130,397 research outputs found
Is there a role for music in the ICU?
No full textBackground\ud
Alternatives to sedative medications, such as music, may alleviate the anxiety associated with ventilatory support.\ud
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Methods\ud
Objective: The aim of the study was to test whether listening to self-initiated patient-directed music (PDM) can reduce anxiety and sedative exposure during ventilatory support in critically ill patients.\ud
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Design: This study was a randomized clinical trial.\ud
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Setting: In 12 ICUs of five hospitals in the Minneapolis–St Paul, Minnesota area, 373 patients receiving acute mechanical ventilatory support for respiratory failure were enrolled between September 2006 and March 2011. Of the patients included in the study, 86% were white, 52% were female, and the mean age was 59 years. The patients had a mean Acute Physiology, Age and Chronic Health Evaluation III score of 63 and a mean of 5.7 study days.\ud
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Interventions: The patients received self-initiated PDM (n =126) with preferred selections tailored by a music therapist, or self-initiated use of noise-canceling headphones (NCH; n = 122), or usual care (n = 125).\ud
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Outcomes: Daily assessments of anxiety (on a 100 mm visual analog scale) and two aggregate measures of sedative exposure (intensity and frequency) were assessed.\ud
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Results\ud
Patients in the PDM group listened to music for a mean of 79.8 (median (range) 12 (0 to 796)) minutes/day. Patients in the NCH group wore the noise-abating headphones for a mean of 34.0 (median (range), 0 (0 to 916)) minutes/day. The mixed-models analysis showed that, at any time point, patients in the PDM group had an anxiety score that was 19.5 points lower (95% confidence interval, −32.2 to −6.8) than patients in the usual care group (P = 0.003). By the fifth study day, anxiety was reduced by 36.5% in PDM patients. The treatment × time interaction showed that PDM significantly reduced both measures of sedative exposure. Compared with usual care, the PDM group had reduced sedation intensity by −0.18 (95% confidence interval, −0.36 to −0.004) points/day (P = 0.05) and had reduced frequency by −0.21 (95% confidence interval, −0.37 to −0.05) points/day (P = 0.01). The PDM group had reduced sedation frequency by −0.18 (95% confidence interval, −0.36 to −0.004) points/day versus the NCH group (P = 0.04). By the fifth study day, the PDM patients received two fewer sedative doses (reduction of 38%) and had a reduction of 36% in sedation intensity.\ud
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Conclusions\ud
Among ICU patients receiving acute ventilatory support for respiratory failure, PDM resulted in greater reduction in anxiety compared with usual care, but not compared with NCH. Concurrently, PDM resulted in greater reduction in sedation frequency compared with usual care or NCH, and greater reduction in sedation intensity compared with usual care but not compared with NCH
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Scholarly Communication and Publishing Lunch and Learn Talk #11: The ULS Open Access Author Fee Fund
No full textAt the May 2014 talk, you will learn about the ULS Open Access Author Fee Fund--what it is, why we do it, how it works, and how the program is going so far
The R&D Tax Incentives
No full textThis article sets out some background information and reflections of the author on the R&D tax incentive schemes included in the Common Corporate Tax Base (CCTB) Proposal. In particular the author analyzes the stimulus to private R&D through ad hoc tax incentives included in the CCTB Proposal and dives into the actual provisions included in the Proposal highlighting the most relevant issues connected with their design and interpretation. Moreover, the author explores the interaction between the CCTB Proposal and the granting by Member States of domestic R&D tax incentives
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