384 resultados para Problem behaviours


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Objective This study highlights the serious consequences of ignoring reverse causality bias in studies on compensation-related factors and health outcomes and demonstrates a technique for resolving this problem of observational data. Study Design and Setting Data from an English longitudinal study on factors, including claims for compensation, associated with recovery from neck pain (whiplash) after rear-end collisions are used to demonstrate the potential for reverse causality bias. Although it is commonly believed that claiming compensation leads to worse recovery, it is also possible that poor recovery may lead to compensation claims—a point that is seldom considered and never addressed empirically. This pedagogical study compares the association between compensation claiming and recovery when reverse causality bias is ignored and when it is addressed, controlling for the same observable factors. Results When reverse causality is ignored, claimants appear to have a worse recovery than nonclaimants; however, when reverse causality bias is addressed, claiming compensation appears to have a beneficial effect on recovery, ceteris paribus. Conclusion To avert biased policy and judicial decisions that might inadvertently disadvantage people with compensable injuries, there is an urgent need for researchers to address reverse causality bias in studies on compensation-related factors and health.

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A number of online algorithms have been developed that have small additional loss (regret) compared to the best “shifting expert”. In this model, there is a set of experts and the comparator is the best partition of the trial sequence into a small number of segments, where the expert of smallest loss is chosen in each segment. The regret is typically defined for worst-case data / loss sequences. There has been a recent surge of interest in online algorithms that combine good worst-case guarantees with much improved performance on easy data. A practically relevant class of easy data is the case when the loss of each expert is iid and the best and second best experts have a gap between their mean loss. In the full information setting, the FlipFlop algorithm by De Rooij et al. (2014) combines the best of the iid optimal Follow-The-Leader (FL) and the worst-case-safe Hedge algorithms, whereas in the bandit information case SAO by Bubeck and Slivkins (2012) competes with the iid optimal UCB and the worst-case-safe EXP3. We ask the same question for the shifting expert problem. First, we ask what are the simple and efficient algorithms for the shifting experts problem when the loss sequence in each segment is iid with respect to a fixed but unknown distribution. Second, we ask how to efficiently unite the performance of such algorithms on easy data with worst-case robustness. A particular intriguing open problem is the case when the comparator shifts within a small subset of experts from a large set under the assumption that the losses in each segment are iid.

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Staffing rural and remote schools is an important policy issue for the public good. This paper examines the private issues it also poses for teachers with families working in these communities, as they seek to reconcile careers with educational choices for children. The paper first considers historical responses to staffing rural and remote schools in Australia, and the emergence of neoliberal policy encouraging marketisation of the education sector. We report on interviews about considerations motivating household mobility with 11 teachers across regional, rural and remote communities in Queensland. Like other middle-class parents, these teachers prioritised their children’s educational opportunities over career opportunities. The analysis demonstrates how teachers in rural and remote communities constitute a special group of educational consumers with insider knowledge and unique dilemmas around school choice. Their heightened anxieties around school choice under neoliberal policy are shown to contribute to the public issue of staffing rural and remote schools.

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Driver cognitions about aggressive driving of others are potentially important to the development of evidence-based interventions. Previous research has suggested that perceptions that other drivers are intentionally aggressive may influence recipient driver anger and subsequent aggressive responses. Accordingly, recent research on aggressive driving has attempted to distinguish between intentional and unintentional motives in relation to problem driving behaviours. This study assessed driver cognitive responses to common potentially provocative hypothetical driving scenarios to explore the role of attributions in driver aggression. A convenience sample of 315 general drivers 16–64 yrs (M = 34) completed a survey measuring trait aggression (Aggression Questionnaire AQ), driving anger (Driving Anger Scale, DAS), and a proxy measure of aggressive driving behaviour (Australian Propensity for Angry Driving AusPADS). Purpose designed items asked for drivers’ ‘most likely’ thought in response to AusPADS scenarios. Response options were equivalent to causal attributions about the other driver. Patterns in endorsements of attribution responses to the scenarios suggested that drivers tended to adopt a particular perception of the driving of others regardless of the depicted circumstances: a driving attributional style. No gender or age differences were found for attributional style. Significant differences were detected between attributional styles for driving anger and endorsement of aggressive responses to driving situations. Drivers who attributed the on-road event to the other being an incompetent or dangerous driver had significantly higher driving anger scores and endorsed significantly more aggressive driving responses than those drivers who attributed other driver’s behaviour to mistakes. In contrast, drivers who gave others the ‘benefit of the doubt’ endorsed significantly less aggressive driving responses than either of these other two groups, suggesting that this style is protective.

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Purpose To systematically review the Theory of Planned Behaviour studies predicting self-care intentions and behaviours in populations with and at-risk of diabetes. Methods A systematic review using six electronic databases was conducted in 2013. A standardised protocol was used for appraisal. Studies eligibility included a measure of behaviour for healthy eating, physical activity, glucose monitoring, medication use (ii) the TPB variables (iii) the TPB tested in populations with diabetes or at-risk. Results Sixteen studies were appraised for testing the utility of the TPB. Studies included cross-sectional (n=7); prospective (n=5) and randomised control trials (n=4). Intention (18% – 76%) was the most predictive construct for all behaviours. Explained variance for intentions were similar across cross-sectional (28 -76%); prospective (28 -73%); and RCT studies (18 - 63%). RCTs (18 - 43%) provided slightly stronger evidence for predicting behaviour. Conclusions Few studies tested predictability of the TPB in populations with or at-risk of diabetes. This review highlighted differences in the predictive utility of the TPB suggesting that the model is behaviour and population specific. Findings on key determinants of specific behaviours contribute to a better understanding of mechanisms of behaviour change and are useful in designing targeted behavioural interventions for different diabetes populations.

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Unlicensed driving remains a serious problem for road safety, despite ongoing improvements in traffic law enforcement practices and technology. While it does not play a direct causative role in road crashes, unlicensed driving undermines the integrity of the driver licensing system and is associated with a range of high-risk behaviours. This report examines official road crash data from Queensland for the years 2003-08 to compare the crash involvement patterns of unlicensed drivers with those of licensed drivers and explore the scope and nature of unlicensed driving. This study replicates and extends upon two previous studies examining the involvement of unlicensed drivers in crashes in Queensland (Watson, 2004a; 2004b; Watson & Steinhardt, 2006).

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Unlicensed driving is a serious problem in many countries, despite ongoing improvements in traffic law enforcement practices and technology. Unlike alcohol impairment and speeding, unlicensed driving does not play a direct causative role in road crashes. However it represents a major problem for road safety in two respects. Firstly, it undermines the effectiveness of driver licensing systems by preventing the allocation of demerit points and reducing the impact of licence loss (Watson, 2004b). Secondly, there is a growing body of evidence linking unlicensed driving to a cluster of high-risk behaviours including drink driving, speeding, failure to wear seat belts and motorcycle use (Griffin & DeLaZerda, 2000; Harrison, 1997; Watson, 1997, 2004b). Consistent with this, utilising the quasi-induced exposure method, Watson (2004a) estimated that in Queensland, unlicensed drivers were almost three times more likely to be involved in a reported crash than licensed drivers.

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Unlicensed driving remains a serious problem for road safety, despite ongoing improvements in traffic law enforcement practices and technology. While it does not play a direct causative role in road crashes, unlicensed driving undermines the integrity of the driver licensing system and is associated with a range of high-risk behaviours. The Queensland Transport and Main Roads (TMR) commissioned a program of research with separate components relating to different aspects of unlicensed driving. Drawing on Australian and international studies, the Unlicensed and Unregistered Vehicle (UUV) project explores the nature of unlicensed driving in Queensland, consolidates the available research evidence and identifies gaps in current knowledge relating to the driving behaviours of unlicensed drivers.

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Background Child sexual abuse is a significant global problem in both magnitude and sequelae. The most widely used primary prevention strategy has been the provision of school-based education programmes. Although programmes have been taught in schools since the 1980s, their effectiveness requires ongoing scrutiny. Objectives To systematically assess evidence of the effectiveness of school-based education programmes for the prevention of child sexual abuse. Specifically, to assess whether: programmes are effective in improving students’ protective behaviours and knowledge about sexual abuse prevention; behaviours and skills are retained over time; and participation results in disclosures of sexual abuse, produces harms, or both. Search methods In September 2014, we searched CENTRAL, OvidMEDLINE, EMBASE and 11 other databases.We also searched two trials registers and screened the reference lists of previous reviews for additional trials. Selection criteria We selected randomised controlled trials (RCTs), cluster-RCTs, and quasi-RCTs of school-based education interventions for the prevention of child sexual abuse compared with another intervention or no intervention. Data collection and analysis Two review authors independently assessed the eligibility of trials for inclusion, extracted data, and assessed risk of bias.We summarised data for six outcomes: protective behaviours; knowledge of sexual abuse or sexual abuse prevention concepts; retention of protective behaviours over time; retention of knowledge over time; harm; and disclosures of sexual abuse. School-

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Guaranteeing Quality of Service (QoS) with minimum computation cost is the most important objective of cloud-based MapReduce computations. Minimizing the total computation cost of cloud-based MapReduce computations is done through MapReduce placement optimization. MapReduce placement optimization approaches can be classified into two categories: homogeneous MapReduce placement optimization and heterogeneous MapReduce placement optimization. It is generally believed that heterogeneous MapReduce placement optimization is more effective than homogeneous MapReduce placement optimization in reducing the total running cost of cloud-based MapReduce computations. This paper proposes a new approach to the heterogeneous MapReduce placement optimization problem. In this new approach, the heterogeneous MapReduce placement optimization problem is transformed into a constrained combinatorial optimization problem and is solved by an innovative constructive algorithm. Experimental results show that the running cost of the cloud-based MapReduce computation platform using this new approach is 24:3%-44:0% lower than that using the most popular homogeneous MapReduce placement approach, and 2:0%-36:2% lower than that using the heterogeneous MapReduce placement approach not considering the spare resources from the existing MapReduce computations. The experimental results have also demonstrated the good scalability of this new approach.

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Trade union membership, both in aggregate numbers and in density, has declined in the majority of advanced economies globally over recent decades (Blanchflower, 2007). In Australia, the decline in the 1990s was somewhat more precipitate than in most countries (Peetz, 1998). As discussed in Chapter 1, reasons for the decline are multifactorial, including a more hostile environment to unionism created by employers and the state, difficulties ·with workplace union organisation, and structural change in the economy (Bryson and Gomez, 2005; Bryson et a!., 2011; Ebbinghaus et al., 2011; Payne, 1989; Waddington and Kerr, 2002; Waddington and Whitson, 1997). Our purpose in this chapter is to look beyond aggregate Australian union density data, to examine how age relates to membership decline, and how different age groups, particularly younger workers, are located in the story of union decline. The practical implications of this research are that understanding how unions relate to workers of different age groups, and to workers of different genders amongst those age groups, may lead to improved recruitment and better union organisation.

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Background The overrepresentation of young drivers in road crashes, injuries and fatalities around the world has resulted in a breadth of injury prevention efforts including education, enforcement, engineering, and exposure control. Despite multifaceted intervention, the young driver problem remains a challenge for injury prevention researchers, practitioners and policy-makers. The intractable nature of young driver crash risks suggests that a deeper understanding of their car use – that is, the purpose of their driving – is required to inform the design of more effective young driver countermeasures. Aims This research examined the driving purpose reported by young drivers, including the relationship with self-reported risky driving behaviours including offences. Methods Young drivers with a Learner or Provisional licence participated in three online surveys (N1 = 656, 17–20 years; N2 = 1051, 17–20 years; N3 = 351, 17–21 years) as part of a larger state-wide project in Queensland, Australia. Results A driving purpose scale was developed (the PsychoSocial Purpose Driving Scale, PSPDS), revealing that young drivers drove for psychosocial reasons such as for a sense of freedom and to feel independent. Drivers who reported the greatest psychosocial purpose for driving were more likely to be male and to report more risky driving behaviours such as speeding. Drivers who deliberately avoided on-road police presence and reported a prior driving-related offence had significantly greater PSPDS scores, and higher reporting of psychosocial driving purposes was found over time as drivers transitioned from the supervised Learner licence phase to the independent Provisional (intermediate) licence phase. Discussion and conclusions The psychosocial needs met by driving suggest that effective intervention to prevent young driver injury requires further consideration of their driving purpose. Enforcement, education, and engineering efforts which consider the psychosocial purpose of the driving are likely to be more efficacious than those which presently do not. Road safety countermeasures could reduce the young driver’s exposure to risk through such mechanisms as encouraging the use of public transport.

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Particle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method based on the social behaviors of birds flocking or fish schooling. Although, PSO is represented in solving many well-known numerical test problems, but it suffers from the premature convergence. A number of basic variations have been developed due to solve the premature convergence problem and improve quality of solution founded by the PSO. This study presents a comprehensive survey of the various PSO-based algorithms. As part of this survey, the authors have included a classification of the approaches and they have identify the main features of each proposal. In the last part of the study, some of the topics within this field that are considered as promising areas of future research are listed.

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As China continues to motorise rapidly, solutions are needed to reduce the burden of road trauma that is spread inequitably across the community. Little is currently known about how new drivers are trained to deal with on-road challenges, and little is also known about the perceptions, behaviours and attitudes of road users in China. This paper reports on a pilot study conducted in a driver retraining facility in one Chinese city where people who have had their licence suspended for accrual of 12 demerit points in a one year period must attend compulsory retraining in order to regain their licence. A sample of 239 suspended drivers responded to an anonymous questionnaire that sought information about preferred driving speeds and perceptions of safe driving speeds across two speed zones. Responses indicated that speeds higher than the posted limits were commonly reported, and that there was incongruence between preferred and safe speeds, such that a greater proportion of drivers reported preferred speeds that were substantially faster than what were reported as safe speeds. Participants with more driving experience reported significantly fewer crashes than newly licensed drivers (less than 2 years licensed) but no differences were found in offences when compared across groups with different levels of driving experience. Perceptions of risky behaviours were assessed by asking participants to describe what they considered to be the most dangerous on-road behaviours. Speeding and drink driving were the most commonly reported by far, followed by issues such as fatigue, ignoring traffic rules, not obeying traffic rules, phone use while driving, and non-use of seatbelts, which attracted an extremely low response which seems consistent with previously reported low belt wearing rates, unfavourable attitudes towards seatbelt use, and low levels of enforcement. Finally, observations about culturally specific considerations are made from previous research conducted by the authors and others. Specifically, issues of saving face and the importance and pervasiveness of social networks and social influence are discussed with particular regard to how any future countermeasures need to be informed by a thorough understanding of Chinese customs and culture.

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The number of pedestrian victims at Australian and foreign level crossings has remained stable over the past decade and it continues to be a significant problem. To examine the factors contributing to pedestrians’ unsafe crossing behaviours, direct observations were conducted at three black spot urban level crossings in Brisbane for a total of 45 h during morning and afternoon peak. In total, 129 pedestrians transgressed the active controls. More transgressions were observed at the crossings located in more populated suburbs in close proximity to large shopping centres and school zones, whereas the smallest number of transgressions were observed at the least populated locations. In addition to characteristics associated with the larger socio-economic area, the patterns of transgression could be associated with the properties of the existing safety equipment and the design of each level crossing (i.e. location of the platforms, number of rail tracks). Indeed, the largest number of crossed unoccupied but “at risk” rail tracks (where a train could have passed), was observed at the crossing with the least transgressions. Contrary to previous findings, younger adults were the most frequent transgressors. School children and elderly were most likely to transgress in groups. Potential directions for future research and more effective measures are discussed.