Smoking and drinking behaviours : the role of Reinforcement Sensitivity Theory

This thesis examines the predictions of Jeffrey Gray's Reinforcement Sensitivity Theory in the development of smoking and hazardous drinking behaviours in young women. Impulsivity was found to significantly predict alcohol use and young women who smoked and drank at hazardous levels were significantly more impulsive than hazardous drinkers.

Performance evaluation and improved risk control philosophies for drinking water systems

World-wide, water is the single most used substance by humans every day. Water is also the major cause of illness and death in many countries including the affluent nations. Through this research, new risk control philosophies from catchment to consumers are highlighted. This thesis is about identifying the hazards, evaluating the risks and implementing controls to protect public health from drinking water.

Disordered eating and drinking behaviours : the role of sensitivity to reward and punishment

Examines whether the personality traits of sensitivity to reward and punishment as defined by Jeffrey Gray contributed to the prediction of disordered eating and hazardous alcohol use. Studies were conducted in both subclinical and clinical populations. Heightened sensitivity to reward contributed to the prediction of hazardous alcohol use and heightened sensitivity to punishment contributed to the prediction of disordered eating in women. Women with comorbid bulimia and alcohol dependence were more behaviourally sensitive to reward than normal controls.

Alcohol expectancies and drinking refusal self-efficacy mediate the association of impulsivity with alcohol misuse

Background: Recent work suggests that 2 biologically based traits convey risk for alcohol misuse: reward sensitivity ⁄ drive and (rash) impulsiveness. However, the cognitive mechanisms through which these traits convey risk are unclear. This study tested a model predicting that the risk conveyed by reward sensitivity is mediated by a learning bias for the reinforcing outcomes of alcohol consumption (i.e., positive alcohol expectancy). The model also proposed that the risk conveyed by rash impulsiveness (RI) is mediated by drinkers’ perceived ability to resist alcohol (i.e., drinking refusal self-efficacy).
Methods: Study 1 tested the model in a sample of young adults (n = 342). Study 2 tested the model in a sample of treatment-seeking substance abusers (n = 121). All participants completed a battery of personality, cognitive, and alcohol use questionnaires and models were tested using structural equation modeling.
Results: In both studies, the hypothesized model was found to provide a good fit to the data, and a better fit than alternative models. In both young adults and treatment-seeking individuals, positive alcohol expectancy fully mediated the association between reward sensitivity and hazardous alcohol use. For treatment seekers, drinking refusal self-efficacy fully mediated the association between RI and hazardous drinking. However, there was partial mediation in the young adult sample. Furthermore, neither trait was directly associated with the other cognitive mediator.
Conclusions: The hypothesized model was confirmed on a large sample of young adults and replicated on a sample of treatment-seeking substance abusers. Taken together, these findings shed further light on the mechanisms through which an impulsive temperament may convey risk for alcohol misuse.

Policy and prevention : alcohol industry and non alcohol industry sponsorship of sportspeople and drinking

Aims: To examine the relationship between direct alcohol and non-alcohol sponsorship and drinking in Australian sportspeople.
Methods: Australian sportspeople (N = 652; 51% female) completed questionnaires on alcohol and non-alcohol industry sponsorship (from bars, cafes etc.), drinking behaviour (Alcohol Use Disorders Identification Test (AUDIT)) and known confounders.
Results: 31% reported sponsorship (29.8% alcohol industry; 3.7% both alcohol and non-alcohol industry and 1.5% non-alcohol industry only) Multivariate regression showed that receipt of alcohol industry sponsorship was predictive of higher AUDIT scores (βadj = 1.67, 95% confidence interval (CI ): 0.56–2.78), but non-alcohol industry sponsorship and combinations of both were not (βadj = 0.18, 95% CI: −2.61 to 2.68; and βadj = 2.58, 95% CI: −0.60 to 5.76, respectively).
Conclusion: Governments should consider alternatives to alcohol industry sponsorship of sport. Hypothecated taxes on tobacco have been used successfully for replacing tobacco sponsorship of sport in some countries, and may show equal utility for the alcohol industry’s funding of sport.

Charismatic cops, patriarchs and a few good women : leadership, club culture and young peoples' drinking

The paper reports on key findings of a research project that examined the roles that communitybased
sporting clubs in the Australian state of Victoria play in shaping young people’s understandings and uses of alcohol. Our research imagined clubs as community hubs that are located in complex networks that impact on the ways that clubs understand their locations in communities, and which have unpredictable influences and consequences on club histories, culture and orientations to issues such as young people and alcohol use. The paper focuses on understanding the key roles played by club leaders in facilitating change and transformation in these contexts, particularly in terms of alcohol-related practices and the potential impact of these on young people’s uses and understanding of alcohol. We situate these findings in a framework that draws on the literature of complexity science and complex adaptive systems (CAS) to suggest that these practices and changes need to be understood in ways that allow for complexity, uncertainty, emergent behaviours and adaptive change.

Chlorine decay and biofilm growth in tropical drinking water distribution systems - a case study for Townsville

Water quality modelling is becoming increasingly popular in the water industry due to its applications in drinking water and treated wastewater reuse. Microbial growth and disinfectant decay are the two most important factors to be considered in drinking water if they are to comply with stringent guidelines imposed by relevant water regulatory authorities. In the case of drinking water, an optimum level of disinfectant is an important criterion to have pathogen free water with minimal disinfectant by products (DBPs) below the acceptable levels.

Prediction of chlorine and THMs concentration profile in bulk drinking water distribution systems from laboratory data

Nearly all drinking water distribution systems experience a "natural" reduction of disinfection residuals. The most frequently used disinfectant is chlorine, which can decay due to reactions with organic and inorganic compounds in the water and by liquid/solids reaction with the biofilm, pipe walls and sediments. Usually levels of 0.2-0.5 mg/L of free chlorine are required at the point of consumption to maintain bacteriological safety. Higher concentrations are not desirable as they present the problems of taste and odour and increase formation of disinfection by-products. It is usually a considerable concern for the operators of drinking water distribution systems to manage chlorine residuals at the "optimum level", considering all these issues. This paper describes how the chlorine profile in a drinking water distribution system can be modelled and optimised on the basis of readily and inexpensively available laboratory data. Methods are presented for deriving the laboratory data, fitting a chlorine decay model of bulk water to the data and applying the model, in conjunction with a simplified hydraulic model, to obtain the chlorine profile in a distribution system at steady flow conditions. Two case studies are used to demonstrate the utility of the technique. Melbourne's Greenvale-Sydenham distribution system is unfiltered and uses chlorination as its only treatment. The chlorine model developed from laboratory data was applied to the whole system and the chlorine profile was shown to be accurately simulated. Biofilm was not found to critically affect chlorine decay. In the other case study, Sydney Water's Nepean system was modelled from limited hydraulic data. Chlorine decay and trihalomethane (THM) formation in raw and treated water were measured in a laboratory, and a chlorine decay and THM model was derived on the basis of these data. Simulated chlorine and THM profiles agree well with the measured values available. Various applications of this modelling approach are also briefly discussed.

Efficient management of drinking water distribution systems through the application of water quality modeling

The quality of drinking water generally degrades when it is delivered through a distribution system due to the decay of disinfectant, which subsequently allows the re-growth of microorganisms in the distribution system. A model that describes the changes that occur in the water quality in distribution system is needed to determine whether to enhance the treatment processes or to improve the distribution system so that microbiological criteria are met. This paper describes how chlorine decay kinetics are modeled and the model output is used in finding the elements that are contributing to the consumption of chlorine at the treatment plant other than the water itself; this allows better control of chlorine dosing at the treatment plant, which in tum will reduce the formation of disinfectant by-products. In addition, the model will accurately predict the decay due to the organic/inorganic and nitrogenous compounds that are remaining in the water at any point in the distribution system, which will indicate the status of the distribution system with respect to its chlorine consumption. Further, if re-chlorination is introduced in the distribution system downstream of the treatment plant, the model will predict the chlorine decay due to the slow reacting organic and nitrogenous compounds accurately.

Water quality modelling for drinking water distribution systems

A dynamic water quality model for drinking water distribution systems has been developed in this study, to include processes that occur in the bulk water, as well as those occurring in the biofilm of a distribution system. The model has been validated against water quality data obtained from extensive experimental studies conducted with biofilm reactors. Protein and carbohydrate densities in the biofilm represent biofilm biomass. This model is able to predict the disinfectant decay due to organic matter in the bulk water, as well as that due to biofilm. It simultaneously predicts the growth of biofilm in terms of carbohydrate and protein densities. While this model is complex enough to describe the water quality changes in a distribution system, it is also simple enough to be incorporated into a hydraulic model in order to describe the interaction between disinfectant and microbiological quality throughout a drinking water distribution system.