230 resultados para HEALTH-ASSESSMENT QUESTIONNAIRE


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The purpose was to determine intake of phytoestrogens in a sample of older Australian women, and to investigate associated lifestyle factors. Subjects were an age-stratified sample of 511 women aged 40-80 y, randomly selected from the electoral roll and participating in the Longitudinal Assessment of Ageing in Women at the Royal Brisbane and Women’s Hospital. A cross-sectional study was conducted to assess isoflavone and lignan intake over the past month from food and supplements using a 112-item phytoestrogen frequency questionnaire. Data were also collected on nutrient intakes, physical activity, smoking, alcohol, non-prescription supplements, hormone therapy, education and occupation. Logistic regression was used to evaluate associations between demographic and lifestyle variables and soy/linseed consumption while controlling for age. Isoflavone intakes were significantly higher in the younger compared to older age groups (p<0.001); there were no age-related differences in lignan intake. Forty-five percent of women consumed at least one serve of a soy and/or linseed item and were defined as a soy/linseed consumer. Median (range) intakes by consumers for isoflavones and lignans (3.9 (0-172) mg/d and 2.4 (0.1-33) mg/d) were higher than intakes by non-consumers (0.004 (0-2.6) mg/d and 1.57 (0.44-4.7) mg/d), respectively (p<0.001). Consumers had higher intakes of dietary fibre (p=0.003), energy (p=0.04) and polyunsaturated fat (p=0.004), and higher levels of physical activity (p=0.006), socio-economic position (p<0.001), education (p<0.001) and supplement use (p<0.001). Women who consumed soy or linseed foods differed in lifestyle and demographic characteristics suggesting these factors should be considered when investigating associations with chronic disease outcomes.

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Modern statistical models and computational methods can now incorporate uncertainty of the parameters used in Quantitative Microbial Risk Assessments (QMRA). Many QMRAs use Monte Carlo methods, but work from fixed estimates for means, variances and other parameters. We illustrate the ease of estimating all parameters contemporaneously with the risk assessment, incorporating all the parameter uncertainty arising from the experiments from which these parameters are estimated. A Bayesian approach is adopted, using Markov Chain Monte Carlo Gibbs sampling (MCMC) via the freely available software, WinBUGS. The method and its ease of implementation are illustrated by a case study that involves incorporating three disparate datasets into an MCMC framework. The probabilities of infection when the uncertainty associated with parameter estimation is incorporated into a QMRA are shown to be considerably more variable over various dose ranges than the analogous probabilities obtained when constants from the literature are simply ‘plugged’ in as is done in most QMRAs. Neglecting these sources of uncertainty may lead to erroneous decisions for public health and risk management.

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Objective: This study documents the mental health status of people from Burmese refugee backgrounds, recently arrived in Australia; then examines the contributions of gender, premigration and postmigration factors in predicting mental health. Method: Structured interviews, including a demographic questionnaire, the Harvard Trauma Questionnaire, Postmigration Living Difficulties Checklist and Hopkins Symptom Checklist assessed premigration trauma, postmigration living difficulties, depression, anxiety, somatisation and traumatisation symptoms in a sample of 70 adults across five Burmese ethnic groups. Results: Substantial proportions of participants reported psychological distress in symptomatic ranges including: posttraumatic stress disorder (9%); anxiety (20%), and; depression (36%), as well as significant symptoms of somatisation (37%). Participants reported multiple and severe premigration traumas. Postmigration living difficulties of greatest concern included communication problems and worry about family not in Australia. Gender did not predict mental health. Level of exposure to traumatic events and postmigration living difficulties each made unique and relatively equal contributions to traumatisation symptoms. Postmigration living difficulties made unique contributions to depression, anxiety and somatisation symptoms. Conclusions: While exposure to traumatic events impacted on participants’ mental wellbeing, postmigration living difficulties had greater salience in predicting mental health outcomes of people from Burmese refugee backgrounds. Reported rates of posttraumatic stress disorder symptoms were consistent with a large review of adults across seven western countries. High levels of somatisation pointed to a nuanced expression of distress. Findings have implications for service provision in terms of implementing appropriate interventions to effectively meet the needs of this newly arrived group in Australia.

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Automobiles have deeply impacted the way in which we travel but they have also contributed to many deaths and injury due to crashes. A number of reasons for these crashes have been pointed out by researchers. Inexperience has been identified as a contributing factor to road crashes. Driver’s driving abilities also play a vital role in judging the road environment and reacting in-time to avoid any possible collision. Therefore driver’s perceptual and motor skills remain the key factors impacting on road safety. Our failure to understand what is really important for learners, in terms of competent driving, is one of the many challenges for building better training programs. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. A multidisciplinary approach is necessary to explain how driving abilities evolves with on-road driving experience. To our knowledge, driver assistance systems have never been comprehensively used in a driver training context to assess the safety aspect of driving. The aim and novelty of this thesis is to develop and evaluate an Intelligent Driver Training System (IDTS) as an automated assessment tool that will help drivers and their trainers to comprehensively view complex driving manoeuvres and potentially provide effective feedback by post processing the data recorded during driving. This system is designed to help driver trainers to accurately evaluate driver performance and has the potential to provide valuable feedback to the drivers. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the driving tasks. Therefore, the proposed IDTS utilizes fuzzy set theory for the assessment of driver performance. The proposed research program focuses on integrating the multi-sensory information acquired from the vehicle, driver and environment to assess driving competencies. After information acquisition, the current research focuses on automated segmentation of the selected manoeuvres from the driving scenario. This leads to the creation of a model that determines a “competency” criterion through the driving performance protocol used by driver trainers (i.e. expert knowledge) to assess drivers. This is achieved by comprehensively evaluating and assessing the data stream acquired from multiple in-vehicle sensors using fuzzy rules and classifying the driving manoeuvres (i.e. overtake, lane change, T-crossing and turn) between low and high competency. The fuzzy rules use parameters such as following distance, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvres to assess competency. These rules that identify driving competency were initially designed with the help of expert’s knowledge (i.e. driver trainers). In-order to fine tune these rules and the parameters that define these rules, a driving experiment was conducted to identify the empirical differences between novice and experienced drivers. The results from the driving experiment indicated that significant differences existed between novice and experienced driver, in terms of their gaze pattern and duration, speed, stop time at the T-crossing, lane keeping and the time spent in lanes while performing the selected manoeuvres. These differences were used to refine the fuzzy membership functions and rules that govern the assessments of the driving tasks. Next, this research focused on providing an integrated visual assessment interface to both driver trainers and their trainees. By providing a rich set of interactive graphical interfaces, displaying information about the driving tasks, Intelligent Driver Training System (IDTS) visualisation module has the potential to give empirical feedback to its users. Lastly, the validation of the IDTS system’s assessment was conducted by comparing IDTS objective assessments, for the driving experiment, with the subjective assessments of the driver trainers for particular manoeuvres. Results show that not only IDTS was able to match the subjective assessments made by driver trainers during the driving experiment but also identified some additional driving manoeuvres performed in low competency that were not identified by the driver trainers due to increased mental workload of trainers when assessing multiple variables that constitute driving. The validation of IDTS emphasized the need for an automated assessment tool that can segment the manoeuvres from the driving scenario, further investigate the variables within that manoeuvre to determine the manoeuvre’s competency and provide integrated visualisation regarding the manoeuvre to its users (i.e. trainers and trainees). Through analysis and validation it was shown that IDTS is a useful assistance tool for driver trainers to empirically assess and potentially provide feedback regarding the manoeuvres undertaken by the drivers.

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Purpose: To examine the relationship between visual impairment and functional status in a community-dwelling sample of older adults with glaucoma. Methods: This study included 74 community-dwelling older adults with open-angle glaucoma (aged 74 ± 6 years). Assessment of central vision included high-contrast visual acuity and Pelli-Robson contrast sensitivity. Binocular integrated visual fields were derived from merged monocular Humphrey Field Analyser visual field plots. Functional status outcome measures included physical performance tests (6-min walk test, timed up and go test and lower limb strength), a physical activity questionnaire (Physical Activity Scale for the Elderly) and an overall functional status score. Correlation and linear regression analyses, adjusting for age and gender, examined the association between visual impairment and functional status outcomes. Results: Greater levels of visual impairment were significantly associated with lower levels of functional status among community-dwelling older adults with glaucoma, independent of age and gender. Specifically, lower levels of visual function were associated with slower timed up and go performance, weaker lower limb strength, lower self-reported physical activity, and lower overall functional status scores. Of the components of vision examined, the inferior visual field and contrast factors were the strongest predictors of these functional outcomes, whereas the superior visual field factor was not related to functional status. Conclusions: Greater visual impairment, particularly in the inferior visual field and loss of contrast sensitivity, was associated with poorer functional status among older adults with glaucoma. The findings of this study highlight the potential links between visual impairment and the onset of functional decline. Interventions which promote physical activity among older adults with glaucoma may assist in preventing functional decline, frailty and falls, and improve overall health and well-being.

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Issue addressed: Measures of 'social identity' and 'psychological sense of community' were included within a broader formative research inquiry to gain insight into the identity characteristics and level of connectedness among older recreational road travellers (commonly known as Grey Nomads). The research sought to gain insights on how best to reach or speak to this growing driver cohort. ----- ----- Method: Participants included 631 older recreational road travellers ranging in age from 50 years to over 80 years. Data were obtained through three scales which were incorporated into a larger formative research survey; an identity hierarchy, the Three Factor Model of Social Identity and the Sense of Community Index. ----- ----- Results: Older recreational road travellers see themselves principally as couples, with social group identity being secondary. Although many identified to some degree with the Grey Nomad identity, when asked to self categorise as either members of the Broad Network of Recreational Vehicle Travellers or as Grey Nomads, the majority categorised themselves as the former. Those identifying as Grey Nomads, however, reported significantly higher levels of 'social identification' and 'sense of community'. ----- ----- Conclusion: The Grey Nomad identity may not be the best identity at which to target road safety messages for this cohort. Targeting travelling 'couples' may be more efficacious. Using the 'Grey Nomad' identity is likely to reap at least some success, however, given that many identified to some degree with this group identity. Those identifying as Grey Nomads may be more open to community participation or behaviour change given their significantly higher levels of 'social identity' and 'sense of community'.

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Collagen fibrillation within articular cartilage (AC) plays a key role in joint osteoarthritis (OA) progression and, therefore, studying collagen synthesis changes could be an indicator for use in the assessment of OA. Various staining techniques have been developed and used to determine the collagen network transformation under microscopy. However, because collagen and proteoglycan coexist and have the same index of refraction, conventional methods for specific visualization of collagen tissue is difficult. This study aimed to develop an advanced staining technique to distinguish collagen from proteoglycan and to determine its evolution in relation to OA progression using optical and laser scanning confocal microscopy (LSCM). A number of AC samples were obtained from sheep joints, including both healthy and abnormal joints with OA grades 1 to 3. The samples were stained using two different trichrome methods and immunohistochemistry (IHC) to stain both colourimetrically and with fluorescence. Using optical microscopy and LSCM, the present authors demonstrated that the IHC technique stains collagens only, allowing the collagen network to be separated and directly investigated. Fluorescently-stained IHC samples were also subjected to LSCM to obtain three-dimensional images of the collagen fibres. Changes in the collagen fibres were then correlated with the grade of OA in tissue. This study is the first to successfully utilize the IHC staining technique in conjunction with laser scanning confocal microscopy. This is a valuable tool for assessing changes to articular cartilage in OA.

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The tear film plays an important role preserving the health of the ocular surface and maintaining the optimal refractive power of the cornea. Moreover dry eye syndrome is one of the most commonly reported eye health problems. This syndrome is caused by abnormalities in the properties of the tear film. Current clinical tools to assess the tear film properties have shown certain limitations. The traditional invasive methods for the assessment of tear film quality, which are used by most clinicians, have been criticized for the lack of reliability and/or repeatability. A range of non-invasive methods of tear assessment have been investigated, but also present limitations. Hence no “gold standard” test is currently available to assess the tear film integrity. Therefore, improving techniques for the assessment of the tear film quality is of clinical significance and the main motivation for the work described in this thesis. In this study the tear film surface quality (TFSQ) changes were investigated by means of high-speed videokeratoscopy (HSV). In this technique, a set of concentric rings formed in an illuminated cone or a bowl is projected on the anterior cornea and their reflection from the ocular surface imaged on a charge-coupled device (CCD). The reflection of the light is produced in the outer most layer of the cornea, the tear film. Hence, when the tear film is smooth the reflected image presents a well structure pattern. In contrast, when the tear film surface presents irregularities, the pattern also becomes irregular due to the light scatter and deviation of the reflected light. The videokeratoscope provides an estimate of the corneal topography associated with each Placido disk image. Topographical estimates, which have been used in the past to quantify tear film changes, may not always be suitable for the evaluation of all the dynamic phases of the tear film. However the Placido disk image itself, which contains the reflected pattern, may be more appropriate to assess the tear film dynamics. A set of novel routines have been purposely developed to quantify the changes of the reflected pattern and to extract a time series estimate of the TFSQ from the video recording. The routine extracts from each frame of the video recording a maximized area of analysis. In this area a metric of the TFSQ is calculated. Initially two metrics based on the Gabor filter and Gaussian gradient-based techniques, were used to quantify the consistency of the pattern’s local orientation as a metric of TFSQ. These metrics have helped to demonstrate the applicability of HSV to assess the tear film, and the influence of contact lens wear on TFSQ. The results suggest that the dynamic-area analysis method of HSV was able to distinguish and quantify the subtle, but systematic degradation of tear film surface quality in the inter-blink interval in contact lens wear. It was also able to clearly show a difference between bare eye and contact lens wearing conditions. Thus, the HSV method appears to be a useful technique for quantitatively investigating the effects of contact lens wear on the TFSQ. Subsequently a larger clinical study was conducted to perform a comparison between HSV and two other non-invasive techniques, lateral shearing interferometry (LSI) and dynamic wavefront sensing (DWS). Of these non-invasive techniques, the HSV appeared to be the most precise method for measuring TFSQ, by virtue of its lower coefficient of variation. While the LSI appears to be the most sensitive method for analyzing the tear build-up time (TBUT). The capability of each of the non-invasive methods to discriminate dry eye from normal subjects was also investigated. The receiver operating characteristic (ROC) curves were calculated to assess the ability of each method to predict dry eye syndrome. The LSI technique gave the best results under both natural blinking conditions and in suppressed blinking conditions, which was closely followed by HSV. The DWS did not perform as well as LSI or HSV. The main limitation of the HSV technique, which was identified during the former clinical study, was the lack of the sensitivity to quantify the build-up/formation phase of the tear film cycle. For that reason an extra metric based on image transformation and block processing was proposed. In this metric, the area of analysis was transformed from Cartesian to Polar coordinates, converting the concentric circles pattern into a quasi-straight lines image in which a block statistics value was extracted. This metric has shown better sensitivity under low pattern disturbance as well as has improved the performance of the ROC curves. Additionally a theoretical study, based on ray-tracing techniques and topographical models of the tear film, was proposed to fully comprehend the HSV measurement and the instrument’s potential limitations. Of special interested was the assessment of the instrument’s sensitivity under subtle topographic changes. The theoretical simulations have helped to provide some understanding on the tear film dynamics, for instance the model extracted for the build-up phase has helped to provide some insight into the dynamics during this initial phase. Finally some aspects of the mathematical modeling of TFSQ time series have been reported in this thesis. Over the years, different functions have been used to model the time series as well as to extract the key clinical parameters (i.e., timing). Unfortunately those techniques to model the tear film time series do not simultaneously consider the underlying physiological mechanism and the parameter extraction methods. A set of guidelines are proposed to meet both criteria. Special attention was given to a commonly used fit, the polynomial function, and considerations to select the appropriate model order to ensure the true derivative of the signal is accurately represented. The work described in this thesis has shown the potential of using high-speed videokeratoscopy to assess tear film surface quality. A set of novel image and signal processing techniques have been proposed to quantify different aspects of the tear film assessment, analysis and modeling. The dynamic-area HSV has shown good performance in a broad range of conditions (i.e., contact lens, normal and dry eye subjects). As a result, this technique could be a useful clinical tool to assess tear film surface quality in the future.

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The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation and can also improve productivity and enhance system’s safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. Although a variety of prognostic methodologies have been reported recently, their application in industry is still relatively new and mostly focused on the prediction of specific component degradations. Furthermore, they required significant and sufficient number of fault indicators to accurately prognose the component faults. Hence, sufficient usage of health indicators in prognostics for the effective interpretation of machine degradation process is still required. Major challenges for accurate longterm prediction of remaining useful life (RUL) still remain to be addressed. Therefore, continuous development and improvement of a machine health management system and accurate long-term prediction of machine remnant life is required in real industry application. This thesis presents an integrated diagnostics and prognostics framework based on health state probability estimation for accurate and long-term prediction of machine remnant life. In the proposed model, prior empirical (historical) knowledge is embedded in the integrated diagnostics and prognostics system for classification of impending faults in machine system and accurate probability estimation of discrete degradation stages (health states). The methodology assumes that machine degradation consists of a series of degraded states (health states) which effectively represent the dynamic and stochastic process of machine failure. The estimation of discrete health state probability for the prediction of machine remnant life is performed using the ability of classification algorithms. To employ the appropriate classifier for health state probability estimation in the proposed model, comparative intelligent diagnostic tests were conducted using five different classifiers applied to the progressive fault data of three different faults in a high pressure liquefied natural gas (HP-LNG) pump. As a result of this comparison study, SVMs were employed in heath state probability estimation for the prediction of machine failure in this research. The proposed prognostic methodology has been successfully tested and validated using a number of case studies from simulation tests to real industry applications. The results from two actual failure case studies using simulations and experiments indicate that accurate estimation of health states is achievable and the proposed method provides accurate long-term prediction of machine remnant life. In addition, the results of experimental tests show that the proposed model has the capability of providing early warning of abnormal machine operating conditions by identifying the transitional states of machine fault conditions. Finally, the proposed prognostic model is validated through two industrial case studies. The optimal number of health states which can minimise the model training error without significant decrease of prediction accuracy was also examined through several health states of bearing failure. The results were very encouraging and show that the proposed prognostic model based on health state probability estimation has the potential to be used as a generic and scalable asset health estimation tool in industrial machinery.

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Australian construction and building workers are exposed to serious workplace risks - including injury, illness and death - and although there have been improvements in occupational health and safety (OHS) performance over the past 20 years, the injury and fatality rate in the Australian construction industry remains a matter of concern. The concept of safety culture is rapidly being adopted in the industry, including recognising the critical role that organisational leaders play in overall safety performance. This paper reviews recent research in construction safety leadership and provides some examples and applications relevant to risk reduction in the workforce. By focusing on developing safety competency in those that fulfil safety critical roles, and clearly articulating the relevant safety management tasks, leaders can positively influence the organisation’s safety culture. Finally, some promising research on Safety Effectiveness Indicators (SEIs) may be an industry-friendly solution to reducing workplace risks across the industry, by providing a credible, accurate, and timely measure of safety performance.

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We present a novel method and instrument for in vivo imaging and measurement of the human corneal dynamics during an air puff. The instrument is based on high-speed swept source optical coherence tomography (ssOCT) combined with a custom adapted air puff chamber from a non-contact tonometer, which uses an air stream to deform the cornea in a non-invasive manner. During the short period of time that the deformation takes place, the ssOCT acquires multiple A-scans in time (M-scan) at the center of the air puff, allowing observation of the dynamics of the anterior and posterior corneal surfaces as well as the anterior lens surface. The dynamics of the measurement are driven by the biomechanical properties of the human eye as well as its intraocular pressure. Thus, the analysis of the M-scan may provide useful information about the biomechanical behavior of the anterior segment during the applanation caused by the air puff. An initial set of controlled clinical experiments are shown to comprehend the performance of the instrument and its potential applicability to further understand the eye biomechanics and intraocular pressure measurements. Limitations and possibilities of the new apparatus are discussed.

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This article presents the results of a study on the association between measured air pollutants and the respiratory health of resident women and children in Lao PDR, one of the least developed countries in Southeast Asia. The study, commissioned by the World Health Organisation, included PM10, CO and NO2 measurements made inside 181 dwellings in nine districts within two provinces in Lao PDR over a 5- month period (12/05–04/06), and respiratory health information (via questionnaires and peak expiratory flow rate (PEFR) measurements) for all residents in the same dwellings. Adjusted odds ratios were calculated separately for each health outcome using binary logistic regression. There was a strong and consistent positive association between NO2 and CO for almost all questionnaire-based health outcomes for both women and children. Women in dwellings with higher measured NO2 had more than triple of the odds of almost all of the health outcomes, and higher concentrations of NO2 and CO were significantly associated with lower PEFR. This study supports a growing literature confirming the role of indoor air pollution in the burden of respiratory disease in developing countries. The results will directly support changes in health and housing policy in Lao PDR.