Vision and deaf awareness training is it app.ropriate?

Title
Visual and deaf awareness training is it app.ropriate
Purpose
Some of our most vulnerable patients have a sensory deficit. An app which focused on patients with a vision and/or hearing loss was developed for healthcare students. The intent was to embed the core values necessary for students to provide appropriate care for patients with a sensory deficit.
Setting
Queen’s University Belfast, School of Nursing and Midwifery.
Methods
Stage 1
A review of current sensory awareness training in the United Kingdom
Stage 2
Application for funding
Stage 3
Development of a teaching tool template with the essential aspects required for sensory awareness training
Stage 4
Collaboration with others: Royal National Institute for the Blind, Action on Hearing Loss, Computer technician.
Stage 5
Production and transfer of multimedia outputs onto a software application system.
Stage 6
App Piloted with a sample of lecturers (n=5), undergraduate nursing students (n=20), service users (n=5)
Stage 7
Editing
Stage 8
App made available to all undergraduate nursing students
Stage 9
App evaluation (n=300)



Results
Overall nursing students positively evaluated the app, 100% of students rated the app between good and excellent. Qualitative evidence from service users and practice partnerships was extremely positive:
"At last I feel listened too in respect to my hearing loss and empowered. I don't feel like I am complaining I am actually helping to create something which should benefit staff and all of us with a hearing or vision loss". Patient
“Very insightful into the lives of those with a disability will be so useful in practice as an aid to jog my memory". 1st year nursing student
Conclusion
It is hoped that further evaluation and implementation of the app will show an improved quality to the care delivered to those with a sensory deficit. We believe that by working in partnership with service users we have helped to create an innovative tool that benefits both staff and patients.
Financial disclosure Yes
Funding of £2700 was awarded in 2014 through the Martha McMenamin Memorial Northern Ireland Scholarship.

Tele-Supervised FES-Assisted Exercise for Hemiplegic Upper Limb

Stroke survivors often have upper limb (UL) hemiparesis, limiting their ability to perform activities of daily life (ADLs). Intensive, task-oriented exercise therapy (ET) can improve UL function, but motivation to perform sufficient ET is difficult to maintain. Here we report on a trial in which a workstation was deployed in the homes of chronic stroke survivors to enable tele-coaching of ET in the guise of computer games. Participants performed 6 weeks of 1 hour/day, 5 days/week ET. Hand opening and grasp were assisted with functional electrical stimulation (FES). The primary outcome measure was the Action Research Arm Test (ARAT). Secondary outcome measures included a quantitative test of UL function performed on the workstation, grasp force measurements and transcranial magnetic stimulation (TMS). Improvements were seen in the functional tests, but surprisingly, not in the TMS responses. An important finding was that participants commencing with intermediate functional scores improved the most.

CONCLUSIONS: 1) Daily, tele-supervised FES-ET in chronic stroke survivors is feasible with commercially-available technology. 2) The intervention can significantly improve UL function, particularly in people who start with an intermediate level of function. 3) Significant improvements in UL function can occur in the absence of changes in TMS responses.

Impact of Residual Transmit RF Impairments on Training-Based MIMO Systems

Radio-frequency (RF) impairments, which intimately exist in wireless communication systems, can severely limit the performance of multiple-input-multiple-output (MIMO) systems. Although we can resort to compensation schemes to mitigate some of these impairments, a certain amount of residual impairments always persists. In this paper, we consider a training-based point-to-point MIMO system with residual transmit RF impairments (RTRI) using spatial multiplexing transmission. Specifically, we derive a new linear channel estimator for the proposed model, and show that RTRI create an estimation error floor in the high signal-to-noise ratio (SNR) regime. Moreover, we derive closed-form expressions for the signal-to-noise-plus-interference ratio (SINR) distributions, along with analytical expressions for the ergodic achievable rates of zero-forcing, maximum ratio combining, and minimum mean-squared error receivers, respectively. In addition, we optimize the ergodic achievable rates with respect to the training sequence length and demonstrate that finite dimensional systems with RTRI generally require more training at high SNRs than those with ideal hardware. Finally, we extend our analysis to large-scale MIMO configurations, and derive deterministic equivalents of the ergodic achievable rates. It is shown that, by deploying large receive antenna arrays, the extra training requirements due to RTRI can be eliminated. In fact, with a sufficiently large number of receive antennas, systems with RTRI may even need less training than systems with ideal hardware.

Exodus? The training paths and plans of postgraduate medical trainees, under the Royal College of Physicians of Ireland

Background: In 2006, the Buttimer report highlighted the paucity of demographic data on those applying for and entering postgraduate medical education and training (PGMET) in Ireland. Today, concerns that there is an "exodus" of graduates of Irish medical schools are at the forefront of national discussion, however, published data on PGMET remains inadequate.

Aims: The objectives of this study were to collate existing data relating to trainees and training programmes at three stages of training and to examine the career plans of junior trainees.

Methods: Data from application forms for training programmes, commencing July 2012, under the Royal College of Physicians of Ireland (n = 870), were integrated with data from other existing sources. Candidates entering basic specialist training were surveyed with regard to career plans. Descriptive and comparative analysis was performed in SPSS version 18.

Results: Graduates of Irish medical schools made up over 70 % of appointees. Over 80 % of BST trainees aspired to work as consultants in Ireland, but 92.5 % planned to spend time working abroad (response rate 77 %). Decisions to leave the Irish system were linked to lifestyle, but also to failure to be appointed to higher specialist training. Significant numbers of trainees return to Ireland after a period abroad.

Conclusions: The trainee "exodus" is more complex than is often portrayed. The desire to spend time working outside Ireland must be accounted for in workforce planning and configuration of training programmes. Expansion of HST is a potential solution to reduce the numbers of graduates leaving Ireland post-BST.

A realistic evaluation of track and trigger systems and acute care training for early recognition and treatment of deteriorating ward-based patients: research protocol.

Aim The aim of the study is to evaluate factors that enable or constrain the implementation and service delivery of early warnings systems or acute care training in practice. Background To date there is limited evidence to support the effectiveness of acute care initiatives (early warning systems, acute care training, outreach) in reducing the number of adverse events (cardiac arrest, death, unanticipated Intensive Care admission) through increased recognition and management of deteriorating ward based patients in hospital [1-3]. The reasons posited are that previous research primarily focused on measuring patient outcomes following the implementation of an intervention or programme without considering the social factors (the organisation, the people, external influences) which may have affected the process of implementation and hence measured end-points. Further research which considers the social processes is required in order to understand why a programme works, or does not work, in particular circumstances [4]. Method The design is a multiple case study approach of four general wards in two acute hospitals where Early Warning Systems (EWS) and Acute Life-threatening Events Recognition and Treatment (ALERT) course have been implemented. Various methods are being used to collect data about individual capacities, interpersonal relationships and institutional balance and infrastructures in order to understand the intended and unintended process outcomes of implementing EWS and ALERT in practice. This information will be gathered from individual and focus group interviews with key participants (ALERT facilitators, nursing and medical ALERT instructors, ward managers, doctors, ward nurses and health care assistants from each hospital); non-participant observation of ward organisation and structure; audit of patients' EWS charts and audit of the medical notes of patients who deteriorated during the study period to ascertain whether ALERT principles were followed. Discussion & progress to date This study commenced in January 2007. Ethical approval has been granted and data collection is ongoing with interviews being conducted with key stakeholders. The findings from this study will provide evidence for policy-makers to make informed decisions regarding the direction for strategic and service planning of acute care services to improve the level of care provided to acutely ill patients in hospital. References 1. Esmonde L, McDonnell A, Ball C, Waskett C, Morgan R, Rashidain A et al. Investigating the effectiveness of Critical Care Outreach Services: A systematic review. Intensive Care Medicine 2006; 32: 1713-1721 2. McGaughey J, Alderdice F, Fowler R, Kapila A, Mayhew A, Moutray M. Outreach and Early Warning Systems for the prevention of Intensive Care admission and death of critically ill patients on general hospital wards. Cochrane Database of Systematic Reviews 2007, Issue 3. www.thecochranelibrary.com 3. Winters BD, Pham JC, Hunt EA, Guallar E, Berenholtz S, Pronovost PJ (2007) Rapid Response Systems: A systematic review. Critical Care Medicine 2007; 35 (5): 1238-43 4. Pawson R and Tilley N. Realistic Evaluation. London; Sage: 1997

A realistic evaluation of Early Warning Systems and acute care training in Northern Ireland: findings and recommendations

Statement of purpose The purpose of this concurrent session is to present the main findings and recommendations from a five year study evaluating the implementation of Early Warning Systems (EWS) and the Acute Life-threatening Events: Recognition and Treatment (ALERT) course in Northern Ireland. The presentation will provide delegates with an understanding of those factors that enable and constrain successful implementation of EWS and ALERT in practice in order to provide an impetus for change. Methods The research design was a multiple case study approach of four wards in two hospitals in Northern Ireland. It followed the principles of realist evaluation research which allowed empirical data to be gathered to test and refine RRS programme theory [1]. The stages included identifying the programme theories underpinning EWS and ALERT, generating hypotheses, gathering empirical evidence and refining the programme theories. This approach used a variety of mixed methods including individual and focus group interviews, observation and documentary analysis of EWS compliance data and ALERT training records. A within and across case comparison facilitated the development of mid-range theories from the research evidence. Results The official RRS theories developed from the realist synthesis were critically evaluated and compared with the study findings to develop a mid-range theory to explain what works, for whom in what circumstances. The findings of what works suggests that clinical experience, established working relationships, flexible implementation of protocols, ongoing experiential learning, empowerment and pre-emptive management are key to the success of EWS and ALERT implementation. Each concept is presented as ‘context, mechanism and outcome configurations’ to provide an understanding of how the context impacts on individual reasoning or behaviour to produce certain outcomes. Conclusion These findings highlight the combination of factors that can improve the implementation and sustainability of EWS and ALERT and in light of this evidence several recommendations are made to provide policymakers with guidance and direction for future policy development. References: 1. Pawson R and Tilley N. (1997) Realistic Evaluation. Sage Publications; London Type of submission: Concurrent session Source of funding: Sandra Ryan Fellowship funded by the School of Nursing & Midwifery, Queen’s University of Belfast

Supervised Aggregative Feature Extraction for Big Data Time Series Regression

In many applications, and especially those where batch processes are involved, a target scalar output of interest is often dependent on one or more time series of data. With the exponential growth in data logging in modern industries such time series are increasingly available for statistical modeling in soft sensing applications. In order to exploit time series data for predictive modelling, it is necessary to summarise the information they contain as a set of features to use as model regressors. Typically this is done in an unsupervised fashion using simple techniques such as computing statistical moments, principal components or wavelet decompositions, often leading to significant information loss and hence suboptimal predictive models. In this paper, a functional learning paradigm is exploited in a supervised fashion to derive continuous, smooth estimates of time series data (yielding aggregated local information), while simultaneously estimating a continuous shape function yielding optimal predictions. The proposed Supervised Aggregative Feature Extraction (SAFE) methodology can be extended to support nonlinear predictive models by embedding the functional learning framework in a Reproducing Kernel Hilbert Spaces setting. SAFE has a number of attractive features including closed form solution and the ability to explicitly incorporate first and second order derivative information. Using simulation studies and a practical semiconductor manufacturing case study we highlight the strengths of the new methodology with respect to standard unsupervised feature extraction approaches.

Compositional data-driven alternatives to single geochemical component maps

Conventional practice in Regional Geochemistry includes as a final step of any geochemical campaign the generation of a series of maps, to show the spatial distribution of each of the components considered. Such maps, though necessary, do not comply with the compositional, relative nature of the data, which unfortunately make any conclusion based on them sensitive
to spurious correlation problems. This is one of the reasons why these maps are never interpreted isolated. This contribution aims at gathering a series of statistical methods to produce individual maps of multiplicative combinations of components (logcontrasts), much in the flavor of equilibrium constants, which are designed on purpose to capture certain aspects of the data.
We distinguish between supervised and unsupervised methods, where the first require an external, non-compositional variable (besides the compositional geochemical information) available in an analogous training set. This external variable can be a quantity (soil density, collocated magnetics, collocated ratio of Th/U spectral gamma counts, proportion of clay particle fraction, etc) or a category (rock type, land use type, etc). In the supervised methods, a regression-like model between the external variable and the geochemical composition is derived in the training set, and then this model is mapped on the whole region. This case is illustrated with the Tellus dataset, covering Northern Ireland at a density of 1 soil sample per 2 square km, where we map the presence of blanket peat and the underlying geology. The unsupervised methods considered include principal components and principal balances
(Pawlowsky-Glahn et al., CoDaWork2013), i.e. logcontrasts of the data that are devised to capture very large variability or else be quasi-constant. Using the Tellus dataset again, it is found that geological features are highlighted by the quasi-constant ratios Hf/Nb and their ratio against SiO2; Rb/K2O and Zr/Na2O and the balance between these two groups of two variables; the balance of Al2O3 and TiO2 vs. MgO; or the balance of Cr, Ni and Co vs. V and Fe2O3. The largest variability appears to be related to the presence/absence of peat.

Clustering-Based Ensemble Method as an Alternative to Stacking

One of the most popular techniques of generating classifier ensembles is known as stacking which is based on a meta-learning approach. In this paper, we introduce an alternative method to stacking which is based on cluster analysis. Similar to stacking, instances from a validation set are initially classified by all base classifiers. The output of each classifier is subsequently considered as a new attribute of the instance. Following this, a validation set is divided into clusters according to the new attributes and a small subset of the original attributes of the instances. For each cluster, we find its centroid and calculate its class label. The collection of centroids is considered as a meta-classifier. Experimental results show that the new method outperformed all benchmark methods, namely Majority Voting, Stacking J48, Stacking LR, AdaBoost J48, and Random Forest, in 12 out of 22 data sets. The proposed method has two advantageous properties: it is very robust to relatively small training sets and it can be applied in semi-supervised learning problems. We provide a theoretical investigation regarding the proposed method. This demonstrates that for the method to be successful, the base classifiers applied in the ensemble should have greater than 50% accuracy levels.

The Development of TASTER, a Cognitive Training Game Using Human-Centered Design, Tailored for Children with Global and Specific Cognitive Impairments

Children with Prader-Willi syndrome often exhibit challenging behavior in response to changes to routine. This phenomenon has been linked to a deficit in task switching ability which has been observed in children with the syndrome. TASTER is a cognitive training game which is being designed with input from a group of children with Prader- Willi syndrome, which aims to train task switching ability and thus reduce associated challenging behavior.

Agility and search and rescue training differently affects pet dogs' behaviour in socio-cognitive tasks

Both genetic factors and life experiences appear to be important in shaping dogs' responses in a test situation. One potentially highly relevant life experience may be the dog's training history, however few studies have investigated this aspect so far. This paper briefly reviews studies focusing on the effects of training on dogs' performance in cognitive tasks, and presents new, preliminary evidence on trained and untrained pet dogs' performance in an 'unsolvable task'. Thirty-nine adult dogs: 13 trained for search and rescue activities (S&R group), 13 for agility competition (Agility group) and 13 untrained pets (Pet group) were tested. Three 'solvable' trials in which dogs could obtain the food by manipulating a plastic container were followed by an 'unsolvable' trial in which obtaining the food became impossible. The dogs' behaviours towards the apparatus and the people present (owner and researcher) were analysed. Both in the first 'solvable' and in the 'unsolvable' trial the groups were comparable on actions towards the apparatus, however differences emerged in their human-directed gazing behaviour. In fact, results in the 'solvable' trial, showed fewer S&R dogs looking back at a person compared to agility dogs, and the latter alternating their gaze between person and apparatus more frequently than pet dogs. In the unsolvable trial no difference between groups emerged in the latency to look at the person however agility dogs looked longer at the owner than both pet and S&R dogs; whereas S&R dogs exhibited significantly more barking (always occurring concurrently to looking at the person or the apparatus) than both other groups. Furthermore, S&R dogs alternated their gaze between person and apparatus more than untrained pet dogs, with agility dogs falling in between these two groups. Thus overall, it seems that the dogs' human-directed communicative behaviours are significantly influenced by their individual training experiences. © 2009 Elsevier B.V. All rights reserved.

Work-related training and the probability of transitioning from non-permanent to permanent employment

It is widely believed that work-related training increases a worker’s probability of moving up the job-quality ladder. This is usually couched in terms of effects on wages, but it has also been argued that training increases the probability of moving from non-permanent forms of employment to more permanent employment. This hypothesis is tested using nationally representative panel data for Australia, a country where the incidence of non-permanent employment, and especially casual employment, is high by international standards. While a positive association between participation in work-related training and the subsequent probability of moving from either casual or fixed-term contract employment to permanent employment is observed among men, this is shown to be driven not by a causal impact of training on transitions but by differences between those who do and do not receive training; i.e., selection bias.