948 resultados para Health statistics


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Mode of access: Internet.

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Mode of access: Internet.

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Background The problem of silent multiple comparisons is one of the most difficult statistical problems faced by scientists. It is a particular problem for investigating a one-off cancer cluster reported to a health department because any one of hundreds, or possibly thousands, of neighbourhoods, schools, or workplaces could have reported a cluster, which could have been for any one of several types of cancer or any one of several time periods. Methods This paper contrasts the frequentist approach with a Bayesian approach for dealing with silent multiple comparisons in the context of a one-off cluster reported to a health department. Two published cluster investigations were re-analysed using the Dunn-Sidak method to adjust frequentist p-values and confidence intervals for silent multiple comparisons. Bayesian methods were based on the Gamma distribution. Results Bayesian analysis with non-informative priors produced results similar to the frequentist analysis, and suggested that both clusters represented a statistical excess. In the frequentist framework, the statistical significance of both clusters was extremely sensitive to the number of silent multiple comparisons, which can only ever be a subjective "guesstimate". The Bayesian approach is also subjective: whether there is an apparent statistical excess depends on the specified prior. Conclusion In cluster investigations, the frequentist approach is just as subjective as the Bayesian approach, but the Bayesian approach is less ambitious in that it treats the analysis as a synthesis of data and personal judgements (possibly poor ones), rather than objective reality. Bayesian analysis is (arguably) a useful tool to support complicated decision-making, because it makes the uncertainty associated with silent multiple comparisons explicit.

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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 refractive error of a human eye varies across the pupil and therefore may be treated as a random variable. The probability distribution of this random variable provides a means for assessing the main refractive properties of the eye without the necessity of traditional functional representation of wavefront aberrations. To demonstrate this approach, the statistical properties of refractive error maps are investigated. Closed-form expressions are derived for the probability density function (PDF) and its statistical moments for the general case of rotationally-symmetric aberrations. A closed-form expression for a PDF for a general non-rotationally symmetric wavefront aberration is difficult to derive. However, for specific cases, such as astigmatism, a closed-form expression of the PDF can be obtained. Further, interpretation of the distribution of the refractive error map as well as its moments is provided for a range of wavefront aberrations measured in real eyes. These are evaluated using a kernel density and sample moments estimators. It is concluded that the refractive error domain allows non-functional analysis of wavefront aberrations based on simple statistics in the form of its sample moments. Clinicians may find this approach to wavefront analysis easier to interpret due to the clinical familiarity and intuitive appeal of refractive error maps.

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Seasonal patterns have been found in a remarkable range of health conditions, including birth defects, respiratory infections and cardiovascular disease. Accurately estimating the size and timing of seasonal peaks in disease incidence is an aid to understanding the causes and possibly to developing interventions. With global warming increasing the intensity of seasonal weather patterns around the world, a review of the methods for estimating seasonal effects on health is timely. This is the first book on statistical methods for seasonal data written for a health audience. It describes methods for a range of outcomes (including continuous, count and binomial data) and demonstrates appropriate techniques for summarising and modelling these data. It has a practical focus and uses interesting examples to motivate and illustrate the methods. The statistical procedures and example data sets are available in an R package called ‘season’. Adrian Barnett is a senior research fellow at Queensland University of Technology, Australia. Annette Dobson is a Professor of Biostatistics at The University of Queensland, Australia. Both are experienced medical statisticians with a commitment to statistical education and have previously collaborated in research in the methodological developments and applications of biostatistics, especially to time series data. Among other projects, they worked together on revising the well-known textbook "An Introduction to Generalized Linear Models," third edition, Chapman Hall/CRC, 2008. In their new book they share their knowledge of statistical methods for examining seasonal patterns in health.

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Emergency Health Services (EHS), encompassing hospital-based Emergency Departments (ED) and pre-hospital ambulance services, are a significant and high profile component of Australia’s health care system and congestion of these, evidenced by physical overcrowding and prolonged waiting times, is causing considerable community and professional concern. This concern relates not only to Australia’s capacity to manage daily health emergencies but also the ability to respond to major incidents and disasters. EHS congestion is a result of the combined effects of increased demand for emergency care, increased complexity of acute health care, and blocked access to ongoing care (e.g. inpatient beds). Despite this conceptual understanding there is a lack of robust evidence to explain the factors driving increased demand, or how demand contributes to congestion, and therefore public policy responses have relied upon limited or unsound information. The Emergency Health Services Queensland (EHSQ) research program proposes to determine the factors influencing the growing demand for emergency health care and to establish options for alternative service provision that may safely meet patient’s needs. The EHSQ study is funded by the Australian Research Council (ARC) through its Linkage Program and is supported financially by the Queensland Ambulance Service (QAS). This monograph is part of a suite of publications based on the research findings that examines the existing literature, and current operational context. Literature was sourced using standard search approaches and a range of databases as well as a selection of articles cited in the reviewed literature. Public sources including the Australian Institute of Health and Welfare (AIHW), the Council of Ambulance Authorities (CAA) Annual Reports, Australian Bureau of Statistics (ABS) and Department of Health and Ageing (DoHA) were examined for trend data across Australia.

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As the development of ICD-11 progresses, the Australian Bureau of Statistics is beginning to consider what will be required to successfully implement the new version of the classification. This paper will present early thoughts on the following: building understanding amongst the user community of upcoming changes and the implications of those changes; the need for training of coders and data users; development of analytical methods and conduct of comparability studies; processes to test, accept and implement new or updated coding software; assessment of coding quality; changes to data analyses and reporting processes; updates to regular publications; and assessing the resources required for successful implementation.

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Background: Although class attendance is linked to academic performance, questions remain about what determines students’ decisions to attend or miss class. Aims: In addition to the constructs of a common decision-making model, the theory of planned behaviour, the present study examined the influence of student role identity and university student (in-group) identification for predicting both the initiation and maintenance of students’ attendance at voluntary peer-assisted study sessions in a statistics subject. Sample: University students enrolled in a statistics subject were invited to complete a questionnaire at two time points across the academic semester. A total of 79 university students completed questionnaires at the first data collection point, with 46 students completing the questionnaire at the second data collection point. Method: Twice during the semester, students’ attitudes, subjective norm, perceived behavioural control, student role identity, in-group identification, and intention to attend study sessions were assessed via on-line questionnaires. Objective measures of class attendance records for each half-semester (or ‘term’) were obtained. Results: Across both terms, students’ attitudes predicted their attendance intentions, with intentions predicting class attendance. Earlier in the semester, in addition to perceived behavioural control, both student role identity and in-group identification predicted students’ attendance intentions, with only role identity influencing intentions later in the semester. Conclusions: These findings highlight the possible chronology that different identity influences have in determining students’ initial and maintained attendance at voluntary sessions designed to facilitate their learning.

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OBJECTIVE: To identify the factors associated with infertility, seeking advice and treatment with fertility hormones and/or in vitro fertilisation (IVF) among a general population of women. METHODS: Participants in the Australian Longitudinal Study on Women's Health aged 28-33 years in 2006 had completed up to four mailed surveys over 10 years (n=9,145). Parsimonious multivariate logistic regression was used to identify the socio-demographic, biological (including reproductive histories), and behavioural factors associated with infertility, advice and hormonal/IVF treatment. RESULTS: For women who had tried to conceive or had been pregnant (n=5,936), 17% reported infertility. Among women with infertility (n=1031), 72% (n=728) sought advice but only 50% (n=356) used hormonal/IVF treatment. Women had higher odds of infertility when: they had never been pregnant (OR=7.2, 95% CI 5.6-9.1) or had a history of miscarriage (OR range=1.5-4.0) than those who had given birth (and never had a miscarriage or termination). CONCLUSION: Only one-third of women with infertility used hormonal and/or IVF treatment. Women with PCOS or endometriosis were the most proactive in having sought advice and used hormonal/IVF treatment. IMPLICATIONS: Raised awareness of age-related declining fertility is important for partnered women aged approximately 30 years to encourage pregnancy during their prime reproductive years and reduce the risk of infertility.

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Health complaint statistics are important for identifying problems and bringing about improvements to health care provided by health service providers and to the wider health care system. This paper overviews complaints handling by the eight Australian state and territory health complaint entities, based on an analysis of data from their annual reports. The analysis shows considerable variation between jurisdictions in the ways complaint data are defined, collected and recorded. Complaints from the public are an important accountability mechanism and open a window on service quality. The lack of a national approach leads to fragmentation of complaint data and a lost opportunity to use national data to assist policy development and identify the main areas causing consumers to complain. We need a national approach to complaints data collection in order to better respond to patients’ concerns.

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Background: Quality of work life (QWL) is defined as the extent to which employee is satisfied with personal and working needs through participating in the workplace while achieving the organisation’s goals. QWL has been found to influence the commitment and productivity of employees in healthcare organisations, as well as in other industries. However, reliable information on the QWL of PHC nurses is limited. The purpose of this study was to assess the QWL among PHC nurses in the Jazan region, Saudi Arabia. Methods: A descriptive research design, namely, a cross-sectional survey was used in this study. Data were collected using Brooks’ survey of quality of nursing work life (QNWL) and demographic questions. A convenience sample was recruited from 143 PHC centres in Jazan, Saudi Arabia. The Jazan region is located in the southern part of Saudi Arabia. A response rate of 91% (N = 532/585) was achieved (effective RR = 87%, n = 508). Data analysis consisted of descriptive statistics, t-test and one way-analysis of variance. Total scores and sub-scores for QWL Items and item summary statistics were computed and reported, using SPSS version 17 for Windows. Results: Findings suggested that the respondents were dissatisfied with their work life. The major influencing factors were unsuitable working hours/shifts, lack of facilities for nurses, inability to balance work with family needs, inadequacy of family-leave time, poor staffing, management and supervision practices, lack of professional development opportunities, and inappropriate working environment in terms of the level of security, patient care supplies and equipment, and recreation facilities (Break-area). Other essential factors include the community’s view of nursing and inadequate salary. More positively, the majority of nurses were satisfied with their co-workers, satisfied to be nurses and had a sense of belonging in their workplaces. Significant differences were found according to gender, age, marital status, dependent children, dependent adults, nationality, ethnicity, nursing tenure, organisational tenure, positional tenure, and payment per month. No significant differences were found according to education level and location of PHC. Conclusions: These findings can be used by PHC managers and policy makers for developing and appropriately implementing successful plans to improve the QWL. This will help to enhance the home and work environments, improve individual and organisation performance and increase nurses’ commitment.