994 resultados para Fuzzy Chronic Poverty
Resumo:
Objective: To determine whether primary care management of chronic heart failure (CHF) differed between rural and urban areas in Australia. Design: A cross-sectional survey stratified by Rural, Remote and Metropolitan Areas (RRMA) classification. The primary source of data was the Cardiac Awareness Survey and Evaluation (CASE) study. Setting: Secondary analysis of data obtained from 341 Australian general practitioners and 23 845 adults aged 60 years or more in 1998. Main outcome measures: CHF determined by criteria recommended by the World Health Organization, diagnostic practices, use of pharmacotherapy, and CHF-related hospital admissions in the 12 months before the study. Results: There was a significantly higher prevalence of CHF among general practice patients in large and small rural towns (16.1%) compared with capital city and metropolitan areas (12.4%) (P < 0.001). Echocardiography was used less often for diagnosis in rural towns compared with metropolitan areas (52.0% v 67.3%, P < 0.001). Rates of specialist referral were also significantly lower in rural towns than in metropolitan areas (59.1% v 69.6%, P < 0.001), as were prescribing rates of angiotensin-converting enzyme inhibitors (51.4% v 60.1%, P < 0.001). There was no geographical variation in prescribing rates of β-blockers (12.6% [rural] v 11.8% [metropolitan], P = 0.32). Overall, few survey participants received recommended “evidence-based practice” diagnosis and management for CHF (metropolitan, 4.6%; rural, 3.9%; and remote areas, 3.7%). Conclusions: This study found a higher prevalence of CHF, and significantly lower use of recommended diagnostic methods and pharmacological treatment among patients in rural areas.
Resumo:
Background: Chronic diseases including type 2 diabetes are a leading cause of morbidity and mortality in midlife and older Australian women. There are a number of modifiable risk factors for type 2 diabetes and other chronic diseases including smoking, nutrition, physical activity and overweight and obesity. Little research has been conducted in the Australian context to explore the perceived barriers to health promotion activities in midlife and older Australian women with a chronic disease. Aims: The primary aim of this study was to explore women’s perceived barriers to health promotion activities to reduce modifiable risk factors, and the relationship of perceived barriers to smoking behaviour, fruit and vegetable intake, physical activity and body mass index. A secondary aim of this study was to investigate nurses’ perceptions of the barriers to action for women with a chronic disease, and to compare those perceptions with those of the women. Methods: The study was divided into two phases where Phase 1 was a cross sectional survey of women, aged over 45 years with type 2 diabetes who were attending Diabetes clinics in the Primary and Community Health Service of the Metro North Health Service District of Queensland Health (N = 22). The women were a subsample of women participating in a multi-model lifestyle intervention, the ‘Reducing Chronic Disease among Adult Australian Women’ project. Phase 2 of the study was a cross sectional online survey of nurses working in Primary and Community Health Service in the Metro North Health Service District of Queensland Health (N = 46). Pender’s health promotion model was used as the theoretical framework for this study. Results: Women in this study had an average total barriers score of 32.18 (SD = 9.52) which was similar to average scores reported in the literature for women with a range of physical disabilities and illnesses. The leading five barriers for this group of women were: concern about safety; too tired; not interested; lack of information about what to do; with lack of time and feeling I can’t do things correctly the equal fifth ranked barriers. In this study there was no statistically significant difference in average total barriers scores between women in the intervention group and those is the usual care group of the parent study. There was also no significant relationship between the women’s socio-demographic variables and lifestyle risk factors and their level of perceived barriers. Nurses in the study had an average total barriers score of 44.48 (SD = 6.24) which was higher than all other average scores reported in the literature. The leading five barriers that nurses perceived were an issue for women with a chronic disease were: lack of time and interferes with other responsibilities the leading barriers; embarrassment about appearance; lack of money; too tired and lack of support from family and friends. There was no significant relationship between the nurses’ sociodemographic and nursing variables and the level of perceived barriers. When comparing the results of women and nurses in the study there was a statistically significant difference in the median total barriers score between the groups (p < 0.001), where the nurses perceived the barriers to be higher (Md = 43) than the women (Md = 33). There was also a significant difference in the responses to the individual barriers items in fifteen of the eighteen items (p < 0.002). Conclusion: Although this study is limited by a small sample size, it contributes to understanding the perception of midlife and older women with a chronic disease and also the perception of nurses, about the barriers to healthy lifestyle activities that women face. The study provides some evidence that the perceptions of women and nurses may differ and argues that these differences may have significant implications for clinical practice. The study recommends a greater emphasis on assessing and managing perceived barriers to health promotion activities in health education and policy development and proposes a conceptual model for understanding perceived barriers to action.
Resumo:
Background: Chronic disease presents overwhelming challenges to elderly patients, their families, health care providers and the health care system. The aim of this study was to explore a theoretical model for effective management of chronic diseases, especially type 2 diabetes mellitus and/or cardiovascular disease. The assumed theoretical model considered the connections between physical function, mental health, social support and health behaviours. The study effort was to improve the quality of life for people with chronic diseases, especially type 2 diabetes and/or cardiovascular disease and to reduce health costs. Methods: A cross-sectional post questionnaire survey was conducted in early 2009 from a randomised sample of Australians aged 50 to 80 years. A total of 732 subjects were eligible for analysis. Firstly, factors influencing respondents‘ quality of life were investigated through bivariate and multivariate regression analysis. Secondly, the Theory of Planned Behaviour (TPB) model for regular physical activity, healthy eating and medication adherence behaviours was tested for all relevant respondents using regression analysis. Thirdly, TPB variable differences between respondents who have diabetes and/or cardiovascular disease and those without these diseases were compared. Finally, the TPB model for three behaviours including regular physical activity, healthy eating and medication adherence were tested in respondents with diabetes and/or cardiovascular diseases using Structure Equation Modelling (SEM). Results: This was the first study combining the three behaviours using a TPB model, while testing the influence of extra variables on the TPB model in one study. The results of this study provided evidence that the ageing process was a cumulative effect of biological change, socio-economic environment and lifelong behaviours. Health behaviours, especially physical activity and healthy eating were important modifiable factors influencing respondents‘ quality of life. Since over 80% of the respondents had at least one chronic disease, it was important to consider supporting older people‘s chronic disease self-management skills such as healthy diet, regular physical activity and medication adherence to improve their quality of life. Direct measurement of the TPB model was helpful in understanding respondents‘ intention and behaviour toward physical activity, healthy eating and medication adherence. In respondents with diabetes and/or cardiovascular disease, the TPB model predicted different proportions of intention toward three different health behaviours with 39% intending to engage in physical activity, 49% intending to engage in healthy eating and 47% intending to comply with medication adherence. Perceived behavioural control, which was proven to be the same as self-efficacy in measurement in this study, played an important role in predicting intention towards the three health behaviours. Also social norms played a slightly more important role than attitude for physical activity and medication adherence, while attitude and social norms had similar effects on healthy eating in respondents with diabetes and/or cardiovascular disease. Both perceived behavioural control and intention directly predicted recent actual behaviours. Physical activity was more a volitional control behaviour than healthy eating and medication adherence. Step by step goal setting and motivation was more important for physical activity, while accessibility, resources and other social environmental factors were necessary for improving healthy eating and medication adherence. The extra variables of age, waist circumference, health related quality of life and depression indirectly influenced intention towards the three behaviours mainly mediated through attitude and perceived behavioural control. Depression was a serious health problem that reduced the three health behaviours‘ motivation, mediated through decreased self-efficacy and negative attitude. This research provided evidence that self-efficacy is similar to perceived behavioural control in the TPB model and intention is a proximal goal toward a particular behaviour. Combining four sources of information in the self-efficacy model with the TPB model would improve chronic disease patients‘ self management behaviour and reach an improved long-term treatment outcome. Conclusion: Health intervention programs that target chronic disease management should focus on patients‘ self-efficacy. A holistic approach which is patient-centred and involves a multidisciplinary collaboration strategy would be effective. Supporting the socio-economic environment and the mental/ emotional environment for older people needs to be considered within an integrated health care system.
Resumo:
This paper reports a longitudinal analysis of 20 necessity driven micro-entrepreneurs operating in Beira, Central Mozambique, who received funding and training from the same NGO to establish or grow their business activities and reports the development of these entrepreneurs in terms of their acquired entrepreneurial potential for long-term success. The results indicate there is a process of entrepreneurial becoming that is not just about access to finance but especially learning and, when successful, this process supports the transformation of survival micro-enterprises into entrepreneurial micro-businesses. The concept of ‘becoming’ contains an implicit temporal dimension. Becoming suggests a transformation over time: a change from what one is already. In this study, we witness a significant change in understanding how a business needs to operate, in recognizing opportunities, thinking more creatively, and building self-confidence.
Resumo:
This article presents a visual servoing system to follow a 3D moving object by a Micro Unmanned Aerial Vehicle (MUAV). The presented control strategy is based only on the visual information given by an adaptive tracking method based on the colour information. A visual fuzzy system has been developed for servoing the camera situated on a rotary wing MAUV, that also considers its own dynamics. This system is focused on continuously following of an aerial moving target object, maintaining it with a fixed safe distance and centred on the image plane. The algorithm is validated on real flights on outdoors scenarios, showing the robustness of the proposed systems against winds perturbations, illumination and weather changes among others. The obtained results indicate that the proposed algorithms is suitable for complex controls task, such object following and pursuit, flying in formation, as well as their use for indoor navigation
Resumo:
Increasing global competitiveness worldwide has forced manufacturing organizations to produce high-quality products more quickly and at a competitive cost. In order to reach these goals, they need good quality components from suppliers at optimum price and lead time. This actually forced all the companies to adapt different improvement practices such as lean manufacturing, Just in Time (JIT) and effective supply chain management. Applying new improvement techniques and tools cause higher establishment costs and more Information Delay (ID). On the contrary, these new techniques may reduce the risk of stock outs and affect supply chain flexibility to give a better overall performance. But industry people are unable to measure the overall affects of those improvement techniques with a standard evaluation model .So an effective overall supply chain performance evaluation model is essential for suppliers as well as manufacturers to assess their companies under different supply chain strategies. However, literature on lean supply chain performance evaluation is comparatively limited. Moreover, most of the models assumed random values for performance variables. The purpose of this paper is to propose an effective supply chain performance evaluation model using triangular linguistic fuzzy numbers and to recommend optimum ranges for performance variables for lean implementation. The model initially considers all the supply chain performance criteria (input, output and flexibility), converts the values to triangular linguistic fuzzy numbers and evaluates overall supply chain performance under different situations. Results show that with the proposed performance measurement model, improvement area for each variable can be accurately identified.