1,721,187 research outputs found
Epidemiology
Full text linkR21 AG046839/AG/NIA NIH HHSUnited States/R21 CA198172/CA/NCI NIH HHSUnited States/R21 OH010769/OH/NIOSH CDC HHSUnited States/R25 GM113686/GM/NIGMS NIH HHSUnited States/UL1 TR001453/TR/NCATS NIH HHSUnited States/TL1 TR001454/TR/NCATS NIH HHSUnited States
J Nurs Home Res Sci
Full text linkIn 2012, nursing homes were considered the most dangerous workplaces in the United States. While other industries have guidelines that limit manual lifting of stable objects to 6450 pounds, the same is not so in the nursing home industry where residents requiring physical assistance may weigh over 250 pounds and where the prevalence of obesity among residents is increasing. Safe patient handling legislation in nursing homes has been enacted in nine of the United States since 2005 (Hawaii, Illinois, Maryland, Minnesota, New Jersey, New York, Ohio, Rhode Island, and Texas). This paper reviews the problem of worker injuries in nursing homes, describes the legislation passed to address the problem, and reviews the data available on the effectiveness of the legislation. No national studies evaluating the effectiveness of safe patient handling state policies on nursing home injuries exists, although the National Institute on Occupational Safety and Health has recently funded a national evaluation.R21 OH010769/OH/NIOSH CDC HHSUnited States
Med Care
Full text linkPurposeTo investigate the ability of the propensity score to reduce confounding bias in the presence of nondifferential misclassification of treatment, using simulations.MethodsUsing an example from the pregnancy medication safety literature, we carried out simulations to quantify the effect of nondifferential misclassification of treatment under varying scenarios of sensitivity and specificity, exposure prevalence (10%, 50%), outcome type (continuous and binary), true outcome (null and increased risk), confounding direction, and different propensity score applications (matching, stratification, weighting, regression), and obtained measures of bias and 95% confidence interval coverage.ResultsAll methods were subject to substantial bias towards the null due to nondifferential exposure misclassification (range: 0% to 47% for 50% exposure prevalence and 0% to 80% for 10% exposure prevalence), particularly if specificity was low (<97%). Propensity score stratification produced the least biased effect estimates. We observed that the impact of sensitivity and specificity on the bias and coverage for each adjustment method is strongly related to prevalence of exposure: as exposure prevalence decreases and/or outcomes are continuous rather than categorical, the effect of misclassification is magnified, producing larger biases and loss of coverage of 95% confidence intervals. Propensity score matching resulted in unpredictably biased effect estimates.ConclusionThe results of this study underline the importance of assessing exposure misclassification in observational studies in the context of propensity score methods. While propensity score methods reduce confounding bias, bias owing to nondifferential misclassification is of potentially greater concern.R21 AG046839/AG/NIA NIH HHS/United StatesR21 CA198172/CA/NCI NIH HHS/United StatesR21 OH010769/OH/NIOSH CDC HHS/United StatesR25 GM113686/GM/NIGMS NIH HHS/United StatesR56 NR015498/NR/NINR NIH HHS/United StatesTL1 TR001454/TR/NCATS NIH HHS/United State
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Reducing Off-Label Antipsychotic Use in Older Adults: Time to Look Beyond the Doors of Nursing Homes
No full textThe vexing problem of off‐label use of antipsychotics in nursing homes continues to challenge the industry. Food and Drug Administration black box warnings in 2005 and 2008 about the serious adverse effects of offlabel use of antipsychotics in older adults had little effect on the prevalence of antipsychotic use in nursing homes.1 The 2011 Department of Health and Human Services Officer of Inspector General report noted that 83% of Medicare claims for atypical antipsychotic drugs for nursing home residents were associated with off‐label conditions and 88% with dementia.2 In response, the Centers for Medicare and Medicaid Services (CMS) launched a national initiative to reduce atypical antipsychotic use in nursing homes.3 The partnerships and other administrative initiatives are working, with a 35% relative reduction in the use of antipsychotics in nursing homes since the launch of the initiative (from 23.9% in fourth quarter 2011 to 15.5% in second quarter 2017).4 As new, ambitious targets for reductions in off‐label antipsychotic use are set for nursing homes, the Government Accountability Office has called for expansion beyond nursing homes to other settings.5 In this issue of the Journal of the American Geriatrics Society, Zhang and colleagues6 provide novel data to inform expanded efforts by evaluating where antipsychotics prescribed in nursing homes were first initiated
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe 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
- …
