Childhood burn injuries are a leading cause of death and disability worldwide and a major public health concern. Children younger than five years of age are more at risk. Majority of burn incidents occur as accidents within the home. Poor parental burn hazard perception and knowledge of burns first aid have been reported. This PhD project aimed to determine whether a targeted preventative parenting intervention ‘Toddler-safe’ improved parental burns safety and first aid knowledge and behaviour in the home, and reduced the risk of future childhood burns. A systematic review of the literature was undertaken to assess the effectiveness of parenting interventions at preventing unintentional injuries in pre-school children. The review found that parenting interventions that provided home visitation, education, and free/discounted safety devices, delivered on a one-to-one basis, during the perinatal or early postnatal period, were associated with significantly fewer childhood injuries, and improvements in parental safety knowledge and practices. However, there was a lack of prevention intervention research specifically for burn injuries in children under the age of five. Findings from the systematic review informed the design and methodology of the Toddler-Safe study. Toddler-Safe was conducted as a randomised controlled trial. One hundred and fifty six parents allocated to the intervention arm of the trial received an intervention consisting of a burns safety and first aid video, and an injury safety leaflet. An equal number of controls received only the injury safety leaflet. The study was evaluated using pre- and post-test questionnaires. Outcome measures included first aid knowledge and burns prevention, knowledge, attitude, and practices; and parent-reported or medically attended injuries. Just over half of the study participants were available for follow-up at six months. Non-responders were found to be younger and from lower socioeconomic backgrounds. Toddler-Safe was not effective at improving parental burns prevention and first aid knowledge, attitudes, and practices at ii follow-up. Burn injuries were reported in four children living with participating families. Participant attrition and omission of key knowledge and attitude topics from the intervention were major limitations of the study.

Cystic fibrosis-related diabetes (CFRD) is a secondary form of diabetes, associated with increasing age in subjects with Cystic Fibrosis (CF). With improved life expectancy, CFRD is anticipated to increase in prevalence in addition to its complications. The aim of this study was to investigate the use of HbA1c as an early predictor of disease, as well as investigate microvascular and macrovascular complications in an adult CF cohort attending the All Wales Cystic Fibrosis Centre. The current method of using the conventional oral glucose tolerance test (OGTT) to diagnose CFRD was compared to using glycated haemoglobin (HbA1c). The findings demonstrated that a HbA1c value ≥ 5.5%/36mmol/mol was significantly predictive of the development of dysglycaemia over a 6-year period. The association between HbA1c and development of diabetic retinopathy (DR) was analysed. The study demonstrated 23% of CF patients with CFRD screened for DR had evidence of moderate to severe diabetic retinopathy. They had a higher HbAc1 and longer duration of CFRD compared to those without severe forms of DR. This suggests that microvascular complications are present in CFRD and to a similar extent as in type 1 diabetes mellitus. The prevalence of cardiac autonomic neuropathy (CAN) in CFRD was tested in 71 subjects with CF. CF subjects who were of an older age group demonstrated an inverse correlation with heart rate variability (HRV) during deep breathing (p < 0.05). CF dysglyaemic individuals with severe forms of diabetic retinopathy had reduced HRV during deep breathing compared to subjects with mild or no DR (p < 0.05). The presence of arterial stiffness in CFRD was examined in 65 CF subjects and 31 healthy volunteers. Age, gender and mean arterial pressure were significant predictors of increased augmentation index (AIx) and pulse wave velocity (PWV). Glycaemic control did not influence the arterial stiffness measurement outcomes. The CF group demonstrated a greater Aix than healthy volunteers (HV) (P < 0.05) when other variables were controlled in the analysis, suggesting possible increased inflammatory mechanism leading to increased Aix accounting for these findings. CF dysglycaemic subjects had greater PWV than CFNGT subjects which was only significant at the 10% level. The study findings demonstrate HbA1c has a predictive value in the diagnosis of CFRD based on a positive OGTT. Severe DR is prevalent in CFRD and is associated with a reduction in HRV during deep breathing. Glycaemic control is not predictive of arterial stiffness, in contrast to age, gender and MAP. Thus future consideration of the use of HbA1c may help to predict individuals with underlying dysglycaemia and reduce the risk of the development of associated microvascular complications.

One of the biggest challenges in psychiatric genetics is examining the effects of interactions between genetic variants on the aetiologies of complex disorders. Current techniques involve looking at linear combinations of the variants, as considering all the possible combinations of interactions is computationally unfeasible. The work in this thesis attempted to address this problem by using a machine learning model called a Support Vector Machine (SVM). These algorithms are capable of either building linear models or using kernel methods to consider the effects of interactions. The dataset used for all of the experiments was taken from a study looking into sufferers of treatment-resistant schizophrenia receiving the medication, Clozapine, with controls taken from the Wellcome Trust Case/Control Consortium study. The first experiment used information from the individual Single Nucleotide Polymorphisms (SNPs) as inputs to the SVMs, and compared the results with a technique called a polygenic score, a linear combination of the risk contributions of the SNPs that provides a single risk score for each individual. When more SNPs were entered into the models, one of the non-linear kernels provided better results than the linear SVMs. The second experiment attempted to explain this behaviour by using simulated phenotypes made from different contributions of main effects and interactions. The results strongly suggested that interactions were making a contribution. The final experiment looked at using risk scores made from gene sets. The models identified a set involved in synaptic development that has been previously implicated in schizophrenia, and when the scores from the individual genes were entered, the non-linear kernels again showed improvement, suggesting that there are interactions occurring between these genes. The conclusion was that using SVMs is an effective way to assess for the possible presence of interactions, before searching for them explicitly.

During the past decade, there has been a great interest in creating mathematical models to describe the properties of connectivity in the human brain. One of the established tools to describe these interactions among regions of the brain is graph theory. However, graph theoretical methods were mainly designed for the analysis of single network which is problematic for neuroscientists wishing to study groups of subjects. Specifically, studies using the Rich Club (RC) graph measure require cumbersome methods to make statistical inferences. In the first part of this work, we propose a framework to analyse the inter-subject variability in Rich Club organisation. The proposed framework is used to identify the changes in RC coefficient and RC organisation in patients with schizophrenia relative to healthy control. We follow this work by proposing a novel method, named Rich Block (RB), which is a combination of the tradition Rich Club and Stochastic Block Models (SBM). We show that using RBs can not only facilitate an inter-subject statistical inference, it can also account for differences in profile of connectivity, and control for subject-level covariates. We validate the Rich Block approach by simulating networks of different size and structure. We find that RB accurately estimates RC coefficients and RC organisations, specifically, in network with large number of nodes and blocks. With real data we use RB to identify changes in coefficient and organisation of highly connected sub-graphs of hub blocks in schizophrenia. In the final portion of this work, we examine the methods used to define each edge in networks formed from resting-state functional magnetic resonance imaging (rs-fMRI). The standard approach in rs-fMRI is to divide the brain into regions, extract time series, and compute the temporal correlation between each region. These correlations are assumed to follow standard results, when in fact serial autocorrelation in the time series can corrupt these results. While some authors have proposed corrections to account for autocorrelation, they are poorly documented and always assume homogeneity of autocorrelation over brain regions. Thus we propose a method to account for bias in interregion correlation estimates due to autocorrelation. We develop an exact method and an approximate, more computationally efficient method that adjusts for the sampling variability in the correlation coefficient. We use inter-subject scrambled real-data to validate the proposed methods under a null setting, and intact real-data to examine the impact of our method on graph theoretical measures. We find that the standard methods fail to practically correct the sensitivity and specificity level due to over-simplifying the temporal structure of BOLD time series, while even our approximate method is substantially more accurate.

This thesis encompasses an overview and critical analysis of 11 publications of clinical and translational cardiac electrophysiology research that has been executed over the last seven years. The focus of this dissertation and the selected papers is on the use of electroanatomic mapping technology to define the arrhythmogenic substrate in patients with structural heart disease and ventricular arrhythmias. Such advancements in elucidating the mechanisms and pathophysiology underlying scar-related ventricular tachycardia have yielded improved clinical outcomes for patients with drug-refractory ventricular arrhythmias. Chapter 1 describes the epidemiologic background and introduces the concept of intracardiac mapping and the technological evolution that has provided the basis for this current body of work. Chapter 2 and Chapter 3 provide a detailed description of how electroanatomic mapping studies have provided critical insight into disease pathogenesis in patients with dilated nonischemic cardiomyopathy arrhythmogenic right ventricular cardiomyopathy (ARVC). The clinical impact and relevance of these studies are discussed based on conventional electroanatomic mapping technologies to define abnormal physiological substrates. Chapter 3 also addresses important considerations regarding percutaneous epicardial mapping and ablation that have been derived from extensive clinical experience. Chapter 4 and Chapter 5 describe the evolution of mapping technologies and the use of high-resolution mapping system technologies. These chapters discuss the potential clinical advantages of these technologies during substrate and activation mapping, particularly in post-infarct ventricular scar and VT. Finally, Chapter 6 concludes this thesis with final thoughts on the broader context of the lessons that have been learned from the studies that are presented in this thesis and implications for future work.

This thesis investigates the writing process in narratives by Greek deaf students in two different conditions: a) translation from Greek Sign Language into written Greek from video stimuli and b) direct composition in written Greek from picture stimuli. Following language assessments, the deaf students were divided into three language groups according to their differing abilities in Greek Sign Language and written Greek:. Two parameters were manipulated: language skills and source material used or writing. The study aims to answer the questions: a) How do the different groups make use of the source material (Le. Which students benefit from the use of sign language)? b) Which material produces better written texts? and c) What are the characteristics of the language produced, among the different groups (Le. the profile of errors)? Four qualitative analyses have been undertaken on the texts: amount/type of information given, organisation of information, grammatical characteristics of the text, and error analysis. The results show that the use of sign language in the writing process has positive effects only on specific groups and on specific aspects of writing. Keywords: Deaf students, writing, narratives, bilingualism, translation, direct writing.

Background: Body composition is affected by diseases, and affects responses to medical treatments, dosage of medicines, etc., while an abnormal body composition contributes to the causation of many chronic diseases. While we have reliable biochemical tests for certain nutritional parameters of body composition, such as iron or iodine status, and we have harnessed nuclear physics to estimate the body’s content of trace elements, the very basic quantification of body fat content and muscle mass remains highly problematic. Both body fat and muscle mass are vitally important, as they have opposing influences on chronic disease, but they have seldom been estimated as part of population health surveillance. Instead, most national surveys have merely reported BMI and waist, or sometimes the waist/hip ratio; these indices are convenient but do not have any specific biological meaning. Anthropometry offers a practical and inexpensive method for muscle and fat estimation in clinical and epidemiological settings; however, its use is imperfect due to many limitations, such as a shortage of reference data, misuse of terminology, unclear assumptions, and the absence of properly validated anthropometric equations. To date, anthropometric methods are not sensitive enough to detect muscle and fat loss. Aims: The aim of this thesis is to estimate Adipose/fat and muscle mass in health disease and during weight loss through; 1. evaluating and critiquing the literature, to identify the best-published prediction equations for adipose/fat and muscle mass estimation; 2. to derive and validate adipose tissue and muscle mass prediction equations; and 3.to evaluate the prediction equations along with anthropometric indices and the best equations retrieved from the literature in health, metabolic illness and during weight loss. Methods: a Systematic review using Cochrane Review method was used for reviewing muscle mass estimation papers that used MRI as the reference method. Fat mass estimation papers were critically reviewed. Mixed ethnic, age and body mass data that underwent whole body magnetic resonance imaging to quantify adipose tissue and muscle mass (dependent variable) and anthropometry (independent variable) were used in the derivation/validation analysis. Multiple regression and Bland-Altman plot were applied to evaluate the prediction equations. To determine how well the equations identify metabolic illness, English and Scottish health surveys were studied. Statistical analysis using multiple regression and binary logistic regression were applied to assess model fit and associations. Also, populations were divided into quintiles and relative risk was analysed. Finally, the prediction equations were evaluated by applying them to a pilot study of 10 subjects who underwent whole-body MRI, anthropometric measurements and muscle strength before and after weight loss to determine how well the equations identify adipose/fat mass and muscle mass change. Results: The estimation of fat mass has serious problems. Despite advances in technology and science, prediction equations for the estimation of fat mass depend on limited historical reference data and remain dependent upon assumptions that have not yet been properly validated for different population groups. Muscle mass does not have the same conceptual problems; however, its measurement is still problematic and reference data are scarce. The derivation and validation analysis in this thesis was satisfactory, compared to prediction equations in the literature they were similar or even better. Applying the prediction equations in metabolic illness and during weight loss presented an understanding on how well the equations identify metabolic illness showing significant associations with diabetes, hypertension, HbA1c and blood pressure. And moderate to high correlations with MRI-measured adipose tissue and muscle mass before and after weight loss. Conclusion: Adipose tissue mass and to an extent muscle mass can now be estimated for many purposes as population or groups means. However, these equations must not be used for assessing fatness and categorising individuals. Further exploration in different populations and health surveys would be valuable.

In 2008, the Organ Donation Taskforce was asked to consider the impact of introducing an opt-out system for organ donation in the United Kingdom. The Taskforce conducted a thorough investigation, which included information gathering from both the public and experts in the field of healthcare, ethics and law and a thorough appraisal of the countries currently operating an opt-out system. Having reviewed this evidence the ODT conceded that whilst the numbers of organs generated may increase under an opt-out system, conversely, because of the way the system actually works, they felt there was a risk that its introduction may cause a backlash amongst the general public resulting in a decrease in organ donations. They based their concerns around fears that such a system would remove the potential for spontaneous acts of goodwill, denying people the opportunity to give a gift, and may deny the opportunity for individuals to determine whether their organs should be donated, thereby precluding choice and the right to self-determination. This might ultimately compromise public trust in the system. This thesis challenges the assumptions made by the Organ Donation Taskforce in respect of introducing an opt-out system. It casts doubt on their claims about compromising privacy interests and then looks to reconcile the potential issues which may arise under an opt-out system; these are preventing the choice to act altruistically and acting in such a way as to undermine public trust. Both of these may result in policy failure. It will advocate a system which addresses the issues raised by the ODT and acts to provide respect for self-determination; this is a soft opt-out system with a combined registry. Such a system would increase the supply of organs for those in need of a transplant, and remain consistent with a society's values in terms of demonstrating respect for individual choice regarding donation.

Background: Moderate to severe chronic pain affects one in five of adults. The prevalence and impact of pain increase with age. Pain may increase the risk of mortality but the relationship is not clear. Aims: To test the hypothesis that pain increases the risk of mortality, to test if the relationship was dependent on pain classification and identify mediators and moderators of the relationship. Methods: A systematic review and meta-analysis evaluated existing evidence. Survival analyses (Cox’s proportional hazard modelling and a novel technique to assess mediation within survival models) were conducted on two large population studies of adults aged ≥50 years; the English Longitudinal Study of Ageing (ELSA) (n=6324) and the North Staffordshire Osteoarthritis Project (NorStOP) (n=10985). Lifestyle, health, social and psychological factors were tested as potential mediators. Sex and comorbidity were tested as moderators. Results: In the systematic review pooled analysis from 7 studies revealed a modest but non-significant risk of mortality for people with chronic pain (Mortality Rate Ratio 1.14, 95%CI (0.95, 1.37)). In survival analyses the relationship with mortality was influenced by pain classification: pain that was troubling (1.29 (1.12, 1.49)) or that interfered with daily activities (1.88 (1.54, 2.29)) was associated with an increased risk of mortality while reporting any pain was not (1.06 (0.95, 1.19)). The strongest mediators in ELSA that were replicated in NorStOP were functional limitation (Hazard Ratio 1.31; 95%CI (1.20, 1.39)), physical inactivity (1.14 (1.10, 1.20)) and poor self-rated health (1.32 (1.23, 1.41)). Sex and comorbidity moderated the extent of some mediating pathways (e.g. depression) but the findings were inconsistent between datasets. Conclusion: Specific opportunities to reduce mortality risk for people with pain were identified. At a population level, mortality risk for people with pain could be reduced by the effective management of pain and its impact.

Musculoskeletal conditions, including arthritis, have a global impact, causing increased disability and reduced quality of life. Previous research has demonstrated negative attitudes and beliefs about arthritis exist which means the condition is often undermanaged and deprioritised. One potential influence on such attitudes is the media. Understanding how the media constructs arthritis, and what impact media constructions have on perceptions of arthritis, will shed light on factors that influence attitudes and management of the condition in everyday life. This research aimed to investigate media constructions of arthritis. Mixed methods were used, including media analysis of highest circulating newspapers (n=11) and magazines (n=3), and focus groups (n=2) to explore reception of media messages. Results were analysed using a combination of thematic, discourse and imagery analyses. A total of 1014 newspaper and 18 magazine articles were analysed. Arthritis was conceptualised in three ways - as a disease, condition or ailment. As such, arthritis was not presented as a singular condition; instead the construction, enactment and reality of arthritis were multiple. These multiple conceptualisations were shaped by wider social issues, such as understandings of disability (saints or scroungers) and ageing (peril or promise), and their representation in the media was determined by factors of media production (audience targeting, commercial interests and ‘newsworthiness’). The focus group findings reflected these perceptions, as well as illustrating that media trust and credibility influence how media messages are received and interpreted by the general public. Recognising arthritis as multiple is important for health care professionals and patients, as the multiple conceptualisations can impact on how arthritis is enacted, and may affect perceptions of legitimacy and deservedness. Media representations of arthritis may lead to the condition being deprioritised and could present a barrier to the uptake of self-management strategies recommended in current guidelines.