The effect of previous hamstring strain injuries on the change in eccentric hamstring strength during preseason training in elite Australian footballers

Background Hamstring strain injuries (HSIs) are the most common injury type in Australian football and the rate of recurrence has been consistently high for a number of years. Long lasting neuromuscular inhibition has been noted in previously injured athletes but it is not known if this influences athletes adaptive response to training. Purpose To determine if elite Australian footballers with a prior unilateral HSI (previously injured group) display lesser improvements in eccentric hamstring strength during pre-season training compared to athletes without a history of HSI (control group). Study design Prospective cohort study. Methods Ninety-nine elite Australian footballers participated (17 with a history of unilateral HSI in the previous 12 month period). Eccentric hamstring strength was assessed at the start and end of pre-season training using an instrumented Nordic hamstring device. Change in eccentric strength across preseason was determine in absolute terms and normalised to start of preseason strength. Start of preseason strength was used as a covariate to control for differences in starting strength. Results The left and right limbs in the control group showed no difference in absolute or relative change (left limb absolute change, 60.7±72.9N; relative change, 1.28±0.34; right limb absolute change, 48.6±83.8N; relative change, 1.24±0.43) . Similarly, the injured and uninjured limbs from the previously injured group showed no difference for either absolute or relative measures of change (injured limb absolute change, 13.1±57.7N; relative change, 1.07±0.18; uninjured limb absolute change, 14.7±54.0N; relative change, 1.07±0.22N). The previously injured group displayed a significantly lesser increase in eccentric hamstring strength across the preseason (absolute change, 13.9±55.0; relative change, 1.07±0.20) compared to the control group (absolute change, 54.6±78.5; relative change, 1.26±0.39) for both absolute and relative measures (p < 0.001), even after controlling for differences in start of pre-season eccentric hamstring strength, which had a significant effect on strength improvement. Conclusion Elite Australian footballers with a unilateral HSI history displayed lesser improvements in eccentric hamstring strength across preseason training. The smaller improvements were not restricted to the previously injured limb as the contralateral limb also displayed similarly small improvements in eccentric strength. Whether this is the cause of or the result of injury remains to be seen, but it has the potential to contribute to the risk of hamstring strain re-injury.

Fuzzy logic to evaluate driving maneuvers: An integrated approach to improve training

Driver training is one of the interventions aimed at mitigating the number of crashes that involve novice drivers. Our failure to understand what is really important for learners, in terms of risky driving, is one of the many drawbacks restraining us to build better training programs. Currently, there is a need to develop and evaluate Advanced Driving Assistance Systems that could comprehensively assess driving competencies. The aim of this paper is to present a novel Intelligent Driver Training System (IDTS) that analyses crash risks for a given driving situation, providing avenues for improvement and personalisation of driver training programs. The analysis takes into account numerous variables acquired synchronously from the Driver, the Vehicle and the Environment (DVE). The system then segments out the manoeuvres within a drive. This paper further presents the usage of fuzzy set theory to develop the safety inference rules for each manoeuvre executed during the drive. This paper presents a framework and its associated prototype that can be used to comprehensively view and assess complex driving manoeuvres and then provide a comprehensive analysis of the drive used to give feedback to novice drivers.

‘Healthy mobile check-ins’ study: using GIS in smartphones to track use of urban environment by survivors of endometrial cancer

Aims/Objectives Our study aims to test the capacity of a newly developed smartphone innovation to obtain data on social, structural, and spatial determinants of the daily health-related behaviours of women living in urban Brisbane neighbourhoods who have survived endometrial cancer. Methods The women used a mobile web app designed specifically for the project to record GIS/location data on every destination they visited within their local urban neighbourhoods over a two-week period. Additionally, we gathered textual data on the social context/reasons for travel, as well as mode of transport to reach these destinations. The data was transported to SPSS and Google Earth for statistical and spatial analysis. We then met with the women to discuss lifestyle interventions to maximise their use of their local neighbourhoods in ways that could increase their physical activity levels and improve their overall health and well-being. These interventions will be evaluated and translated into a large-scale national study if effective. Results Initial findings about patterns in the group’s use of the local urban environment will be displayed, including daily distances travelled, types of locations visited, walking levels, use of public transport, use of green spaces and use of health-related resources. Any socio-demograpahic differences found between the women will be reported. Qualitative, quantitative, and spatial/mapping data will be displayed Conclusion The benefits and limitations of the mobile website designed to collect a range of data types about human-neighbourhood interactions with implications for intervention design will be discussed.

Using Bayesian Mixture Models That Combine Expert Knowledge and GIS Data to Define Ecoregions

Conservation planning and management programs typically assume relatively homogeneous ecological landscapes. Such “ecoregions” serve multiple purposes: they support assessments of competing environmental values, reveal priorities for allocating scarce resources, and guide effective on-ground actions such as the acquisition of a protected area and habitat restoration. Ecoregions have evolved from a history of organism–environment interactions, and are delineated at the scale or level of detail required to support planning. Depending on the delineation method, scale, or purpose, they have been described as provinces, zones, systems, land units, classes, facets, domains, subregions, and ecological, biological, biogeographical, or environmental regions. In each case, they are essential to the development of conservation strategies and are embedded in government policies at multiple scales.

The ethical intricacies of injury rehabilitation within a dance training context

Exploring the ethical issues present in professional practice within the field of sport, exercise and performance psychology, this case study outlines challenges that may be encountered, ways to address issues should they arise, and the overall ethical considerations of supporting injury rehabilitation within a dance training context.

Proactive training system for safe and efficient precast installation

The construction industry is a crucial component of the Hong Kong economy, and the safety and efficiency of workers are two of its main concerns. The current approach to training workers relies primarily on instilling practice and experience in conventional teacher-apprentice settings on and off site. Both have their limitations however, on-site training is very inefficient and interferes with progress on site, while off-site training provides little opportunity to develop the practical skills and awareness needed through hands-on experience. A more effective way is to train workers in safety awareness and efficient working by current novel information technologies. This paper describes a new and innovative prototype system – the Proactive Construction Management System (PCMS) – to train precast installation workers to be highly productive while being fully aware of the hazards involved. PCMS uses Chirp-Spread-Spectrum-based (CSS) real-time location technology and Unity3D-based data visualisation technology to track construction resources (people, equipment, materials, etc.) and provide real-time feedback and post-event visualisation analysis in a training environment. A trial of a precast facade installation on a real site demonstrates the benefits gained by PCMS in comparison with equivalent training using conventional methods. It is concluded that, although the study is based on specific industrial conditions found in Hong Kong construction projects, PCMS may well attract wider interest and use in future.

The protective mechanisms of first aid training within a school-based program for early adolescents

This thesis was concerned with the protective mechanisms of first aid training in the context of peer support. Using a randomised control trial design the current program of research explores first aid training in the school setting and identifies the key components of effective school-based first aid training programs. In particular, examining whether first aid training and associated knowledge could be protective for early adolescents. This broader framing considered whether first aid impacted on increasing behaviour and attitudes towards helping an injured friend, and reducing personal risk taking and related injury.

Regressive measures won’t help youth into work or training

The 2014 federal budget implemented a so-called crackdown on what Minister for Social Services Kevin Andrews calls young people who are content to “sit on the couch at home and pick up a welfare cheque”. The crackdown will change access to income support for people under 30 years of age. From January 1 2015, all young people seeking Newstart Allowance and Youth Allowance for the first time will be required to “demonstrate appropriate job search and participation in employment services support for six months before receiving payments”. Upon qualifying, recipients must then spend 25 hours per week in Work for the Dole in order to receive income support for a six-month period. What happens beyond this six months is unclear. What is clear is that these policy changes, together with the Minister’s accompanying statements, are informed by a deficit view of disadvantaged youth. It is a view that demonstrates how little politicians know or understand about these young peoples’ past circumstances.

How do experts think about statistics? Hints for improving undergraduate and postgraduate training

Experts are increasingly being called upon to quantify their knowledge, particularly in situations where data is not yet available or of limited relevance. In many cases this involves asking experts to estimate probabilities. For example experts, in ecology or related fields, might be called upon to estimate probabilities of incidence or abundance of species, and how they relate to environmental factors. Although many ecologists undergo some training in statistics at undergraduate and postgraduate levels, this does not necessarily focus on interpretations of probabilities. More accurate elicitation can be obtained by training experts prior to elicitation, and if necessary tailoring elicitation to address the expert’s strengths and weaknesses. Here we address the first step of diagnosing conceptual understanding of probabilities. We refer to the psychological literature which identifies several common biases or fallacies that arise during elicitation. These form the basis for developing a diagnostic questionnaire, as a tool for supporting accurate elicitation, particularly when several experts or elicitors are involved. We report on a qualitative assessment of results from a pilot of this questionnaire. These results raise several implications for training experts, not only prior to elicitation, but more strategically by targeting them whilst still undergraduate or postgraduate students.

The QUT Training Model for Peer Leader Capacity Building

QUT has enacted a university-wide Peer Program’s Strategy which aims to improve student success and graduate outcomes. A component of this strategy is a training model providing relevant, quality-assured and timely training for all students who take on leadership roles. The training model is designed to meet the needs of the growing scale and variety of peer programs, and to recognise the multiple roles and programs in which students may be involved during their peer leader journey. The model builds peer leader capacity by offering centralised, beginning and ongoing training modules, delivered by in-house providers, covering topics which prepare students to perform their role safely, inclusively, accountably and skilfully. The model also provides efficiencies by differentiating between ‘core competency' and ‘program-specific’ modules, thus avoiding training duplication across multiple programs, and enabling training to be individually and flexibly formatted to suit the specific and unique needs of each program.

Centroid training to achieve effective text classification

Traditional text classification technology based on machine learning and data mining techniques has made a big progress. However, it is still a big problem on how to draw an exact decision boundary between relevant and irrelevant objects in binary classification due to much uncertainty produced in the process of the traditional algorithms. The proposed model CTTC (Centroid Training for Text Classification) aims to build an uncertainty boundary to absorb as many indeterminate objects as possible so as to elevate the certainty of the relevant and irrelevant groups through the centroid clustering and training process. The clustering starts from the two training subsets labelled as relevant or irrelevant respectively to create two principal centroid vectors by which all the training samples are further separated into three groups: POS, NEG and BND, with all the indeterminate objects absorbed into the uncertain decision boundary BND. Two pairs of centroid vectors are proposed to be trained and optimized through the subsequent iterative multi-learning process, all of which are proposed to collaboratively help predict the polarities of the incoming objects thereafter. For the assessment of the proposed model, F1 and Accuracy have been chosen as the key evaluation measures. We stress the F1 measure because it can display the overall performance improvement of the final classifier better than Accuracy. A large number of experiments have been completed using the proposed model on the Reuters Corpus Volume 1 (RCV1) which is important standard dataset in the field. The experiment results show that the proposed model has significantly improved the binary text classification performance in both F1 and Accuracy compared with three other influential baseline models.