443 resultados para Railroad safety, Bayesian methods, Accident modification factor, Countermeasure selection


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Statisticians along with other scientists have made significant computational advances that enable the estimation of formerly complex statistical models. The Bayesian inference framework combined with Markov chain Monte Carlo estimation methods such as the Gibbs sampler enable the estimation of discrete choice models such as the multinomial logit (MNL) model. MNL models are frequently applied in transportation research to model choice outcomes such as mode, destination, or route choices or to model categorical outcomes such as crash outcomes. Recent developments allow for the modification of the potentially limiting assumptions of MNL such as the independence from irrelevant alternatives (IIA) property. However, relatively little transportation-related research has focused on Bayesian MNL models, the tractability of which is of great value to researchers and practitioners alike. This paper addresses MNL model specification issues in the Bayesian framework, such as the value of including prior information on parameters, allowing for nonlinear covariate effects, and extensions to random parameter models, so changing the usual limiting IIA assumption. This paper also provides an example that demonstrates, using route-choice data, the considerable potential of the Bayesian MNL approach with many transportation applications. This paper then concludes with a discussion of the pros and cons of this Bayesian approach and identifies when its application is worthwhile

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Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

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Background Situational driving factors, including fatigue, distraction, inattention and monotony, are recognised killers in Australia, contributing to an estimated 40% of fatal crashes and 34% of all crashes . More often than not the main contributing factor is identified as fatigue, yet poor driving performance has been found to emerge early in monotonous conditions, independent of fatigue symptoms and time on task. This early emergence suggests an important role for monotony. However, much road safety research suggests that monotony is solely a task characteristic that directly causes fatigue and associated symptoms and there remains an absence of consistent evidence explaining the relationship. Objectives We report an experimental study designed to disentangle the characteristics and effects of monotony from those associated with fatigue. Specifically, we examined whether poor driving performance associated with hypovigilance emerges as a consequence of monotony, independent of fatigue. We also examined whether monotony is a multidimensional construct, determined by environmental characteristics and/or task demands that independently moderate sustained attention and associated driving performance. Method Using a driving simulator, participants completed four, 40 minute driving scenarios. The scenarios varied in the degree of monotony as determined by the degree of variation in road design (e.g., straight roads vs. curves) and/or road side scenery. Fatigue, as well as a number of other factors known to moderate vigilance and driving performance, was controlled for. To track changes across time, driving performance was assessed in five minute time periods using a range of behavioural, subjective and physiological measures, including steering wheel movements, lane positioning, electroencephalograms, skin conductance, and oculomotor activity. Results Results indicate that driving performance is worse in monotonous driving conditions characterised by low variability in road design. Critically, performance decrements associated with monotony emerge very early, suggesting monotony effects operate independent of fatigue. Conclusion Monotony is a multi-dimensional construct where, in a driving context, roads containing low variability in design are monotonous and those high in variability are non-monotonous. Importantly, low variability in road side scenery does not appear to exacerbate monotony or associated poor performance. However, high variability in road side scenery can act as a distraction and impair sustained attention and poor performance when driving on monotonous roads. Furthermore, high sensation seekers seem to be more susceptible to distraction when driving on monotonous roads. Implications of our results for the relationship between monotony and fatigue, and the possible construct-specific detection methods in a road safety context, will be discussed.

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Now in its second edition, this book describes tools that are commonly used in transportation data analysis. The first part of the text provides statistical fundamentals while the second part presents continuous dependent variable models. With a focus on count and discrete dependent variable models, the third part features new chapters on mixed logit models, logistic regression, and ordered probability models. The last section provides additional coverage of Bayesian statistical modeling, including Bayesian inference and Markov chain Monte Carlo methods. Data sets are available online to use with the modeling techniques discussed.

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The Intermodal Surface Transportation Efficiency Act (ISTEA) of 1991 mandated the consideration of safety in the regional transportation planning process. As part of National Cooperative Highway Research Program Project 8-44, "Incorporating Safety into the Transportation Planning Process," we conducted a telephone survey to assess safety-related activities and expertise at Governors Highway Safety Associations (GHSAs), and GHSA relationships with metropolitan planning organizations (MPOs) and state departments of transportation (DOTs). The survey results were combined with statewide crash data to enable exploratory modeling of the relationship between GHSA policies and programs and statewide safety. The modeling objective was to illuminate current hurdles to ISTEA implementation, so that appropriate institutional, analytical, and personnel improvements can be made. The study revealed that coordination of transportation safety across DOTs, MPOs, GHSAs, and departments of public safety is generally beneficial to the implementation of safety. In addition, better coordination is characterized by more positive and constructive attitudes toward incorporating safety into planning.

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Fatigue has been recognised as the primary contributing factor in approximately 15% of all fatal road crashes in Australia. To develop effective countermeasures for managing fatigue, this study investigates why drivers continue to drive when sleepy, and driver perceptions and behaviours in regards to countermeasures. Based on responses from 305 Australian drivers, it was identified that the major reasons why these participants continued to drive when sleepy were: wanting to get to their destination; being close to home; and time factors. Participants’ perceptions and use of 18 fatigue countermeasures were investigated. It was found that participants perceived the safest strategies, including stopping and sleeping, swapping drivers and stopping for a quick nap, to be the most effective countermeasures. However, it appeared that their knowledge of safe countermeasures did not translate into their use of these strategies. For example, although the drivers perceived stopping for a quick nap to be an effective countermeasure, they reported more frequent use of less safe methods such as stopping to eat or drink and winding down the window. This finding suggests that, while practitioners should continue educating drivers, they may need a greater focus on motivating drivers to implement safe fatigue countermeasures.

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The greatly increased risk of being killed or injured in a car crash for the young novice driver has been recognised in the road safety and injury prevention literature for decades. Risky driving behaviour has consistently been found to contribute to traffic crashes. Researchers have devised a number of instruments to measure this risky driving behaviour. One tool developed specifically to measure the risky behaviour of young novice drivers is the Behaviour of Young Novice Drivers Scale (BYNDS) (Scott-Parker et al., 2010). The BYNDS consists of 44 items comprising five subscales for transient violations, fixed violations, misjudgement, risky driving exposure, and driving in response to their mood. The factor structure of the BYNDS has not been examined since its development in a matched sample of 476 novice drivers aged 17-25 years. Method: The current research attempted to refine the BYNDS and explore its relationship with the self-reported crash and offence involvement and driving intentions of 390 drivers aged 17-25 years (M = 18.23, SD = 1.58) in Queensland, Australia, during their first six months of independent driving with a Provisional (intermediate) driver’s licence. A confirmatory factor analysis was undertaken examining the fit of the originally proposed BYNDS measurement model. Results: The model was not a good fit to the data. A number of iterations removed items with low factor loadings, resulting in a 36-item revised BYNDS which was a good fit to the data. The revised BYNDS was highly internally consistent. Crashes were associated with fixed violations, risky driving exposure, and misjudgement; offences were moderately associated with risky driving exposure and transient violations; and road-rule compliance intentions were highly associated with transient violations. Conclusions: Applications of the BYNDS in other young novice driver populations will further explore the factor structure of both the original and revised BYNDS. The relationships between BYNDS subscales and self-reported risky behaviour and attitudes can also inform countermeasure development, such as targeting young novice driver non-compliance through enforcement and education initiatives.

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Most crash severity studies ignored severity correlations between driver-vehicle units involved in the same crashes. Models without accounting for these within-crash correlations will result in biased estimates in the factor effects. This study developed a Bayesian hierarchical binomial logistic model to identify the significant factors affecting the severity level of driver injury and vehicle damage in traffic crashes at signalized intersections. Crash data in Singapore were employed to calibrate the model. Model fitness assessment and comparison using Intra-class Correlation Coefficient (ICC) and Deviance Information Criterion (DIC) ensured the suitability of introducing the crash-level random effects. Crashes occurring in peak time, in good street lighting condition, involving pedestrian injuries are associated with a lower severity, while those in night time, at T/Y type intersections, on right-most lane, and installed with red light camera have larger odds of being severe. Moreover, heavy vehicles have a better resistance on severe crash, while crashes involving two-wheel vehicles, young or aged drivers, and the involvement of offending party are more likely to result in severe injuries.

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Increased use of powered two-wheelers (PTWs) often underlies increases in the number of reported crashes, promoting research into PTW safety. PTW riders are overrepresented in crash and injury statistics relative to exposure and, as such, are considered vulnerable road users. PTW use has increased substantially over the last decade in many developed countries. One such country is Australia, where moped and scooter use has increased at a faster rate than motorcycle use in recent years. Increased moped use is particularly evident in the State of Queensland which is one of four Australian jurisdictions where moped riding is permitted for car licence holders and a motorcycle licence is not required. A moped is commonly a small motor scooter and is limited to a maximum design speed of 50 km/h and a maximum engine cylinder capacity of 50 cubic centimetres. Scooters exceeding either of these specifications are classed as motorcycles in all Australian jurisdictions. While an extensive body of knowledge exists on motorcycle safety, some of which is relevant to moped and scooter safety, the latter PTW types have received comparatively little focused research attention. Much of the research on moped safety to date has been conducted in Europe where they have been popular since the mid 20th century, while some studies have also been conducted in the United States. This research is of limited relevance to Australia due to socio-cultural, economic, regulatory and environmental differences. Moreover, while some studies have compared motorcycles to mopeds in terms of safety, no research to date has specifically examined the differences and similarities between mopeds and larger scooters, or between larger scooters and motorcycles. To address the need for a better understanding of moped and scooter use and safety, the current program of research involved three complementary studies designed to achieve the following aims: (1) develop better knowledge and understanding of moped and scooter usage trends and patterns; and (2) determine the factors leading to differences in moped, scooter and motorcycle safety. Study 1 involved six-monthly observations of PTW types in inner city parking areas of Queensland’s capital city, Brisbane, to monitor and quantify the types of PTW in use over a two year period. Study 2 involved an analysis of Queensland PTW crash and registration data, primarily comparing the police-reported crash involvement of mopeds, scooters and motorcycles over a five year period (N = 7,347). Study 3 employed both qualitative and quantitative methods to examine moped and scooter usage in two components: (a) four focus group discussions with Brisbane-based Queensland moped and scooter riders (N = 23); and (b) a state-wide survey of Queensland moped and scooter riders (N = 192). Study 1 found that of the PTW types parked in inner city Brisbane over the study period (N = 2,642), more than one third (36.1%) were mopeds or larger scooters. The number of PTWs observed increased at each six-monthly phase, but there were no significant changes in the proportions of PTW types observed across study phases. There were no significant differences in the proportions or numbers of PTW type observed by season. Study 2 revealed some important differences between mopeds, scooters and motorcycles in terms of safety and usage through analysis of crash and registration data. All Queensland PTW registrations doubled between 2001 and 2009, but there was an almost fifteen-fold increase in moped registrations. Mopeds subsequently increased as a proportion of Queensland registered PTWs from 1.2 percent to 8.8 percent over this nine year period. Moped and scooter crashes increased at a faster rate than motorcycle crashes over the five year study period from July 2003 to June 2008, reflecting their relatively greater increased usage. Crash rates per 10,000 registrations for the study period were only slightly higher for mopeds (133.4) than for motorcycles and scooters combined (124.8), but estimated crash rates per million vehicle kilometres travelled were higher for mopeds (6.3) than motorcycles and scooters (1.7). While the number of crashes increased for each PTW type over the study period, the rate of crashes per 10,000 registrations declined by 40 percent for mopeds compared with 22 percent for motorcycles and scooters combined. Moped and scooter crashes were generally less severe than motorcycle crashes and this was related to the particular crash characteristics of the PTW types rather than to the PTW types themselves. Compared to motorcycle and moped crashes, scooter crashes were less likely to be single vehicle crashes, to involve a speeding or impaired rider, to involve poor road conditions, or to be attributed to rider error. Scooter and moped crashes were more likely than motorcycle crashes to occur on weekdays, in lower speed zones and at intersections. Scooter riders were older on average (39) than moped (32) and motorcycle (35) riders, while moped riders were more likely to be female (36%) than scooter (22%) or motorcycle riders (7%). The licence characteristics of scooter and motorcycle riders were similar, with moped riders more likely to be licensed outside of Queensland and less likely to hold a full or open licence. The PTW type could not be identified in 15 percent of all cases, indicating a need for more complete recording of vehicle details in the registration data. The focus groups in Study 3a and the survey in Study 3b suggested that moped and scooter riders are a heterogeneous population in terms of demographic characteristics, riding experience, and knowledge and attitudes regarding safety and risk. The self-reported crash involvement of Study 3b respondents suggests that most moped and scooter crashes result in no injury or minor injury and are not reported to police. Study 3 provided some explanation for differences observed in Study 2 between mopeds and scooters in terms of crash involvement. On the whole, scooter riders were older, more experienced, more likely to have undertaken rider training and to value rider training programs. Scooter riders were also more likely to use protective clothing and to seek out safety-related information. This research has some important practical implications regarding moped and scooter use and safety. While mopeds and scooters are generally similar in terms of usage, and their usage has increased, scooter riders appear to be safer than moped riders due to some combination of superior skills and safer riding behaviour. It is reasonable to expect that mopeds and scooters will remain popular in Queensland in future and that their usage may further increase, along with that of motorcycles. Future policy and planning should consider potential options for encouraging moped riders to acquire better riding skills and greater safety awareness. While rider training and licensing appears an obvious potential countermeasure, the effectiveness of rider training has not been established and other options should also be strongly considered. Such options might include rider education and safety promotion, while interventions could also target other road users and urban infrastructure. Future research is warranted in regard to moped and scooter safety, particularly where the use of those PTWs has increased substantially from low levels. Research could address areas such as rider training and licensing (including program evaluations), the need for more detailed and reliable data (particularly crash and exposure data), protective clothing use, risks associated with lane splitting and filtering, and tourist use of mopeds. Some of this research would likely be relevant to motorcycle use and safety, as well as that of mopeds and scooters.

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A range of risk management initiatives have been introduced in organisations in attempt to reduce occupational road incidents. However a discrepancy exists between the initiatives that are frequently implemented in organisations and the initiatives that have demonstrated scientific merit in improving occupational road safety. Given that employees’ beliefs may facilitate or act as a barrier to implementing initiatives, it is important to understand whether initiatives with scientific merit are perceived to be effective by employees. To explore employee perceptions pertaining to occupational road safety initiatives, a questionnaire was administered to 679 employees sourced from four Australian organisations. Participants ranged in age from 18 years to 65 years (M = 42, SD = 11). Participants rated 35 initiatives based on how effective they thought they would be in improving road safety in their organisation. The initiatives perceived by employees to be most effective in managing occupational road risks comprised: making vehicle safety features standard e.g. passenger airbags; practical driver skills training; and investigation of serious vehicle incidents. The initiatives perceived to be least effective in managing occupational road risks comprised: signing a promise card commitment to drive safely; advertising the organisation’s phone number on vehicles for complaints and compliments; and consideration of driving competency in staff selection process. Employee perceptions were analysed at a factor level and at an initiative level. The mean scores for the three extracted factors revealed that employees believed occupational road risks could best be managed by the employer implementing engineering and human resource methods to enhance road safety. Initiatives relating to employer management of identified risk factors were perceived to be more effective than feedback or motivational methods that required employees to accept responsibility for their driving safety. Practitioners can use the findings from this study to make informed decisions about how they select, manage and market occupational safety initiatives.

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Background The implementation of the Australian Consumer Law in 2011 highlighted the need for better use of injury data to improve the effectiveness and responsiveness of product safety (PS) initiatives. In the PS system, resources are allocated to different priority issues using risk assessment tools. The rapid exchange of information (RAPEX) tool to prioritise hazards, developed by the European Commission, is currently being adopted in Australia. Injury data is required as a basic input to the RAPEX tool in the risk assessment process. One of the challenges in utilising injury data in the PS system is the complexity of translating detailed clinical coded data into broad categories such as those used in the RAPEX tool. Aims This study aims to translate hospital burns data into a simplified format by mapping the International Statistical Classification of Disease and Related Health Problems (Tenth Revision) Australian Modification (ICD-10-AM) burn codes into RAPEX severity rankings, using these rankings to identify priority areas in childhood product-related burns data. Methods ICD-10-AM burn codes were mapped into four levels of severity using the RAPEX guide table by assigning rankings from 1-4, in order of increasing severity. RAPEX rankings were determined by the thickness and surface area of the burn (BSA) with information extracted from the fourth character of T20-T30 codes for burn thickness, and the fourth and fifth characters of T31 codes for the BSA. Following the mapping process, secondary data analysis of 2008-2010 Queensland Hospital Admitted Patient Data Collection (QHAPDC) paediatric data was conducted to identify priority areas in product-related burns. Results The application of RAPEX rankings in QHAPDC burn data showed approximately 70% of paediatric burns in Queensland hospitals were categorised under RAPEX levels 1 and 2, 25% under RAPEX 3 and 4, with the remaining 5% unclassifiable. In the PS system, prioritisations are made to issues categorised under RAPEX levels 3 and 4. Analysis of external cause codes within these levels showed that flammable materials (for children aged 10-15yo) and hot substances (for children aged <2yo) were the most frequently identified products. Discussion and conclusions The mapping of ICD-10-AM burn codes into RAPEX rankings showed a favourable degree of compatibility between both classification systems, suggesting that ICD-10-AM coded burn data can be simplified to more effectively support PS initiatives. Additionally, the secondary data analysis showed that only 25% of all admitted burn cases in Queensland were severe enough to trigger a PS response.

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Purpose: This randomized, multicenter trial compared first-line trastuzumab plus docetaxel versus docetaxel alone in patients with human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer (MBC). Patients and Methods: Patients were randomly assigned to six cycles of docetaxel 100 mg/m 2 every 3 weeks, with or without trastuzumab 4 mg/kg loading dose followed by 2 mg/kg weekly until disease progression. Results: A total of 186 patients received at least one dose of the study drug. Trastuzumab plus docetaxel was significantly superior to docetaxel alone in terms of overall response rate (61% v 34%; P = .0002), overall survival (median, 31.2 v 22.7 months; P = .0325), time to disease progression (median, 11.7 v 6.1 months; P = .0001), time to treatment failure (median, 9.8 v 5.3 months; P = .0001), and duration of response (median, 11.7 v 5.7 months; P = .009). There was little difference in the number and severity of adverse events between the arms. Grade 3 to 4 neutropenia was seen more commonly with the combination (32%) than with docetaxel alone (22%), and there was a slightly higher incidence of febrile neutropenia in the combination arm (23% v 17%). One patient in the combination arm experienced symptomatic heart failure (1%). Another patient experienced symptomatic heart failure 5 months after discontinuation of trastuzumab because of disease progression, while being treated with an investigational anthracycline for 4 months. Conclusion: Trastuzumab combined with docetaxel is superior to docetaxel alone as first-line treatment of patients with HER2-positive MBC in terms of overall survival, response rate, response duration, time to progression, and time to treatment failure, with little additional toxicity. © 2005 by American Society of Clinical Oncology.

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Background The implementation of the Australian Consumer Law in 2011 highlighted the need for better use of injury data to improve the effectiveness and responsiveness of product safety (PS) initiatives. In the PS system, resources are allocated to different priority issues using risk assessment tools. The rapid exchange of information (RAPEX) tool to prioritise hazards, developed by the European Commission, is currently being adopted in Australia. Injury data is required as a basic input to the RAPEX tool in the risk assessment process. One of the challenges in utilising injury data in the PS system is the complexity of translating detailed clinical coded data into broad categories such as those used in the RAPEX tool. Aims This study aims to translate hospital burns data into a simplified format by mapping the International Statistical Classification of Disease and Related Health Problems (Tenth Revision) Australian Modification (ICD-10-AM) burn codes into RAPEX severity rankings, using these rankings to identify priority areas in childhood product-related burns data. Methods ICD-10-AM burn codes were mapped into four levels of severity using the RAPEX guide table by assigning rankings from 1-4, in order of increasing severity. RAPEX rankings were determined by the thickness and surface area of the burn (BSA) with information extracted from the fourth character of T20-T30 codes for burn thickness, and the fourth and fifth characters of T31 codes for the BSA. Following the mapping process, secondary data analysis of 2008-2010 Queensland Hospital Admitted Patient Data Collection (QHAPDC) paediatric data was conducted to identify priority areas in product-related burns. Results The application of RAPEX rankings in QHAPDC burn data showed approximately 70% of paediatric burns in Queensland hospitals were categorised under RAPEX levels 1 and 2, 25% under RAPEX 3 and 4, with the remaining 5% unclassifiable. In the PS system, prioritisations are made to issues categorised under RAPEX levels 3 and 4. Analysis of external cause codes within these levels showed that flammable materials (for children aged 10-15yo) and hot substances (for children aged <2yo) were the most frequently identified products. Discussion and conclusions The mapping of ICD-10-AM burn codes into RAPEX rankings showed a favourable degree of compatibility between both classification systems, suggesting that ICD-10-AM coded burn data can be simplified to more effectively support PS initiatives. Additionally, the secondary data analysis showed that only 25% of all admitted burn cases in Queensland were severe enough to trigger a PS response.

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Introduction and Aim: Sexual assaults commonly involve alcohol use by the perpetrator, victim, or both. Beliefs about alcohol’s effects may impact on people’s perceptions of and responses to men and women who have had such experiences while intoxicated from alcohol. This study aimed to develop an alcohol expectancy scale that captures young adults’ beliefs about alcohol’s role in sexual aggression and victimisation. Design and Methods: Based on pilot focus groups, an initial pool of 135 alcohol expectancy items was developed, checked for readability and face validity, and administered via a cross-sectional survey to 201 male and female university students (18-25 years). Items were specified in terms of three target drinkers: self, men, and women. In addition, a social desirability measure was included. Results: Principal Axis Factoring revealed a 4-factor solution for the targets men and women and a 5-factor solution for the target self with 72 items retained. Factors related to sexual coercion, sexual vulnerability, confidence, self-centredness, and negative cognitive and behavioural effects. Social desirability issues were evident for the target self, but not for the targets men and women. Discussion and Conclusions: Young adults link alcohol’s effects with sexual vulnerabilities via perceived risky cognitions and behaviours. Due to social desirability, these expectancies may be difficult to explicate for the self but may be accessible instead via other-oriented assessment. The Sexual Coercion and Vulnerability Alcohol Expectancy Scale has potential as a tool to elucidate the established tendency for observers to excuse intoxicated sexual perpetrators while blaming intoxicated victims.