405 resultados para national average

em Queensland University of Technology - ePrints Archive


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Objective To identify the occupational risks for Australian paramedics, by describing the rate of injuries and fatalities and comparing those rates with other reports. Design and participants Retrospective descriptive study using data provided by Safe Work Australia for the period 2000–2010. The subjects were paramedics who had been injured in the course of their duties and for whom a claim had been made for workers compensation payments. Main outcome measures Rates of injury calculated from the data provided. Results The risk of serious injury among Australian paramedics was found to be more than seven times higher than the Australian national average. The fatality rate for paramedics was about six times higher than the national average. On average, every 2 years during the study period, one paramedic died and 30 were seriously injured in vehicle crashes. Ten Australian paramedics were seriously injured each year as a result of an assault. The injury rate for paramedics was more than two times higher than the rate for police officers. Conclusions The high rate of occupational injuries and fatalities among paramedics is a serious public health issue. The risk of injury in Australia is similar to that in the United States. While it may be anticipated that injury rates would be higher as a result of the nature of the work and environment of paramedics, further research is necessary to identify and validate the strategies required to minimise the rates of occupational injury for paramedics.

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Injury is the fourth leading cause of death in Australia. Injury rates in Queensland are amongst the highest in Australia and 21.5% of people surveyed for this research reported that their lifestyle or that of an immediate family member had been permanently affected by injury. Injury results in over 40,000 hospital admissions and 200,000 attendances at hospital Emergency Departments in Queensland each year. Queensland's death rate from injuries is higher than the national average, with consistently higher rates of deaths related to transport injuries. Queensland statistics also show higher than national average rates of injuries due to falls, homicide and accidental drowning. (Pike, Muller, Baade & Ward, 2000) In 2000-01 injuries represented over $4 billion (or 8%) of total health system expenditure, and 185,000 disability-adjusted life years (DALYs), or 7% of the total morbidity burden of disease and injury in Australia in 2003. (Begg, Vos, Barker, Stevenson, Stanley & Lopez, 2007). Injury is one of seven key health areas identified by the Commonwealth, state and territory governments for priority attention as National Health Priority Areas

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Cohen (1977) reviewed the then current research on occupational safety and stated that both strong company commitment to safety, and communication between all levels of a company are the most influential factors to improving safety. Other relevant factors included careful selection of staff, and early and continuous training throughout the lifetime with the company. These continue to be important factors in OHS today. There has been a continued decrease in the injury rates since Cohen’s review within the Australian construction industry, however, the construction industry has far more injuries and ill-health than the Australian average, with one fatality occurring on average per week in the Australian Construction Industry. The Fatality rate in the building and construction industry remains three times higher than the national average, and 15% of all industry fatalities are in the building and construction industry. In addition the construction industry pays one of the highest workers’ compensation premium rates – in 2001 alone approximately 0.5% ($267 million) of revenue would have to be allocated to the direct cost of 1998/99 compensations (Office of the Federal Safety Commissioner, 2006). Based on these statistics there is a need to measure and improve safety performance within the construction industry.

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Purpose Over the past decade, the Queensland wine industry has experienced a greater percentage growth than the Australian national average. The aim of the research undertaken for this article is to identify specific national and international strategies that have allowed the industry to achieve this level of growth. Design/methodology/approach The study involved a quantitative survey of all Queensland wineries at the time (n=101), using a five-point Likert-scaled questionnaire with questions developed from the literature, together with a small-scale qualitative survey involving in-depth interviews of winery managers and industry leaders. Findings The findings indicated that key strategies in the domestic sector included a focus on cellar door sales combined with establishing links with the tourism industry, together with an incremental expansion of domestic markets. For the international sector, additional strategies included targeting familiar, psychically-close and niche markets in the initial stages of exporting, as well as taking advantage of firm-specific strengths and managerial competencies. Originality/value Not previously regarded as a major wine producing region of Australia, the Queensland wine industry has received limited attention in the literature, particularly the reasons for its rapid growth in recent years. The article helps to identify the strategies used by wineries in growing the industry.

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Emergency health is a critical component of Australia’s health system and one which is increasingly congested from growing demand and blocked access to inpatient beds. The Emergency Health Services Queensland (EHSQ) study aims to identify the factors driving increased demand for emergency health and to evaluate strategies which may safely reduce the future demand growth. This monograph addresses the characteristics of users of emergency health services with an aim to identify those that appear to contribute to demand growth. This study utilises data on patients treated by Emergency Departments (ED) and Queensland Ambulance Service (QAS) across Queensland. ED data was derived from the Emergency Department Information System (EDIS) for the period 2001-02 through to 2010-11. Ambulance data was extracted from the QAS’ Ambulance Information Management System (AIMS) and electronic Ambulance Report Form (eARF) for the period 2001-02 through to 2009-10. Due to discrepancies and comparability issues for ED data, this monograph compares data from the 2003-04 time period with 2010-11 data for 21 of the reporting EDs. Also a snapshot of users for the 2010-11 financial year for 31 reporting EDs is used to describe the characteristics of users and to compare those characteristics with population demographics. For QAS data, the 2002-03 and 2009-10 time periods were selected for detailed analyses to identify trends. • Demand for emergency health care services is increasing, representing both increased population and increased relative utilisation. Per capita demand for ED attention has increased by 2% per annum over the last decade and for ambulance attention by 3.7% per annum. • The growth in ED demand is prominent in more urgent triage categories with actual decline in less urgent patients. An estimated 55% of patients attend hospital EDs outside of normal working hours. There is no evidence that patients presenting out of hours are significantly different to those presenting within working hours; they have similar triage assessments and outcomes. • Patients suffering from injuries and poisoning comprise 28% of the ED workload (an increase of 65% in the study period), whilst declines of 32% in cardiovascular and circulatory conditions, and musculoskeletal problems have been observed. • 25.6% of patients attending EDs are admitted to hospital. 19% of admitted patients and 7% of patients who die in the ED are triage category 4 or 5 on arrival. • The average age of ED patients is 35.6 years. Demand has grown in all age groups and amongst both men and women. Men have higher utilisation rates for ED in all age groups. The only group where the growth rate in women has exceeded men is in the 20-29 age group; this growth is particularly in the injury and poisoning categories. • Considerable attention has been paid publicly to ED performance criteria. It is worth noting that 50% of all patients were treated within 33 minutes of arrival. • Patients from lower socioeconomic areas appear to have higher utilisation rates and the utilisation rate for indigenous people appears to exceed those of European and other backgrounds. The utilisation rates for immigrant people is generally less than that of Australian born however it has not been possible to eliminate the confounding impact of different age and socioeconomic profiles. • Demand for ambulance service is also increasing at a rate that exceeds population growth. Utilisation rates have increased by an average of 5% per annum in Queensland compared to 3.6% nationally, and the utilisation rate in Queensland is 27% higher than the national average. • The growth in ambulance utilisation has also been amongst the more urgent categories of dispatch and utilisation rates are higher in rural and regional areas than in the metropolitan area. The demand for ambulance increases with age but the growth in demand for ambulance service has been more prominent in younger age groups. These findings contribute significantly to an understanding of the growth in demand for emergency health. It shows that the growth is amongst patients in genuine need of emergency healthcare and public rhetoric that the congestion of emergency health services is due to inappropriate attendees is unable to be substantiated. The consistency of the growth in demand over the last decade reflects not only the changing demographics of the Australian population but also the changes in health status, standards of acute health care and other social factors. The growth is also amongst patients with acute injury and poisoning which is inconsistent with rates of chronic disease as a fundamental driver. We have also interviewed patients in regard to their decision making choices for acute health care and the factors that influence these decisions and this will be the subject of a third Monograph and publications.

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Background: Understanding the spatial distribution of suicide can inform the planning, implementation and evaluation of suicide prevention activity. This study explored spatial clusters of suicide in Australia, and investigated likely socio-demographic determinants of these clusters. Methods: National suicide and population data at a statistical local area (SLA) level were obtained from the Australian Bureau of Statistics for the period of 1999 to 2003. Standardised mortality ratios (SMR) were calculated at the SLA level, and Geographic Information System (GIS) techniques were applied to investigate the geographical distribution of suicides and detect clusters of high risk in Australia. Results: Male suicide incidence was relatively high in the northeast of Australia, and parts of the east coast, central and southeast inland, compared with the national average. Among the total male population and males aged 15 to 34, Mornington Shire had the whole or a part of primary high risk cluster for suicide, followed by the Bathurst-Melville area, one of the secondary clusters in the north coastal area of the Northern Territory. Other secondary clusters changed with the selection of cluster radius and age group. For males aged 35 to 54 years, only one cluster in the east of the country was identified. There was only one significant female suicide cluster near Melbourne while other SLAs had very few female suicide cases and were not identified as clusters. Male suicide clusters had a higher proportion of Indigenous population and lower median socio-economic index for area (SEIFA) than the national average, but their shapes changed with selection of maximum cluster radii setting. Conclusion: This study found high suicide risk clusters at the SLA level in Australia, which appeared to be associated with lower median socio-economic status and higher proportion of Indigenous population. Future suicide prevention programs should focus on these high risk areas.

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In this rural population, we found birth rate was 12% with a male-female ratio of 1.08. The infant mortality was 11.5% which was much lower than the national average.

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Objective: To evaluate the burden of malignant neoplasms in Shandong Province in order to provide scientific evidence for policy-making. Methods: The main data for this study were from Shandong third cause of death sampling survey in 2006 and Shandong 2007 cancer prevalence survey. YLLs, YLDs, DALYs and disability weights of each type of cancers were calculated according to the global burdens of disease (GBD) methodology. The direct method was used to estimate YLDs. The uncertainty analysis was conducted following the methodology in GBD study. Results: The total cancers burden in Shandong population was 1 383 thousands DALYs. Lung cancer, liver cancer, stomach cancer and esophagus cancer were the top four cancers with the highest health burden. The burden of the four major cancers together accounted for 71.45% of the total burden of all cancers. 95% of the total burden of malignant tumors was caused by premature death, and only 5.26% of the total cancer burden was due to disability. The uncertainty of total burden estimate was around±11%, the uncertainty of YLDs was bigger than that of YLLs. Conclusion: The health burden due to cancers in Shandong population is heavier than that of the national average level. Liver cancer, lung cancer and stomach cancer should be the major cancers for disease control and prevention in Shandong.

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Which statistic would you use if you were writing the newspaper headline for the following media release: "Tassie’s death rate of deaths arising from transport-related injuries was 13 per 100,000 people, or 50% higher than the national average”? (Martain, 2007). The rate “13 per 100,000” sounds very small whereas “50% higher” sounds quite large. Most people are aware of the tendency to choose between reporting data as actual numbers or using percents in order to gain attention. Looking at examples like this one can help students develop a critical quantitative literacy viewpoint when dealing with “authentic contexts” (Australian Curriculum, Assessment and Reporting Authority [ACARA], 2013a, p. 37, 67). The importance of the distinction between reporting information in raw numbers or percents is not explicitly mentioned in the Australian Curriculum: Mathematics (ACARA, 2013b, p. 42). Although the document specifically mentions making “connections between equivalent fractions, decimals and percentages” [ACMNA131] in Year 6, there is no mention of the fundamental relationship between percent and the raw numbers represented in a part-whole fashion. Such understanding, however, is fundamental to the problem solving that is the focus of the curriculum in Years 6 to 9. The purpose of this article is to raise awareness of the opportunities to distinguish between the use of raw numbers and percents when comparisons are being made in contexts other than the media. It begins with the authors’ experiences in the classroom, which motivated a search in the literature, followed by a suggestion for a follow-up activity.

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Reforms to the national research and research training system by the Commonwealth Government of Australia sought to effectively connect research conducted in universities to Australia's national innovation system. Research training has a key role in ensuring an adequate supply of highly skilled people for the national innovation system. During their studies, research students produce and disseminate a massive amount of new knowledge. Prior to this study, there was no research that examined the contribution of research training to Australia's national innovation system despite the existence of policy initiatives aiming to enhance this contribution. Given Australia's below average (but improving) innovation performance compared to other OECD countries, the inclusion of Finland and the United States provided further insights into the key research question. This study examined three obvious ways that research training contributes to the national innovation systems in the three countries: the international mobility and migration of research students and graduates, knowledge production and distribution by research students, and the impact of research training as advanced human capital formation on economic growth. Findings have informed the concept of a research training culture of innovation that aims to enhance the contribution of research training to Australia's national innovation system. Key features include internationally competitive research and research training environments; research training programs that equip students with economically-relevant knowledge and the capabilities required by employers operating in knowledge-based economies; attractive research careers in different sectors; a national commitment to R&D as indicated by high levels of gross and business R&D expenditure; high private and social rates of return from research training; and the horizontal coordination of key organisations that create policy for, and/or invest in research training.

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This report maps the current state of entrepreneurship in Australia using data from the Global Entrepreneurship Monitor (GEM) for the year 2011. Entrepreneurship is regarded as a crucial driver for economic well-being. Entrepreneurial activity in new and established firms drives innovation and creates jobs. Entrepreneurs also fuel competition thereby contributing indirectly to market and productivity growth along with improving competitiveness of the national economy. Given the economic landscape that exists as a result of the global financial crisis (GFC), it is probably more important than ever for us to understand the effects and drivers of entrepreneurial activity and attitudes in Australia. The central finding of this report is that entrepreneurship is certainly alive and well in Australia. With 10.5 per cent of the adult population involved in setting up a new business or owning a newly founded business as measured by the total entrepreneurial activity rate (TEA) in 2011, Australia ranks second only to the United States among the innovation-driven (developed) economies. Compared with 2010 the TEA rate has increased by 2.7 percentage points. Furthermore, in regard to employee entrepreneurial activity (EEA) rate in established firms, Australia ranks above average. According to GEM data, 5 per cent of the adult population is engaged in developing or launching new products, a new business unit or subsidiary for their employer. Further analysis of the GEM data also clearly shows that Australia compares well with other major economies in terms of the ‘quality’ of entrepreneurial activities being pursued. Indeed, it is not only the quantity of entrepreneurs but also the level of their aspirations and business goals that are important drivers for economic growth. On average, for each business started in Australia driven by the lack of alternatives for the founder to generate income from any other source, there are five other businesses started where the founders specifically want to take advantage of a business opportunity that they believe will increase their personal income or independence. With respect to innovativeness, 31 per cent of Australian new businesses offer products or services which they consider to be new to customers or where very few, or in some cases no, other businesses offer the same product or service. Both these indicators are higher than the average for innovation-driven economies. Somewhat below average is the international orientation of Australian entrepreneurs whereby only 12 per cent aim at having a substantial share of customers from international markets. So what drives this high quantity and quality of entrepreneurship in Australia? The analysis of the data suggests it is a combination of both business opportunities and entrepreneurial skills. It seems that around 50 per cent of the Australian population identify opportunities for a start-up venture and believe that they have the necessary skills to start a business. Furthermore, a large majority of the Australian population report that high media attention for entrepreneurship provides successful role models for prospective entrepreneurs. As a result, 12 per cent of our respondents have expressed the intention to start a business within the next three years. These numbers are all well above average when compared to the other major economies. With regard to gender, the GEM survey shows a high proportion of female entrepreneurs. Approximately 8.4 per cent of adult females are actually involved in setting up a business or have recently done so. Although this female TEA rate is slightly down from 2010, Australia ranks second among the innovation-driven economies. This paints a healthy picture of access to entrepreneurial opportunities for Australian women.

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Consensual stereotypes of some groups are relatively accurate, whereas others are not. Previous work suggesting that national character stereotypes are inaccurate has been criticized on several grounds. In this article we (a) provide arguments for the validity of assessed national mean trait levels as criteria for evaluating stereotype accuracy and (b) report new data on national character in 26 cultures from descriptions (N= 3323) of the typical male or female adolescent, adult, or old person in each. The average ratings were internally consistent and converged with independent stereotypes of the typical culture member, but were weakly related to objective assessments of personality. We argue that this conclusion is consistent with the broader literature on the inaccuracy of national character stereotypes

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Land-use regression (LUR) is a technique that can improve the accuracy of air pollution exposure assessment in epidemiological studies. Most LUR models are developed for single cities, which places limitations on their applicability to other locations. We sought to develop a model to predict nitrogen dioxide (NO2) concentrations with national coverage of Australia by using satellite observations of tropospheric NO2 columns combined with other predictor variables. We used a generalised estimating equation (GEE) model to predict annual and monthly average ambient NO2 concentrations measured by a national monitoring network from 2006 through 2011. The best annual model explained 81% of spatial variation in NO2 (absolute RMS error=1.4 ppb), while the best monthly model explained 76% (absolute RMS error=1.9 ppb). We applied our models to predict NO2 concentrations at the ~350,000 census mesh blocks across the country (a mesh block is the smallest spatial unit in the Australian census). National population-weighted average concentrations ranged from 7.3 ppb (2006) to 6.3 ppb (2011). We found that a simple approach using tropospheric NO2 column data yielded models with slightly better predictive ability than those produced using a more involved approach that required simulation of surface-to-column ratios. The models were capable of capturing within-urban variability in NO2, and offer the ability to estimate ambient NO2 concentrations at monthly and annual time scales across Australia from 2006–2011. We are making our model predictions freely available for research.

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This paper investigates quality of service (QoS) and resource productivity implications of transit route passenger loading and travel time. It highlights the value of occupancy load factor as a direct passenger comfort QoS measure. Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia, is used to investigate time series correlation between occupancy load factor and passenger average travel time. Correlation is strong across the entire span of service in both directions. Passengers tend to be making longer, peak direction commuter trips under significantly less comfortable conditions than off-peak. The Transit Capacity and Quality of Service Manual uses segment based load factor as a measure of onboard loading comfort QoS. This paper provides additional insight into QoS by relating the two route based dimensions of occupancy load factor and passenger average travel time together in a two dimensional format, both from the passenger’s and operator’s perspectives. Future research will apply Value of Time to QoS measurement, reflecting perceived passenger comfort through crowding and average time spent onboard. This would also assist in transit service quality econometric modeling. The methodology can be readily applied in a practical setting where AFC data for fixed scheduled routes is available. The study outcomes also provide valuable research and development directions.

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This presentation investigates quality of service (QoS) and resource productivity implications of transit route passenger loading and travel time. It highlights the value of occupancy load factor as a direct passenger comfort QoS measure. Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia, is used to investigate time series correlation between occupancy load factor and passenger average travel time. Correlation is strong across the entire span of service in both directions. Passengers tend to be making longer, peak direction commuter trips under significantly less comfortable conditions than off-peak. The Transit Capacity and Quality of Service Manual uses segment based load factor as a measure of onboard loading comfort QoS. This paper provides additional insight into QoS by relating the two route based dimensions of occupancy load factor and passenger average travel time together in a two dimensional format, both from the passenger’s and operator’s perspectives. Future research will apply Value of Time to QoS measurement, reflecting perceived passenger comfort through crowding and average time spent onboard. This would also assist in transit service quality econometric modeling. The methodology can be readily applied in a practical setting where AFC data for fixed scheduled routes is available. The study outcomes also provide valuable research and development directions.