37,784 research outputs found

    Use of a 3-item short-form version of the Barthel Index for use in stroke: systematic review and external validation

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    Background and Purpose—There may be a potential to reduce the number of items assessed in the Barthel Index (BI), and shortened versions of the BI have been described. We sought to collate all existing short-form BI (SF-BI) and perform a comparative validation using clinical trial data. Methods—We performed a systematic review across multidisciplinary electronic databases to find all published SF-BI. Our validation used the VISTA (Virtual International Stroke Trials Archive) resource. We describe concurrent validity (agreement of each SF-BI with BI), convergent and divergent validity (agreement of each SF-BI with other outcome measures available in the data set), predictive validity (association of prognostic factors with SF-BI outcomes), and content validity (item correlation and exploratory factor analyses). Results—From 3546 titles, we found 8 articles describing 6 differing SF-BI. Using acute trial data (n=8852), internal reliability suggested redundancy in BI (Cronbach α, 0.96). Each SF-BI demonstrated a strong correlation with BI, modified Rankin Scale, National Institutes of Health Stroke Scale (all ρ≄0.83; P<0.001). Using rehabilitation trial data (n=332), SF-BI demonstrated modest correlation with quality of life measures Stroke Impact Scale and 5 domain EuroQOL (ρ≄0.50, P<0.001). Prespecified prognostic factors were associated with SF-BI outcomes (all P<0.001). Our factor analysis described a 3 factor structure, and item reduction suggested an optimal 3-item SF-BI comprising bladder control, transfer, and mobility items in keeping with 1 of the 3-item SF-BI previously described in the literature. Conclusions—There is redundancy in the original BI; we have demonstrated internal and external validity of a 3-item SF-BI that should be simple to use

    Correlation Between Lumbopelvic and Sagittal Parameters and Health-Related Quality of Life in Adults With Lumbosacral Spondylolisthesis.

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    Study Design:Secondary analysis of prospective, multicenter data. Objective:To evaluate impact of sagittal parameters on health-related quality of life (HRQoL) in adults with lumbosacral spondylolisthesis. Methods:Adults with unoperated lumbosacral spondylolisthesis were identified in the Spinal Deformity Study Group database. Pearson's correlations were calculated between SF-12 (Short Form-12)/Scoliosis Research Society-30 (SRS-30) scores and radiographic parameters (C7 sagittal vertical axis [SVA] deviation, T1 pelvic angle, pelvic tilt [PT], pelvic incidence, sacral slope, slip angle, Meyerding slip grade, Labelle classification). Main effects linear regression models measured association between individual health status measures and individual radiographic predictor variables. Results:Forty-five patients were analyzed (male, 15; female, 30; average age 40.5 ± 18.7 years; 14 low-grade, 31 high-grade). For low-grade slips, SVA had strong negative correlations with SF-12 mental component score (MCS), SRS-30 appearance, mental, and satisfaction domains (r = -0.57, r = -0.60, r = -0.58, r = -0.53, respectively; P < .05). For high-grade slips, slip angle had a moderate negative correlation with SF-12 MCS (r = -0.36; P = .05) and SVA had strong negative correlations with SF-12 physical component score (PCS), SRS-30 appearance and activity domains (r = -0.48, r = -0.48, r = -0.45; P < .05) and a moderate negative correlation with SRS-30 total (r = -0.37; P < .05). T1 pelvic angle had a moderate negative correlation with SF-12 PCS and SRS-30 appearance (r = -0.37, r = -0.36; P ≀ .05). For every 1° increase in PT, there was a 0.04-point decrease in SRS appearance, 0.05-point decrease in SRS activity, 0.06-point decrease in SRS satisfaction, and 0.04-point decrease in SRS total score (P < .05). Conclusion:Lumbosacral spondylolisthesis in adults negatively affects HRQoL. Multiple radiographic sagittal parameters negatively affect HRQoLs for patients with low- and high-grade slips. Improvement of sagittal parameters is an important goal of surgery for adults with lumbosacral spondylolisthesis

    Using Query Term Order for Result Summarisation

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    We report on two experiments performed to test the importance of Term Order in automatic summarisation. Experiment one was undertaken as part of DUC 2004 to which three systems were submitted, each with a different summarisation approach. The system that used document Term Order outperformed those that did not use Term Order in the ROUGE evaluation. Experiment two made use of human evaluations of search engine results, comparing our Query Term Order summaries with a simulation of current Google search engine result summaries in terms of summary quality. Our QTO system’s summaries aided users’ relevance judgements to a significantly greater extent than Google’s

    Approaches to learning and competitive attitude in students in higher education

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    The degree to which individuals are able to nominate or change their approach to learning in order to meet the needs of the learning situation opens a lengthy and complex debate. Some evidence exists for a shift in approach depending on the experience of the learner and demands of the task, while other evidence is available which indicates stability of approach to learning over time and across task. The present study examines the relationship between approaches to learning and competitive attitude in undergraduate students. Previous research has reported a link between constructs such as achievement orientation and personality traits and cognitive strategies and it was suggested here that competitive attitude may be one mediating factor in students’ approaches to learning. Findings did not reveal a convincing relationship between competitiveness and approaches to learning and it is suggested that further exploration of trait constructs such as competitiveness may not yield meaningful evidence regarding the stability of students’ approaches to learning. There was also no evidence that the student experience of higher education cultivates competitiveness in students as cross-sectional comparisons of student year groups revealed only negligible and statistically non-significant differences in competitive attitude

    Development of the Web Users Self-Efficacy scale (WUSE)

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    The aim of this research was to develop a scale that could evaluate an individuals confidence in using the Internet. Web-based resources are becoming increasingly important within higher education and it is therefore vital that students and staff feel confident and competent in the access, provision, and utilisation of these resources. The scale developed here represents an extension of previous research (Cassidy & Eachus, 2002) that developed a measure of self-efficacy in the context of computer use. An iterative approach was used in the development of the Web User Self-Efficacy scale (WUSE) and the participants were recruited from the student body of a large University in the North West of the United Kingdom, and globally via a web site set up for this purpose. Initial findings suggest that the scale has acceptable standards of reliability and validity though work is continuing to refine the scale and improve the psychometric properties of the tool

    Can Automatic Abstracting Improve on Current Extracting Techniques in Aiding Users to Judge the Relevance of Pages in Search Engine Results?

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    Current search engines use sentence extraction techniques to produce snippet result summaries, which users may find less than ideal for determining the relevance of pages. Unlike extracting, abstracting programs analyse the context of documents and rewrite them into informative summaries. Our project aims to produce abstracting summaries which are coherent and easy to read thereby lessening users’ time in judging the relevance of pages. However, automatic abstracting technique has its domain restriction. For solving this problem we propose to employ text classification techniques. We propose a new approach to initially classify whole web documents into sixteen top level ODP categories by using machine learning and a Bayesian classifier. We then manually create sixteen templates for each category. The summarisation techniques we use include a natural language processing techniques to weight words and analyse lexical chains to identify salient phrases and place them into relevant template slots to produce summaries
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