Flexible Training Strategy (National Task Force on Medical Staffing)

Flexible Training Strategy (National Task Force on Medical Staffing) The Flexible Training Strategy, while endorsing flexible/part-time options recognises that the preferred option for the majority of doctors-in-training and consultants is most likely to continue to be full-time training and work. Click here to download PDF

Flexible Training Strategy (National Task Force on Medical Staffing)

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Proceedings of national seminar on postgraduate medical education and training

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Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Strategic Review of Medical Training and Career Structure Interim Report

Click here to download Strategic Review of Medical Training and Career Structure Interim Report PDF 44kb Click here to download Strategic Review of Medical Training and Career Structure Terms of Reference PDF 59KB

Effect of a Road Safety Training Program on Drivers' Comparative Optimism

Reducing comparative optimism regarding risk perceptions in traffic accidents has been proven to be particularly difficult (Delhomme, 2000). This is unfortunate because comparative optimism is assumed to impede preventive action. The present study tested whether a road safety training course could reduce drivers' comparative optimism in high control situations. Results show that the training course efficiently reduced comparative optimism in high control, but not in low control situations. Mechanisms underlying this finding and implications for the design of road safety training courses are discussed.

Strategic Review of Medical Training and Career Structures Report on Medical Career Structures and Pathways following completion of Specialist Training

The Minister for Health decided, in July 2013, to establish a Working Group, chaired by Professor Brian MacCraith, President of DCU, to carry out a strategic review of medical training and career structure. The Working Group will examine and make high-level recommendations relating to training and career pathways for doctors with a view to: From January-April 2014, the Working Group prioritised work on career structures and pathways following completion of specialist training in order to report to the Minister for Health on these issues in this report. Download the Report (PDF, 800 kb)  

Strategic Review of Medical Training and Career Structure Final Report

  Final report of the Strategic Review Working Group chaired by Professor Brian MacCraith (President, DCU) This final report focuses on issues relating to strategic medical workforce planning and career planning and mentoring supports for trainee doctors and makes recommendations. It also addresses specific issues in relation to the specialties of public health medicine, general practice and the community-based aspects of psychiatry.   Download the report here.  

Patients satisfaction in an academic walk-in centre : a new model of residents training achieved by family doctors

Introduction Walk-in centers may improve access to healthcare for some patients, due to their convenient location and extensive opening hours, with no need for appointment. Herein we describe and assess a new model of walk-in centre, characterized by care provided by residents and supervision achieved by experienced family doctors. Main aim of the study was to assess patients satisfaction about the care they received from residents and the supervision by family doctors. Secondary aim was to describe walk-in patients demographic characteristics and to identify potential associations with satisfaction. Methods The study was conducted in the walk-in centre of Lausanne. Patients who consulted between in April 2011 were automatically included and received a questionnaire in French. We used a five-point Likert scale, from "not at all satisfied" to "very satisfied", converted from 1 to 5. We focused on the satisfaction regarding residents care and supervision by a family doctor. The former was divided in three categories: "Skills", "Treatment" and "Behaviour". Mean satisfaction was calculated for each category and a multivariable logistic model was applied in order to identify associations among patients demographics. Results Response rate was 47% [184/395], Walk-in patients were more likely to be women, young, with a high education level. Patients were very satisfied with residents care, with median satisfaction between 4.5 and 5, for each category. Over than 90% of patients were "satisfied" or "very satisfied" that a family doctor was involved in the consultation. Age showed the major association of satisfaction. Discussion Patients were highly satisfied with care provided by residents and with involvement of a family doctor in the consultation. Older age showed the major association with satisfaction with a positive impact. The high satisfaction reported by walk-in patients supports this new model of walk-in centre.

Skeletal muscle mitochondria in the elderly: effects of physical fitness and exercise training.

CONTEXT: Sarcopenia is thought to be associated with mitochondrial (Mito) loss. It is unclear whether the decrease in Mito content is consequent to aging per se or to decreased physical activity. OBJECTIVES: The objective of the study was to examine the influence of fitness on Mito content and function and to assess whether exercise could improve Mito function in older adults. DESIGN AND SUBJECTS: Three distinct studies were conducted: 1) a cross-sectional observation comparing Mito content and fitness in a large heterogeneous cohort of older adults; 2) a case-control study comparing chronically endurance-trained older adults and sedentary (S) subjects matched for age and gender; and 3) a 4-month exercise intervention in S. SETTING: The study was conducted at a university-based clinical research center. OUTCOMES: Mito volume density (MitoVd) was assessed by electron microscopy from vastus lateralis biopsies, electron transport chain proteins by Western blotting, mRNAs for transcription factors involved in M biogenesis by quantitative RT-PCR, and in vivo oxidative capacity (ATPmax) by (31)P-magnetice resonance spectroscopy. Peak oxygen uptake was measured by graded exercise test. RESULTS: Peak oxygen uptake was strongly correlated with MitoVd in 80 60- to 80-year-old adults. Comparison of chronically endurance-trained older adults vs S revealed differences in MitoVd, ATPmax, and some electron transport chain protein complexes. Finally, exercise intervention confirmed that S subjects are able to recover MitoVd, ATPmax, and specific transcription factors. CONCLUSIONS: These data suggest the following: 1) aging per se is not the primary culprit leading to Mito dysfunction; 2) an aerobic exercise program, even at an older age, can ameliorate the loss in skeletal muscle Mito content and may prevent aging muscle comorbidities; and 3) the improvement of Mito function is all about content.