Models of psychological service provision under Australia's better outcomes in mental health care program

The Access to Allied Psychological Services component of Australia's Better Outcomes in Mental Health Care program enables eligible general practitioners to refer consumers to allied health professionals for affordable, evidence-based mental health care, via 108 projects conducted by Divisions of General Practice. The current study profiled the models of service delivery across these projects, and examined whether particular models were associated with differential levels of access to services. We found: 76% of projects were retaining their allied health professionals under contract, 28% via direct employment, and 7% some other way; Allied health professionals were providing services from GPs' rooms in 63% of projects, from their own rooms in 63%, from a third location in 42%; and The referral mechanism of choice was direct referral in 51% of projects, a voucher system in 27%, a brokerage system in 24%, and a register system in 25%. Many of these models were being used in combination. No model was predictive of differential levels of access, suggesting that the approach of adapting models to the local context is proving successful.

Elasticity, yielding and episodicity in simple models of mantle convection

We explore the implications of refinements in the mechanical description of planetary constituents on the convection modes predicted by finite-element simulations. The refinements consist in the inclusion of incremental elasticity, plasticity (yielding) and multiple simultaneous creep mechanisms in addition to the usual visco-plastic models employed in the context of unified plate-mantle models. The main emphasis of this paper rests on the constitutive and computational formulation of the model. We apply a consistent incremental formulation of the non-linear governing equations avoiding the computationally expensive iterations that are otherwise necessary to handle the onset of plastic yield. In connection with episodic convection simulations, we point out the strong dependency of the results on the choice of the initial temperature distribution. Our results also indicate that the inclusion of elasticity in the constitutive relationships lowers the mechanical energy associated with subduction events.

Simulation of air traffic controllers' behaviour using the operator choice model

The Operator Choice Model (OCM) was developed to model the behaviour of operators attending to complex tasks involving interdependent concurrent activities, such as in Air Traffic Control (ATC). The purpose of the OCM is to provide a flexible framework for modelling and simulation that can be used for quantitative analyses in human reliability assessment, comparison between human computer interaction (HCI) designs, and analysis of operator workload. The OCM virtual operator is essentially a cycle of four processes: Scan Classify Decide Action Perform Action. Once a cycle is complete, the operator will return to the Scan process. It is also possible to truncate a cycle and return to Scan after each of the processes. These processes are described using Continuous Time Probabilistic Automata (CTPA). The details of the probability and timing models are specific to the domain of application, and need to be specified using domain experts. We are building an application of the OCM for use in ATC. In order to develop a realistic model we are calibrating the probability and timing models that comprise each process using experimental data from a series of experiments conducted with student subjects. These experiments have identified the factors that influence perception and decision making in simplified conflict detection and resolution tasks. This paper presents an application of the OCM approach to a simple ATC conflict detection experiment. The aim is to calibrate the OCM so that its behaviour resembles that of the experimental subjects when it is challenged with the same task. Its behaviour should also interpolate when challenged with scenarios similar to those used to calibrate it. The approach illustrated here uses logistic regression to model the classifications made by the subjects. This model is fitted to the calibration data, and provides an extrapolation to classifications in scenarios outside of the calibration data. A simple strategy is used to calibrate the timing component of the model, and the results for reaction times are compared between the OCM and the student subjects. While this approach to timing does not capture the full complexity of the reaction time distribution seen in the data from the student subjects, the mean and the tail of the distributions are similar.

Accelerated leap methods for simulating discrete stochastic chemical kinetics

Biologists are increasingly conscious of the critical role that noise plays in cellular functions such as genetic regulation, often in connection with fluctuations in small numbers of key regulatory molecules. This has inspired the development of models that capture this fundamentally discrete and stochastic nature of cellular biology - most notably the Gillespie stochastic simulation algorithm (SSA). The SSA simulates a temporally homogeneous, discrete-state, continuous-time Markov process, and of course the corresponding probabilities and numbers of each molecular species must all remain positive. While accurately serving this purpose, the SSA can be computationally inefficient due to very small time stepping so faster approximations such as the Poisson and Binomial τ-leap methods have been suggested. This work places these leap methods in the context of numerical methods for the solution of stochastic differential equations (SDEs) driven by Poisson noise. This allows analogues of Euler-Maruyuma, Milstein and even higher order methods to be developed through the Itô-Taylor expansions as well as similar derivative-free Runge-Kutta approaches. Numerical results demonstrate that these novel methods compare favourably with existing techniques for simulating biochemical reactions by more accurately capturing crucial properties such as the mean and variance than existing methods.