Using microteaching to enhance teacher efficacy in pre-service teachers

This study examined pre-service teachers’ efficacy in relation to the utilisation of microteaching as an assessment tool for postgraduate education students in Australia. Three hundred and fifteen pre-service teachers completed the teacher efficacy survey and additional qualitative questions at Time 1 and 208 completed the survey and questions at Time 2. A principal components analysis conducted on the Time 1 survey data revealed teacher efficacy to be comprised of two components: ‘teacher efficacy in classroom management’ and ‘personal teacher efficacy’. Repeated measures ANOVAs conducted on the 208 participants who completed the survey at Time 1 and 2 revealed that efficacy on both components increased significantly over time, and that internet students had higher efficacy levels than internal students. The qualitative data revealed that pre-service teachers enter teaching in order to positively impact on children, yet are concerned about behaviour management in the classroom. In addition, this data highlighted the positive impact that microteaching had on their developing teacher identity.

Alternative analytical methods for the identification of cancer-related symptom clusters

Advances in symptom management strategies through a better understanding of cancer symptom clusters depend on the identification of symptom clusters that are valid and reliable. The purpose of this exploratory research was to investigate alternative analytical approaches to identify symptom clusters for patients with cancer, using readily accessible statistical methods, and to justify which methods of identification may be appropriate for this context. Three studies were undertaken: (1) a systematic review of the literature, to identify analytical methods commonly used for symptom cluster identification for cancer patients; (2) a secondary data analysis to identify symptom clusters and compare alternative methods, as a guide to best practice approaches in cross-sectional studies; and (3) a secondary data analysis to investigate the stability of symptom clusters over time. The systematic literature review identified, in 10 years prior to March 2007, 13 cross-sectional studies implementing multivariate methods to identify cancer related symptom clusters. The methods commonly used to group symptoms were exploratory factor analysis, hierarchical cluster analysis and principal components analysis. Common factor analysis methods were recommended as the best practice cross-sectional methods for cancer symptom cluster identification. A comparison of alternative common factor analysis methods was conducted, in a secondary analysis of a sample of 219 ambulatory cancer patients with mixed diagnoses, assessed within one month of commencing chemotherapy treatment. Principal axis factoring, unweighted least squares and image factor analysis identified five consistent symptom clusters, based on patient self-reported distress ratings of 42 physical symptoms. Extraction of an additional cluster was necessary when using alpha factor analysis to determine clinically relevant symptom clusters. The recommended approaches for symptom cluster identification using nonmultivariate normal data were: principal axis factoring or unweighted least squares for factor extraction, followed by oblique rotation; and use of the scree plot and Minimum Average Partial procedure to determine the number of factors. In contrast to other studies which typically interpret pattern coefficients alone, in these studies symptom clusters were determined on the basis of structure coefficients. This approach was adopted for the stability of the results as structure coefficients are correlations between factors and symptoms unaffected by the correlations between factors. Symptoms could be associated with multiple clusters as a foundation for investigating potential interventions. The stability of these five symptom clusters was investigated in separate common factor analyses, 6 and 12 months after chemotherapy commenced. Five qualitatively consistent symptom clusters were identified over time (Musculoskeletal-discomforts/lethargy, Oral-discomforts, Gastrointestinaldiscomforts, Vasomotor-symptoms, Gastrointestinal-toxicities), but at 12 months two additional clusters were determined (Lethargy and Gastrointestinal/digestive symptoms). Future studies should include physical, psychological, and cognitive symptoms. Further investigation of the identified symptom clusters is required for validation, to examine causality, and potentially to suggest interventions for symptom management. Future studies should use longitudinal analyses to investigate change in symptom clusters, the influence of patient related factors, and the impact on outcomes (e.g., daily functioning) over time.

Development and synthesis of innovative approaches to the surgical assessment of articular cartilage degeneration

This research has established, through ultrasound, near infrared spectroscopy and biomechanics experiments, parameters and parametric relationships that can form the framework for quantifying the integrity of the articular cartilage-on-bone laminate, and objectively distinguish between normal/healthy and abnormal/degenerated joint tissue, with a focus on articular cartilage. This has been achieved by: 1. using traditional experimental methods to produce new parameters for cartilage assessment; 2. using novel methodologies to develop new parameters; and 3. investigating the interrelationships between mechanical, structural and molec- ular properties to identify and select those parameters and methodologies that can be used in a future arthroscopic probe based on points 1 and 2. By combining the molecular, micro- and macro-structural characteristics of the tissue with its mechanical properties, we arrive at a set of critical benchmarking parameters for viable and early-stage non-viable cartilage. The interrelationships between these characteristics, examined using a multivariate analysis based on principal components analysis, multiple linear regression and general linear modeling, could then to deter- mine those parameters and relationships which have the potential to be developed into a future clinical device. Specifically, this research has found that the ultrasound and near infrared techniques can subsume the mechanical parameters and combine to characterise the tissue at the molecular, structural and mechanical levels over the full depth of the cartilage matrix. It is the opinion in this thesis that by enabling the determination of the precise area of in uence of a focal defect or disease in the joint, demarcating the boundaries of articular cartilage with dierent levels of degeneration around a focal defect, better surgical decisions that will advance the processes of joint management and treatment will be achieved. Providing the basis for a surgical tool, this research will contribute to the enhancement and quanti�cation of arthroscopic procedures, extending to post- treatment monitoring and as a research tool, will enable a robust method for evaluating developing (particularly focalised) treatments.

Rumination, post-traumatic growth, and distress : structural equation modelling with cancer survivors

Objective Theoretical models of post-traumatic growth (PTG) have been derived in the general trauma literature to describe the post-trauma experience that facilitates the perception of positive life changes. To develop a statistical model identifying factors that are associated with PTG, structural equation modelling (SEM) was used in the current study to assess the relationships between perception of diagnosis severity, rumination, social support, distress, and PTG. Method A statistical model of PTG was tested in a sample of participants diagnosed with a variety of cancers (N=313). Results An initial principal components analysis of the measure used to assess rumination revealed three components: intrusive rumination, deliberate rumination of benefits, and life purpose rumination. SEM results indicated that the model fit the data well and that 30% of the variance in PTG was explained by the variables. Trauma severity was directly related to distress, but not to PTG. Deliberately ruminating on benefits and social support were directly related to PTG. Life purpose rumination and intrusive rumination were associated with distress. Conclusions The model showed that in addition to having unique correlating factors, distress was not related to PTG, thereby providing support for the notion that these are discrete constructs in the post-diagnosis experience. The statistical model provides support that post-diagnosis experience is simultaneously shaped by positive and negative life changes and that one or the other outcome may be prevalent or may occur concurrently. As such, an implication for practice is the need for supportive care that is holistic in nature.

A comparison of methods for classifying clinical samples based on proteomics data : a case study for statistical and machine learning approaches

The discovery of protein variation is an important strategy in disease diagnosis within the biological sciences. The current benchmark for elucidating information from multiple biological variables is the so called “omics” disciplines of the biological sciences. Such variability is uncovered by implementation of multivariable data mining techniques which come under two primary categories, machine learning strategies and statistical based approaches. Typically proteomic studies can produce hundreds or thousands of variables, p, per observation, n, depending on the analytical platform or method employed to generate the data. Many classification methods are limited by an n≪p constraint, and as such, require pre-treatment to reduce the dimensionality prior to classification. Recently machine learning techniques have gained popularity in the field for their ability to successfully classify unknown samples. One limitation of such methods is the lack of a functional model allowing meaningful interpretation of results in terms of the features used for classification. This is a problem that might be solved using a statistical model-based approach where not only is the importance of the individual protein explicit, they are combined into a readily interpretable classification rule without relying on a black box approach. Here we incorporate statistical dimension reduction techniques Partial Least Squares (PLS) and Principal Components Analysis (PCA) followed by both statistical and machine learning classification methods, and compared them to a popular machine learning technique, Support Vector Machines (SVM). Both PLS and SVM demonstrate strong utility for proteomic classification problems.

Socioeconomic status and health outcomes in a developing country

Although the relationship between socioeconomic status (SES) and health is well documented for developed countries, less evidence has been presented for developing countries. The aim of this paper is to analyse this relationship at the household level for Fiji, a developing country in the South Pacific, using original household survey data. To allow for the endogeneity of SES status in the household health production function, we utilize a simultaneous equation approach where estimates are achieved by full information maximum likelihood. By restricting our sample to one, relatively small island, and including area and district hospital effects, physical geography effects are unpacked from income effects. We measure SES, as permanent income which is constructed using principal components analysis. An alternative specification considers transitory household income. We find that a 1% increase in wealth (our measure of permanent income) would lead to a 15% decrease in the probability of an incapacitating illness occurring intra-household. Although the presence of a strong relationship indicates that relatively small improvements in SES status can significantly improve health at the household level, it is argued that the design of appropriate policy would also require an understanding of the various mechanisms through which the relationship operates.

The individual and interactive relationship between long chain omega-3 polyunsaturated fatty acids and physical activity as predictors of cognition in cognitively impaired and non-impaired older adults

Alterations in cognitive function are characteristic of the aging process in humans and other animals. However, the nature of these age related changes in cognition is complex and is likely to be influenced by interactions between genetic predispositions and environmental factors resulting in dynamic fluctuations within and between individuals. These inter and intra-individual fluctuations are evident in both so-called normal cognitive aging and at the onset of cognitive pathology. Mild Cognitive Impairment (MCI), thought to be a prodromal phase of dementia, represents perhaps the final opportunity to mitigate cognitive declines that may lead to terminal conditions such as dementia. The prognosis for people with MCI is mixed with the evidence suggesting that many will remain stable within 10-years of diagnosis, many will improve, and many will transition to dementia. If the characteristics of people who do not progress to dementia from MCI can be identified and replicated in others it may be possible to reduce or delay dementia onset, thus reducing a growing personal and public health burden. Furthermore, if MCI onset can be prevented or delayed, the burden of cognitive decline in aging populations worldwide may be reduced. A cognitive domain that is sensitive to the effects of advancing age, and declines in which have been shown to presage the onset of dementia in MCI patients, is executive function. Moreover, environmental factors such as diet and physical activity have been shown to affect performance on tests of executive function. For example, improvements in executive function have been demonstrated as a result of increased aerobic and anaerobic physical activity and, although the evidence is not as strong, findings from dietary interventions suggest certain nutrients may preserve or improve executive functions in old age. These encouraging findings have been demonstrated in older adults with MCI and their non-impaired peers. However, there are some gaps in the literature that need to be addressed. For example, little is known about the effect on cognition of an interaction between diet and physical activity. Both are important contributors to health and wellbeing, and a growing body of evidence attests to their importance in mental and cognitive health in aging individuals. Yet physical activity and diet are rarely considered together in the context of cognitive function. There is also little known about potential underlying biological mechanisms that might explain the physical activity/diet/cognition relationship. The first aim of this program of research was to examine the individual and interactive role of physical activity and diet, specifically long chain polyunsaturated fatty acid consumption(LCn3) as predictors of MCI status. The second aim is to examine executive function in MCI in the context of the individual and interactive effects of physical activity and LCn3.. A third aim was to explore the role of immune and endocrine system biomarkers as possible mediators in the relationship between LCn3, physical activity and cognition. Study 1a was a cross-sectional analysis of MCI status as a function of erythrocyte proportions of an interaction between physical activity and LCn3. The marine based LCn3s eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) have both received support in the literature as having cognitive benefits, although comparisons of the relative benefits of EPA or DHA, particularly in relation to the aetiology of MCI, are rare. Furthermore, a limited amount of research has examined the cognitive benefits of physical activity in terms of MCI onset. No studies have examined the potential interactive benefits of physical activity and either EPA or DHA. Eighty-four male and female adults aged 65 to 87 years, 50 with MCI and 34 without, participated in Study 1a. A logistic binary regression was conducted with MCI status as a dependent variable, and the individual and interactive relationships between physical activity and either EPA or DHA as predictors. Physical activity was measured using a questionnaire and specific physical activity categories were weighted according to the metabolic equivalents (METs) of each activity to create a physical activity intensity index (PAI). A significant relationship was identified between MCI outcome and the interaction between the PAI and EPA; participants with a higher PAI and higher erythrocyte proportions of EPA were more likely to be classified as non-MCI than their less active peers with less EPA. Study 1b was a randomised control trial using the participants from Study 1a who were identified with MCI. Given the importance of executive function as a determinant of progression to more severe forms of cognitive impairment and dementia, Study 1b aimed to examine the individual and interactive effect of physical activity and supplementation with either EPA or DHA on executive function in a sample of older adults with MCI. Fifty male and female participants were randomly allocated to supplementation groups to receive 6-months of supplementation with EPA, or DHA, or linoleic acid (LA), a long chain polyunsaturated omega-6 fatty acid not known for its cognitive enhancing properties. Physical activity was measured using the PAI from Study 1a at baseline and follow-up. Executive function was measured using five tests thought to measure different executive function domains. Erythrocyte proportions of EPA and DHA were higher at follow-up; however, PAI was not significantly different. There was also a significant improvement in three of the five executive function tests at follow-up. However, regression analyses revealed that none of the variance in executive function at follow-up was predicted by EPA, DHA, PAI, the EPA by PAI interaction, or the DHA by PAI interaction. The absence of an effect may be due to a small sample resulting in limited power to find an effect, the lack of change in physical activity over time in terms of volume and/or intensity, or a combination of both reduced power and no change in physical activity. Study 2a was a cross-sectional study using cognitively unimpaired older adults to examine the individual and interactive effects of LCn3 and PAI on executive function. Several possible explanations for the absence of an effect were identified. From this consideration of alternative explanations it was hypothesised that post-onset interventions with LCn3 either alone or in interation with self-reported physical activity may not be beneficial in MCI. Thus executive function responses to the individual and interactive effects of physical activity and LCn3 were examined in a sample of older male and female adults without cognitive impairment (n = 50). A further aim of study 2a was to operationalise executive function using principal components analysis (PCA) of several executive function tests. This approach was used firstly as a data reduction technique to overcome the task impurity problem, and secondly to examine the executive function structure of the sample for evidence of de-differentiation. Two executive function components were identified as a result of the PCA (EF 1 and EF 2). However, EPA, DHA, the PAI, or the EPA by PAI or DHA by PAI interactions did not account for any variance in the executive function components in subsequent hierarchical multiple regressions. Study 2b was an exploratory correlational study designed to explore the possibility that immune and endocrine system biomarkers may act as mediators of the relationship between LCn3, PAI, the interaction between LCn3 and PAI, and executive functions. Insulin-like growth factor-1 (IGF-1), an endocrine system growth hormone, and interleukin-6 (IL-6) an immune system cytokine involved in the acute inflammatory response, have both been shown to affect cognition including executive functions. Moreover, IGF-1 and IL-6 have been shown to be antithetical in so far as chronically increased IL-6 has been associated with reduced IGF-1 levels, a relationship that has been linked to age related morbidity. Further, physical activity and LCn3 have been shown to modulate levels of both IGF-1 and IL-6. Thus, it is possible that the cognitive enhancing effects of LCn3, physical activity or their interaction are mediated by changes in the balance between IL-6 and IGF-1. Partial and non-parametric correlations were conducted in a subsample of participants from Study 2a (n = 13) to explore these relationships. Correlations of interest did not reach significance; however, the coefficients were quite large for several relationships suggesting studies with larger samples may be warranted. In summary, the current program of research found some evidence supporting an interaction between EPA, not DHA, and higher energy expenditure via physical activity in differentiating between older adults with and without MCI. However, a RCT examining executive function in older adults with MCI found no support for increasing EPA or DHA while maintaining current levels of energy expenditure. Furthermore, a cross-sectional study examining executive function in older adults without MCI found no support for better executive function performance as a function of increased EPA or DHA consumption, greater energy expenditure via physical activity or an interaction between physical activity and either EPA or DHA. Finally, an examination of endocrine and immune system biomarkers revealed promising relationships in terms of executive function in non-MCI older adults particularly with respect to LCn3 and physical activity. Taken together, these findings demonstrate a potential benefit of increasing physical activity and LCn3 consumption, particularly EPA, in mitigating the risk of developing MCI. In contrast, no support was found for a benefit to executive function as a result of increased physical activity, LCn3 consumption or an interaction between physical activity and LCn3, in participants with and without MCI. These results are discussed with reference to previous findings in the literature including possible limitations and opportunities for future research.

Plasma metabolomics reveals biomarkers of the atherosclerosis

Atherosclerotic cardiovascular disease remains the leading cause of morbidity and mortality in industrialized societies. The lack of metabolite biomarkers has impeded the clinical diagnosis of atherosclerosis so far. In this study, stable atherosclerosis patients (n=16) and age- and sex-matched non-atherosclerosis healthy subjects (n=28) were recruited from the local community (Harbin, P. R. China). The plasma was collected from each study subject and was subjected to metabolomics analysis by GC/MS. Pattern recognition analyses (principal components analysis, orthogonal partial least-squares discriminate analysis, and hierarchical clustering analysis) commonly demonstrated plasma metabolome, which was significantly different from atherosclerotic and non-atherosclerotic subjects. The development of atherosclerosis-induced metabolic perturbations of fatty acids, such as palmitate, stearate, and 1-monolinoleoylglycerol, was confirmed consistent with previous publication, showing that palmitate significantly contributes to atherosclerosis development via targeting apoptosis and inflammation pathways. Altogether, this study demonstrated that the development of atherosclerosis directly perturbed fatty acid metabolism, especially that of palmitate, which was confirmed as a phenotypic biomarker for clinical diagnosis of atherosclerosis.

Metabolic urinary profiling of alcohol hepatotoxicity and intervention effects of Yin Chen Hao Tang in rats using ultra-performance liquid chromatography/electrospray ionization quadruple time-of-flight mass spectrometry

This paper was designed to study metabonomic characters of the hepatotoxicity induced by alcohol and the intervention effects of Yin Chen Hao Tang (YCHT), a classic traditional Chinese medicine formula for treatment of jaundice and liver disorders in China. Urinary samples from control, alcohol- and YCHT-treated rats were analyzed by ultra-performance liquid chromatography/electrospray ionization quadruple time-of-flight mass spectrometry (UPLC/ESI-QTOF-MS) in positive ionization mode. The total ion chromatograms obtained from the control, alcohol- and YCHT-treated rats were easily distinguishable using a multivariate statistical analysis method such as the principal components analysis (PCA). The greatest difference in metabolic profiling was observed from alcohol-treated rats compared with the control and YCHT-treated rats. The positive ions m/z 664.3126 (9.00 min) was elevated in urine of alcohol-treated rats, whereas, ions m/z 155.3547 (10.96 min) and 708.2932 (9.01 min) were at a lower concentration compared with that in urine of control rats, however, these ions did not indicate a statistical difference between control rats and YCHT-treated rats. The ion m/z 664.3126 was found to correspond to ceramide (d18:1/25:0), providing further support for an involvement of the sphingomyelin signaling pathway in alcohol hepatotoxicity and the intervention effects of YCHT.

Pavlovian Fear Conditioning Activates a Common Pattern of Neurons in the Lateral Amygdala of Individual Brains

Understanding the physical encoding of a memory (the engram) is a fundamental question in neuroscience. Although it has been established that the lateral amygdala is a key site for encoding associative fear memory, it is currently unclear whether the spatial distribution of neurons encoding a given memory is random or stable. Here we used spatial principal components analysis to quantify the topography of activated neurons, in a select region of the lateral amygdala, from rat brains encoding a Pavlovian conditioned fear memory. Our results demonstrate a stable, spatially patterned organization of amygdala neurons are activated during the formation of a Pavlovian conditioned fear memory. We suggest that this stable neuronal assembly constitutes a spatial dimension of the engram. © 2011 This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.

Using objective physical activity measures with youth : How many days of monitoring are needed?

Purpose The purpose of this study was to establish the minimal number of days of monitoring required for accelerometers to assess usual physical activity in children. Methods A total of 381 students (189 M, 192 F) wore a CSA 7164 uniaxial accelerometer for seven consecutive days. To examine age-related trends students were grouped as follows: Group I: grades 1-3 (N = 92); Group II: grades 4-6 (N = 98); Group III: grades 7-9 (N = 97); Group IV: grades 10-12 (N = 94). Average daily time spent in moderate-to-vigorous physical activity (MVPA) was calculated from minute-by-minute activity counts using the regression equation developed by Freedson et al. (1997). Results Compared with adolescents in grades 7 to 12, children in grades 1 to 6 exhibited less day-to-day variability in MVPA behavior. Spearman-Brown analysts indicated that between 4 and 5 d of monitoring would be necessary to a achieve a reliability of 0.80 in children, and between 8 and 9 d of monitoring would be necessary to achieve a reliability of 0.80 in adolescents. Within all grade levels, the 7-d monitoring protocol produced acceptable estimates of daily participation in MVPA (R = 0.76 (0.71-0.81) to 0.87 (0.84-0.90)). Compared with weekdays, children exhibited significantly higher levels of MVPA on weekends, whereas adolescents exhibited significantly lower levels of MVPA on weekends. Principal components analysis revealed two distinct time components for MVPA during the day for children (early morning, rest of the day), and three distinct time components for MVPA during the day for adolescents (morning, afternoon, early evening). Conclusions These results indicate that a 7-d monitoring protocol provides reliable estimates of usual physical activity behavior in children and adolescents and accounts for potentially important differences in weekend versus weekday activity behavior as well as differences in activity patterns within a given day.

Patterns of diversity in fatty acid composition in the Australian groundnut germplasm collection

Knowledge of the amounts and types of fatty acids in groundnut oil is beneficial, particularly from a nutritional standpoint. Germplasm evaluation data for fatty acid composition on 819 accessions of groundnut (Arachis hypogaea L.) from the Australian Tropical Field Crops Genetic Resource Centre, Biloela, Queensland were examined. Data for eight quantitative fatty acid descriptors have been documented. Statistical assessment, via methods of pattern analysis, summarised and described the patterns of variation in fatty acid composition of the groundnut accessions in the Australian germplasm collection. Presentation of the results from principal components analysis and hierarchical cluster analysis using a biplot was shown to be a very useful interpretative tool. Such a biplot enables a simultaneous examination of the relationships among all the accessions and the fatty acids. Unlike that information available via database searches, the results from contribution analysis together with the biplot provide a global picture of the diversity available for use in plant breeding programs. The use of standardised data for eight fatty acids, compared to using three specific fatty acids, provided a better description of the total diversity available because it remains relevant with possible changes in the nutritional preferences for fatty acids. Fatty acid composition was found to vary in relation to the branching pattern of the accessions. This pattern is generally indicative of the botanical types of groundnuts; Virginia (alternate) compared to Spanish and Valencia (sequential) botanical types.

Audit fees and asset securitization risks

The thesis investigates “where were the auditors in asset securitizations”, a criticism of the audit profession before and after the onset of the global financial crisis (GFC). Asset securitizations increase audit complexity and audit risks, which are expected to increase audit fees. Using US bank holding company data from 2003 to 2009, this study examines the association between asset securitization risks and audit fees, and its changes during the global financial crisis. The main test is based on an ordinary least squares (OLS) model, which is adapted from the Fields et al. (2004) bank audit fee model. I employ a principal components analysis to address high correlations among asset securitization risks. Individual securitization risks are also separately tested. A suite of sensitivity tests indicate the results are robust. These include model alterations, sample variations, further controls in the tests, and correcting for the securitizer self-selection problem. A partial least squares (PLS) path modelling methodology is introduced as a separate test, which allows for high intercorrelations, self-selection correction, and sequential order hypotheses in one simultaneous model. The PLS results are consistent with the main results. The study finds significant and positive associations between securitization risks and audit fees. After the commencement of the global financial crisis in 2007, there was an increased focus on the role of audits on asset securitization risks resulting from bank failures; therefore I expect that auditors would become more sensitive to bank asset securitization risks after the commencement of the crisis. I find that auditors appear to focus on different aspects of asset securitization risks during the crisis and that auditors appear to charge a GFC premium for banks. Overall, the results support the view that auditors consider asset securitization risks and market changes, and adjust their audit effort and risk considerations accordingly.

Temporal trends and bioavailability assessment of heavy metals in the sediments of Deception Bay, Queensland, Australia

Thirteen sites in Deception Bay, Queensland, Australia were sampled three times over a period of 7 months and assessed for contamination by a range of heavy metals, primarily As, Cd, Cr, Cu, Pb and Hg. Fraction analysis, enrichment factors and Principal Components Analysis-Absolute Principal Component Scores (PCA-APCS) analysis were conducted in order to identify the potential bioavailability of these elements of concern and their sources. Hg and Te were identified as the elements of highest enrichment in Deception Bay while marine sediments, shipping and antifouling agents were identified as the sources of the Weak acid Extractable Metals (WE-M), with antifouling agents showing long residence time for mercury contamination. This has significant implications for the future of monitoring and regulation of heavy metal contamination within Deception Bay.