33 research outputs found

    The prevalence and risk factors of chronic noncommunicable lung diseases in adults in rural and urban Sudan

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    Non-communicable diseases (NCDs) are a major and increasing global health issue. They represent 71% (41million) of all global deaths including 3.9 million due to chronic respiratory diseases (CRDs) and chronic obstructive pulmonary disease (COPD) in particular. COPD is now the third most common cause of death globally; 90% of COPD deaths occur in Low and Middle-Income Countries (LMICs). Sub-Saharan Africa (SSA) and Middle East and North Africa (MENA) countries report similar mortality rates from COPD of 18 per 100,000 population. However, the burden of COPD SSA is disputed and reports offer variable prevalence estimates, ranging from 4.1% to 22.2%. The work in this thesis set out to contribute new knowledge to this area by conducting a review of the literature about non-communicable lung disease in SSA and MENA and through population-based crosssectional studies (one urban and one rural) of the burden of non-communicable lung disease in adults in Sudan. For the literature review, a broad review was undertaken to capture the breadth of work on non-communicable lung disease in SSA and MENA. The two cross-sectional studies were done to the same core Burden of Obstructive Lung Diseases (BOLD) protocol. The urban study was done in Khartoum state and sampled from the non-institutionalised population aged 40 years and above; the rural study was done in Gezira state and used the same sampling approach but with an extended age range – 18 and above. Alongside the rural study the potential role for digital data was explored for future studies of this nature. Review of the literature found that whilst research has been done in this area, it is limited in breadth and depth. The prevalence of chronic respiratory symptoms (mainly shortness of breath was 10.9% and 18.7% in the urban and rural study participants, respectively). The prevalence of post bronchodilator airflow obstruction was 10.3% and 14.8% in urban Sudan and 5.5% and 7.7% in rural Sudan using Lower Limit of Normal (LLN) and Global Initiative for Chronic Obstructive Lung Disease (GOLD) definitions respectively. Older age was the main factor associated with airflow obstruction in both populations and helps to explain the difference in prevalence between the urban and rural studies as the latter included younger participants. Low Forced Vital Capacity (FVC) prevalence estimates were similar in the urban and rural studies - 58.1% vs 58% (Third National Health and Nutrition Examination Survey (NHANES) reference values), respectively. Pilot testing of digital compared to paper-based data capture found high levels of agreement between the two approaches suggesting that the former could be adopted in future work of this nature. Taken together, the work presented in this thesis highlights the limited breadth and depth of research on non-communicable lung disease in SSA and MENA to date and identifies a high burden of chronic respiratory symptoms and spirometric abnormalities (mainly low FVC) in adults in urban and rural Sudan. These findings suggest there is a substantial but underrecognised burden of non-communicable lung disease in Sudan and elsewhere in SSA and MENA that calls for greater attention from the research community alongside public health and health system strengthening for the prevention and control of these problems

    Decision-Support for Rheumatoid Arthritis Using Bayesian Networks: Diagnosis, Management, and Personalised Care.

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    PhD Theses.Bayesian networks (BNs) have been widely proposed for medical decision support. One advantage of a BN is reasoning under uncertainty, which is pervasive in medicine. Another advantage is that a BN can be built from both data and knowledge and so can be applied in circumstances where a complete dataset is not available. In this thesis, we examine how BNs can be used for the decision support challenges of chronic diseases. As a case study, we study Rheumatoid Arthritis (RA), which is a chronic inflammatory disease causing swollen and painful joints. The work has been done as part of a collaborative project including clinicians from Barts and the London NHS Trust involved in the treatment of RA. The work covers three stages of decision support, with progressively less available data. The first decision support stage is diagnosis. Various criteria have been proposed by clinicians for early diagnosis but these criteria are deterministic and so do not capture diagnostic uncertainty, which is a concern for patients with mild symptoms in the early stages of the disease. We address this problem by building a BN model for diagnosing RA. The diagnostic BN model is built using both a dataset of 360 patients provided by the clinicians and their knowledge as experts in this domain. The choice of factors to include in the diagnostic model is informed by knowledge, including a model of the care pathway which shows what information is available for diagnosis. Knowledge is used to classify the factors as risk factors, relevant comorbidities, evidence of pathogenesis mechanism, signs, symptoms, and serology results, so that the structure of BN model matches the clinical understanding of RA. Since most of the factors are present in the dataset, we are able to train the parameters of the diagnostic BN from the data. This diagnostic BN model obtains promising results in differentiating RA cases from other inflammatory arthritis cases. Aware that eliciting knowledge is time-consuming and could limit the uptake of these techniques, we consider two alternative approaches. First, we compare its diagnostic performance with an alternative BN model entirely learnt from data; we argue that having a clinically meaningful structure allows us to explain clinical scenarios in a way that cannot be done with the model learnt purely from data. We also examine whether useful knowledge can be retrieved from existing vi medical ontologies, such as SNOMED CT and UMLS. Preliminary results show that it could be feasible to use such sources to partially automate knowledge collection. After patients have been diagnosed with RA, they are monitored regularly by a clinical team until the activity of their disease becomes low. The typical care arrangement has two challenges: first, regular meetings with clinicians occur infrequently at fixed intervals (e.g., every six months), during which time the activity of the disease can increase (or ‘flare’) and decrease several times. Secondly, the best medications or combinations of medications must be found for each patient, but changes can only be made when the patient visits the clinic. We therefore develop this stage of decision support in two parts: the first and simplest part looks at how the frequency of clinic appointments could be varied; the second part builds on this to support decisions to adjust medication dosage. We describe this as the ‘self-management’ decision support model. Disease activity is commonly measured with Disease Activity Score 28 (DAS28). Since the joint count parts of this can be assessed by the patient, the possibility of collecting regular (e.g., weekly) DAS28 data has been proposed. It is not yet in wide use, perhaps because of the overheads to the clinical team of reviewing data regularly. The dataset available to us for this work came from a feasibility study conducted by the clinical collaborators of one system for collecting data from patients, although the frequency is only quarterly. The aim of the ‘self-management’ decision support system is therefore to sit between patient-entered data and the clinical team, saving the work of clinically assessing all the data. Specifically, in the first part we wish to predict disease activity so that an appointment should be made sooner, distinguishing this from patients whose disease is well-managed so that the interval between appointments can be increased. To achieve this, we build a dynamic BN (DBN) model to monitor disease activity and to indicate to patients and their clinicians whether a clinical review is needed. We use the data and a set of dummy patient scenarios designed by the experts to evaluate the performance of the DBN. The second part of the ‘self-management’ decision support stage extends the DBN to give advice on adjustments to the medication dosage. This is of particular clinical interest since one class of medications used (biological disease-modifying antirheumatic drugs) are very expensive and, although effective at reducing disease activity, can have severe adverse reactions. For both these reasons, decision support that allowed a patient to ‘taper’ the dosage of medications without frequent clinic visits would be very useful. This extension does not meet all the decision support needs, which ideally would also cover decision-making about the choice of medications. However, we have found that as yet there is neither sufficient data nor knowledge for this. vii The third and final stage of decision support is targeted at patients who live with RA. RA can have profound impacts on the quality of life (QoL) of those who live with it, affecting work, financial status, friendships, and relationships. Information from patient organisations such as the leaflets prepared by the National Rheumatoid Arthritis Society (NRAS) contains advice on managing QoL, but the advice is generic, leaving it up to each patient to select the advice most relevant to their specific circumstances. Our aim is therefore to build a BN-based decision support system to personalise the recommendations for enhancing the QoL of RA patients. We have built a BN to infer three components of QoL (independence, participation, and empowerment) and shown how this can be used to target advice. Since there is no data, the BN is developed from expert knowledge and literature. To evaluate the resulting system, including the BN, we use a set of patient interviews conducted and coded by our collaborators. The recommendations of the system were compared with those of experts in a set of test scenarios created from the interviews; the comparison shows promising results

    Supporting pharmacists and prescribers in paediatrics:explorations of current practice and electronic systems for medicine related decision support

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    There is a lack of published literature describing resource and support needs of paediatric prescribers and pharmacists. In order to understand how to support this group of healthcare professionals it is first necessary to identify their current use of resources when prescribing and providing pharmacy services in paediatrics. The methods used in this thesis were mixed. They included: focus groups with prescribers, self-completed questionnaires with paediatric pharmacy staff and paediatric prescribers, interviews with electronic prescribing leaders and documentary analysis of board meeting minutes from paediatric hospitals in England. The resource reported to be used most frequently and most useful by both pharmacists and prescribers was the British National Formulary for Children. The BNFc was reported to be useful due to its current information and ease of use. Pharmacist and prescriber participants reported using a wide range of resources suggesting that there is no single resource that meets their information needs when working in paediatrics. There was general agreement that the current poor availability of some paediatric prescribing information could have an adverse effect on the care of patients. Pharmacy staff reported that an electronic medicines management system improved the supply of medication to inpatients, but described a need for additional development of the system for it to be suitable for all medication supply. Paediatric hospital board minutes reported a range of interventions to improve prescribing, but few reported outcomes. To conclude: this thesis describes the extensive resource needs of both paediatric pharmacists and prescribers. The choice of resource is not affected by the status of its accreditation with NICE, raising a question of the value of this accreditation process. The lack of collaboration between paediatric hospitals regarding strategies used to improve paediatric prescribing is not acceptable and may lead to duplication of work or investment in poor support solutions

    An empirical evaluation of m-health service users’ behaviours: A case of Bangladesh

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    A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy.Mobile health (m-health) services are revolutionising healthcare in the developing world by improving accessibility, affordability, and availability. Although these services are revolutionising healthcare in various ways, there are growing concerns regarding users' service quality perceptions and overall influence on satisfaction and usage behaviours. In developing countries, access to healthcare and low healthcare costs are insufficient if users lack confidence in healthcare service quality. Bangladesh's Directorate General of Health Services (DGHS) provides the only government-sponsored m-health service available to the entire population. DGHS's m-health service, available since 2009, is yet to be evaluated in terms of users' perceptions of the quality of service and its impact on satisfaction and usage. Hence, this study developed a conceptual model for evaluating the associations between overall DGHS m-health service quality, satisfaction, and usage behaviours. This study operationalised overall m-health service quality as a higher-order construct with three dimensions- platform quality, information quality, and outcome quality, and nine corresponding subdimensions-privacy, systems availability, systems reliability, systems efficiency, responsiveness, empathy, assurance, emotional benefit, and functional benefit. Moreover, researchers in various service domains, including- healthcare, marketing, environmental protection, and information systems, evaluated and confirmed the influence of social and personal norms on satisfaction and behavioural outcomes like- intention to use. Despite this, no research has been conducted to determine whether these normative components affect m-health users' service satisfaction and usage behaviours. As a result, this study included social and personal norms along with overall service quality into the conceptual model to assess the influence of these variables on users' satisfaction and m-health service usage behaviours. Data was collected from two districts in Bangladesh- Dhaka and Rajshahi, utilising the online survey approach. A total of 417 usable questionnaires were analysed using partial least squares structural equation modelling to investigate the relationships between the constructs in Warp PLS. The study confirms that all three dimensions of service quality and their corresponding subdimensions influence users' overall perceptions of DGHS m-health service quality. Moreover, overall DGHS m-health service quality has a significant direct association with satisfaction and an indirect association with usage behaviours through satisfaction. While social norms do not influence satisfaction and usage behaviours within the DGHS m-health context, personal norms directly influence users' satisfaction and indirectly influence usage behaviours through satisfaction. Theoretically, the study contributes by framing the influence of users' overall m-health service quality perceptions, social and personal norms on their actual usage behaviours rather than the intention to use. It also extends the existing knowledge by assessing and comparing m-health users' continuous and discontinuous behaviours. Methodologically this study confirms the usefulness of partial least squares structural equational modelling to analyse a complex model including a higher order construct (i.e., overall perceived service quality). Practically, the study demonstrates the importance of users' satisfaction in addition to service quality, as service quality only affects usage behaviours through satisfaction in the current study context. Additionally, knowing that personal norms significantly influence service satisfaction motivates providers of m-health services to strive to enhance users' personal norms toward m-health service to enhance service satisfaction and usage. Overall, the study will help enhance patient outcomes and m-health service usage

    Transforming HIV Prevention & Care for Marginalised Populations: using information & communication technologies (ICTs) in community-based & led approaches

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    [Extract] Information and communication technology (ICT) is transforming community-based and community-led HIV prevention and care services for gay men, other men who have sex with men (MSM) and transgender people. This book celebrates and shares crucial work of frontline HIV workers, activists, researchers and educators whom are using innovative ICT. The book builds on, and extends the work included in two earlier issues of Digital Culture & Education (DCE), entitled 'Prevention is a solution: Building the HIVe'(Singh and Walsh, 2012) and 'Innovative programmatic approaches to HIV prevention and care services for gay men, other men who have sex with men (MSM) and transgender persons using information and communication technology (ICT)'(Adams, Klindera, Walsh and Wolf, 2014). It also includes three additional articles published by the journal

    Transforming HIV Prevention & Care for Marginalised Populations: using information & communication technologies (ICTs) in community-based & led approaches

    Get PDF
    [Extract] Information and communication technology (ICT) is transforming community-based and community-led HIV prevention and care services for gay men, other men who have sex with men (MSM) and transgender people. This book celebrates and shares crucial work of frontline HIV workers, activists, researchers and educators whom are using innovative ICT. The book builds on, and extends the work included in two earlier issues of Digital Culture & Education (DCE), entitled 'Prevention is a solution: Building the HIVe'(Singh and Walsh, 2012) and 'Innovative programmatic approaches to HIV prevention and care services for gay men, other men who have sex with men (MSM) and transgender persons using information and communication technology (ICT)'(Adams, Klindera, Walsh and Wolf, 2014). It also includes three additional articles published by the journal

    Perceptions of Economic, Health, and Environmental Effects of Hydraulic Fracturing in Indiana

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    Effects of hydraulic fracturing (HF) have become a controversial public health issue in the United States. The purpose of this qualitative case study was to explore community members\u27 perceptions of economic, health, and environmental effects of HF in Gibson County, Indiana. The conceptual framework was adapted from the health belief model and was named the HF health impact belief model (HFHIBM). Data were collected from stratified purposeful non-randomly selected 32 Gibson community members, using semi structured questionnaires, complete observations, and existing documents. Stratification was based on factors influencing perception, such as, gender, race, level of education, age or technology exposure, and level of media use. The observed community showed no economic boom or prevalent diseases, with functional and few abandoned pump jacks located on some of the farmlands. Data collected from the returned questionnaires were analyzed using hand coding and software. The results revealed that 72% of participants lacked awareness of HF, 90.6% reported lack of involvement in the decision-making process to locate HF near their community, and 21.6% of the 40.6% of participants with awareness reported that HF should be continued if the benefits outweigh the negative effects. Based on the constructs of HFHIBM, the low awareness of HF has implications on the community\u27s acceptance of HF, and the use of sustainable and environmentally safe alternatives may result in better acceptance of HF. Increased awareness of HF may lead to the development of environmentally friendly, sustainable preventive actions, better community health outcomes such as reduced morbidity and mortality rates, and improved drinking water quality in neighboring communities

    Critical Thinking Skills Profile of High School Students In Learning Science-Physics

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    This study aims to describe Critical Thinking Skills high school students in the city of Makassar. To achieve this goal, the researchers conducted an analysis of student test results of 200 people scattered in six schools in the city of Makassar. The results of the quantitative descriptive analysis of the data found that the average value of students doing the interpretation, analysis, and inference in a row by 1.53, 1.15, and 1.52. This value is still very low when compared with the maximum value that may be obtained by students, that is equal to 10.00. This shows that the critical thinking skills of high school students are still very low. One fact Competency Standards science subjects-Physics is demonstrating the ability to think logically, critically, and creatively with the guidance of teachers and demonstrate the ability to solve simple problems in daily life. In fact, according to Michael Scriven stated that the main task of education is to train students and or students to think critically because of the demands of work in the global economy, the survival of a democratic and personal decisions and decisions in an increasingly complex society needs people who can think well and make judgments good. Therefore, the need for teachers in the learning device scenario such as: driving question or problem, authentic Investigation: Science Processes
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