331 resultados para Health Design


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Harmful Algal Blooms (HABs) have become an important environmental concern along the western coast of the United States. Toxic and noxious blooms adversely impact the economies of coastal communities in the region, pose risks to human health, and cause mortality events that have resulted in the deaths of thousands of fish, marine mammals and seabirds. One goal of field-based research efforts on this topic is the development of predictive models of HABs that would enable rapid response, mitigation and ultimately prevention of these events. In turn, these objectives are predicated on understanding the environmental conditions that stimulate these transient phenomena. An embedded sensor network (Fig. 1), under development in the San Pedro Shelf region off the Southern California coast, is providing tools for acquiring chemical, physical and biological data at high temporal and spatial resolution to help document the emergence and persistence of HAB events, supporting the design and testing of predictive models, and providing contextual information for experimental studies designed to reveal the environmental conditions promoting HABs. The sensor platforms contained within this network include pier-based sensor arrays, ocean moorings, HF radar stations, along with mobile sensor nodes in the form of surface and subsurface autonomous vehicles. FreewaveTM radio modems facilitate network communication and form a minimally-intrusive, wireless communication infrastructure throughout the Southern California coastal region, allowing rapid and cost-effective data transfer. An emerging focus of this project is the incorporation of a predictive ocean model that assimilates near-real time, in situ data from deployed Autonomous Underwater Vehicles (AUVs). The model then assimilates the data to increase the skill of both nowcasts and forecasts, thus providing insight into bloom initiation as well as the movement of blooms or other oceanic features of interest (e.g., thermoclines, fronts, river discharge, etc.). From these predictions, deployed mobile sensors can be tasked to track a designated feature. This focus has led to the creation of a technology chain in which algorithms are being implemented for the innovative trajectory design for AUVs. Such intelligent mission planning is required to maneuver a vehicle to precise depths and locations that are the sites of active blooms, or physical/chemical features that might be sources of bloom initiation or persistence. The embedded network yields high-resolution, temporal and spatial measurements of pertinent environmental parameters and resulting biology (see Fig. 1). Supplementing this with ocean current information and remotely sensed imagery and meteorological data, we obtain a comprehensive foundation for developing a fundamental understanding of HAB events. This then directs labor- intensive and costly sampling efforts and analyses. Additionally, we provide coastal municipalities, managers and state agencies with detailed information to aid their efforts in providing responsible environmental stewardship of their coastal waters.

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A key concern in the field of contemporary fashion/textiles design is the emergence of ‘fast fashion’: best explained as "buy it Friday, wear it Saturday and throw it away on Sunday" (O'Loughlin, 2007). In this contemporary retail atmosphere of “pile it high: sell it cheap” and “quick to market”, even designer goods have achieved a throwaway status. This modern culture of consumerism is the antithesis of sustainability and is proving a dilemma surrounding sustainable practice for designers and producers in the disciplines (de Blas, 2010). Design researchers including those in textiles/fashion have begun to explore what is a key question in the 21st century in order to create a vision and reason for their disciplines: Can products be designed to have added value to the consumer and hence contribute to a more sustainable industry? Fashion Textiles Design has much to answer for in contributing to the problems of unsustainable practices on a global scale in design, production and waste. However, designers within this field also have great potential to contribute to practical ‘real world’ solutions. ----- ----- This paper provides an overview of some of the design and technological developments from the fashion/textiles industry, endorsing a model where designers and technicians use their transferrable skills for wellbeing rather than desire. Smart materials in the form of responsive and adaptive fibres and fabrics combined with electro active devices, and ICT are increasingly shaping many aspects of society particularly in the leisure industry and interactive consumer products are ever more visible in healthcare. Combinations of biocompatible delivery devices with bio sensing elements can create analyse, sense and actuate early warning and monitoring systems which can be linked to data logging and patient records via intelligent networks. Patient sympathetic, ‘smart’ fashion/textiles applications based on interdisciplinary expertise utilising textiles design and technology is emerging. An analysis of a series of case studies demonstrates the potential of fashion textiles design practitioners to exploit the concept of value adding through technological garment and textiles applications and enhancement for health and wellbeing and in doing so contribute to a more sustainable future fashion/textiles design industry.

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The perceived benefits of Wellness Education in University environments are substantiated by a number of studies in relation to the place, impact and purpose of Wellness curricula. Many authors recommend that Wellness curriculum design must include personal experiences, reflective practice and active self-managed learning approaches in order to legitimise the adoption of Wellness as a personal lifestyle approach. Wellness Education provides opportunities to engage in learning self-regulation skills both within and beyond the context of the Wellness construct. Learner success is optimised by creating authentic opportunities to develop and practice self regulation strategies that facilitate making meaning of life's experiences. Such opportunities include provision of options for self determined outcomes and are scaffolded according to learner needs; thus, configuring a learner-centred curriculum in Wellness Education would potentially benefit by overlaying principles from the domains of Self Determination Theory, Self Regulated Learning and Transformative Education Theory to highlight authentic, transformative learning as a lifelong approach to Wellness.

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In 2008, a three-year pilot ‘pay for performance’ (P4P) program, known as ‘Clinical Practice Improvement Payment’ (CPIP) was introduced into Queensland Health (QHealth). QHealth is a large public health sector provider of acute, community, and public health services in Queensland, Australia. The organisation has recently embarked on a significant reform agenda including a review of existing funding arrangements (Duckett et al., 2008). Partly in response to this reform agenda, a casemix funding model has been implemented to reconnect health care funding with outcomes. CPIP was conceptualised as a performance-based scheme that rewarded quality with financial incentives. This is the first time such a scheme has been implemented into the public health sector in Australia with a focus on rewarding quality, and it is unique in that it has a large state-wide focus and includes 15 Districts. CPIP initially targeted five acute and community clinical areas including Mental Health, Discharge Medication, Emergency Department, Chronic Obstructive Pulmonary Disease, and Stroke. The CPIP scheme was designed around key concepts including the identification of clinical indicators that met the set criteria of: high disease burden, a well defined single diagnostic group or intervention, significant variations in clinical outcomes and/or practices, a good evidence, and clinician control and support (Ward, Daniels, Walker & Duckett, 2007). This evaluative research targeted Phase One of implementation of the CPIP scheme from January 2008 to March 2009. A formative evaluation utilising a mixed methodology and complementarity analysis was undertaken. The research involved three research questions and aimed to determine the knowledge, understanding, and attitudes of clinicians; identify improvements to the design, administration, and monitoring of CPIP; and determine the financial and economic costs of the scheme. Three key studies were undertaken to ascertain responses to the key research questions. Firstly, a survey of clinicians was undertaken to examine levels of knowledge and understanding and their attitudes to the scheme. Secondly, the study sought to apply Statistical Process Control (SPC) to the process indicators to assess if this enhanced the scheme and a third study examined a simple economic cost analysis. The CPIP Survey of clinicians elicited 192 clinician respondents. Over 70% of these respondents were supportive of the continuation of the CPIP scheme. This finding was also supported by the results of a quantitative altitude survey that identified positive attitudes in 6 of the 7 domains-including impact, awareness and understanding and clinical relevance, all being scored positive across the combined respondent group. SPC as a trending tool may play an important role in the early identification of indicator weakness for the CPIP scheme. This evaluative research study supports a previously identified need in the literature for a phased introduction of Pay for Performance (P4P) type programs. It further highlights the value of undertaking a formal risk assessment of clinician, management, and systemic levels of literacy and competency with measurement and monitoring of quality prior to a phased implementation. This phasing can then be guided by a P4P Design Variable Matrix which provides a selection of program design options such as indicator target and payment mechanisms. It became evident that a clear process is required to standardise how clinical indicators evolve over time and direct movement towards more rigorous ‘pay for performance’ targets and the development of an optimal funding model. Use of this matrix will enable the scheme to mature and build the literacy and competency of clinicians and the organisation as implementation progresses. Furthermore, the research identified that CPIP created a spotlight on clinical indicators and incentive payments of over five million from a potential ten million was secured across the five clinical areas in the first 15 months of the scheme. This indicates that quality was rewarded in the new QHealth funding model, and despite issues being identified with the payment mechanism, funding was distributed. The economic model used identified a relative low cost of reporting (under $8,000) as opposed to funds secured of over $300,000 for mental health as an example. Movement to a full cost effectiveness study of CPIP is supported. Overall the introduction of the CPIP scheme into QHealth has been a positive and effective strategy for engaging clinicians in quality and has been the catalyst for the identification and monitoring of valuable clinical process indicators. This research has highlighted that clinicians are supportive of the scheme in general; however, there are some significant risks that include the functioning of the CPIP payment mechanism. Given clinician support for the use of a pay–for-performance methodology in QHealth, the CPIP scheme has the potential to be a powerful addition to a multi-faceted suite of quality improvement initiatives within QHealth.

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Increasingly, national and international governments have a strong mandate to develop national e-health systems to enable delivery of much-needed healthcare services. Research is, therefore, needed into appropriate security and reliance structures for the development of health information systems which must be compliant with governmental and alike obligations. The protection of e-health information security is critical to the successful implementation of any e-health initiative. To address this, this paper proposes a security architecture for index-based e-health environments, according to the broad outline of Australia’s National E-health Strategy and National E-health Transition Authority (NEHTA)’s Connectivity Architecture. This proposal, however, could be equally applied to any distributed, index-based health information system involving referencing to disparate health information systems. The practicality of the proposed security architecture is supported through an experimental demonstration. This successful prototype completion demonstrates the comprehensibility of the proposed architecture, and the clarity and feasibility of system specifications, in enabling ready development of such a system. This test vehicle has also indicated a number of parameters that need to be considered in any national indexed-based e-health system design with reasonable levels of system security. This paper has identified the need for evaluation of the levels of education, training, and expertise required to create such a system.

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The number of children with special health care needs surviving infancy and attending school has been increasing. Due to their health status, these children may be at risk of low social-emotional and learning competencies (e.g., Lightfoot, Mukherjee, & Sloper, 2000; Zehnder, Landolt, Prchal, & Vollrath, 2006). Early social problems have been linked to low levels of academic achievement (Ladd, 2005), inappropriate behaviours at school (Shiu, 2001) and strained teacher-child relationships (Blumberg, Carle, O‘Connor, Moore, & Lippmann, 2008). Early learning difficulties have been associated with mental health problems (Maughan, Rowe, Loeber, & Stouthamer-Loeber, 2003), increased behaviour issues (Arnold, 1997), delinquency (Loeber & Dishion, 1983) and later academic failure (Epstein, 2008). Considering the importance of these areas, the limited research on special health care needs in social-emotional and learning domains is a factor driving this research. The purpose of the current research is to investigate social-emotional and learning competence in the early years for Australian children who have special health care needs. The data which informed this thesis was from Growing up in Australia: The Longitudinal Study of Australian Children. This is a national, longitudinal study being conducted by the Commonwealth Department of Families, Housing, Community Services and Indigenous Affairs. The study has a national representative sample, with data collection occurring biennially, in 2004 (Wave 1), 2006 (Wave 2) and 2008 (Wave 3). Growing up in Australia uses a cross-sequential research design involving two cohorts, an Infant Cohort (0-1 at recruitment) and a Kindergarten Cohort (4-5 at recruitment). This study uses the Kindergarten Cohort, for which there were 4,983 children at recruitment. Three studies were conducted to address the objectives of this thesis. Study 1 used Wave 1 data to identify and describe Australian children with special health care needs. Children who identified as having special health care needs through the special health care needs screener were selected. From this, descriptive analyses were run. The results indicate that boys, children with low birth weight and children from families with low levels of maternal education are likely to be in the population of children with special health care needs. Further, these children are likely to be using prescription medications, have poor general health and are likely to have specific condition diagnoses. Study 2 used Wave 1 data to examine differences between children with special health care needs and their peers in social-emotional competence and learning competence prior to school. Children identified by the special health care needs screener were chosen for the case group (n = 650). A matched case control group of peers (n = 650), matched on sex, cultural and linguistic diversity, family socioeconomic position and age, were the comparison group. Social-emotional competence was measured through Social/Emotional Domain scores taken from the Growing up in Australia Outcome Index, with learning competence measured through Learning Domain scores. Results suggest statistically significant differences in scores between the two groups. Children with special health care needs have lower levels of social-emotional and learning competence prior to school compared to their peers. Study 3 used Wave 1 and Wave 2 data to examine the relationship between special health care needs at Wave 1 and social-emotional competence and learning competence at Wave 2, as children started school. The sample for this study consisted of children in the Kindergarten Cohort who had teacher data at Wave 2. Results from multiple regression models indicate that special health care needs prior to school (Wave 1) significantly predicts social-emotional competence and learning competence in the early years of school (Wave 2). These results indicate that having special health care needs prior to school is a risk factor for the social-emotional and learning domains in the early years of school. The results from these studies give valuable insight into Australian children with special health care needs and their social-emotional and learning competence in the early years. The Australia population of children with special health care needs were primarily male children, from families with low maternal education, were likely to be of poor health and taking prescription medications. It was found that children with special health care needs were likely to have lower social-emotional competence and learning competence prior to school compared to their peers. Results indicate that special health care needs prior to school were predictive of lower social-emotional and learning competencies in the early years of school. More research is required into this unique population and their competencies over time. However, the current research provides valuable insight into an under researched 'at risk' population.

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The expanding interest in electrospinning fibers for bioengineering includes a significant use of polyesters, including poly(3-caprolactone) (PCL). This review summarizes literature on PCL and selected blends, and provides extensive descriptions of the broad range of parameters used in manufacturing such electrospun fibers. Furthermore the chemical, physical and biological approaches for characterizing the electrospun material are described and opinions offered on important information to include in future publications with this electrospun material.

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Background It is well known that lifestyle factors including overweight/obesity, physical inactivity, smoking and alcohol use are largely related with morbidity and mortality of chronic diseases including diabetes and cardiovascular diseases. The effect of lifestyle factors on people’s mental health who have a chronic disease is less defined in the research. The World Health Organisation has defined health as “a state of complete physical, mental and social well-being”. It is important, therefore to develop an understanding of the relationships between lifestyle and mental health as this may have implications for maximising the efficacy of health promotion in people with chronic diseases. Objectives The overall aim of the research was to examine the relationships between lifestyle factors and mental health among Australian midlife and older women. Methodology The current research measured four lifestyle factors including weight status, physical activity, smoking and alcohol use. Three interconnecting studies were undertaken to develop a comprehensive understanding of the relationships between lifestyle factors and mental health. Study 1 investigated the longitudinal effect of lifestyle factors on mental health by using midlife and older women randomly selected from the community. Study 2 adopted a cross-sectional design, and compared the effect of lifestyle factors on mental health between midlife and older women with and without diabetes. Study 3 examined the mediating effect of self-efficacy in the relationships between lifestyle factors and mental health among midlife and older women with diabetes. A questionnaire survey was chosen as the means to gather information, and multiple linear regression analysis was conducted as the primary statistical approach. Results The research showed that the four lifestyle factors including weight status, physical activity, smoking and alcohol use did impact on mental health among Australian midlife and older women. First, women with a higher BMI had lower levels of mental health than women with normal weight, but as women age, the mental health of women who were overweight and obese becomes better than that of women with normal weight. Second, women who were physically active had higher levels of mental health than those who were not. Third, smoking adversely impacted on women’s mental health. Finally, those who were past-drinkers had less anxiety symptoms than women who were non-drinkers as they age. Women with diabetes appeared to have lower levels of mental health compared to women without. However, the disparities of mental health between two groups were confounded by low levels of physical activity and co-morbidities. This finding underlines the effect of physical activity on women’s mental health, and highlights the potential of reducing the gap of mental health by promoting physical activity. In addition, self-efficacy was shown to be the mediator of the relationships between BMI, physical activity and depression, suggesting that enhancing people’s self-efficacy may be useful for mental health improvement. Conclusions In conclusion, Australian midlife and older women who live with a healthier lifestyle have higher levels of mental health. It is suggested that strategies aiming to improve people’s mental health may be more effective if they focus on enhancing people’s self-efficacy levels. This study has implications to both health education and policy development. It indicates that health professionals may need to consider clients’ mental health as an integrated part of lifestyle changing process. Furthermore, given that lifestyle factors impact on both physical and mental health, lifestyle modification should continue to be the focus of policy development.

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The role of the occupational health nurse is broad and includes health care provider, manager/coordinator, educator/advisor, and case manager and consultant, depending on the type of industry and the country in which the nurse practices. Regardless of the type of role, the occupational health nurse must participate in continuing nursing education (CNE) activities. This study describes the roles, credentials, and number of CNE activities undertaken by occupational health nurses working in Ontario, Canada. Using a non-experimental descriptive design, a questionnaire was mailed to all practicing occupational health nurses who are members (n = 900) of a local nursing association. Three hundred fifty-four questionnaires were returned. Nurses reported a variety of roles in the following categories: case management, health promotion, policy development, infection control/travel health, ergonomics, education, research, health and safety, direct care, consultation, disaster preparedness, and industrial hygiene. Sixty-five percent of nurses held an occupational health nurse credential, and 19% of nurses attended more than 100 hours of CNE annually. Occupational health nurses have multiple workplace roles. Many attend CNE activities and they often prepare for credentialing.

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Background There has been increasing interest in assessing the impacts of temperature on mortality. However, few studies have used a case–crossover design to examine non-linear and distributed lag effects of temperature on mortality. Additionally, little evidence is available on the temperature-mortality relationship in China, or what temperature measure is the best predictor of mortality. Objectives To use a distributed lag non-linear model (DLNM) as a part of case–crossover design. To examine the non-linear and distributed lag effects of temperature on mortality in Tianjin, China. To explore which temperature measure is the best predictor of mortality; Methods: The DLNM was applied to a case¬−crossover design to assess the non-linear and delayed effects of temperatures (maximum, mean and minimum) on deaths (non-accidental, cardiopulmonary, cardiovascular and respiratory). Results A U-shaped relationship was consistently found between temperature and mortality. Cold effects (significantly increased mortality associated with low temperatures) were delayed by 3 days, and persisted for 10 days. Hot effects (significantly increased mortality associated with high temperatures) were acute and lasted for three days, and were followed by mortality displacement for non-accidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. Conclusions In Tianjin, extreme cold and hot temperatures increased the risk of mortality. Results suggest that the effects of cold last longer than the effects of heat. It is possible to combine the case−crossover design with DLNMs. This allows the case−crossover design to flexibly estimate the non-linear and delayed effects of temperature (or air pollution) whilst controlling for season.

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Background Providing ongoing family centred support is an integral part of childhood cancer care. For families living in regional and remote areas, opportunities to receive specialist support are limited by the availability of health care professionals and accessibility, which is often reduced due to distance, time, cost and transport. The primary aim of this work is to investigate the cost-effectiveness of videotelephony to support regional and remote families returning home for the first time with a child newly diagnosed with cancer Methods/design We will recruit 162 paediatric oncology patients and their families to a single centre randomised controlled trial. Patients from regional and remote areas, classified by Accessibility/Remoteness Index of Australia (ARIA+) greater than 0.2, will be randomised to a videotelephone support intervention or a usual support control group. Metropolitan families (ARIA+ ≤ 0.2) will be recruited as an additional usual support control group. Families allocated to the videotelephone support intervention will have access to usual support plus education, communication, counselling and monitoring with specialist multidisciplinary team members via a videotelephone service for a 12-week period following first discharge home. Families in the usual support control group will receive standard care i.e., specialist multidisciplinary team members provide support either face-to-face during inpatient stays, outpatient clinic visits or home visits, or via telephone for families who live far away from the hospital. The primary outcome measure is parental health related quality of life as measured using the Medical Outcome Survey (MOS) Short Form SF-12 measured at baseline, 4 weeks, 8 weeks and 12 weeks. The secondary outcome measures are: parental informational and emotional support; parental perceived stress, parent reported patient quality of life and parent reported sibling quality of life, parental satisfaction with care, cost of providing improved support, health care utilisation and financial burden for families. Discussion This investigation will establish the feasibility, acceptability and cost-effectiveness of using videotelephony to improve the clinical and psychosocial support provided to regional and remote paediatric oncology patients and their families.