The psychiatric diagnosis of Borderline Personality Disorder (BPD) leads to service users experiencing stigmatising and disempowering attitudes from professional mental health staff. To date, a nursing theory has not been developed to understand mental health nurses’ personal and professional constructions towards service users with this diagnosis. The development of such theory may enable improved service user engagement, collaboration and recovery for this group of individuals. This study answered the questions of determining the nature of mental health nurses’ beliefs towards service users with a diagnosis of BPD and how these beliefs affect their therapeutic relationships with this service user group. An ethnographic approach was used in this study. Data was collected using a combination of observation of the patient assessment and allocation meeting within a community mental health team; and ethnographic interviews with named nurses for service users with a diagnosis of Borderline Personality Disorder. A reflective journal was also kept by the lead researcher. N-Vivo Version 7 was used to aid data analysis and this involved examining the scripts for repetitive patterns or sequences including descriptions, figures of speech, metaphors etc. in order to illuminate differences between different practices and contexts. Findings from the study elicited a model of how CPNs construct BPD categorisations and a potential pathway to alienation is described together with recommendations for the development of CMHTs and CPNs when working with BPD. Development of reflexive practice can be a vehicle for developing alternative constructions of BPD and recovery informed practice can reduce stigmatising practices experienced by service users with BPD.

Mathematical models have been applied to biology and health to gain a better understanding of physiological systems and disease, as well as to improve levels of treatment and care for certain conditions. This thesis will focus on two different methodologies to investigate models of health, namely delay differential equations andBayesian based data mining. The first approach uses delay differential equations to model the glucose-insulin regulation system. Many models exist in this area, typically including four exponential functions, and take a number of different forms. The model used here is a system of two delay differential equations with two time delays. The one delay form of this model has previously been widely studied, but less is known about the two delay system from an analytical view point. This work improves upon the existing models by incorporating Hill functions instead of exponential functions. The new model presented is studied for its appropriateness and robustness to changing parameters such as glucose infusion rate and insulin degradation. A local and global stability of the two-delay system is presented both in general terms and explicitly using Lyapunov functionals and linear matrix inequalities. The second method employs data mining techniques including a robust and transparent naïve Bayes classifier for classification and prediction of aspects of health. A study into prediction of post-stroke mortality is made on a data set of stroke patients. Interesting results are obtained for the classification of naturally arising mortality periods and an investigation into the role of age as a risk factor for post-stroke mortality. A wide range of risk factors are then investigated for significance which are used to build new predictive models. These two approaches have the joint aim of improving the understanding of aspects of health through mathematical modelling techniques. A new model of the glucose-insulin regulatory system is developed and for the first time an analysis of the global stability of the two-delay model by use of a Lyapunov functional is provided. The second approach sees typical and robust data mining techniques used to analyse medical data. New models for stroke mortality and prediction of diabetes and obesity are created, which review risk factors and also illustrate the benefit of data mining techniques for analysing medical data.

This thesis explores the impact of changes in health policy introduced by Conservative administrations in the period 1987 to 1995 on the definition, management and control of professional work within general medical practice. The research underpinning this work combined secondary analysis, large-scale primary fieldwork and qualitative research with clinicians and managers. The first stage of primary fieldwork was conducted during the period September 1994 to June 1995 and consisted of a postal survey of 750 practices across England and Wales. This was followed up with a second phase of research involving depth interviews with managers and clinicians, delivered in the period July to November 1995. This pluralist methodology sought to connect micro and macro levels of analysis in exploring the relationship between the state, professions and managers in primary care. The research explores the extent to which a number of professional freedoms have been challenged by policy change including political, economic and technical autonomy and the extent to which this had changed the position and rewards of managers in general practice. Employing a multi-dimensional approach to the analysis of power this thesis suggests that prevailing theories of a decline in professional power, based primarily on economic relations at the macro level cannot account for the complexity of relations found in UK general practice. Further, studies focusing at the collective level of bargaining between the state and the medical profession in the UK have over-estimated the impact of policy change due to a neglect of study at the micro level. Rather this study has revealed a complex picture of both continuity and change in which general practitioners have lost, retained and in some cases extended their power as a result of policy initiatives. Whilst professional freedoms have remained relatively intact, the impact of policy change on the occupation of Practice Management has been more significant, with prevailing discourses of `managerialism' creating gendered struggles over the definition and meaning of management in primary care. This work therefore calls for a multi-dimensional account of social life which can explain the complex interaction of differing sites of power, within which a wide range of power resources are deployed. Further this work would endorse a dynamic concept of power in which 'patterns of interaction' (Bradley 1999) are fluid and changeable rather than fixed and self-sustaining systems. It is argued here that constraints on social action are created by the history of past agency, embedded in institutions and social practices that both shape, and are shaped by the agency of individuals.

The aim of this thesis is to develop a theoretical model to explore how sociomaterial networks, involving large-scale automation, come into being, persist and change over time, within a healthcare environment. It does so by bridging the gap between design, implementation and use of large-scale pathology automation (LSPA) within two United Kingdom (UK) National Health Service (NHS) laboratories. A longitudinal, multi-site, ethnographic approach was used, along with semi-structured interviews, template analysis and participant observation of LSPA ‘in-practice’. This research has suggested that design features, embedded within the material properties of LSPA, were purposefully intended to bring about organisational change. In both user organisations, the material affordances of LSPA resulted in anticipated skill mix changes. However, material constraints required the enforcement of changes to organisational routines, creating operational difficulties, which were then subsequently transferred across organisational boundaries by the researcher/manager. The identification of these sociomaterial affordances and constraints, in conjunction with humans acting as boundary objects, had the unintended consequence of influencing strategic decision making and initiating structural and cultural change. The development and practical application of the resulting SociomANTerial model allowed the researcher to trace the analytical history of these organisational changes over time and consider the impact of broader social structures such as power. Ultimately it is suggested that a greater emphasis on collaboration between users, designers and corporate agents will result in more innovative approaches for technology adoption and improved organisational design.

Rural and geographically isolated, the majority of Nepalese communities have very low incomes, poor transportation, and scarce health care resources; these people provide the context for this study. The consequences of these deprivations include high maternal and infant mortality rates, high prevalence of infectious disease and poverty. There are therefore exceptional challenges and disparities in meeting health care needs. However the recent advent of modern information communication technology (ICT) or Telemedicine has unleashed a new wave of opportunities for supporting the delivery of health care services. Despite suggestions that telemedicine will offer hope in developing countries there is only limited published evidence to support this claim. Telemedicine is and must remain a process of the delivery of care rather than a technology. The system must connect patients and healthcare professionals in a chain of care, rather than follow the wide array of existing or new and advanced technology. The successful introduction of telemedicine with tangible outputs requires an in-depth understanding of the existing health care system of the country and its challenges; strongly expressed ‘genuine need’ for the service by all the stakeholders as interested partners (patients, practitioners, health care service providers and the public); the actual status of ICT infrastructure in the country and costs. This study used a Participatory Action Research (PAR) approach to explore the feasibility, acceptability and impact of a telemedicine system in partnership with Dhulikhel Hospital: Kathmandu University Hospital and with three of its 12 rural, remote outreach centres, and the populations they serve. Participatory, repeated data collection methods included surveys, interviewing, listening and being with staff and communities over a two year period. The researcher and researched engaged in a complex inter-locking journey from which the Unlocking, Unblocking and Validation concepts emerged. The findings of this study emphasise the pivotal role that the rural health care workers play. Telemedicine not only has a place in improving access to healthcare through enhanced communication but it also empowers health care workers. These people need continued support to develop their competencies and boost their confidence within the changing health care environment. In conclusion telemedicine is primarily about people rather than technology. Effective and holistic telemedicine development is built upon a combined, interactive model involving access, communication and empowerment.

Healthcare assistants (HCAs) have been a longstanding feature of the Irish health service workforce albeit under different guises such as nursing auxiliary or nursing aide. However, concerns have been growing about this workforce since scandals in the UK (Winterbourne View and Mid-Staffordshire) and Ireland (Aras Attracta) reported appalling standards of care being administered by unregulated care assistant staff members to vulnerable adults in residential settings. Whilst recognising these concerns and acknowledging that the role continues to evolve and grow in significance from a policy perspective no proposal has being posited for the professional regulation for this occupational group. The purpose of this study is to explore the changing role of Healthcare Assistants in Ireland and to consider the potential need for professional regulation in the public interest. This thesis makes use of two central theories proposed to explain the pattern and motivation of professional regulation in healthcare, public interest theory and public choice theory. An explorative in-depth case study approach combining a number of different data-gathering methods, including focus groups with HCAs, semi-structured interviews with senior managers and other key stakeholders and document analysis, was adopted. The findings reveal the existence of a three tiered HCA workforce – qualified, part qualified and unqualified that is a source of confusion at the interface between HCAs and registered nurses for delegated tasks and subsequently viewed as a risk to patient safety. This study makes a valuable contribution to a neglected area of knowledge by presenting for the first time the views of HCAs and senior managers regarding professional regulation for the evolving HCA workforce in Ireland. The study also makes a valuable contribution to practice by developing a series of recommendations regarding regulation and governance of the HCA workforce.

The morphological analysis of blood smear slides by haematologists or haematopathologists is one of the diagnostic procedures available to evaluate the presence of acute leukaemia. This operation is a complex and costly process, and often lacks standardized accuracy owing to a variety of factors, including insufficient expertise and operator fatigue. This research proposes an intelligent decision support system for automatic detection of acute lymphoblastic leukaemia (ALL) using microscopic blood smear images to overcome the above barrier. The work has four main key stages. (1) Firstly, a modified marker-controlled watershed algorithm integrated with the morphological operations is proposed for the segmentation of the membrane of the lymphocyte and lymphoblast cell images. The aim of this stage is to isolate a lymphocyte/lymphoblast cell membrane from touching and overlapping of red blood cells, platelets and artefacts of the microscopic peripheral blood smear sub-images. (2) Secondly, a novel clustering algorithm with stimulating discriminant measure (SDM) of both within- and between-cluster scatter variances is proposed to produce robust segmentation of the nucleus and cytoplasm of lymphocytic cell membranes. The SDM measures are used in conjunction with Genetic Algorithm for the clustering of nucleus, cytoplasm, and background regions. (3) Thirdly, a total of eighty features consisting of shape, texture, and colour information from the nucleus and cytoplasm of the identified lymphocyte/lymphoblast images are extracted. (4) Finally, the proposed feature optimisation algorithm, namely a variant of Bare-Bones Particle Swarm Optimisation (BBPSO), is presented to identify the most significant discriminative characteristics of the nucleus and cytoplasm segmented by the SDM-based clustering algorithm. The proposed BBPSO variant algorithm incorporates Cuckoo Search, Dragonfly Algorithm, BBPSO, and local and global random walk operations of uniform combination, and Lévy flights to diversify the search and mitigate the premature convergence problem of the conventional BBPSO. In addition, it also employs subswarm concepts, self-adaptive parameters, and convergence degree monitoring mechanisms to enable fast convergence. The optimal feature subsets identified by the proposed algorithm are subsequently used for ALL detection and classification. The proposed system achieves the highest classification accuracy of 96.04% and significantly outperforms related meta-heuristic search methods and related research for ALL detection.

Sexual dimorphism of skeletal muscle can occur due to age and many of these age-related changes in skeletal muscle appear to be influenced by gender. In humans, the muscle mass peaks in the second decade while loss of muscle mass (sarcopenia) starts between the third and the fifth decade of life. In system biology, the function of genes still needs to be understood and understanding gene function remains a significant challenge. Several machine learning and computational techniques have been used to understand. However, these previous attempts have not produced enough interpretation of the impact of age on skeletal muscle mass across both gender. Although there are several thousands of genes, very few differentially expressed genes play an active role in understanding the age and gender differences. The core aim of this thesis is to uncover new biomarkers that can contribute towards the prevention of sarcopenia progress in humans according to the gene expression levels of skeletal muscle tissues. The main contributions are the development of machine learning methods based on majority voting of multi-evaluation methods and multi-feature selection methods in order to analyse microarray data and identify subsets of genes related to muscle mass loss in ageing males and females. Previously, statistical methods were used to find important genes related to the impact of age on muscle mass loss. Multi-filter and multi- wrapper based systems are proposed in this thesis to identify different and common sarcopenia-related genes in males and females based on human skeletal muscle. Genes are first sorted using three different evaluation methods (t-test, Entropy and Receiver operating characteristic). Then, important genes are obtained using majority voting based on the principle that combining multiple models can improve the generalization of the system. Experiments were conducted on three different microarray gene expression datasets and results have indicated a significant increase in classification accuracy up to 10% associated with sarcopenia when compared with existing systems.

The development of novel molecular tools has provided the scientific community with quick, easy, and scientifically sound ways of identifying individual strains belonging to the Burkholderia cepacia complex (Bcc). Bcc strains isolated from the sputum of 44 patients attending the Freeman Hospital Cardiopulmonary Transplant Unit were genotyped using recA PCR-RFLP analysis, and a clonality study performed using PFGE analysis. It was found that B. cenocepacia and B. multivorans were the predominant colonizing strains in these patients, and that infection with the ET-12 epidemic clone was the most prevalent strain amongst B. cenocepacia- infected patients. It was also found that pre-transplant strains remained responsible for post-transplant infections. Phenotypic methods for the identification of Bcc strains and closely related organisms have been difficult to develop. A collection of 493 strains including Burkholderia cepacia (genomovars I- IX), Pseudomonas aeruginosa, and other closely related organisms, were investigated for their abilities to produce a wide range of peptidases, glycosidases, esterases and other miscellaneous enzymes using both chromogenic and fluorogenic substrates. The 312 Bcc strains within the collection were also screened for their capacity to oxidise a number of carbohydrates. The heterogeneous nature of all nine Bcc species was confirmed by this study, as was the close phenotypic relationship of B. cepacia and B. cenocepacia. Some substrates, however, were shown to have some taxonomic utility for the differentiation of species within the Bcc and also for closely related organisms. Metabolic activities that showed diagnostic potential included production of 13-ribosidase, 13-xylosidase and 13-glucosidase, as well as oxidation of cellobiose, maltose and trehalose. Screening for palmitate esterase and a or 13-trypsin production was useful for the differentiation of Pandoraea sp. and Ralstonia picketti respectively. CF infections caused by P. aeruginosa and Bcc strains, are most successfully treated using two or three drug combinations. A number of cell wall-acting antibiotics were tested in combination with the phosphonopeptide alafosfalin for synergistic effects against Bcc and P. aeruginosa strains. Alafosfalin was most effective in combination with ceftazidime against Bcc strains, and in combination with tobramycin and ceftazidime as a triple combination against P. aeruginosa.

An interest in human coping applicable to endemic disease environments such as Bangladesh now includes disease mitigation and management through self-care. Although a frequently utilised treatment, research into the reasons behind self-care preference, types of self-care practised and the implications this has for individuals and communities in developing countries such as Bangladesh is lacking. This research therefore examines the adoption of self-care in Bangladesh and seeks to understand if it is an effective disease management strategy. A mixed methods approach was employed, targeting a representative sample of different gender, age and socioeconomic status across three locations. 630 questionnaires, 47 semi-structured interviews, 15 focus group discussions, 20 key informant interviews and a series of participatory research tools were applied to explore how and why people use self-care. Data were also used to identify behaviours indicative of appropriate and inappropriate self-care that are beneficial or detrimental to the individual. A detailed and complex picture of self-care emerged. It is widely used to prevent and respond to illness through traditional, herbal and modern pharmaceutical actions. Common illnesses and endemic diseases such as fever and diarrhoeal diseases were most frequently treated through self-care. A declining natural resource base, a hazardous flood environment and communication breakdown between doctors and patients can restrict self-care adoption. However, economic savings on healthcare expenditure, reduced opportunity costs and the means to preserve dignity represented positive aspects of self-care amongst participants. Examination of these factors demonstrated the failings of current health service provision as well as the potential for better self-care integration into existing healthcare approaches. Wider lessons for disease management were therefore derived from self-care including the importance of low cost manifold strategies and the value of local knowledge and ownership. It is concluded that although self-care is not a panacea for the burden of ill health there is evidence to suggest it can play a crucial role in coping with the insurmountable disease risks people face in Bangladesh. In doing so the research contributes to understanding self-care in developing countries as an integrated and integral component of the primary health care system and infectious disease risk reduction more widely.