The use of narrative text for injury surveillance research : a systematic review

Objective: To summarise the extent to which narrative text fields in administrative health data are used to gather information about the event resulting in presentation to a health care provider for treatment of an injury, and to highlight best practise approaches to conducting narrative text interrogation for injury surveillance purposes.----- Design: Systematic review----- Data sources: Electronic databases searched included CINAHL, Google Scholar, Medline, Proquest, PubMed and PubMed Central.. Snowballing strategies were employed by searching the bibliographies of retrieved references to identify relevant associated articles.----- Selection criteria: Papers were selected if the study used a health-related database and if the study objectives were to a) use text field to identify injury cases or use text fields to extract additional information on injury circumstances not available from coded data or b) use text fields to assess accuracy of coded data fields for injury-related cases or c) describe methods/approaches for extracting injury information from text fields.----- Methods: The papers identified through the search were independently screened by two authors for inclusion, resulting in 41 papers selected for review. Due to heterogeneity between studies metaanalysis was not performed.----- Results: The majority of papers reviewed focused on describing injury epidemiology trends using coded data and text fields to supplement coded data (28 papers), with these studies demonstrating the value of text data for providing more specific information beyond what had been coded to enable case selection or provide circumstantial information. Caveats were expressed in terms of the consistency and completeness of recording of text information resulting in underestimates when using these data. Four coding validation papers were reviewed with these studies showing the utility of text data for validating and checking the accuracy of coded data. Seven studies (9 papers) described methods for interrogating injury text fields for systematic extraction of information, with a combination of manual and semi-automated methods used to refine and develop algorithms for extraction and classification of coded data from text. Quality assurance approaches to assessing the robustness of the methods for extracting text data was only discussed in 8 of the epidemiology papers, and 1 of the coding validation papers. All of the text interrogation methodology papers described systematic approaches to ensuring the quality of the approach.----- Conclusions: Manual review and coding approaches, text search methods, and statistical tools have been utilised to extract data from narrative text and translate it into useable, detailed injury event information. These techniques can and have been applied to administrative datasets to identify specific injury types and add value to previously coded injury datasets. Only a few studies thoroughly described the methods which were used for text mining and less than half of the studies which were reviewed used/described quality assurance methods for ensuring the robustness of the approach. New techniques utilising semi-automated computerised approaches and Bayesian/clustering statistical methods offer the potential to further develop and standardise the analysis of narrative text for injury surveillance.

Multivariate methods to identify cancer-related symptom clusters

Multivariate methods are required to assess the interrelationships among multiple, concurrent symptoms. We examined the conceptual and contextual appropriateness of commonly used multivariate methods for cancer symptom cluster identification. From 178 publications identified in an online database search of Medline, CINAHL, and PsycINFO, limited to articles published in English, 10 years prior to March 2007, 13 cross-sectional studies met the inclusion criteria. Conceptually, common factor analysis (FA) and hierarchical cluster analysis (HCA) are appropriate for symptom cluster identification, not principal component analysis. As a basis for new directions in symptom management, FA methods are more appropriate than HCA. Principal axis factoring or maximum likelihood factoring, the scree plot, oblique rotation, and clinical interpretation are recommended approaches to symptom cluster identification.

Comparison of three expert elicitation methods for logistic regression on predicting the presence of the threatened brush-tailed rock-wallaby petrogale penicillata

Numerous expert elicitation methods have been suggested for generalised linear models (GLMs). This paper compares three relatively new approaches to eliciting expert knowledge in a form suitable for Bayesian logistic regression. These methods were trialled on two experts in order to model the habitat suitability of the threatened Australian brush-tailed rock-wallaby (Petrogale penicillata). The first elicitation approach is a geographically assisted indirect predictive method with a geographic information system (GIS) interface. The second approach is a predictive indirect method which uses an interactive graphical tool. The third method uses a questionnaire to elicit expert knowledge directly about the impact of a habitat variable on the response. Two variables (slope and aspect) are used to examine prior and posterior distributions of the three methods. The results indicate that there are some similarities and dissimilarities between the expert informed priors of the two experts formulated from the different approaches. The choice of elicitation method depends on the statistical knowledge of the expert, their mapping skills, time constraints, accessibility to experts and funding available. This trial reveals that expert knowledge can be important when modelling rare event data, such as threatened species, because experts can provide additional information that may not be represented in the dataset. However care must be taken with the way in which this information is elicited and formulated.

Submission to Travelsafe : vehicle impoundment for drink drivers

This submission has been prepared in response to the Parliamentary Travelsafe Committee's Inquiry into vehicle impoundment for drink drivers to address research relevant to the committee’s investigation into whether: • Drink drivers in Queensland continue to drive illegally after being apprehended by police or disqualified from driving by the courts; • The incidence of repeat drink driving undermines the effectiveness of existing penalties for drink driving offences; and • Vehicle impoundment and/or ignition key confiscation are cost-effective deterrents that will reduce drink driving recidivism, relating to other existing or potential methods of managing offenders.

Multi-objective mission flight planning in civil unmanned aerial systems

Unmanned Aerial Vehicles (UAVs) are emerging as an ideal platform for a wide range of civil applications such as disaster monitoring, atmospheric observation and outback delivery. However, the operation of UAVs is currently restricted to specially segregated regions of airspace outside of the National Airspace System (NAS). Mission Flight Planning (MFP) is an integral part of UAV operation that addresses some of the requirements (such as safety and the rules of the air) of integrating UAVs in the NAS. Automated MFP is a key enabler for a number of UAV operating scenarios as it aids in increasing the level of onboard autonomy. For example, onboard MFP is required to ensure continued conformance with the NAS integration requirements when there is an outage in the communications link. MFP is a motion planning task concerned with finding a path between a designated start waypoint and goal waypoint. This path is described with a sequence of 4 Dimensional (4D) waypoints (three spatial and one time dimension) or equivalently with a sequence of trajectory segments (or tracks). It is necessary to consider the time dimension as the UAV operates in a dynamic environment. Existing methods for generic motion planning, UAV motion planning and general vehicle motion planning cannot adequately address the requirements of MFP. The flight plan needs to optimise for multiple decision objectives including mission safety objectives, the rules of the air and mission efficiency objectives. Online (in-flight) replanning capability is needed as the UAV operates in a large, dynamic and uncertain outdoor environment. This thesis derives a multi-objective 4D search algorithm entitled Multi- Step A* (MSA*) based on the seminal A* search algorithm. MSA* is proven to find the optimal (least cost) path given a variable successor operator (which enables arbitrary track angle and track velocity resolution). Furthermore, it is shown to be of comparable complexity to multi-objective, vector neighbourhood based A* (Vector A*, an extension of A*). A variable successor operator enables the imposition of a multi-resolution lattice structure on the search space (which results in fewer search nodes). Unlike cell decomposition based methods, soundness is guaranteed with multi-resolution MSA*. MSA* is demonstrated through Monte Carlo simulations to be computationally efficient. It is shown that multi-resolution, lattice based MSA* finds paths of equivalent cost (less than 0.5% difference) to Vector A* (the benchmark) in a third of the computation time (on average). This is the first contribution of the research. The second contribution is the discovery of the additive consistency property for planning with multiple decision objectives. Additive consistency ensures that the planner is not biased (which results in a suboptimal path) by ensuring that the cost of traversing a track using one step equals that of traversing the same track using multiple steps. MSA* mitigates uncertainty through online replanning, Multi-Criteria Decision Making (MCDM) and tolerance. Each trajectory segment is modeled with a cell sequence that completely encloses the trajectory segment. The tolerance, measured as the minimum distance between the track and cell boundaries, is the third major contribution. Even though MSA* is demonstrated for UAV MFP, it is extensible to other 4D vehicle motion planning applications. Finally, the research proposes a self-scheduling replanning architecture for MFP. This architecture replicates the decision strategies of human experts to meet the time constraints of online replanning. Based on a feedback loop, the proposed architecture switches between fast, near-optimal planning and optimal planning to minimise the need for hold manoeuvres. The derived MFP framework is original and shown, through extensive verification and validation, to satisfy the requirements of UAV MFP. As MFP is an enabling factor for operation of UAVs in the NAS, the presented work is both original and significant.

An adolescent injury intervention : selecting targeted behaviours with implications for program design and evaluation

Objectives: This paper sought to identify the behaviour change targets for an injury prevention program; Skills for Preventing Injury in Youth, SPIY. The aim was to explore how such behaviours could subsequently be implemented and evaluated in the program. Methods and Design: The quantitative procedure involved a survey with 267 Year 8 and 9 students (mean age 13.23 years) regarding their engagement in risk-taking behaviours that may lead to injury. The qualitative study involved 30 students aged 14 to 17 years reporting their experiences of injury and risk-taking. Results: Injury risk behaviours co-occurred among three-quarters of those who reported engaging in any alcohol use or transport or violence related injury risk behaviour. Students described in detail some of these experiences. Conclusions: The selection process of identifying target behaviours for change for an injury prevention program is described. Adolescents’ description of such risk behaviours can inform the process of operationalising and contextualising program content and deciding on evaluation methodology. The design of an effective injury prevention program involves considerable preparatory work and this paper was able to describe the process of identifying the behavioural targets for change that can be operationalised and evaluated in the injury prevention program, SPIY.

Bayes factor based speaker clustering for speaker diarization

This paper proposes the use of the Bayes Factor to replace the Bayesian Information Criterion (BIC) as a criterion for speaker clustering within a speaker diarization system. The BIC is one of the most popular decision criteria used in speaker diarization systems today. However, it will be shown in this paper that the BIC is only an approximation to the Bayes factor of marginal likelihoods of the data given each hypothesis. This paper uses the Bayes factor directly as a decision criterion for speaker clustering, thus removing the error introduced by the BIC approximation. Results obtained on the 2002 Rich Transcription (RT-02) Evaluation dataset show an improved clustering performance, leading to a 14.7% relative improvement in the overall Diarization Error Rate (DER) compared to the baseline system.

Addressing issues in sparseness, ecological bias and formulation of the adjacency matrix in Bayesian spatio-temporal analysis of disease counts

The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.

A multicast routing scheme for efficient safety message dissemination in VANET

Vehicular ad hoc network (VANET) is a wireless ad hoc network that operates in a vehicular environment to provide communication between vehicles. VANET can be used by a diverse range of applications to improve road safety. Cooperative collision warning system (CCWS) is one of the safety applications that can provide situational awareness and warning to drivers by exchanging safety messages between cooperative vehicles. Currently, the routing strategies for safety message dissemination in CCWS are scoped broadcast. However, the broadcast schemes are not efficient as a warning message is sent to a large number of vehicles in the area, rather than only the endangered vehicles. They also cannot prioritize the receivers based on their critical time to avoid collision. This paper presents a more efficient multicast routing scheme that can reduce unnecessary transmissions and also use adaptive transmission range. The multicast scheme involves methods to identify an abnormal vehicle, the vehicles that may be endangered by the abnormal vehicle, and the latest time for each endangered vehicle to receive the warning message in order to avoid the danger. We transform this multicast routing problem into a delay-constrained minimum Steiner tree problem. Therefore, we can use existing algorithms to solve the problem. The advantages of our multicast routing scheme are mainly its potential to support various road traffic scenarios, to optimize the wireless channel utilization, and to prioritize the receivers.

Driver behaviour and decision making at railway level crossings : An exploratory on-road case study

Crashes at rail level crossings represent a significant problem, both in Australia and worldwide. Advances in driving assessment methods, such as the provision of on-road instrumented test vehicles, now provide researchers with the opportunity to further understand driver behaviour at rail level crossings in ways not previously possible. This paper gives an overview of a recent on-road pilot study of driver behaviour at rail level crossings in which 25 participants drove a pre-determined route, incorporating 4 rail level crossings, using MUARC's instrumented On-Road Test Vehicle (ORTeV). Drivers provided verbal commentary whilst driving the route, and a range of other data were collected, including eye fixations, forward, cockpit and driver video, and vehicle data (speed, braking, steering wheel angle, lane tracking etc). Participants also completed a post trial cognitive task analysis interview. Extracts from the wider analyses are used to examine in depth driver behaviour at one of the rail level crossings encountered during the study. The analysis presented, along with the overall analysis undertaken, gives insight into the driver and wider systems factors that shape behaviour at rail level crossings, and highlights the utility of using a multi-method, instrumented vehicle approach for gathering data regarding driver behaviour in different contexts.

Red clover (Trifolium pratense) isoflavones and serum homocysteine in premenopausal women : a pilot study

Background: There is limited information on the effect of isoflavones on homocysteine concentrations, a risk factor for a number of chronic diseases. Methods: Twenty-three premenopausal women participated in a double-blind, randomized, parallel study for four menstrual cycles. Subjects consumed either placebo or purified red clover (Trifolium pratense) isoflavone (86mg/day) tablets. Blood samples were collected weekly during cycles 1, 3, and 4 for determination of serum folate and total homocysteine concentrations. Dietary intake was monitored monthly. Results: Concentrations of folate and homocysteine in serum did not change significantly in either group, and there were no significant differences observed between the follicular and luteal phases of the menstrual cycle. The participants' dietary records indicated that nutrient intake was constant, and compliance was confirmed by analysis of urinary isoflavone concentrations and tablet counts in returned containers. Conclusions: These results suggest that in the absence of any dietary modification, supplementation with purified isoflavones that are predominantly methoxylated has no effect on serum homocysteine or folate in premenopausal women.

Driving performance on monotonous roads

Driving on motorways has largely been reduced to a lane-keeping task with cruise control. Rapidly, drivers are likely to get bored with such a task and take their attention away from the road. This is of concern in terms of road safety – particularly for professional drivers - since inattention has been identified as one of the main contributing factors to road crashes and is estimated to be involved in 20 to 30% of these crashes. Furthermore, drivers are not aware that their vigilance level has decreased and that their driving performance is impaired. Intelligent Transportation System (ITS) intervention can be used as a countermeasure against vigilance decrement. This paper aims to identify a variety of metrics impacted during monotonous driving - ranging from vehicle data to physiological variables - and relate them to two monotonous factors namely the monotony of the road design (straightness) and the monotony of the environment (landscape, signage, traffic). Data are collected in a driving simulator instrumented with an eye tracking system, a heart rate monitor and an electrodermal activity device (N=25 participants). The two monotonous factors are varied (high and low) leading to the use of four different driving scenarios (40 minutes each). We show with Generalised Linear Mixed Models that driver performance decreases faster when the road is monotonous. We also highlight that road monotony impairs a variety of driving performance and vigilance measures, ranging from speed, lateral position of the vehicle to physiological measurements such as heart rate variability, blink frequency and electrodermal activity. This study informs road designers of the importance of having a varied road environment. It also provides a range of metrics that can be used to detect in real-time the impairment of driving performance on monotonous roads. Such knowledge could result in the development of an in-vehicle device warning drivers at early signs of driving performance impairment on monotonous roads.

Safety implications of increased moped and scooter use in an Australian city

Drawing on two studies within a larger program of research into scooter and moped safety in Queensland, Australia, some key safety concerns specific to the use of these vehicles are discussed. A five phase observational study is used to identify distribution of powered two-wheeler (PTW) types in the city centre of Brisbane, Australia’s third largest city. Data were first collected in August 2008, and thereafter at six-monthly intervals. Stationary PTWs were directly observed in designated parking areas. Four focus groups involving 23 Brisbane riders were held in March 2009, aiming to explore perspectives on safety and transport planning in a semi-structured format. Information gathered in the focus groups informed development of a questionnaire targeting a larger sample of scooter and moped riders. The observations made to date indicate that 36% of all PTWs parked in Brisbane’s inner city are either mopeds or larger scooters, with the remaining 64% accounted for by motorcycles (n = 2037). These data suggest that mopeds and scooters are a significant transport mode in Brisbane, yet little is known about their safety relative to that of motorcycles. In focus groups, main motivating factors for scooter or moped use included parking availability, traffic congestion, cost, time-efficiency and enjoyment. Moped riders were generally younger and less experienced than other scooter riders, less likely to wear protective clothing, and less likely to have undertaken rider training. The focus groups have helped to identify some particular safety concerns regarding moped use in a jurisdiction requiring no motorcycle licence or rider training.

Structural behaviour and design of cold-formed steel beams at elevated temperatures

Cold-formed steel members are extensively used in the building construction industry, especially in residential, commercial and industrial buildings. In recent times, fire safety has become important in structural design due to increased fire damage to properties and loss of lives. However, past research into the fire performance of cold-formed steel members has been limited, and was confined to compression members. Therefore a research project was undertaken to investigate the structural behaviour of compact cold-formed steel lipped channel beams subject to inelastic local buckling and yielding, and lateral-torsional buckling effects under simulated fire conditions and associated section and member moment capacities. In the first phase of this research, an experimental study based on tensile coupon tests was undertaken to obtain the mechanical properties of elastic modulus and yield strength and the stress-strain relationship of cold-formed steels at uniform ambient and elevated temperatures up to 700oC. The mechanical properties deteriorated with increasing temperature and are likely to reduce the strength of cold-formed beams under fire conditions. Predictive equations were developed for yield strength and elastic modulus reduction factors while a modification was proposed for the stressstrain model at elevated temperatures. These results were used in the numerical modelling phases investigating the section and member moment capacities. The second phase of this research involved the development and validation of two finite element models to simulate the behaviour of compact cold-formed steel lipped channel beams subject to local buckling and yielding, and lateral-torsional buckling effects. Both models were first validated for elastic buckling. Lateral-torsional buckling tests of compact lipped channel beams were conducted at ambient temperature in order to validate the finite element model in predicting the non-linear ultimate strength behaviour. The results from this experimental study did not agree well with those from the developed experimental finite element model due to some unavoidable problems with testing. However, it highlighted the importance of magnitude and direction of initial geometric imperfection as well as the failure direction, and thus led to further enhancement of the finite element model. The finite element model for lateral-torsional buckling was then validated using the available experimental and numerical ultimate moment capacity results from past research. The third phase based on the validated finite element models included detailed parametric studies of section and member moment capacities of compact lipped channel beams at ambient temperature, and provided the basis for similar studies at elevated temperatures. The results showed the existence of inelastic reserve capacity for compact cold-formed steel beams at ambient temperature. However, full plastic capacity was not achieved by the mono-symmetric cold-formed steel beams. Suitable recommendations were made in relation to the accuracy and suitability of current design rules for section moment capacity. Comparison of member capacity results from finite element analyses with current design rules showed that they do not give accurate predictions of lateral-torsional buckling capacities at ambient temperature and hence new design rules were developed. The fourth phase of this research investigated the section and member moment capacities of compact lipped channel beams at uniform elevated temperatures based on detailed parametric studies using the validated finite element models. The results showed the existence of inelastic reserve capacity at elevated temperatures. Suitable recommendations were made in relation to the accuracy and suitability of current design rules for section moment capacity in fire design codes, ambient temperature design codes as well as those proposed by other researchers. The results showed that lateral-torsional buckling capacities are dependent on the ratio of yield strength and elasticity modulus reduction factors and the level of non-linearity in the stress-strain curves at elevated temperatures in addition to the temperature. Current design rules do not include the effects of non-linear stress-strain relationship and therefore their predictions were found to be inaccurate. Therefore a new design rule that uses a nonlinearity factor, which is defined as the ratio of the limit of proportionality to the yield stress at a given temperature, was developed for cold-formed steel beams subject to lateral-torsional buckling at elevated temperatures. This thesis presents the details and results of the experimental and numerical studies conducted in this research including a comparison of results with predictions using available design rules. It also presents the recommendations made regarding the accuracy of current design rules as well as the new developed design rules for coldformed steel beams both at ambient and elevated temperatures.