A Study of the Value of Mechanical Aids in the Teaching/Learning of Swimming with Advanced Swimmers

Problem: This study was concerned with effectiveness of a commercially produced hand-paddle as a teaching/learning aid for learning the arm action of the front crawl swimming stroke. Procedure: The population was restricted to two classes from the general program at the Advanced Swimmer Level of the Health, Physical Education and Recreation Department of the University of North Dakota. The two samples were randomly divided into experimental and traditional groups. Data were collected by means of a subjective rating instrument designed by the researcher. Students were rated on a pre-test and post-test after eight hours of instruction. Statistically, the data were treated by using t tests for comparisons both within groups and between groups. An ,05 alpha level of significance was selected a priori for the determination of significance in the analyses. Conclusions: 1. The use of the hand-paddles did not result in significantly better performance of the arm stroke in the front crawl than that obtained by subjects using no mechanical aids, 2, The traditional group in Sample Two did not improve significantly and all other groups did during the experimentation period. Recommendations: 1. It is recommended, as a result of improvements found in the data obtained from the Experimental Groups, that a long-range study of the effects of hand-paddles be undertaken, 2. As a result of the significant level of improvement made by the Experimental Groups, it is recommended that coaches and teachers be prepared to use the hand-paddles with some of their students. 3. It is further recommended that tests based on strength, power, endurance, and speed be carried out using the hand-paddles as aids in developing these aspects of various swimming strokes, 4. Since there is now more than one type of hand-paddle available, it is recommended that studies comparing the various types of paddles be initiated, 5. The most important recommendation made by this researcher is that more experimentation be carried out in regard to mechanical learning aids for the recreational swimmer. This could be done at the beginning, intermediate and advanced levels and also over a longer period of instruction

Developing a predictive modelling capacity for a climate change-vulnerable blanket bog habitat: Assessing 1961-1990 baseline relationships

Aim: Understanding the spatial distribution of high priority habitats and developing predictive models using climate and environmental variables to replicate these distributions are desirable conservation goals. The aim of this study was to model and elucidate the contributions of climate and topography to the distribution of a priority blanket bog habitat in Ireland, and to examine how this might inform the development of a climate change predictive capacity for peat-lands in Ireland. Methods: Ten climatic and two topographic variables were recorded for grid cells with a spatial resolution of 1010 km, covering 87% of the mainland land surface of Ireland. Presence-absence data were matched to these variables and generalised linear models (GLMs) fitted to identify the main climatic and terrain predictor variables for occurrence of the habitat. Candidate predictor variables were screened for collinearity, and the accuracy of the final fitted GLM was evaluated using fourfold cross-validation based on the area under the curve (AUC) derived from a receiver operating characteristic (ROC) plot. The GLM predicted habitat occurrence probability maps were mapped against the actual distributions using GIS techniques. Results: Despite the apparent parsimony of the initial GLM using only climatic variables, further testing indicated collinearity among temperature and precipitation variables for example. Subsequent elimination of the collinear variables and inclusion of elevation data produced an excellent performance based on the AUC scores of the final GLM. Mean annual temperature and total mean annual precipitation in combination with elevation range were the most powerful explanatory variable group among those explored for the presence of blanket bog habitat. Main conclusions: The results confirm that this habitat distribution in general can be modelled well using the non-collinear climatic and terrain variables tested at the grid resolution used. Mapping the GLM-predicted distribution to the observed distribution produced useful results in replicating the projected occurrence of the habitat distribution over an extensive area. The methods developed will usefully inform future climate change predictive modelling for Irelan

“Employment and arthritis: making it work” a randomized controlled trial evaluating an online program to help people with inflammatory arthritis maintain employment (study protocol)

Background: Arthritis and musculoskeletal conditions are the leading cause of long-term work disability (WD), an outcome with a major impact on quality of life and a high cost to society. The importance of decreased at-work productivity has also recently been recognized. Despite the importance of these problems, few interventions have been developed to reduce the impact of arthritis on employment. We have developed a novel intervention called “Making It Work”, a program to help people with inflammatory arthritis (IA) deal with employment issues, prevent WD and improve at-work productivity. After favorable results in a proof-of-concept study, we converted the program to a web-based format for broader dissemination and improved accessibility. The objectives of this study are: 1) to evaluate in a randomized controlled trial (RCT) the effectiveness of the program at preventing work cessation and improving at-work productivity; 2) to perform a cost-utility analysis of the intervention. Methods/Design 526 participants with IA will be recruited from British Columbia, Alberta, and Ontario in Canada. The intervention consists of a) 5 online group sessions; b) 5 web-based e-learning modules; c) consultations with an occupational therapist for an ergonomic work assessment and a vocational rehabilitation counselor. Questionnaires will be administered online at baseline and every 6 months to collect information about demographics, disease measures, costs, work-related risk factors for WD, quality of life, and work outcomes. Primary outcomes include at-work productivity and time to work cessation of > 6 months for any reason. Secondary outcomes include temporary work cessation, number of days missed from work per year, reduction in hours worked per week, quality adjusted life year for the cost utility analysis, and changes from baseline in employment risk factors. Analysis of Variance will evaluate the intervention’s effect on at-work productivity, and multivariable Cox regression models will estimate the risk of work cessation associated with the intervention after controlling for risk factors for WD and other important predictors imbalanced at baseline. Discussion This program fills an important gap in arthritis health services and addresses an important and costly problem. Knowledge gained from the RCT will be useful to health care professionals, policy planners and arthritis stakeholders. Trial registration ClinicalTrials.gov NCT01852851 ; registered April 13, 2012; first participant randomized on July 6, 2013.Medicine, Department ofOccupational Science and Occupational Therapy, Department ofPhysical Therapy, Department ofPopulation and Public Health (SPPH), School ofRheumatology, Division ofNon UBCMedicine, Faculty ofReviewedFacult

Novel methods improve prediction of species' distributions from occurrence data

Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species' distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species' occurrence data. Presence-only data were effective for modelling species' distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve