Conference Poster
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(2023-10-17)Conference PosterBackground: Opioid agonist treatment consumers can experience stigma when collecting and consuming their medications at community pharmacies. We sought to evaluate if pharmacist attitudes and behaviours towards opioid agonist treatment customers influenced consumer perceptions and experiences of treatment effectiveness. Methods: New South Wales community pharmacists were recruited in person, and they assisted in recruiting consumers by distributing study flyers. Surveys were completed by 63 pharmacists and eligible pharmacy opioid agonist treatment consumers completed baseline (n = 132) and follow up surveys (n = 112). Consumer outcomes were analysed at both timepoints with reference to their pharmacist’s responses, their experiences of stigma, and demographic variables. Results: Pharmacists reported low levels of explicit stigma towards consumers and high levels of support for the treatment model overall, possibly indicating selection and social desirability biases. The number of complete pharmacist attitude measures that could be matched with two or three of their opioid agonist consumers was small (n = 40), which precluded finding any meaningful relationships between pharmacist implicit attitudes and consumer experiences. Although consumers experienced substantial levels of stigma and other hardships due to their medication, they did not report any significant changes in wellbeing or service experiences over time which reflects the stabilising and enduring nature of treatment. Conclusion: Although stigma is understood to be an important contributor to opioid agonist treatment dissatisfaction, its forms and effects on consumer wellbeing are difficult to measure and evaluate. Stigma experienced by opioid agonist consumers in the treatment setting may be less influential than other sources of social exclusion and discrimination in their lives.
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(2022-05-30)Conference Poster
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(2022-01-09)Conference PosterSince disruptive events can cause negative impacts on a city's regular traffic order and economic activities, it is crucial that the transport network is resilient against disaster to prevent significant economic losses and ensure regular social, economic and traffic order. This study tackles the problem of resilient road pre-investment with the aim of resilience optimisation of traffic systems. First, we use the Shapley value to determine the critical candidate links that needs to be upgraded. Second, we proposed the Economic-based Network Resilience Measurement (ENRM) as a performance indicator to evaluate the network level resilience from the economic perspective. Third, a bi-level multi-objective optimisation model is formulated to identify the optimal capacity improvement for candidate critical links, where the objectives of the upper-level model are to minimise the ENRM and pre-enhancement budget. The lower-level model is the integrated computable general equilibrium (CGE) model that includes the CGE sub-model, which can be applied to capture economic impacts and traffic sub-model that optimises travelers’ behaviors under user equilibrium conditions. Genetic Algorithm (GA) heuristic approach is used to solve the proposed bi-level model. A case study of the optimisation framework is presented using a simplified Sydney network. Results suggest that ENRM decreases with the increase in investment. However, the Pareto-optimality is observed and the marginal utility decreases with the increase in investment budget. Furthermore, the more severe the disaster, the greater the marginal utility of investment.
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(2021-03-06)Conference PosterDetecting reactive oxygen species (ROS) that play a critical role as redox modulators and signalling molecules in biological systems currently requires invasive methods such as ROS-specific indicators for imaging and quantification. We developed a non-invasive, real-time, label-free imaging technique for assessing the level of ROS in live cells and thawed cryopreserved tissues that is compatible with invivo imaging. The (AFMI) system used in this study is based on an adapted IX83 Olympus microscope as previously reported. It provides narrow excitation wavelength ranges (±5nm) from high power LEDs and several filter cubes to produce defined spectral regions, which span the excitation (340 nm–510 nm) and emission (420 nm–650 nm) wavelength ranges. In total, 18 distinct spectral channels (Nch= 18) are available and the samples are imaged in all these channels