The Children's Depression Scale : assessment of factor structure with data from a normal population

A study investigated the reliability and construct validity of the Children's Depression Scale. The revised subscales were shown to have strong construct and face validity and high reliability.

The Queensland study of melanoma : Environmental and genetic associations (Q-MEGA); Study design, baseline characteristics, and repeatability of phenotype and sun exposure measures

Cutaneous malignant melanoma (CMM) is a major health issue in Queensland, Australia, which has the world’s highest incidence. Recent molecular and epidemiologic studies suggest that CMM arises through multiple etiological pathways involving gene-environment interactions. Understanding the potential mechanisms leading to CMM requires larger studies than those previously conducted. This article describes the design and baseline characteristics of Q-MEGA, the Queensland Study of Melanoma: Environmental and Genetic Associations, which followed up 4 population-based samples of CMM patients in Queensland, including children, adolescents, men aged over 50, and a large sample of adult cases and their families, including twins. Q-MEGA aims to investigate the roles of genetic and environmental factors, and their interaction, in the etiology of melanoma. Three thousand, four hundred and seventy-one participants took part in the follow-up study and were administered a computer-assisted telephone interview in 2002-2005. Updated data on environmental and phenotypic risk factors, and 2777 blood samples were collected from interviewed participants as well as a subset of relatives. This study provides a large and well-described population-based sample of CMM cases with follow-up data. Characteristics of the cases and repeatability of sun exposure and phenotype measures between the baseline and the follow-up surveys, from 6 to 17 years later, are also described.

Maternal age and paternal age are associated with distinct childhood behavioural outcomes in a general population birth cohort

Abstract Background Recent studies show that advanced paternal age (APA) is associated with an increased risk of neurodevelopmental disorders such as autism, bipolar disorder and schizophrenia. A body of evidence also suggests that individuals who develop schizophrenia show subtle deviations in a range of behavioural domains during their childhood. The aim of the study was to examine the relationship between paternal and maternal ages and selected behavioural measures in children using a large birth cohort. Method Participants were singleton children (n = 21,753) drawn from the US Collaborative Perinatal Project. The outcome measures were assessed at 7 years. The main analyses examined the relationship between parental age and behavioural measures when adjusted for a range of potentially confounding variables, including age of the other parent, maternal race, socio-economic measures, sex, gestation length, maternal marital status, parental mental illness, and child's age-at-testing. Results Advanced paternal age was associated with a significantly increased risk of adverse ‘externalizing’ behaviours at age seven years. For every five year increase in paternal age, the odds of higher ‘externalizing’ behaviours was increased by 12% (OR = 1.12; 95% CI = 1.03, 1.21, p < 0.0001). The relationship persisted after adjusting for potential confounding factors. ‘Internalizing’ behavioural outcome was not associated with advanced paternal age. In contrast, advanced maternal age was significantly protective against adverse ‘externalizing’ behavioural outcomes, but associated with an increased risk of adverse ‘internalizing’ behavioural outcomes. Discussion The offspring of older fathers show a distinctly different pattern of behaviours compared to the offspring of older mothers. The diverse socio-cultural and biologically-mediated factors that underpin these findings remain to be clarified. In light of secular trends related to delayed parenthood, the mechanisms underlying these findings warrant closer scrutiny.

A pilot study utilising cross-age peer tutoring as a method of intervention for anxious adolescents

Anxiety disorders are the most common psychopathology experienced by young people, with up to 18% of adolescents developing an anxiety disorder. The consequences of these disorders, if left untreated, include impaired peer relationships, school absenteeism and self-concept problems. In addition, anxiety disorders may play a causal role in the development of depression in young people, precede eating disorders and predispose adolescents to substance abuse disorders. While the school is often chosen as a place to provide early intervention for this debilitating disorder, the fact that excessive anxiety is often not recognised in school and that young people are reluctant to seek help, makes identifying these adolescents difficult. Even when these young people are identified, there are problems in providing sensitive programs which are not stigmatising to them within a school setting. One method which may engage this adolescent population could be cross-age peer tutoring. This paper reports on a small pilot study using the “Worrybusters” program and a cross-age peer tutoring method to engage the anxious adolescents. These anxious secondary school students planned activities for teacher-referred anxious primary school students for a term in the high school setting and then delivered those activities to the younger students weekly in the next term in the primary school. Although the secondary school students decreased their scores on anxiety self-report measures there were no significant differences for primary school students’ self-reports. However, the primary school parent reports indicated a significant decrease in their child’s anxiety.

Factors related to the presentation of thin and thick nodular melanoma from a population-based cancer registry in Queensland Australia

Purpose: Worldwide, the incidence of thick melanoma has not declined, and the nodular melanoma (NM) subtype accounts for nearly 40% of newly-diagnosed thick melanoma. To assess differences between patients with thin (≤2.00 mm) and thick (≥2.01 mm) nodular melanoma, we evaluated factors such as demographics, melanoma detection patterns, tumor visibility, and physician screening for NM alone and compared clinical presentation and anatomic location of NM with superficial spreading melanoma (SSM). Methods We utilized data from a large population-based study of Queensland (Australia) residents diagnosed with melanoma. Queensland residents aged 20 to 75 years with histologically confirmed first primary invasive cutaneous melanoma were eligible for the study, and all questionnaires were conducted by telephone (response rate 77.9%). Results During this four-year period, 369 patients with nodular melanoma were interviewed, of whom 56.7% were diagnosed with tumors ≤ 2.00 mm. Men, older individuals, and those who had not been screened by a physician in the past three years were more likely to have nodular tumors of greater thickness. Thickest nodular melanoma (4 mm+) was also most common in persons who had not been screened by a doctor within the past three years (OR 3.75; 95% CI 1.47-9.59). Forty-six percent of patients with thin nodular melanoma (≤ 2.00 mm) reported a change in color, compared with 64% of patients with thin SSM and 26% of patients with thick nodular melanoma (>2.00 mm). Conclusion Awareness of factors related to earlier detection of potentially fatal nodular melanomas, including the benefits of a physician examination, should be useful in enhancing public and professional education strategies. Particular awareness of clinical warning signs associated with thin nodular melanoma should allow for more prompt diagnosis and treatment of this subtype.

Population Monte Carlo Algorithm in High Dimensions

The population Monte Carlo algorithm is an iterative importance sampling scheme for solving static problems. We examine the population Monte Carlo algorithm in a simplified setting, a single step of the general algorithm, and study a fundamental problem that occurs in applying importance sampling to high-dimensional problem. The precision of the computed estimate from the simplified setting is measured by the asymptotic variance of estimate under conditions on the importance function. We demonstrate the exponential growth of the asymptotic variance with the dimension and show that the optimal covariance matrix for the importance function can be estimated in special cases.

A population survey of the penetrance of contact lens wear in Australia : rationale, methodology and results

Purpose: A population based, cross-sectional telephone survey was conducted to estimate the total penetrance of contact lens wear in Australia. Methods: A total of 42,749 households around Australia were randomly selected from the national electronic telephone directory based on postcode distribution. Before contact was attempted, letters of introduction were sent. The number of individuals and contact lens wearers in each household was ascertained and lens wearers were interviewed to determine details of lens type and mode of wear using a structured questionnaire. Results: Of households contacted, 59.2% (19,171/32,405) agreed to participate. Response rates were only marginally higher amongst households that first received a letter of introduction. In these households, 35,914 individuals were identified, of which, 1,798 were contact lens wearers. The penetrance of contact lens wear during the study period was 5.01% (95% CI: 4.78-5.24). Soft hydrogel lenses had the largest penetrance in the community, (66.7% of all wearers), however, their market share decreased significantly over the study period with increased uptake of newly introduced lens types. Conclusions: The penetrance of contact lens wear concurs with market estimates and equates to approximately 680,000 contact lens wearers aged between 15 and 64 years in Australia. The low response rate obtained in this study highlights the difficulty in contemporary use of telephone survey methodology

Digital kids, analogue students : a mixed methods study of students' engagement with a school-based Web 2.0 learning innovation

The inquiry documented in this thesis is located at the nexus of technological innovation and traditional schooling. As we enter the second decade of a new century, few would argue against the increasingly urgent need to integrate digital literacies with traditional academic knowledge. Yet, despite substantial investments from governments and businesses, the adoption and diffusion of contemporary digital tools in formal schooling remain sluggish. To date, research on technology adoption in schools tends to take a deficit perspective of schools and teachers, with the lack of resources and teacher ‘technophobia’ most commonly cited as barriers to digital uptake. Corresponding interventions that focus on increasing funding and upskilling teachers, however, have made little difference to adoption trends in the last decade. Empirical evidence that explicates the cultural and pedagogical complexities of innovation diffusion within long-established conventions of mainstream schooling, particularly from the standpoint of students, is wanting. To address this knowledge gap, this thesis inquires into how students evaluate and account for the constraints and affordances of contemporary digital tools when they engage with them as part of their conventional schooling. It documents the attempted integration of a student-led Web 2.0 learning initiative, known as the Student Media Centre (SMC), into the schooling practices of a long-established, high-performing independent senior boys’ school in urban Australia. The study employed an ‘explanatory’ two-phase research design (Creswell, 2003) that combined complementary quantitative and qualitative methods to achieve both breadth of measurement and richness of characterisation. In the initial quantitative phase, a self-reported questionnaire was administered to the senior school student population to determine adoption trends and predictors of SMC usage (N=481). Measurement constructs included individual learning dispositions (learning and performance goals, cognitive playfulness and personal innovativeness), as well as social and technological variables (peer support, perceived usefulness and ease of use). Incremental predictive models of SMC usage were conducted using Classification and Regression Tree (CART) modelling: (i) individual-level predictors, (ii) individual and social predictors, and (iii) individual, social and technological predictors. Peer support emerged as the best predictor of SMC usage. Other salient predictors include perceived ease of use and usefulness, cognitive playfulness and learning goals. On the whole, an overwhelming proportion of students reported low usage levels, low perceived usefulness and a lack of peer support for engaging with the digital learning initiative. The small minority of frequent users reported having high levels of peer support and robust learning goal orientations, rather than being predominantly driven by performance goals. These findings indicate that tensions around social validation, digital learning and academic performance pressures influence students’ engagement with the Web 2.0 learning initiative. The qualitative phase that followed provided insights into these tensions by shifting the analytics from individual attitudes and behaviours to shared social and cultural reasoning practices that explain students’ engagement with the innovation. Six indepth focus groups, comprising 60 students with different levels of SMC usage, were conducted, audio-recorded and transcribed. Textual data were analysed using Membership Categorisation Analysis. Students’ accounts converged around a key proposition. The Web 2.0 learning initiative was useful-in-principle but useless-in-practice. While students endorsed the usefulness of the SMC for enhancing multimodal engagement, extending peer-topeer networks and acquiring real-world skills, they also called attention to a number of constraints that obfuscated the realisation of these design affordances in practice. These constraints were cast in terms of three binary formulations of social and cultural imperatives at play within the school: (i) ‘cool/uncool’, (ii) ‘dominant staff/compliant student’, and (iii) ‘digital learning/academic performance’. The first formulation foregrounds the social stigma of the SMC among peers and its resultant lack of positive network benefits. The second relates to students’ perception of the school culture as authoritarian and punitive with adverse effects on the very student agency required to drive the innovation. The third points to academic performance pressures in a crowded curriculum with tight timelines. Taken together, findings from both phases of the study provide the following key insights. First, students endorsed the learning affordances of contemporary digital tools such as the SMC for enhancing their current schooling practices. For the majority of students, however, these learning affordances were overshadowed by the performative demands of schooling, both social and academic. The student participants saw engagement with the SMC in-school as distinct from, even oppositional to, the conventional social and academic performance indicators of schooling, namely (i) being ‘cool’ (or at least ‘not uncool’), (ii) sufficiently ‘compliant’, and (iii) achieving good academic grades. Their reasoned response therefore, was simply to resist engagement with the digital learning innovation. Second, a small minority of students seemed dispositionally inclined to negotiate the learning affordances and performance constraints of digital learning and traditional schooling more effectively than others. These students were able to engage more frequently and meaningfully with the SMC in school. Their ability to adapt and traverse seemingly incommensurate social and institutional identities and norms is theorised as cultural agility – a dispositional construct that comprises personal innovativeness, cognitive playfulness and learning goals orientation. The logic then is ‘both and’ rather than ‘either or’ for these individuals with a capacity to accommodate both learning and performance in school, whether in terms of digital engagement and academic excellence, or successful brokerage across multiple social identities and institutional affiliations within the school. In sum, this study takes us beyond the familiar terrain of deficit discourses that tend to blame institutional conservatism, lack of resourcing and teacher resistance for low uptake of digital technologies in schools. It does so by providing an empirical base for the development of a ‘third way’ of theorising technological and pedagogical innovation in schools, one which is more informed by students as critical stakeholders and thus more relevant to the lived culture within the school, and its complex relationship to students’ lives outside of school. It is in this relationship that we find an explanation for how these individuals can, at the one time, be digital kids and analogue students.

Terminally-ill people living alone without a caregiver: an Australian national scoping study of palliative care needs

Home-based palliative care services are facing increasing challenges in servicing the needs of clients who live alone and without a primary caregiver. The findings from the analysis of 721 services’ records from three Australian states, and feedback from health professionals in interviews and postal surveys, demonstrated that there were aspects of being on one’s own with a terminal illness and living at home that require a specialised approach and support. This study explored the issues of palliative care patients living alone, from a service provider perspective, and provided evidence-based information to assist with service planning. The study made recommendations to the Australian Department of Health and Ageing about services considered important in developing support structures for this growing population.

Does quality of life among breast cancer survivors one year after diagnosis differ depending on urban and non-urban residence? A comparative study

Background: This study examined the quality of life (QOL), measured by the Functional Assessment of Cancer Therapy (FACT) questionnaire, among urban (n=277) and non-urban (n=323) breast cancer survivors and women from the general population (n=1140) in Queensland, Australia. ---------- Methods: Population-based samples of breast cancer survivors aged <75 years who were 12 months post-diagnosis and similarly-aged women from the general population were recruited between 2002 and 2007. ---------- Results: Age-adjusted QOL among urban and non-urban breast cancer survivors was similar, although QOL related to breast cancer concerns was the weakest domain and was lower among non-urban survivors than their urban counterparts (36.8 versus 40.4, P<0.01). Irrespective of residence, breast cancer survivors, on average, reported comparable scores on most QOL scales as their general population peers, although physical well-being was significantly lower among non-urban survivors (versus the general population, P<0.01). Overall, around 20%-33% of survivors experienced lower QOL than peers without the disease. The odds of reporting QOL below normative levels were increased more than two-fold for those who experienced complications following surgery, reported upper-body problems, had higher perceived stress levels and/or a poor perception of handling stress (P<0.01 for all). ---------- Conclusions: Results can be used to identify subgroups of women at risk of low QOL and to inform components of tailored recovery interventions to optimize QOL for these women following cancer treatment.

Hierarchical models for 2D presence/absence data having ambiguous zeroes: With a biogeographical case study on dingo behaviour

This dissertation is primarily an applied statistical modelling investigation, motivated by a case study comprising real data and real questions. Theoretical questions on modelling and computation of normalization constants arose from pursuit of these data analytic questions. The essence of the thesis can be described as follows. Consider binary data observed on a two-dimensional lattice. A common problem with such data is the ambiguity of zeroes recorded. These may represent zero response given some threshold (presence) or that the threshold has not been triggered (absence). Suppose that the researcher wishes to estimate the effects of covariates on the binary responses, whilst taking into account underlying spatial variation, which is itself of some interest. This situation arises in many contexts and the dingo, cypress and toad case studies described in the motivation chapter are examples of this. Two main approaches to modelling and inference are investigated in this thesis. The first is frequentist and based on generalized linear models, with spatial variation modelled by using a block structure or by smoothing the residuals spatially. The EM algorithm can be used to obtain point estimates, coupled with bootstrapping or asymptotic MLE estimates for standard errors. The second approach is Bayesian and based on a three- or four-tier hierarchical model, comprising a logistic regression with covariates for the data layer, a binary Markov Random field (MRF) for the underlying spatial process, and suitable priors for parameters in these main models. The three-parameter autologistic model is a particular MRF of interest. Markov chain Monte Carlo (MCMC) methods comprising hybrid Metropolis/Gibbs samplers is suitable for computation in this situation. Model performance can be gauged by MCMC diagnostics. Model choice can be assessed by incorporating another tier in the modelling hierarchy. This requires evaluation of a normalization constant, a notoriously difficult problem. Difficulty with estimating the normalization constant for the MRF can be overcome by using a path integral approach, although this is a highly computationally intensive method. Different methods of estimating ratios of normalization constants (N Cs) are investigated, including importance sampling Monte Carlo (ISMC), dependent Monte Carlo based on MCMC simulations (MCMC), and reverse logistic regression (RLR). I develop an idea present though not fully developed in the literature, and propose the Integrated mean canonical statistic (IMCS) method for estimating log NC ratios for binary MRFs. The IMCS method falls within the framework of the newly identified path sampling methods of Gelman & Meng (1998) and outperforms ISMC, MCMC and RLR. It also does not rely on simplifying assumptions, such as ignoring spatio-temporal dependence in the process. A thorough investigation is made of the application of IMCS to the three-parameter Autologistic model. This work introduces background computations required for the full implementation of the four-tier model in Chapter 7. Two different extensions of the three-tier model to a four-tier version are investigated. The first extension incorporates temporal dependence in the underlying spatio-temporal process. The second extensions allows the successes and failures in the data layer to depend on time. The MCMC computational method is extended to incorporate the extra layer. A major contribution of the thesis is the development of a fully Bayesian approach to inference for these hierarchical models for the first time. Note: The author of this thesis has agreed to make it open access but invites people downloading the thesis to send her an email via the 'Contact Author' function.

Unraveling the complexity of driving while intoxicated: a study into the prevalence of psychiatric and substance abuse comorbidity

Objective Research is beginning to provide an indication of the co-occurring substance abuse and mental health needs for the driving under the influence (DUI) population. This study aimed to examine the extent of such psychiatric problems among a large sample size of DUI offenders entering treatment in Texas. Methods This is a study of 36,373 past year DUI clients and 308,714 non-past year DUI clients admitted to Texas treatment programs between 2005 and 2008. Data were obtained from the State's administrative dataset. Results Analysis indicated that non-past year DUI clients were more likely to present with more severe illicit substance use problems, while past year DUI clients were more likely to have a primary problem with alcohol. Nevertheless, a cannabis use problem was also found to be significantly associated with DUI recidivism in the last year. In regards to mental health status, a major finding was that depression was the most common psychiatric condition reported by DUI clients, including those with more than one DUI offence in the past year. This cohort also reported elevated levels of Bipolar Disorder compared to the general population, and such a diagnosis was also associated with an increased likelihood of not completing treatment. Additionally, female clients were more likely to be diagnosed with mental health problems than males, as well as more likely to be placed on medications at admission and more likely to have problems with methamphetamine, cocaine, and opiates. Conclusions DUI offenders are at an increased risk of experiencing comorbid psychiatric disorders, and thus, corresponding treatment programs need to cater for a range of mental health concerns that are likely to affect recidivism rates.

Reliability prediction using the non-parametric explicit hazard model : a case study

Survival probability prediction using covariate-based hazard approach is a known statistical methodology in engineering asset health management. We have previously reported the semi-parametric Explicit Hazard Model (EHM) which incorporates three types of information: population characteristics; condition indicators; and operating environment indicators for hazard prediction. This model assumes the baseline hazard has the form of the Weibull distribution. To avoid this assumption, this paper presents the non-parametric EHM which is a distribution-free covariate-based hazard model. In this paper, an application of the non-parametric EHM is demonstrated via a case study. In this case study, survival probabilities of a set of resistance elements using the non-parametric EHM are compared with the Weibull proportional hazard model and traditional Weibull model. The results show that the non-parametric EHM can effectively predict asset life using the condition indicator, operating environment indicator, and failure history.

Socioeconomic inequality profiles in physical and developmental health from 0-7 years : Australian National Study

Background: Early and persistent exposure to socioeconomic disadvantage impairs children’s health and wellbeing. However, it is unclear at what age health inequalities emerge or whether these relationships vary across ages and outcomes. We address these issues using cross-sectional Australian population data on the physical and developmental health of children at ages 0-1, 2-3, 4-5 and 6-7 years. Methods: 10 physical and developmental health outcomes were assessed in 2004 and 2006 for two cohorts each comprising around 5000 children. Socioeconomic position was measured as a composite of parental education, occupation and household income. Results: Lower socioeconomic position was associated with increased odds for poor outcomes. For physical health outcomes and socio-emotional competence, associations were similar across age groups and were consistent with either threshold effects (for poor general health, special healthcare needs and socio-emotional competence) or gradient effects (for illness with wheeze, sleep problems and injury). For socio-emotional difficulties, communication, vocabulary and emergent literacy, stronger socioeconomic associations were observed. The patterns were linear or accelerated and varied across ages. Conclusions: From very early childhood, social disadvantage was associated with poorer outcomes across most measures of physical and developmental health and showed no evidence of either strengthening or attenuating at older compared to younger ages. Findings confirm the importance of early childhood as a key focus for health promotion and prevention efforts.

Population-based survival estimates for childhood cancer in Australia during the period 1997–2006

Background: This study provides the latest available relative survival data for Australian childhood cancer patients. Methods: Data from the population-based Australian Paediatric Cancer Registry were used to describe relative survival outcomes using the period method for 11 903 children diagnosed with cancer between 1983 and 2006 and prevalent at any time between 1997 and 2006. Results: The overall relative survival was 90.4% after 1 year, 79.5% after 5 years and 74.7% after 20 years. Where information onstage at diagnosis was available (lymphomas, neuroblastoma, renal tumours and rhabdomyosarcomas), survival was significantly poorer for more-advanced stage. Survival was lower among infants compared with other children for those diagnosed with leukaemia, tumours of the central nervous system and renal tumours but higher for neuroblastoma. Recent improvements in overall childhood cancer survival over time are mainly because of improvements among leukaemia patients. Conclusion: The high and improving survival prognosis for children diagnosed with cancer in Australia is consistent with various international estimates. However, a 5-year survival estimate of 79% still means that many children who are diagnosed with cancer will die within 5 years, whereas others have long-term health morbidities and complications associated with their treatments. It is hoped that continued developments in treatment protocols will result in further improvements in survival.