicillata

1. Species' distribution modelling relies on adequate data sets to build reliable statistical models with high predictive ability. However, the money spent collecting empirical data might be better spent on management. A less expensive source of species' distribution information is expert opinion. This study evaluates expert knowledge and its source. In particular, we determine whether models built on expert knowledge apply over multiple regions or only within the region where the knowledge was derived. 2. The case study focuses on the distribution of the brush-tailed rock-wallaby Petrogale penicillata in eastern Australia. We brought together from two biogeographically different regions substantial and well-designed field data and knowledge from nine experts. We used a novel elicitation tool within a geographical information system to systematically collect expert opinions. The tool utilized an indirect approach to elicitation, asking experts simpler questions about observable rather than abstract quantities, with measures in place to identify uncertainty and offer feedback. Bayesian analysis was used to combine field data and expert knowledge in each region to determine: (i) how expert opinion affected models based on field data and (ii) how similar expert-informed models were within regions and across regions. 3. The elicitation tool effectively captured the experts' opinions and their uncertainties. Experts were comfortable with the map-based elicitation approach used, especially with graphical feedback. Experts tended to predict lower values of species occurrence compared with field data. 4. Across experts, consensus on effect sizes occurred for several habitat variables. Expert opinion generally influenced predictions from field data. However, south-east Queensland and north-east New South Wales experts had different opinions on the influence of elevation and geology, with these differences attributable to geological differences between these regions. 5. Synthesis and applications. When formulated as priors in Bayesian analysis, expert opinion is useful for modifying or strengthening patterns exhibited by empirical data sets that are limited in size or scope. Nevertheless, the ability of an expert to extrapolate beyond their region of knowledge may be poor. Hence there is significant merit in obtaining information from local experts when compiling species' distribution models across several regions.

Integration of opinion into customer analysis model

Nowadays, Opinion Mining is getting more important than before especially in doing analysis and forecasting about customers’ behavior for businesses purpose. The right decision in producing new products or services based on data about customers’ characteristics means profit for organization/company. This paper proposes a new architecture for Opinion Mining, which uses a multidimensional model to integrate customers’ characteristics and their comments about products (or services). The key step to achieve this objective is to transfer comments (opinions) to a fact table that includes several dimensions, such as, customers, products, time and locations. This research presents a comprehensive way to calculate customers’ orientation for all possible products’ attributes. A use case study is also presented in this paper to show the advantages of using OLAP and data cubes to analyze costumers’ opinions.

Automated speed enforcement in Australia : recent examples of the influence of public opinion on program sustainability

In Australia, speeding remains a substantial contributor to road trauma. The National Road Safety Strategy (2011-2020) highlighted the need to harness community support for current and future speed management strategies. Australia is known for intensive speed camera programs which are both automated and manual, employing covert and overt methods. Recent developments in the area of automated speed enforcement in Australia help to illustrate the important link between community attitudes to speed enforcement and subsequent speed camera policy developments. A perceived lack of community confidence in camera programs prompted reviews in New South Wales and Victoria in 2011 by the jurisdictional Auditor-General. This paper explores automated speed camera enforcement in Australia with particular reference to the findings of these two reports as they relate to the level of public support for and community attitudes towards automated speed enforcement. It also provides comment on the evolving nature of automated speed enforcement according to previously identified controversies and dilemmas associated with speed camera programs.

Integration of opinion into customer analysis model

As e-commerce is becoming more and more popular, the number of customer reviews that a product receives grows rapidly. In order to enhance customer satisfaction and their shopping experiences, it has become important to analysis customers reviews to extract opinions on the products that they buy. Thus, Opinion Mining is getting more important than before especially in doing analysis and forecasting about customers’ behavior for businesses purpose. The right decision in producing new products or services based on data about customers’ characteristics means profit for organization/company. This paper proposes a new architecture for Opinion Mining, which uses a multidimensional model to integrate customers’ characteristics and their comments about products (or services). The key step to achieve this objective is to transfer comments (opinions) to a fact table that includes several dimensions, such as, customers, products, time and locations. This research presents a comprehensive way to calculate customers’ orientation for all possible products’ attributes.

Anatomy of sand beach ridges : evidence from severe Tropical Cyclone Yasi and its predecessors, northeast Queensland, Australia

[1] Four well-identified tropical cyclones over the past century have been responsible for depositing distinct units of predominantly quartzose sand and gravel to form the most seaward beach ridge at several locations along the wet tropical coast of northeast Queensland, Australia. These units deposited by tropical cyclones display a key sedimentary signature characterized by a sharp basal erosional contact, a coarser grain size than the underlying facies and a coarse-skewed trend toward the base. Coarse-skewed distributions with minimal change in mean grain size also characterize the upper levels of the high-energy deposited units at locations within the zone of maximum onshore winds during the tropical cyclone. These same coarse skew distributions are not apparent in sediments deposited at locations where predominantly offshore winds occurred during the cyclone, which in the case of northeast Australia is north of the eye-crossing location. These sedimentary signatures, along with the geochemical indicators and the degraded nature of the microfossil assemblages, have proven to be useful proxies to identify storm-deposited units within the study site and can also provide useful proxies in older beach ridges where advanced pedogenesis has obscured visual stratigraphic markers. As a consequence, more detailed long-term histories of storms and tropical cyclones can now be developed.

Integration of Opinion Mining into customer analysis model

This research proposes a multi-dimensional model for Opinion Mining, which integrates customers' characteristics and their opinions about products (or services). Customer opinions are valuable for companies to deliver right products or services to their customers. This research presents a comprehensive framework to evaluate opinions' orientation based on products' hierarchy attributes. It also provides an alternative way to obtain opinion summaries for different groups of customers and different categories of produces.

The Statutory Defence(s) of 'peer professional opinion'

In the wake of the GFC and with ever increasing consumer-protection-related laws, clients are more aware of their rights and your obligations as a professional valuer. They also are more likely to take legal action if, as a result of their reliance on a valuation, they suffer a financial loss. In some Australian jurisdictions, in response to a claim of negligence, the professional valuer may be able to raise a professional practice defence under civil liability legislation. This article considers the nature of this statutory defence, what is required to rely upon it and in which jurisdictions it applies.

Integrating science through Bayesian Belief Networks : case study of Lyngbya in Moreton Bay

Bayesian Belief Networks (BBNs) are emerging as valuable tools for investigating complex ecological problems. In a BBN, the important variables in a problem are identified and causal relationships are represented graphically. Underpinning this is the probabilistic framework in which variables can take on a finite range of mutually exclusive states. Associated with each variable is a conditional probability table (CPT), showing the probability of a variable attaining each of its possible states conditioned on all possible combinations of it parents. Whilst the variables (nodes) are connected, the CPT attached to each node can be quantified independently. This allows each variable to be populated with the best data available, including expert opinion, simulation results or observed data. It also allows the information to be easily updated as better data become available ----- ----- This paper reports on the process of developing a BBN to better understand the initial rapid growth phase (initiation) of a marine cyanobacterium, Lyngbya majuscula, in Moreton Bay, Queensland. Anecdotal evidence suggests that Lyngbya blooms in this region have increased in severity and extent over the past decade. Lyngbya has been associated with acute dermatitis and a range of other health problems in humans. Blooms have been linked to ecosystem degradation and have also damaged commercial and recreational fisheries. However, the causes of blooms are as yet poorly understood.