605 resultados para Contextual factors
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Process modeling grammars are used by analysts to describe information systems domains in terms of the business operations an organization is conducting. While prior research has examined the factors that lead to continued usage behavior, little knowledge has been established as to what extent characteristics of the users of process modeling grammars inform usage behavior. In this study, a theoretical model is advanced that incorporates determinants of continued usage behavior as well as key antecedent individual difference factors of the grammar users, such as modeling experience, modeling background and perceived grammar familiarity. Findings from a global survey of 529 grammar users support the hypothesized relationships of the model. The study offers three central contributions. First, it provides a validated theoretical model of post-adoptive modeling grammar usage intentions. Second, it discusses the effects of individual difference factors of grammar users in the context of modeling grammar usage. Third, it provides implications for research and practice.
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Purpose: Worldwide, the incidence of thick melanoma has not declined, and the nodular melanoma (NM) subtype accounts for nearly 40% of newly-diagnosed thick melanoma. To assess differences between patients with thin (≤2.00 mm) and thick (≥2.01 mm) nodular melanoma, we evaluated factors such as demographics, melanoma detection patterns, tumor visibility, and physician screening for NM alone and compared clinical presentation and anatomic location of NM with superficial spreading melanoma (SSM). Methods We utilized data from a large population-based study of Queensland (Australia) residents diagnosed with melanoma. Queensland residents aged 20 to 75 years with histologically confirmed first primary invasive cutaneous melanoma were eligible for the study, and all questionnaires were conducted by telephone (response rate 77.9%). Results During this four-year period, 369 patients with nodular melanoma were interviewed, of whom 56.7% were diagnosed with tumors ≤ 2.00 mm. Men, older individuals, and those who had not been screened by a physician in the past three years were more likely to have nodular tumors of greater thickness. Thickest nodular melanoma (4 mm+) was also most common in persons who had not been screened by a doctor within the past three years (OR 3.75; 95% CI 1.47-9.59). Forty-six percent of patients with thin nodular melanoma (≤ 2.00 mm) reported a change in color, compared with 64% of patients with thin SSM and 26% of patients with thick nodular melanoma (>2.00 mm). Conclusion Awareness of factors related to earlier detection of potentially fatal nodular melanomas, including the benefits of a physician examination, should be useful in enhancing public and professional education strategies. Particular awareness of clinical warning signs associated with thin nodular melanoma should allow for more prompt diagnosis and treatment of this subtype.
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Background: The seasonality of suicide has long been recognised. However, little is known about the relative importance of socio-environmental factors in the occurrence of suicide in different geographical areas. This study examined the association of climate, socioeconomic and demographic factors with suicide in Queensland, Australia, using a spatiotemporal approach. Methods: Seasonal data on suicide, demographic variables and socioeconomic indexes for areas in each Local Government Area (LGA) between 1999 and 2003 were acquired from the Australian Bureau of Statistics. Climate data were supplied by the Australian Bureau of Meteorology. A multivariable generalized estimating equation model was used to examine the impact of socio-environmental factors on suicide. Results: The preliminary data analyses show that far north Queensland had the highest suicide incidence (e.g., Cook and Mornington Shires), while the south-western areas had the lowest incidence (e.g., Barcoo and Bauhinia Shires) in all the seasons. Maximum temperature, unemployment rate, the proportion of Indigenous population and the proportion of population with low individual income were statistically significantly and positively associated with suicide. There were weaker but not significant associations for other variables. Conclusions: Maximum temperature, the proportion of Indigenous population and unemployment rate appeared to be major determinants of suicide at a LGA level in Queensland.
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Background: Relatively little research attention has been given to the development of standardised and psychometrically sound scales for measuring influences relevant to the utilisation of health services. This study aims to describe the development, validation and internal reliability of some existing and new scales to measure factors that are likely to influence utilisation of preventive care services provided by general practitioners in Australia.----- Methods: Relevant domains of influence were first identified from a literature review and formative research. Items were then generated by using and adapting previously developed scales and published findings from these. The new items and scales were pre-tested and qualitative feedback was obtained from a convenience sample of citizens from the community and a panel of experts. Principal Components Analyses (PCA) and internal reliability testing (Cronbach's alpha) were then conducted for all of the newly adapted or developed scales utilising data collected from a self-administered mailed survey sent to a randomly selected population-based sample of 381 individuals (response rate 65.6 per cent).----- Results: The PCA identified five scales with acceptable levels of internal consistency were: (1) social support (ten items), alpha 0.86; (2) perceived interpersonal care (five items), alpha 0.87, (3) concerns about availability of health care and accessibility to health care (eight items), alpha 0.80, (4) value of good health (five items), alpha 0.79, and (5) attitudes towards health care (three items), alpha 0.75.----- Conclusion The five scales are suitable for further development and more widespread use in research aimed at understanding the determinants of preventive health services utilisation among adults in the general population.
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In response to a range of contextual drivers, the worldwide adoption of ERP Systems in Higher Education Institutions (HEIs) has increased substantially over the past decade. Though this demand continues to grow, with HEIs now a main target market for ERP vendors, little has been published on the topic. This paper reports a sub-study of a larger research effort that aims to contribute to understanding the phenomenon of ERP adoption and evaluation in HEIs in the Australasian region. It presents a descriptive case study conducted at Queensland University of Technology (QUT) in Australia, with emphasis on challenges with ERP adoption. The case study provides rich contextual details about ERP system selection, customisation, integration and evaluation, and insights into the role of consultants in the HE sector. Through this analysis, the paper (a) provides evidence of the dearth of ERP literature pertaining to the HE sector; (b) yields insights into differentiating factors in the HE sector that warrants specific research attention, and (c) offers evidence of how key ERP decisions such as systems selection, customisation, integration, evaluation, and consultant engagement are influenced by the specificities of the HE sector.
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Overweight and obesity are two of the most important emerging public health issues in our time and regarded by the World Health Organisation [WHO] (1998) as a worldwide epidemic. The prevalence of obesity in the USA is the highest in the world, and Australian obesity rates fall into second place. Currently, about 60% of Australian adults are overweight (BMI „d 25kg/m2). The socio-demographic factors associated with overweight and/or obesity have been well demonstrated, but many of the existing studies only examined these relationships at one point of time, and did not examine whether significant relationships changed over time. Furthermore, only limited previous research has examined the issue of the relationship between perception of weight status and actual weight status, as well as factors that may impact on people¡¦s perception of their body weight status. Aims: The aims of the proposed research are to analyse the discrepancy between perceptions of weight status and actual weight status in Australian adults; to examine if there are trends in perceptions of weight status in adults between 1995 to 2004/5; and to propose a range of health promotion strategies and furth er research that may be useful in managing physical activity, healthy diet, and weight reduction. Hypotheses: Four alternate hypotheses are examined by the research: (1) there are associations between independent variables (e.g. socio -demographic factors, physical activity and dietary habits) and overweight and/or obesity; (2) there are associations between the same independent variables and the perception of overweight; (3) there are associations between the same independent variables and the discrepancy between weight status and perception of weight status; and (4) there are trends in overweight and/or obesity, perception of overweight, and the discrepancy in Australian adults from 1995 to 2004/5. Conceptual Framework and Methods: A conceptual framework is developed that shows the associations identified among socio -demographic factors, physical activity and dietary habits with actual weight status, as well as examining perception of weight status. The three latest National Health Survey data bases (1995 , 2001 and 2004/5) were used as the primary data sources. A total of 74,114 Australian adults aged 20 years and over were recruited from these databases. Descriptive statistics, bivariate analyses (One -Way ANOVA tests, unpaired t-tests and Pearson chi-square tests), and multinomial logistic regression modelling were used to analyse the data. Findings: This research reveals that gender, main language spoken at home, occupation status, household structure, private health insurance status, and exercise are related to the discrepancy between actual weight status and perception of weight status, but only gender and exercise are related to the discrepancy across the three time point s. The current research provides more knowledge about perception of weight status independently. Factors which affect perception of overweight are gender, age, language spoken at home, private health insurance status, and diet ary habits. The study also finds that many factors that impact overweight and/or obesity also have an effect on perception of overweight, such as age, language spoken at home, household structure, and exercise. However, some factors (i.e. private health insurance status and milk consumption) only impact on perception of overweight. Furthermore, factors that are rel ated to people’s overweight are not totally related to people’s underestimation of their body weight status in the study results. Thus, there are unknown factors which can affect people’s underestimation of their body weight status. Conclusions: Health promotion and education activities should provide education about population health education and promotion and education for particular at risk sub -groups. Further research should take the form of a longitudinal study design ed to examine the causal relationship between overweight and/or obesity and underestimation of body weight status, it should also place more attention on the relationships between overweight and/or obesity and dietary habits, with a more comprehensive representation of SES. Moreover, further research that deals with identification of characteristics about perception of weight status, in particular the underestimation of body weight status should be undertaken.
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The growth of the Penaeus monodon prawn aquaculture industry in Australia is hampered by a reliance on wild-caught broodstock. This species has proven difficult to breed from if broodstock are reared in captivity. Studies were therefore carried out to investigate factors controlling reproduction and influencing egg quality. Results of the studies revealed that patterns of nutrient accumulation during early ovary development are altered by captive conditions, possibly contributing to reduce larval quality. The sinus gland hormones were shown, together with the environment, to regulate two stages of ovary development. In a separate study it was further revealed that the hormone methyl farnesoate (MF) could negatively regulate the final stages of ovary development. Lastly it was shown that broodstock reared in captivity are less likely to mate and that this is due to inherent problems in both the male and the female prawns.
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Business Process Management (BPM) in recent years has become a highest priority area for most organizations. Since this concept is multidisciplinary, success in this endeavour requires considering different factors. A number of studies have been conducted to identify these factors; however, most are limited to the introduction of high-level factors or to the identification of the means of success within only a specific context. This paper presents a holistic framework of success factors as well as the associated means for achieving success. This framework introduces nine factors, namely culture, leadership, communication, Information Technology, strategic alignment, people, project management, performance measurement and methodology. Each of these factors are characterized further by defining some sub-constructs and under each sub construct the means for achieving success are also introduced. This framework including means for achieving success can be useful for BPM project stakeholders in adequately planning the initiative and checking the progress during the implementation.
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Traffic safety is a major concern world-wide. It is in both the sociological and economic interests of society that attempts should be made to identify the major and multiple contributory factors to those road crashes. This paper presents a text mining based method to better understand the contextual relationships inherent in road crashes. By examining and analyzing the crash report data in Queensland from year 2004 and year 2005, this paper identifies and reports the major and multiple contributory factors to those crashes. The outcome of this study will support road asset management in reducing road crashes.
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Background: While the relationship between socioeconomic disadvantage and cardiovascular disease (CVD) is well established, the role that traditional cardiovascular risk factors play in this association remains unclear. We examined the association between education attainment and CVD mortality and the extent to which behavioural, social and physiological factors explained this relationship. Methods: Adults (n=38 355) aged 40-69 years living in Melbourne, Australia were recruited in 1990-1994. Subjects with baseline CVD risk factor data ascertained through questionnaire and physical measurement were followed for an average of 9.4 years with CVD deaths verified by review of medical records and autopsy reports. Results: CVD mortality was higher for those with primary education only compared to those who had completed tertiary education, with a hazard ratio (HR) of 1.66 (95% confidence interval [CI] 1.11-2.49) after adjustment for age, country of birth and gender. Those from the lowest educated group had a more adverse cardiovascular risk factor profile compared to the highest educated group, and adjustment for these risk factors reduced the HR to 1.18 (95% CI 0.78-1.77). In analysis of individual risk factors, smoking and waist circumference explained most of the difference in CVD mortality between the highest and lowest education groups. Conclusions: Most of the excess CVD mortality in lower socioeconomic groups can be explained by known risk factors, particularly smoking and overweight. While targeting cardiovascular risk factors should not divert efforts from addressing the underlying determinants of health inequalities, it is essential that known risk factors are addressed effectively among lower socioeconomic groups.
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Background: There are innumerable diabetes studies that have investigated associations between risk factors, protective factors, and health outcomes; however, these individual predictors are part of a complex network of interacting forces. Moreover, there is little awareness about resilience or its importance in chronic disease in adulthood, especially diabetes. Thus, this is the first study to: (1) extensively investigate the relationships among a host of predictors and multiple adaptive outcomes; and (2) conceptualise a resilience model among people with diabetes. Methods: This cross-sectional study was divided into two research studies. Study One was to translate two diabetes-specific instruments (Problem Areas In Diabetes, PAID; Diabetes Coping Measure, DCM) into a Chinese version and to examine their psychometric properties for use in Study Two in a convenience sample of 205 outpatients with type 2 diabetes. In Study Two, an integrated theoretical model is developed and evaluated using the structural equation modelling (SEM) technique. A self-administered questionnaire was completed by 345 people with type 2 diabetes from the endocrine outpatient departments of three hospitals in Taiwan. Results: Confirmatory factor analyses confirmed a one-factor structure of the PAID-C which was similar to the original version of the PAID. Strong content validity of the PAID-C was demonstrated. The PAID-C was associated with HbA1c and diabetes self-care behaviours, confirming satisfactory criterion validity. There was a moderate relationship between the PAID-C and the Perceived Stress Scale, supporting satisfactory convergent validity. The PAID-C also demonstrated satisfactory stability and high internal consistency. A four-factor structure and strong content validity of the DCM-C was confirmed. Criterion validity demonstrated that the DCM-C was significantly associated with HbA1c and diabetes self-care behaviours. There was a statistical correlation between the DCM-C and the Revised Ways of Coping Checklist, suggesting satisfactory convergent validity. Test-retest reliability demonstrated satisfactory stability of the DCM-C. The total scale of the DCM-C showed adequate internal consistency. Age, duration of diabetes, diabetes symptoms, diabetes distress, physical activity, coping strategies, and social support were the most consistent factors associated with adaptive outcomes in adults with diabetes. Resilience was positively associated with coping strategies, social support, health-related quality of life, and diabetes self-care behaviours. Results of the structural equation modelling revealed protective factors had a significant direct effect on adaptive outcomes; however, the construct of risk factors was not significantly related to adaptive outcomes. Moreover, resilience can moderate the relationships among protective factors and adaptive outcomes, but there were no interaction effects of risk factors and resilience on adaptive outcomes. Conclusion: This study contributes to an understanding of how risk factors and protective factors work together to influence adaptive outcomes in blood sugar control, health-related quality of life, and diabetes self-care behaviours. Additionally, resilience is a positive personality characteristic and may be importantly involved in the adjustment process among people living with type 2 diabetes.
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Suicide has drawn much attention from both the scientific community and the public. Examining the impact of socio-environmental factors on suicide is essential in developing suicide prevention strategies and interventions, because it will provide health authorities with important information for their decision-making. However, previous studies did not examine the impact of socio-environmental factors on suicide using a spatial analysis approach. The purpose of this study was to identify the patterns of suicide and to examine how socio-environmental factors impact on suicide over time and space at the Local Governmental Area (LGA) level in Queensland. The suicide data between 1999 and 2003 were collected from the Australian Bureau of Statistics (ABS). Socio-environmental variables at the LGA level included climate (rainfall, maximum and minimum temperature), Socioeconomic Indexes for Areas (SEIFA) and demographic variables (proportion of Indigenous population, unemployment rate, proportion of population with low income and low education level). Climate data were obtained from Australian Bureau of Meteorology. SEIFA and demographic variables were acquired from ABS. A series of statistical and geographical information system (GIS) approaches were applied in the analysis. This study included two stages. The first stage used average annual data to view the spatial pattern of suicide and to examine the association between socio-environmental factors and suicide over space. The second stage examined the spatiotemporal pattern of suicide and assessed the socio-environmental determinants of suicide, using more detailed seasonal data. In this research, 2,445 suicide cases were included, with 1,957 males (80.0%) and 488 females (20.0%). In the first stage, we examined the spatial pattern and the determinants of suicide using 5-year aggregated data. Spearman correlations were used to assess associations between variables. Then a Poisson regression model was applied in the multivariable analysis, as the occurrence of suicide is a small probability event and this model fitted the data quite well. Suicide mortality varied across LGAs and was associated with a range of socio-environmental factors. The multivariable analysis showed that maximum temperature was significantly and positively associated with male suicide (relative risk [RR] = 1.03, 95% CI: 1.00 to 1.07). Higher proportion of Indigenous population was accompanied with more suicide in male population (male: RR = 1.02, 95% CI: 1.01 to 1.03). There was a positive association between unemployment rate and suicide in both genders (male: RR = 1.04, 95% CI: 1.02 to 1.06; female: RR = 1.07, 95% CI: 1.00 to 1.16). No significant association was observed for rainfall, minimum temperature, SEIFA, proportion of population with low individual income and low educational attainment. In the second stage of this study, we undertook a preliminary spatiotemporal analysis of suicide using seasonal data. Firstly, we assessed the interrelations between variables. Secondly, a generalised estimating equations (GEE) model was used to examine the socio-environmental impact on suicide over time and space, as this model is well suited to analyze repeated longitudinal data (e.g., seasonal suicide mortality in a certain LGA) and it fitted the data better than other models (e.g., Poisson model). The suicide pattern varied with season and LGA. The north of Queensland had the highest suicide mortality rate in all the seasons, while there was no suicide case occurred in the southwest. Northwest had consistently higher suicide mortality in spring, autumn and winter. In other areas, suicide mortality varied between seasons. This analysis showed that maximum temperature was positively associated with suicide among male population (RR = 1.24, 95% CI: 1.04 to 1.47) and total population (RR = 1.15, 95% CI: 1.00 to 1.32). Higher proportion of Indigenous population was accompanied with more suicide among total population (RR = 1.16, 95% CI: 1.13 to 1.19) and by gender (male: RR = 1.07, 95% CI: 1.01 to 1.13; female: RR = 1.23, 95% CI: 1.03 to 1.48). Unemployment rate was positively associated with total (RR = 1.40, 95% CI: 1.24 to 1.59) and female (RR=1.09, 95% CI: 1.01 to 1.18) suicide. There was also a positive association between proportion of population with low individual income and suicide in total (RR = 1.28, 95% CI: 1.10 to 1.48) and male (RR = 1.45, 95% CI: 1.23 to 1.72) population. Rainfall was only positively associated with suicide in total population (RR = 1.11, 95% CI: 1.04 to 1.19). There was no significant association for rainfall, minimum temperature, SEIFA, proportion of population with low educational attainment. The second stage is the extension of the first stage. Different spatial scales of dataset were used between the two stages (i.e., mean yearly data in the first stage, and seasonal data in the second stage), but the results are generally consistent with each other. Compared with other studies, this research explored the variety of the impact of a wide range of socio-environmental factors on suicide in different geographical units. Maximum temperature, proportion of Indigenous population, unemployment rate and proportion of population with low individual income were among the major determinants of suicide in Queensland. However, the influence from other factors (e.g. socio-culture background, alcohol and drug use) influencing suicide cannot be ignored. An in-depth understanding of these factors is vital in planning and implementing suicide prevention strategies. Five recommendations for future research are derived from this study: (1) It is vital to acquire detailed personal information on each suicide case and relevant information among the population in assessing the key socio-environmental determinants of suicide; (2) Bayesian model could be applied to compare mortality rates and their socio-environmental determinants across LGAs in future research; (3) In the LGAs with warm weather, high proportion of Indigenous population and/or unemployment rate, concerted efforts need to be made to control and prevent suicide and other mental health problems; (4) The current surveillance, forecasting and early warning system needs to be strengthened, to trace the climate and socioeconomic change over time and space and its impact on population health; (5) It is necessary to evaluate and improve the facilities of mental health care, psychological consultation, suicide prevention and control programs; especially in the areas with low socio-economic status, high unemployment rate, extreme weather events and natural disasters.
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In this research, we aim to identify factors that significantly affect the clickthrough of Web searchers. Our underlying goal is determine more efficient methods to optimize the clickthrough rate. We devise a clickthrough metric for measuring customer satisfaction of search engine results using the number of links visited, number of queries a user submits, and rank of clicked links. We use a neural network to detect the significant influence of searching characteristics on future user clickthrough. Our results show that high occurrences of query reformulation, lengthy searching duration, longer query length, and the higher ranking of prior clicked links correlate positively with future clickthrough. We provide recommendations for leveraging these findings for improving the performance of search engine retrieval and result ranking, along with implications for search engine marketing