An evidence-based program to improve analgesic practice and pain outcomes in residential aged care facilities

Pain is common in individuals living in residential aged care facilities (RACFs), and a number of obstacles have been identified as recurring barriers to adequate pain management. To address this, the Australian Pain Society developed 27 recommendations for comprehensive good practice in the identification, assessment, and management of pain. This study reviewed preexisting pain management practice at five Australian RACFs and identified changes needed to implement the recommendations and then implemented an evidence-based program that aimed to facilitate better pain management. The program involved staff training and education and revised in-house pain-management procedures. Reviews occurred before and after the program and included the assessment of 282 residents for analgesic use and pain status. Analgesic use improved after the program (P<.001), with a decrease in residents receiving no analgesics (from 15% to 6%) and an increase in residents receiving around-the-clock plus as-needed analgesics (from 24% to 43%). There were improvements in pain relief for residents with scores indicative of pain, with Abbey pain scale (P=.005), Pain Assessment in Advanced Dementia Scale (P=.001), and Non-communicative Patient's Pain Assessment Instrument scale (P<.001) scores all improving. Although physical function declined as expected, Medical Outcomes Study 36-item Short-Form Survey bodily pain scores also showed improvement (P=.001). Better evidence-based practice and outcomes in RACFs can be achieved with appropriate training and education. Investing resources in the aged care workforce using this program improved analgesic practice and pain relief in participating sites. Further attention to the continued targeted pain management training of aged care staff is likely to improve pain-focused care for residents.

Learning-based Relevance Feedback for Web-based Relation Completion

In a pilot application based on web search engine calledWeb-based Relation Completion (WebRC), we propose to join two columns of entities linked by a predefined relation by mining knowledge from the web through a web search engine. To achieve this, a novel retrieval task Relation Query Expansion (RelQE) is modelled: given an entity (query), the task is to retrieve documents containing entities in predefined relation to the given one. Solving this problem entails expanding the query before submitting it to a web search engine to ensure that mostly documents containing the linked entity are returned in the top K search results. In this paper, we propose a novel Learning-based Relevance Feedback (LRF) approach to solve this retrieval task. Expansion terms are learned from training pairs of entities linked by the predefined relation and applied to new entity-queries to find entities linked by the same relation. After describing the approach, we present experimental results on real-world web data collections, which show that the LRF approach always improves the precision of top-ranked search results to up to 8.6 times the baseline. Using LRF, WebRC also shows performances way above the baseline.

An MRF based abnormal event detection approach using motion and appearance features

Abnormal event detection has attracted a lot of attention in the computer vision research community during recent years due to the increased focus on automated surveillance systems to improve security in public places. Due to the scarcity of training data and the definition of an abnormality being dependent on context, abnormal event detection is generally formulated as a data-driven approach where activities are modeled in an unsupervised fashion during the training phase. In this work, we use a Gaussian mixture model (GMM) to cluster the activities during the training phase, and propose a Gaussian mixture model based Markov random field (GMM-MRF) to estimate the likelihood scores of new videos in the testing phase. Further-more, we propose two new features: optical acceleration, and the histogram of optical flow gradients; to detect the presence of any abnormal objects and speed violations in the scene. We show that our proposed method outperforms other state of the art abnormal event detection algorithms on publicly available UCSD dataset.

Towards Vision-Based Pose- and Condition-Invariant Place Recognition along Routes

Vision-based place recognition involves recognising familiar places despite changes in environmental conditions or camera viewpoint (pose). Existing training-free methods exhibit excellent invariance to either of these challenges, but not both simultaneously. In this paper, we present a technique for condition-invariant place recognition across large lateral platform pose variance for vehicles or robots travelling along routes. Our approach combines sideways facing cameras with a new multi-scale image comparison technique that generates synthetic views for input into the condition-invariant Sequence Matching Across Route Traversals (SMART) algorithm. We evaluate the system’s performance on multi-lane roads in two different environments across day-night cycles. In the extreme case of day-night place recognition across the entire width of a four-lane-plus-median-strip highway, we demonstrate performance of up to 44% recall at 100% precision, where current state-of-the-art fails.

The OnTrack Diabetes web-based program for type 2 diabetes and dysphoria self-management: A randomized controlled trial protocol

Background: The prevalence of type 2 diabetes is rising with the majority of patients practicing inadequate disease self-management. Depression, anxiety, and diabetes-specific distress present motivational challenges to adequate self-care. Health systems globally struggle to deliver routine services that are accessible to the entire population, in particular in rural areas. Web-based diabetes self-management interventions can provide frequent, accessible support regardless of time and location Objective: This paper describes the protocol of an Australian national randomized controlled trial (RCT) of the OnTrack Diabetes program, an automated, interactive, self-guided Web program aimed to improve glycemic control, diabetes self-care, and dysphoria symptoms in type 2 diabetes patients. Methods: A small pilot trial is conducted that primarily tests program functionality, efficacy, and user acceptability and satisfaction. This is followed by the main RCT, which compares 3 treatments: (1) delayed program access: usual diabetes care for 3 months postbaseline followed by access to the full OnTrack Diabetes program; (2) immediate program: full access to the self-guided program from baseline onward; and (3) immediate program plus therapist support via Functional Imagery Training (FIT). Measures are administered at baseline and at 3, 6, and 12 months postbaseline. Primary outcomes are diabetes self-care behaviors (physical activity participation, diet, medication adherence, and blood glucose monitoring), glycated hemoglobin A1c (HbA1c) level, and diabetes-specific distress. Secondary outcomes are depression, anxiety, self-efficacy and adherence, and quality of life. Exposure data in terms of program uptake, use, time on each page, and program completion, as well as implementation feasibility will be conducted. Results: This trial is currently underway with funding support from the Wesley Research Institute in Brisbane, Australia. Conclusions: This is the first known trial of an automated, self-guided, Web-based support program that uses a holistic approach in targeting both type 2 diabetes self-management and dysphoria. Findings will inform the feasibility of implementing such a program on an ongoing basis, including in rural and regional locations.

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.

Using a theory of planned behaviour framework to explore hand hygiene beliefs at the ‘5 critical moments’ among Australian hospital-based nurses

Background Improving hand hygiene among health care workers (HCWs) is the single most effective intervention to reduce health care associated infections in hospitals. Understanding the cognitive determinants of hand hygiene decisions for HCWs with the greatest patient contact (nurses) is essential to improve compliance. The aim of this study was to explore hospital-based nurses’ beliefs associated with performing hand hygiene guided by the World Health Organization’s (WHO) 5 critical moments. Using the belief-base framework of the Theory of Planned Behaviour, we examined attitudinal, normative, and control beliefs underpinning nurses’ decisions to perform hand hygiene according to the recently implemented national guidelines. Methods Thematic content analysis of qualitative data from focus group discussions with hospital-based registered nurses from 5 wards across 3 hospitals in Queensland, Australia. Results Important advantages (protection of patient and self), disadvantages (time, hand damage), referents (supportive: patients, colleagues; unsupportive: some doctors), barriers (being too busy, emergency situations), and facilitators (accessibility of sinks/products, training, reminders) were identified. There was some equivocation regarding the relative importance of hand washing following contact with patient surroundings. Conclusions The belief base of the theory of planned behaviour provided a useful framework to explore systematically the underlying beliefs of nurses’ hand hygiene decisions according to the 5 critical moments, allowing comparisons with previous belief studies. A commitment to improve nurses’ hand hygiene practice across the 5 moments should focus on individual strategies to combat distraction from other duties, peer-based initiatives to foster a sense of shared responsibility, and management-driven solutions to tackle staffing and resource issues. Hand hygiene following touching a patient’s surroundings continues to be reported as the most neglected opportunity for compliance.

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.

Emergency pre-hospital disaster response training. What's the state of play?

Study/Objective This study examines the current state of disaster response education for Australian paramedics from a national and international perspective and identifies both potential gaps in content and challenges to the sustainability of knowledge acquired through occasional training. Background As demands for domestic and international disaster response increase, experience in the field has begun to challenge traditional assumptions that response to mass casualty events requires little specialist training. The need for a “streamlined process of safe medical team deployment into disaster regions”1 is generally accepted and, in Australia, the emergence of national humanitarian aid training has begun to respond to this gap. However, calls for a national framework for disaster health education2 haven’t received much traction. Methods A critical analysis of the peer reviewed and grey literature on the core components/competencies and training methods required to prepare Australian paramedics to contribute to effective health disaster response has been conducted. Research from the past 10 years has been examined along with federal and state policy with regard to paramedic disaster education. Results The literature shows that education and training for disaster response is variable and that an evidence based study specifically designed to outline sets of core competencies for Australian health care professionals has never been undertaken. While such competencies in disaster response have been developed for the American paradigm it is suggested that disaster response within the Australian context is somewhat different to that of the US, and therefore a gap in the current knowledge base exists. Conclusion Further research is needed to develop core competencies specific to Australian paramedics in order to standardise teaching in the area of health disaster management. Until this occurs the task of evaluating or creating disaster curricula that adequately prepares and maintains paramedics for an effective all hazards disaster response is seen as largely unattainable.

An application of fuzzy DL-Based semantic perception to soil container classification

Semantic perception and object labeling are key requirements for robots interacting with objects on a higher level. Symbolic annotation of objects allows the usage of planning algorithms for object interaction, for instance in a typical fetchand-carry scenario. In current research, perception is usually based on 3D scene reconstruction and geometric model matching, where trained features are matched with a 3D sample point cloud. In this work we propose a semantic perception method which is based on spatio-semantic features. These features are defined in a natural, symbolic way, such as geometry and spatial relation. In contrast to point-based model matching methods, a spatial ontology is used where objects are rather described how they "look like", similar to how a human would described unknown objects to another person. A fuzzy based reasoning approach matches perceivable features with a spatial ontology of the objects. The approach provides a method which is able to deal with senor noise and occlusions. Another advantage is that no training phase is needed in order to learn object features. The use-case of the proposed method is the detection of soil sample containers in an outdoor environment which have to be collected by a mobile robot. The approach is verified using real world experiments.

Investigating in-domain data requirements for PLDA training

This paper analyzes the limitations upon the amount of in- domain (NIST SREs) data required for training a probabilistic linear discriminant analysis (PLDA) speaker verification system based on out-domain (Switchboard) total variability subspaces. By limiting the number of speakers, the number of sessions per speaker and the length of active speech per session available in the target domain for PLDA training, we investigated the relative effect of these three parameters on PLDA speaker verification performance in the NIST 2008 and NIST 2010 speaker recognition evaluation datasets. Experimental results indicate that while these parameters depend highly on each other, to beat out-domain PLDA training, more than 10 seconds of active speech should be available for at least 4 sessions/speaker for a minimum of 800 speakers. If further data is available, considerable improvement can be made over solely out-domain PLDA training.

Specialist nursing training in Poland: Applications for neuroscience nursing

Background: Nurses have a pivotal role in providing, facilitating, advocating and promoting the best possible care and outcome for the client. To ensure decisions and actions are based on current standards of practice, nurses must be accountable for participation in ongoing education in their area of practice. Aim: To present a description of the current state of Polish nursing education and specialized model for neurological and neurosurgical nursing that can be utilized for both undergraduate and postgraduate continuing education in Poland. Data sources: The model of postgraduate training introduced in Poland in 2000 was taken into consideration in developing the framework for neuroscience nursing postgraduate continuing education presented here. The framework for neurological continuing education is also based on a review of the literature and is consistent with Poland’s legally binding professional nursing regulations (normative and implementing regulations). Conclusion: The model demonstrates the need for the content of pre- and post-undergraduate degree education in neurological nursing to be graduated, based on the frameworks for undergraduate education (acquiring the knowledge and basic skills for performing the work of nurses) and postgraduate education (acquiring knowledge and specialist skills necessary for providing advanced nursing care including medical acts on patients with nervous system diseases). Implications for nursing: New and advanced skills gained in specialization training can be applied to complex functions, roles and professional tasks undertaken by nurses in relation to care of patients with neurological dysfunctions.

Report: The Canadian Best Practices Educational Toolkits: Translating evidence-based stroke recommendations into practical implementation resources

The Canadian Best Practice Recommendations for Stroke Care are intended to reduce variations in stroke care and facilitate closure of the gap between evidence and practice (Lindsay et al., 2010). The publication of best practice recommendations is only the beginning of this process. The guidelines themselves are not sufficient to change practice and increase consistency in care. Therefore, a key objective of the Canadian Stroke Network (CSN) Best Practices Working Group (BPWG) is to encourage and facilitate ongoing professional development and training for health care professionals providing stroke care. This is addressed through a multi-factorial approach to the creation and dissemination of inter-professional implementation tools and resources. The resources developed by CSN span pre-professional education, ongoing professional development, patient education and may be used to inform systems change. With a focus on knowledge translation, several inter-professional point-of-care tools have been developed by the CSN in collaboration with numerous professional organizations and expert volunteers. These resources are used to facilitate awareness, understanding and applications of evidence-based care across stroke care settings. Similar resources are also developed specifically for stroke patients, their families and informal caregivers, and the general public. With each update of the Canadian Best Practice Recommendations for Stroke Care, the BPWG and topic-specific writing groups propose priority areas for ongoing resource development. In 2010, two of these major educational initiatives were undertaken and recently completed—one to support continuing education for health care professionals regarding secondary stroke prevention and the other to educate families, informal caregivers and the public about pediatric stroke. This paper presents an overview of these two resources, and we encourage health care professionals to integrate these into their personal learning plans and tool kits for patients.

Small firm training: Just meeting the day-to-day needs of the business

Purpose The purpose of this paper is to explore what the attitudes of small firm owner-managers are to developing the skills of their key resources and then examine how these and other factors affect owner-managers’ preferences for training these employees. Design/methodology/approach This study of training in small road transport firms in West Australia is cast in light of the literature on human resource management in small firms underpinned by insights drawn using the resource based view of the firm. Small firms (less than 20 people) dominate this industry, while the increasing freight task, and extreme distances between West Australian ports, towns and mines highlight this sectors’ importance. Survey results from 39 small road transport firms and interviews with nine owner-managers are analysed. Findings Legislative, regulatory and licensing requirements were shown to be a key determinant of skills development. Employers ensured that basic standards for employee certification and qualification were met, as the penalty for not doing so would be too high. Regulations drove the need for certain types of training – licenses, fatigue management, occupational health and safety, handling dangerous goods, the Maritime Security Identification Card card, forklift license, mine site inductions – while owner-managers knew where to get the training their staff needed. Although regulation appeared most visible in prescribing what happened in relation to training for drivers, the relevance of owner-managers’ attitudes could not be ignored, nor could conditions in the firms external environment as this shaped how these requirements were met. Research limitations/implications The RBV is useful in showing how skill development enabled similarity in skills across firms, while the attitudes owner-managers and economic and social conditions meant what happened in firms around skill development varied. The importance of small firm owner-managers’ attitudes are clearly highlighted and shown to influence organizational decisions and choices around training, but these were not independent of the regulatory framework and the economic and social conditions within which the firm operated. The small firms in this study did engage workers in formal training when necessary but it was put in the context of the idiosyncratic approach of the owner-manager and the day-to-day needs of the firm. “Training” was essentially about ensuring certain types of skills were held by employees and then passing on knowledge to ensure the behavior of employees was consistent with the owner-manager’s vision for the firm in its current environment. Originality/value Ways industry and government can encourage training activity that goes beyond the day-to-day firm needs are suggested.

Effects of resistance training on measures of muscular strength in people with Parkinson’s disease: A systematic review and meta-analysis

Objective The aim of this systematic review and meta-analysis was to determine the overall effect of resistance training (RT) on measures of muscular strength in people with Parkinson’s disease (PD). Methods Controlled trials with parallel-group-design were identified from computerized literature searching and citation tracking performed until August 2014. Two reviewers independently screened for eligibility and assessed the quality of the studies using the Cochrane risk-of-bias-tool. For each study, mean differences (MD) or standardized mean differences (SMD) and 95% confidence intervals (CI) were calculated for continuous outcomes based on between-group comparisons using post-intervention data. Subgroup analysis was conducted based on differences in study design. Results Nine studies met the inclusion criteria; all had a moderate to high risk of bias. Pooled data showed that knee extension, knee flexion and leg press strength were significantly greater in PD patients who undertook RT compared to control groups with or without interventions. Subgroups were: RT vs. control-without-intervention, RT vs. control-with-intervention, RT-with-other-form-of-exercise vs. control-without-intervention, RT-with-other-form-of-exercise vs. control-with-intervention. Pooled subgroup analysis showed that RT combined with aerobic/balance/stretching exercise resulted in significantly greater knee extension, knee flexion and leg press strength compared with no-intervention. Compared to treadmill or balance exercise it resulted in greater knee flexion, but not knee extension or leg press strength. RT alone resulted in greater knee extension and flexion strength compared to stretching, but not in greater leg press strength compared to no-intervention. Discussion Overall, the current evidence suggests that exercise interventions that contain RT may be effective in improving muscular strength in people with PD compared with no exercise. However, depending on muscle group and/or training dose, RT may not be superior to other exercise types. Interventions which combine RT with other exercise may be most effective. Findings should be interpreted with caution due to the relatively high risk of bias of most studies.